[
  {
    "path": ".cargo/config.toml",
    "content": "[target.wasm32-wasip1]\nrunner = \"wasmtime run --\"\n\n[target.wasm32-wasip2]\nrunner = \"wasmtime run --\"\n"
  },
  {
    "path": ".github/workflows/ci.yml",
    "content": "name: CI\n\non:\n  push:\n    branches:\n      - master\n  pull_request:\n    branches:\n      - master\n  schedule:\n    # Run every night at 8:30 AM UTC\n    - cron: '30 8 * * *'\n\nenv:\n  RUST_BACKTRACE: 1\n\njobs:\n  test:\n    name: Test - ${{ matrix.build }}\n    runs-on: ${{ matrix.os }}\n    strategy:\n      fail-fast: false\n      matrix:\n        build:\n          - linux\n          - macos\n          - windows\n        include:\n          - build: linux\n            label: linux_x64\n            os: ubuntu-latest\n\n          - build: macos\n            label: macos_arm64\n            os: macos-latest\n\n          - build: windows\n            label: windows_x64\n            os: windows-latest\n\n    steps:\n        - name: Checkout source code\n          uses: actions/checkout@v5\n\n        - name: Cache Rust\n          uses: actions/cache@v4\n          with:\n            path: |\n              ~/.cargo/bin/\n              ~/.cargo/registry/index/\n              ~/.cargo/registry/cache/\n              ~/.cargo/git/db/\n              target/\n            key: ${{ runner.os }}-cargo-test-${{ hashFiles('crates/Cargo.lock') }}\n            restore-keys: |\n              ${{ runner.os }}-cargo-test-\n\n        - name: Install Rust Tools\n          uses: taiki-e/install-action@v2\n          with:\n            tool: cargo-nextest, just\n\n        - name: Run tests\n          run: just test\n\n        - name: Run tests (no std)\n          run: just test_nostd\n\n        - name: Run tests (safe)\n          run: just test_safe\n\n        - name: Run tests (no std, safe)\n          run: just test_nostd_safe\n\n  miri:\n    name: Miri\n    runs-on: ubuntu-latest\n    env:\n      MIRIFLAGS: -Zmiri-tag-raw-pointers\n    steps:\n      - name: Checkout source code\n        uses: actions/checkout@v5\n\n      - name: Setup Rust\n        uses: actions-rust-lang/setup-rust-toolchain@v1\n        with:\n          components: miri\n          toolchain: nightly\n\n      - name: Cache Rust\n        uses: actions/cache@v4\n        with:\n          path: |\n            ~/.cargo/bin/\n            ~/.cargo/registry/index/\n            ~/.cargo/registry/cache/\n            ~/.cargo/git/db/\n            target/\n          key: ${{ runner.os }}-cargo-miri-${{ hashFiles('crates/Cargo.lock') }}\n          restore-keys: |\n            ${{ runner.os }}-cargo-miri-${{ hashFiles('crates/Cargo.lock') }}\n\n      - name: Install Rust Tools\n        uses: taiki-e/install-action@v2\n        with:\n          tool: cargo-nextest, just\n\n      - name: Run Miri\n        run: just miri\n\n  clippy:\n    name: Clippy\n    runs-on: ubuntu-latest\n    steps:\n      - name: Checkout source code\n        uses: actions/checkout@v5\n\n      - name: Cache Rust\n        uses: actions/cache@v4\n        with:\n          path: |\n            ~/.cargo/bin/\n            ~/.cargo/registry/index/\n            ~/.cargo/registry/cache/\n            ~/.cargo/git/db/\n            target/\n          key: ${{ runner.os }}-cargo-clippy-${{ hashFiles('crates/Cargo.lock') }}\n          restore-keys: |\n            ${{ runner.os }}-cargo-clippy-\n\n      - name: Install Rust Tools\n        uses: taiki-e/install-action@v2\n        with:\n          tool: cargo-nextest, just\n\n      - name: Run Clippy\n        run: just clippy\n\n  wasi_test:\n    name: WASI Test\n    runs-on: ubuntu-latest\n    steps:\n      - name: Checkout source code\n        uses: actions/checkout@v5\n\n      - name: Setup Rust\n        uses: actions-rust-lang/setup-rust-toolchain@v1\n        with:\n          target: wasm32-wasip1\n          \n      - name: Cache Rust\n        uses: actions/cache@v4\n        with:\n          path: |\n            ~/.cargo/bin/\n            ~/.cargo/registry/index/\n            ~/.cargo/registry/cache/\n            ~/.cargo/git/db/\n            target/\n          key: ${{ runner.os }}-cargo-wasi-test-${{ hashFiles('crates/Cargo.lock') }}\n          restore-keys: |\n            ${{ runner.os }}-cargo-wasi-test-\n\n      - name: Install Rust Tools\n        uses: taiki-e/install-action@v2\n        with:\n          tool: cargo-nextest, just\n\n      - name: Setup `wasmtime`\n        uses: bytecodealliance/actions/wasmtime/setup@v1\n\n      # Serde doesn't work on WASI yet when using OsStr/Path (https://github.com/serde-rs/serde/issues/3020)\n      - name: Run tests\n        run: just std_features=bytes,cstr,osstr,path,sqlx test --target wasm32-wasip1\n\n      - name: Run tests (serde)\n        run: just std_features=bytes,cstr,serde,sqlx test --target wasm32-wasip1\n\n      - name: Run tests (no std)\n        run: just test_nostd --target wasm32-wasip1\n\n      - name: Run tests (safe)\n        run: just std_features=bytes,cstr,osstr,path,sqlx test_safe --target wasm32-wasip1\n\n      - name: Run tests (safe, serde)\n        run: just std_features=bytes,cstr,serde,sqlx test_safe --target wasm32-wasip1\n\n      - name: Run tests (no std, safe)\n        run: just test_nostd_safe --target wasm32-wasip1\n\n  coverage:\n    name: Code Coverage\n    runs-on: ubuntu-latest\n    steps:\n      - name: Checkout source code\n        uses: actions/checkout@v5\n\n      - name: Setup Rust\n        uses: actions-rust-lang/setup-rust-toolchain@v1\n        with:\n          components: llvm-tools-preview\n\n      - name: Cache Rust\n        uses: actions/cache@v4\n        with:\n          path: |\n            ~/.cargo/bin/\n            ~/.cargo/registry/index/\n            ~/.cargo/registry/cache/\n            ~/.cargo/git/db/\n            target/\n          key: ${{ runner.os }}-cargo-coverage-${{ hashFiles('crates/Cargo.lock') }}\n          restore-keys: |\n            ${{ runner.os }}-cargo-coverage-\n\n      - name: Install Rust Tools\n        uses: taiki-e/install-action@v2\n        with:\n          tool: cargo-nextest, cargo-llvm-cov, just\n\n      - name: Run tests with coverage\n        run: just cover_report\n\n      - name: Upload coverage reports to Codecov\n        uses: codecov/codecov-action@v5\n        with:\n            files: codecov.json\n            token: ${{ secrets.CODECOV_TOKEN }}\n"
  },
  {
    "path": ".gitignore",
    "content": "target/\n/Cargo.lock\n/.idea\ntarpaulin-report.html\n**/*.rs.bk\n.DS_Store\n\n"
  },
  {
    "path": "Cargo.toml",
    "content": "[workspace]\nmembers = [\"boxed_flexstr\", \"flexstr_support\", \"inline_flexstr\"]\nexclude = [\"benchmarks\"]\n\n[package]\nname = \"flexstr\"\nversion = \"0.11.7\"\nauthors = [\"Scott Meeuwsen <smeeuwsen@gmail.com>\"]\nlicense = \"MIT OR Apache-2.0\"\ndescription = \"A flexible, simple to use, clone-efficient string type for Rust\"\nrepository = \"https://github.com/nu11ptr/flexstr\"\ndocumentation = \"https://docs.rs/flexstr\"\nkeywords = [\"string\", \"rc_str\", \"arc_str\", \"refcount\", \"inline\"]\ncategories = [\n    \"data-structures\",\n    \"memory-management\",\n    \"no-std\",\n    \"text-processing\",\n]\nreadme = \"README.md\"\nedition = \"2024\"\nexclude = [\"docs/**\"]\n\n[features]\ndefault = [\"std\", \"str\"]\nprost = [\"dep:prost\", \"inline_flexstr/prost\"]\nsqlx_pg_arrays = [\"sqlx\", \"sqlx/postgres\"]\nutoipa = [\"dep:utoipa\", \"inline_flexstr/utoipa\"]\nzeroize = [\"dep:zeroize\", \"inline_flexstr/zeroize\"]\n# Does not use and forbids all unsafe code (unless windows_min_unsafe is also enabled, but that only impacts Windows)\nsafe = [\"flexstr_support/safe\", \"inline_flexstr/safe\"]\nstd = [\"flexstr_support/std\", \"inline_flexstr/std\", \"serde?/std\", \"prost?/std\"]\n# Uses the minimum unsafe code possible to support OsStr/Path on Windows. Doesn't impact any other string types or operating systems.\nwin_min_unsafe = [\n    \"flexstr_support/win_min_unsafe\",\n    \"inline_flexstr/win_min_unsafe\",\n    \"safe\",\n]\n\n# String type features\nbytes = [\"flexstr_support/bytes\", \"inline_flexstr/bytes\"]\ncstr = [\"flexstr_support/cstr\", \"inline_flexstr/cstr\"]\nosstr = [\"flexstr_support/osstr\", \"inline_flexstr/osstr\", \"std\"]\npath = [\"flexstr_support/path\", \"inline_flexstr/path\", \"osstr\"]\nstr = [\"flexstr_support/str\", \"inline_flexstr/str\"]\n\n[dependencies.serde]\nversion = \"1\"\ndefault-features = false\noptional = true\n\n[dependencies.prost]\nversion = \"0.14\"\ndefault-features = false\noptional = true\n\n[dependencies.sqlx]\nversion = \"0.8\"\ndefault-features = false\noptional = true\n\n[dependencies.utoipa]\nversion = \"5\"\noptional = true\n\n[dependencies.zeroize]\nversion = \"1\"\ndefault-features = false\noptional = true\n\n[dependencies.inline_flexstr]\npath = \"inline_flexstr\"\nversion = \"0.1.9\"\ndefault-features = false\n\n[dependencies.flexstr_support]\npath = \"flexstr_support\"\nversion = \"0.1.4\"\ndefault-features = false\n\n[dev-dependencies.serde_json]\nversion = \"1\"\n\n[package.metadata.docs.rs]\nfeatures = [\"bytes\", \"cstr\", \"osstr\", \"path\", \"prost\", \"serde\", \"std\", \"str\", \"utoipa\", \"zeroize\"]\nrustdoc-args = [\"--cfg\", \"docsrs\"]\n"
  },
  {
    "path": "LICENSE",
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  },
  {
    "path": "README.md",
    "content": "# flexstr\n\n[![Crate](https://img.shields.io/crates/v/flexstr)](https://crates.io/crates/flexstr)\n[![Docs](https://docs.rs/flexstr/badge.svg)](https://docs.rs/flexstr)\n[![Build](https://github.com/nu11ptr/flexstr/workflows/CI/badge.svg)](https://github.com/nu11ptr/flexstr/actions)\n[![codecov](https://codecov.io/gh/nu11ptr/flexstr/branch/master/graph/badge.svg?token=yUZ8v2tKPd)](https://codecov.io/gh/nu11ptr/flexstr)\n\nA flexible, simple to use, clone-efficient `String` replacement for Rust. It unifies borrowed, inlined, referenced counted and boxed strings into a single type.\n\n## Overview\n\nIf you've used `Cow`, but you wish cloning owned strings was more performant and that being owned didn't always imply heap allocation, this crate might be what you are looking for. The operations are \"lazy\" (like `Cow`), and it tries not to do work the user is not expecting.\n\n\n> **Users of previous versions:** you should be aware this new version is a ground up rewrite with a solidly different thought process, API and design. Even if the previous versions didn't match your needs, this one might. *Users should be aware that nearly all the string construction code is not yet present in this version.* The new way to do this (workaround?) is to do the work as a `String` and then import it into a `LocalStr` or `SharedStr`. Moving into and out of the boxed variant (`from_owned`) should be near zero cost.\n\n## Features\n\n* Simple: just an enum. You mostly already know how to use it.\n* Borrowed, inlined, reference counted, and boxed strings in a single type\n* O(1) clone\n    * NOTE: first `clone` when variant is `Boxed` is O(n)\n* Mutable (Copy-on-write under the hood, if necessary)\n* Inlined string type can be used on its own\n* Same size a a `String` (3 words wide, even inside an `Option`)\n* Lazy instantiation (no unexpected allocations)\n* No external dependencies\n    * NOTE: `serde`/`sqlx`/`prost` optional for serialization/deserialization/encode/decode\n* Optional `no_std`\n* Optional `safe` feature that forbids any `unsafe` usage\n    * NOTE: This does induce a performance penalty, as would be expected\n    * NOTE 2: `OsStr`/`Path` support on Windows requires at least one unsafe call (`win_min_unsafe` feature).\n* Handles all Rust string types (`str`, `CStr`, `OsStr`, `Path`, `[u8]`)\n\n## Cargo Features\n\n* **prost** = Enable `prost::Message` implementation for protobuf encoding/decoding\n* **safe** = Use all safe functions and add `forbid(unsafe_code)` (performance penalty)\n* **sqlx** = Enable sqlx encode/decode/type support\n* **sqlx_pg_arrays** = Enable sqlx Postgres array support (implies `sqlx` feature)\n* **std** = Use `std` (default)\n* **serde** = add `serde` dependency and adds serialization/deserialization\n* **utoipa** = Enable `utoipa::ToSchema` implementation for OpenAPI schema generation\n* **zeroize** = Enable `zeroize::Zeroize` for secure memory erasure (incompatible with `safe` feature)\n* **win_min_unsafe** = enables the minimum necessary unsafe code on Windows to support `OsStr`/`Path`. No other string types or operating systems are impacted (implies `safe` feature).\n    * NOTE: The code will refuse to compile if this is not specified when ALL the following conditions are true:\n        * The `safe` feature is enabled\n        * The `osstr` and/or `path` feature(s) are enabled\n        * Compiling for Windows\n\n### String Type Features:\n* **str** = Enable `str`-based strings (default)\n* **bytes** = Enable byte-based strings (`[u8]`)\n* **cstr** = Enable `CStr`-based strings\n* **osstr** = Enable `OsStr`-based strings\n* **path** = Enable `Path`-based strings (implies `osstr` feature)\n\n## Example\n\nIt is just an enum that looks like this - you can probably guess much of how it works just by looking at it:\n\n```rust,ignore\n\n// `S` is just the raw string type (typically `str`)\n// `R` is just an `Arc` or an `Rc`.\npub enum FlexStr<'s, S, R> {\n    Borrowed(&'s S),\n    Inlined(InlineFlexStr<S>),\n    RefCounted(R),\n    Boxed(Box<S>),\n}\n\n// You would typically use it via one of the type aliases, for example:\npub type LocalStr<'s> = FlexStr<'s, str, Rc<str>>;\npub type SharedStr<'s> = FlexStr<'s, str, Arc<str>>;\n```\n\nEven that you don't really need to concern yourself with. You can just use it how you would expect a simple wrapper to behave.\n\n```rust\nuse flexstr::*;\n\n// This will be a \"Borrowed\" variant\nlet hello: SharedStr = \"hello\".into();\nassert!(hello.is_borrowed());\n\n// This will be a \"Boxed\" variant\nlet world: SharedStr = \"world\".to_string().into();\nassert!(world.is_boxed());\n\n// This is now \"Inlined\" (since it is short)\nlet hello = hello.into_owned();\nassert!(hello.is_inlined());\n\n// This is now \"Inlined\" as well (since it is short)\nlet world = world.optimize();\nassert!(world.is_inlined());\n\nprintln!(\"{hello} {world}\");\n```\n\n## Performance / Efficiency\n\nThere is no single ideal variant in the enum. They all perform different roles. A naive usage of this crate may or may not result in increased performance/efficiency, but a strategic one, that understands which variant is holding the string at all times, will almost certainly improve memory efficiency and/or performance in string heavy code.\n\n| Enum Variant   |     |                                          Clone                                          |         Memory Efficiency         |           Mutation            |   `String` Conversion   |  `&str` Access   |\n| -------------- | :-: | :-------------------------------------------------------------------------------------: | :-------------------------------: | :---------------------------: | :---------------------: | :--------------: |\n|                |     |                                                                                         |                                   |                               |                         |                  |\n| **Borrowed**   |     |                              ✅ Fastest, O(1), copy 2 words                              |   ✅ **Highest**<br>(reference)    | ❌ Slow, maybe allocate + copy | ❌ Slow, allocate + copy | ✅ Fast, in place |\n| **Inlined**    |     |                              ✅ Fastest, O(1), copy 3 words                              |     ✅ **Highest**<br>(inline)     |       ✅ Fast, in place        | ❌ Slow, allocate + copy | ✅ Fast, in place |\n| **RefCounted** |     | ✅ Local = Very fast, O(1), inc ref count<br>✅ Shared = Fast, O(1), inc atomic ref count | ✅ **Good**<br>(heap, single copy) | ❌ Slow, maybe allocate + copy | ❌ Slow, allocate + copy | ✅ Fast, in place |\n| **Boxed**      |     |                          ❌ Slower, O(n), maybe allocate + copy                          | ❌ **Lowest**<br>(heap, per copy)  |       ✅ Fast, in place        |  ✅ Fast, headers only*   | ✅ Fast, in place |\n\n*In the current version, the usage of `Box<str>` implies that a `String` to `Box<str>` conversion may require an allocation/copy, if there is excess capacity. A new `BoxStr` type is in progress to fix this situation (by maintaining both capacity and length, not just length).\n\n### Benchmarks\n\nIn general, it performs quite well given that it is mostly just a thin wrapper over the stdlib. See the [benchmarks](benchmarks/README.md) page for more details.\n\n## AI Usage\n\nThe code was written by hand with care (although AI tab completion was used). Any contributions should be completely understood by the contributor, whether AI assisted or not.\n\nThe tests on the otherhand were 90%+ generated by AI under my instruction. I've done a cursory review for sanity, but they need more work. Volunteers welcome.\n\n## Status\n\nThis is currently experimental, however, I will be using this at a startup in production code, so it will become production ready at some point.\n\n## Contributions\n\nContributions are welcome so long as they align to my vision for this crate. Currently, it does most of what I want it to do (outside of string construction and mutation, but I'm not ready to start on that yet).\n\n## License\n\nThis project is licensed optionally under either:\n\n* Apache License, Version 2.0, (LICENSE-APACHE\n  or <https://www.apache.org/licenses/LICENSE-2.0>)\n* MIT license (LICENSE-MIT or <https://opensource.org/licenses/MIT>)\n"
  },
  {
    "path": "benchmarks/Cargo.toml",
    "content": "[package]\nname = \"benchmarks\"\nversion = \"0.1.0\"\nedition = \"2024\"\n\n[profile.bench]\ndebug = true\n\n[[bench]]\nname = \"import\"\nharness = false\n\n[[bench]]\nname = \"clone\"\nharness = false\n\n[dev-dependencies]\ncriterion = { version = \"0.8\", features = [\"html_reports\"] }\nflexstr = { path = \"../\" }\ninline_flexstr = { path = \"../inline_flexstr\" }\nflexstr09 = { package = \"flexstr\", git = \"https://github.com/nu11ptr/flexstr\", rev = \"fe86d0a8c8f83676b93653e8627edbc5a634b898\" }\n"
  },
  {
    "path": "benchmarks/README.md",
    "content": "# Benchmarks\n\n## Environment\n\nThe benchmarks were run on a Macbook Pro M1 Max with 32GB of RAM:\n\n```bash\n% cargo version -v\ncargo 1.92.0 (344c4567c 2025-10-21)\nrelease: 1.92.0\ncommit-hash: 344c4567c634a25837e3c3476aac08af84cf9203\ncommit-date: 2025-10-21\nhost: aarch64-apple-darwin\nlibgit2: 1.9.1 (sys:0.20.2 vendored)\nlibcurl: 8.7.1 (sys:0.4.83+curl-8.15.0 system ssl:(SecureTransport) LibreSSL/3.3.6)\nssl: OpenSSL 3.5.4 30 Sep 2025\nos: Mac OS 15.7.1 [64-bit]\n```\n\n## Overview\n\nAt present, FlexStr is mostly just an enum wrapper (the exception being the inline string) that forwards its real world mostly to the stdlib. As such, the primary objective we looking for is:\n\n1. That it does not add too much overhead to importing/instantiation over raw stdlib\n1. That clone performance is fast enough to justify that extra overhead\n\nThe benchmark results meet these goals for me currently. The results are published at the link below.\n\n## Results\n\nThe Criterion benchmark report can be found [here](https://nu11ptr.github.io/flexstr/criterion/report/)\n"
  },
  {
    "path": "benchmarks/archive/0.8.0/README.md",
    "content": "# Benchmarks\n\n## Table of Contents\n\n- [Environment](#environment)\n- [Third Party Crates](#third-party-crates)\n- [Benchmark Pitfalls](#benchmark-pitfalls)\n- [Benchmark Results](#benchmark-results)\n    - [Create and Destroy - Literal](#create-and-destroy---literal)\n    - [Create and Destroy - Computed](#create-and-destroy---computed)\n    - [Clone - Literal](#clone---literal)\n    - [Clone - Computed](#clone---computed)\n    - [Convert](#convert)\n\n## Environment\n\nBenchmarks were run on:\n\n```bash\n$ cargo +nightly version -v\ncargo 1.61.0-nightly (65c8266 2022-03-09)\nrelease: 1.61.0-nightly\ncommit-hash: 65c82664263feddc5fe2d424be0993c28d46377a\ncommit-date: 2022-03-09\nhost: x86_64-unknown-linux-gnu\nlibgit2: 1.4.1 (sys:0.14.1 vendored)\nlibcurl: 7.80.0-DEV (sys:0.4.51+curl-7.80.0 vendored ssl:OpenSSL/1.1.1m)\nos: Pop!_OS 20.04 (focal) [64-bit]\n```\n\n## Third Party Crates\n\nI decided to include some popular 3rd party crates to include in the create/clone benchmarks. I try to be as fair as\npossible, but I'm obviously inherently biased and even the choice of tests is biased. I'm primarily doing this as yet\nanother measuring stick on whether `FlexStr` is performing adequately or not (and now I see some places it is not).\n\nHere are the 3rd party crates and their versions under test:\n\n```\ncompact_str v0.3.1\nflexstr v0.8.0\nkstring v1.0.6\nsmartstring v1.0.0\nsmol_str v0.1.21\n```\n\n\n## Benchmark Pitfalls\n\nThe more testing I do, the more I'm convinced that microbenchmarks are nearly impossible to do accurately. I find\nthat simply moving the order of the benchmarks can make LARGE differences. I also see sudden large jumps and drop offs\neven without doing anything at all. Using `black_box` seems just as sketchy, and without writing a book, find it creates\nthe same problems just skewed slightly differently. Nevermind `nightly` vs `stable`. Due to all this, please take these\nwith a grain of salt (maybe 5). Many of these are inaccurate or just plain wrong.\n\nThat said, they are not totally worthless. We can look for trends and patterns, and benchmarking has revealed some\nperformance surprises that resulted in beneficial code changes. The key things to watch for are (these will also give clues\nwhen benchmarks are impossibly wrong):\n\n* At size 0, we would expect \"empty string\" detection to kick in - should be as fast as a constant more or less\n* For literal tests, we are just testing how fast we can return the item - all work done at compile time\n* For sizes 22 and under (on 64-bit), these are all inlined - we would expect these to be faster than heap allocations\n* For static and inlining, there are zero code differences between `FlexStr` and `AFlexStr` and we shouldn't expect any\nperformance difference at all (even though large differences are shown often!)\n\n## Benchmark Results\n\n### Create and Destroy - Literal\n\nThis just demonstrates the benefits of having a constant vs. heap allocating the constant as `String` is forced to do\n\n|          | `String`                | `AFlexStr`                     | `FlexStr`                        |\n|:---------|:------------------------|:-------------------------------|:-------------------------------- |\n| **`40`** | `8.21 ns` (1.00x)       | `1.06 ns` (✅ **7.74x faster**) | `0.57 ns` (✅ **14.31x faster**)  |\n\n### Create and Destroy - Computed\n\n* String sizes of 10 and 20 are inlining, so gets a boost\n* An ever so slight penalty for the wrapper on heap allocations\n* String sizes of 0 are just empty string constants and any variation here is likely not meaningful\n* Overall I'm happy with how `FlexStr` performs here on inline string creation. I suspect the difference, however, to\n `CompactStr` and probably `SmartString` is just noise\n\n|             | `String`                  | `Rc<str>`                        | `Arc<str>`                       | `FlexStr`                        | `AFlexStr`                       | `CompactStr`                     | `KString`                        | `SmartString`                    | `SmolStr`                         |\n|:------------|:--------------------------|:---------------------------------|:---------------------------------|:---------------------------------|:---------------------------------|:---------------------------------|:---------------------------------|:---------------------------------|:--------------------------------- |\n| **`0`**     | `0.43 ns` (1.00x)         | `10.15 ns` (❌ *23.78x slower*)   | `10.62 ns` (❌ *24.87x slower*)   | `1.05 ns` (❌ *2.47x slower*)     | `0.64 ns` (❌ *1.50x slower*)     | `1.27 ns` (❌ *2.99x slower*)     | `6.79 ns` (❌ *15.91x slower*)    | `7.19 ns` (❌ *16.84x slower*)    | `11.02 ns` (❌ *25.82x slower*)    |\n| **`10`**    | `9.47 ns` (1.00x)         | `9.96 ns` (❌ *1.05x slower*)     | `10.58 ns` (❌ *1.12x slower*)    | `4.87 ns` (✅ **1.94x faster**)   | `6.59 ns` (✅ **1.44x faster**)   | `7.15 ns` (✅ **1.32x faster**)   | `7.46 ns` (✅ **1.27x faster**)   | `9.33 ns` (✅ **1.02x faster**)   | `13.59 ns` (❌ *1.43x slower*)     |\n| **`20`**    | `9.38 ns` (1.00x)         | `9.70 ns` (❌ *1.03x slower*)     | `10.35 ns` (❌ *1.10x slower*)    | `6.27 ns` (✅ **1.49x faster**)   | `6.57 ns` (✅ **1.43x faster**)   | `6.27 ns` (✅ **1.50x faster**)   | `9.79 ns` (❌ *1.04x slower*)     | `9.20 ns` (✅ **1.02x faster**)   | `13.83 ns` (❌ *1.47x slower*)     |\n| **`100`**   | `9.81 ns` (1.00x)         | `10.21 ns` (❌ *1.04x slower*)    | `10.99 ns` (❌ *1.12x slower*)    | `10.55 ns` (❌ *1.08x slower*)    | `10.76 ns` (❌ *1.10x slower*)    | `12.40 ns` (❌ *1.26x slower*)    | `10.42 ns` (❌ *1.06x slower*)    | `16.40 ns` (❌ *1.67x slower*)    | `20.04 ns` (❌ *2.04x slower*)     |\n| **`1000`**  | `13.28 ns` (1.00x)        | `13.94 ns` (❌ *1.05x slower*)    | `14.40 ns` (❌ *1.08x slower*)    | `14.24 ns` (❌ *1.07x slower*)    | `14.34 ns` (❌ *1.08x slower*)    | `14.97 ns` (❌ *1.13x slower*)    | `13.70 ns` (❌ *1.03x slower*)    | `22.58 ns` (❌ *1.70x slower*)    | `25.00 ns` (❌ *1.88x slower*)     |\n| **`16384`** | `135.56 ns` (1.00x)       | `136.80 ns` (❌ *1.01x slower*)   | `316.11 ns` (❌ *2.33x slower*)   | `142.12 ns` (❌ *1.05x slower*)   | `194.22 ns` (❌ *1.43x slower*)   | `188.73 ns` (❌ *1.39x slower*)   | `136.72 ns` (❌ *1.01x slower*)   | `197.77 ns` (❌ *1.46x slower*)   | `200.70 ns` (❌ *1.48x slower*)    |\n\n### Clone - Literal\n\nThis again just demonstrates the benefits of having a constant vs. heap allocating the constant as `String` is forced to do.\n`AFlexStr` being much slower here is likely not correct in the real world as the code is identical to `FlexStr`\n\n|          | `String`                 | `FlexStr`                      | `AFlexStr`                       |\n|:---------|:-------------------------|:-------------------------------|:-------------------------------- |\n| **`40`** | `11.85 ns` (1.00x)       | `4.29 ns` (✅ **2.76x faster**) | `11.93 ns` (❌ *1.01x slower*)    |\n\n### Clone - Computed\n\n* The benefits of simply copying a wrapper and possibly a ref count increment are apparent in `FlexStr`\n* The 10 and 20 sizes being 4x slower makes zero sense - this is compiler derived `Clone` code that literally does one\nless step than `Rc` derived `Clone` code, so we would expect it to be the same or faster. We also don't see this deviation\n in `AFlexStr`\n* `AFlexStr` is nothing more than an enum wrapper over `Arc<str>` for sizes 100 and above, so it being ~5x slower\nthan a plain `Arc<str>` is very odd to say the least\n* `FlexStr` falls pretty hard to `CompactStr` and `SmartString` on inline cloning. I'm not sure why, but I will be looking\ninto this\n* At higher string sizes, the benefits of `Rc` and `Arc` used in `FlexStr` is very benefitical\n\n|             | `String`                  | `Rc<str>`                       | `Arc<str>`                      | `FlexStr`                        | `AFlexStr`                       | `CompactStr`                     | `KString`                        | `SmartString`                    | `SmolStr`                         |\n|:------------|:--------------------------|:--------------------------------|:--------------------------------|:---------------------------------|:---------------------------------|:---------------------------------|:---------------------------------|:---------------------------------|:--------------------------------- |\n| **`0`**     | `5.83 ns` (1.00x)         | `0.69 ns` (✅ **8.47x faster**)  | `4.46 ns` (✅ **1.31x faster**)  | `8.01 ns` (❌ *1.37x slower*)     | `12.33 ns` (❌ *2.12x slower*)    | `3.56 ns` (✅ **1.64x faster**)   | `14.96 ns` (❌ *2.57x slower*)    | `3.64 ns` (✅ **1.60x faster**)   | `12.33 ns` (❌ *2.12x slower*)     |\n| **`10`**    | `11.62 ns` (1.00x)        | `0.77 ns` (✅ **15.07x faster**) | `4.84 ns` (✅ **2.40x faster**)  | `8.12 ns` (✅ **1.43x faster**)   | `12.40 ns` (❌ *1.07x slower*)    | `3.50 ns` (✅ **3.32x faster**)   | `14.99 ns` (❌ *1.29x slower*)    | `2.47 ns` (✅ **4.71x faster**)   | `12.47 ns` (❌ *1.07x slower*)     |\n| **`20`**    | `11.42 ns` (1.00x)        | `0.84 ns` (✅ **13.66x faster**) | `4.78 ns` (✅ **2.39x faster**)  | `8.15 ns` (✅ **1.40x faster**)   | `12.39 ns` (❌ *1.08x slower*)    | `3.49 ns` (✅ **3.27x faster**)   | `15.48 ns` (❌ *1.36x slower*)    | `2.41 ns` (✅ **4.74x faster**)   | `12.42 ns` (❌ *1.09x slower*)     |\n| **`100`**   | `12.61 ns` (1.00x)        | `1.49 ns` (✅ **8.48x faster**)  | `5.11 ns` (✅ **2.47x faster**)  | `2.00 ns` (✅ **6.29x faster**)   | `12.97 ns` (❌ *1.03x slower*)    | `14.63 ns` (❌ *1.16x slower*)    | `17.73 ns` (❌ *1.41x slower*)    | `16.70 ns` (❌ *1.32x slower*)    | `16.76 ns` (❌ *1.33x slower*)     |\n| **`1000`**  | `53.93 ns` (1.00x)        | `3.06 ns` (✅ **17.61x faster**) | `7.52 ns` (✅ **7.17x faster**)  | `2.89 ns` (✅ **18.65x faster**)  | `13.02 ns` (✅ **4.14x faster**)  | `42.74 ns` (✅ **1.26x faster**)  | `56.43 ns` (❌ *1.05x slower*)    | `56.79 ns` (❌ *1.05x slower*)    | `16.79 ns` (✅ **3.21x faster**)   |\n| **`16384`** | `534.58 ns` (1.00x)       | `6.20 ns` (✅ **86.21x faster**) | `7.72 ns` (✅ **69.23x faster**) | `2.60 ns` (✅ **205.65x faster**) | `13.16 ns` (✅ **40.63x faster**) | `467.72 ns` (✅ **1.14x faster**) | `506.98 ns` (✅ **1.05x faster**) | `498.55 ns` (✅ **1.07x faster**) | `18.33 ns` (✅ **29.17x faster**)  |\n\n### Convert\n\nThanks mostly to `ryu` and `itoa`, our primitive conversions handily outperforms `String`\n\n|            | `String`                  | `AFlexStr`                      | `FlexStr`                        |\n|:-----------|:--------------------------|:--------------------------------|:-------------------------------- |\n| **`bool`** | `16.58 ns` (1.00x)        | `1.06 ns` (✅ **15.63x faster**) | `0.67 ns` (✅ **24.83x faster**)  |\n| **`char`** | `10.67 ns` (1.00x)        | `11.46 ns` (❌ *1.07x slower*)   | `13.45 ns` (❌ *1.26x slower*)    |\n| **`i8`**   | `13.32 ns` (1.00x)        | `8.95 ns` (✅ **1.49x faster**)  | `10.05 ns` (✅ **1.32x faster**)  |\n| **`i16`**  | `20.76 ns` (1.00x)        | `18.05 ns` (✅ **1.15x faster**) | `18.10 ns` (✅ **1.15x faster**)  |\n| **`i32`**  | `31.73 ns` (1.00x)        | `14.64 ns` (✅ **2.17x faster**) | `14.55 ns` (✅ **2.18x faster**)  |\n| **`i64`**  | `38.11 ns` (1.00x)        | `19.27 ns` (✅ **1.98x faster**) | `19.30 ns` (✅ **1.97x faster**)  |\n| **`i128`** | `65.98 ns` (1.00x)        | `37.99 ns` (✅ **1.74x faster**) | `37.86 ns` (✅ **1.74x faster**)  |\n| **`f32`**  | `112.65 ns` (1.00x)       | `24.85 ns` (✅ **4.53x faster**) | `25.05 ns` (✅ **4.50x faster**)  |\n| **`f64`**  | `191.50 ns` (1.00x)       | `30.81 ns` (✅ **6.22x faster**) | `30.01 ns` (✅ **6.38x faster**)  |\n\n---\nMade with [criterion-table](https://github.com/nu11ptr/criterion-table)\n\n"
  },
  {
    "path": "benchmarks/archive/0.8.1/README.md",
    "content": "# Benchmarks\n\n## Table of Contents\n\n- [Environment](#environment)\n- [Third Party Crates](#third-party-crates)\n- [Benchmark Pitfalls](#benchmark-pitfalls)\n- [Benchmark Results](#benchmark-results)\n    - [Create and Destroy - Literal](#create-and-destroy---literal)\n    - [Create and Destroy - Computed](#create-and-destroy---computed)\n    - [Clone - Literal](#clone---literal)\n    - [Clone - Computed](#clone---computed)\n    - [Convert](#convert)\n\n## Environment\n\nBenchmarks were run on:\n\n```bash\n$ cargo +nightly version -v\ncargo 1.61.0-nightly (65c8266 2022-03-09)\nrelease: 1.61.0-nightly\ncommit-hash: 65c82664263feddc5fe2d424be0993c28d46377a\ncommit-date: 2022-03-09\nhost: x86_64-unknown-linux-gnu\nlibgit2: 1.4.1 (sys:0.14.1 vendored)\nlibcurl: 7.80.0-DEV (sys:0.4.51+curl-7.80.0 vendored ssl:OpenSSL/1.1.1m)\nos: Pop!_OS 20.04 (focal) [64-bit]\n```\n\n## Third Party Crates\n\nI decided to include some popular 3rd party crates to include in the create/clone benchmarks. I try to be as fair as\npossible, but I'm obviously inherently biased and even the choice of tests is biased. I'm primarily doing this as yet\nanother measuring stick on whether `FlexStr` is performing adequately or not (and now I see some places it is not).\n\nHere are the 3rd party crates and their versions under test:\n\n```\ncompact_str v0.3.1\nflexstr v0.8.0\nkstring v1.0.6\nsmartstring v1.0.0\nsmol_str v0.1.21\n```\n\n\n## Benchmark Pitfalls\n\nThe more testing I do, the more I'm convinced that microbenchmarks are nearly impossible to do accurately. I find\nthat simply moving the order of the benchmarks can make LARGE differences. I also see sudden large jumps and drop offs\neven without doing anything at all. Using `black_box` seems just as sketchy, and without writing a book, find it creates\nthe same problems just skewed slightly differently. Nevermind `nightly` vs `stable`. Due to all this, please take these\nwith a grain of salt (maybe 5). Many of these are inaccurate or just plain wrong.\n\nThat said, they are not totally worthless. We can look for trends and patterns, and benchmarking has revealed some\nperformance surprises that resulted in beneficial code changes. The key things to watch for are (these will also give clues\nwhen benchmarks are impossibly wrong):\n\n* At size 0, we would expect \"empty string\" detection to kick in - should be as fast as a constant more or less\n* For literal tests, we are just testing how fast we can return the item - all work done at compile time\n* For sizes 22 and under (on 64-bit), these are all inlined - we would expect these to be faster than heap allocations\n* For static and inlining, there are zero code differences between `FlexStr` and `AFlexStr` and we shouldn't expect any\nperformance difference at all (even though large differences are shown often!)\n\n## Benchmark Results\n\n### Create and Destroy - Literal\n\nThis just demonstrates the benefits of having a constant vs. heap allocating the constant as `String` is forced to do\n\n|          | `String`                | `FlexStr`                       | `AFlexStr`                       |\n|:---------|:------------------------|:--------------------------------|:-------------------------------- |\n| **`40`** | `7.98 ns` (1.00x)       | `0.55 ns` (🚀 **14.39x faster**) | `0.56 ns` (🚀 **14.32x faster**)  |\n\n### Create and Destroy - Computed\n\n* String sizes of 10 and 20 are inlining, so gets a boost\n* An ever so slight penalty for the wrapper on heap allocations\n* String sizes of 0 are just empty string constants and any variation here is likely not meaningful\n* Overall I'm happy with how `FlexStr` performs here on inline string creation. I suspect the difference, however, to\n `CompactStr` and probably `SmartString` is just noise\n\n|             | `String`                  | `Rc<str>`                        | `Arc<str>`                       | `FlexStr`                        | `AFlexStr`                       | `CompactStr`                     | `KString`                        | `SmartString`                    | `SmolStr`                         |\n|:------------|:--------------------------|:---------------------------------|:---------------------------------|:---------------------------------|:---------------------------------|:---------------------------------|:---------------------------------|:---------------------------------|:--------------------------------- |\n| **`0`**     | `0.43 ns` (1.00x)         | `10.05 ns` (❌ *23.57x slower*)   | `10.80 ns` (❌ *25.34x slower*)   | `0.44 ns` (❌ *1.04x slower*)     | `0.43 ns` (❌ *1.02x slower*)     | `1.06 ns` (❌ *2.49x slower*)     | `6.36 ns` (❌ *14.92x slower*)    | `7.20 ns` (❌ *16.89x slower*)    | `11.02 ns` (❌ *25.85x slower*)    |\n| **`10`**    | `10.04 ns` (1.00x)        | `10.09 ns` (❌ *1.01x slower*)    | `10.73 ns` (❌ *1.07x slower*)    | `6.11 ns` (✅ **1.64x faster**)   | `6.08 ns` (✅ **1.65x faster**)   | `6.95 ns` (✅ **1.44x faster**)   | `8.53 ns` (✅ **1.18x faster**)   | `9.26 ns` (✅ **1.08x faster**)   | `13.61 ns` (❌ *1.36x slower*)     |\n| **`20`**    | `9.59 ns` (1.00x)         | `9.83 ns` (❌ *1.02x slower*)     | `10.44 ns` (❌ *1.09x slower*)    | `4.91 ns` (✅ **1.95x faster**)   | `4.90 ns` (✅ **1.96x faster**)   | `6.32 ns` (✅ **1.52x faster**)   | `9.87 ns` (❌ *1.03x slower*)     | `9.26 ns` (✅ **1.04x faster**)   | `13.58 ns` (❌ *1.42x slower*)     |\n| **`100`**   | `10.58 ns` (1.00x)        | `10.60 ns` (❌ *1.00x slower*)    | `11.27 ns` (❌ *1.07x slower*)    | `11.09 ns` (❌ *1.05x slower*)    | `10.98 ns` (❌ *1.04x slower*)    | `12.01 ns` (❌ *1.13x slower*)    | `10.46 ns` (✅ **1.01x faster**)  | `16.78 ns` (❌ *1.59x slower*)    | `20.29 ns` (❌ *1.92x slower*)     |\n| **`1000`**  | `13.50 ns` (1.00x)        | `13.90 ns` (❌ *1.03x slower*)    | `14.35 ns` (❌ *1.06x slower*)    | `13.91 ns` (❌ *1.03x slower*)    | `14.10 ns` (❌ *1.04x slower*)    | `14.98 ns` (❌ *1.11x slower*)    | `13.44 ns` (✅ **1.00x faster**)  | `22.63 ns` (❌ *1.68x slower*)    | `25.24 ns` (❌ *1.87x slower*)     |\n| **`16384`** | `135.18 ns` (1.00x)       | `135.56 ns` (❌ *1.00x slower*)   | `193.03 ns` (❌ *1.43x slower*)   | `139.29 ns` (❌ *1.03x slower*)   | `193.82 ns` (❌ *1.43x slower*)   | `189.21 ns` (❌ *1.40x slower*)   | `135.17 ns` (✅ **1.00x faster**) | `195.44 ns` (❌ *1.45x slower*)   | `199.77 ns` (❌ *1.48x slower*)    |\n\n### Clone - Literal\n\nThis again just demonstrates the benefits of having a constant vs. heap allocating the constant as `String` is forced to do.\n`AFlexStr` being much slower here is likely not correct in the real world as the code is identical to `FlexStr`\n\n|          | `String`                 | `FlexStr`                      | `AFlexStr`                      |\n|:---------|:-------------------------|:-------------------------------|:------------------------------- |\n| **`40`** | `11.90 ns` (1.00x)       | `1.48 ns` (🚀 **8.04x faster**) | `2.30 ns` (🚀 **5.17x faster**)  |\n\n### Clone - Computed\n\n* The benefits of simply copying a wrapper and possibly a ref count increment are apparent in `FlexStr`\n* The 10 and 20 sizes being 4x slower makes zero sense - this is compiler derived `Clone` code that literally does one\nless step than `Rc` derived `Clone` code, so we would expect it to be the same or faster. We also don't see this deviation\n in `AFlexStr`\n* `AFlexStr` is nothing more than an enum wrapper over `Arc<str>` for sizes 100 and above, so it being ~5x slower\nthan a plain `Arc<str>` is very odd to say the least\n* `FlexStr` falls pretty hard to `CompactStr` and `SmartString` on inline cloning. I'm not sure why, but I will be looking\ninto this\n* At higher string sizes, the benefits of `Rc` and `Arc` used in `FlexStr` is very benefitical\n\n|             | `String`                  | `Rc<str>`                       | `Arc<str>`                      | `FlexStr`                        | `AFlexStr`                      | `CompactStr`                     | `KString`                        | `SmartString`                    | `SmolStr`                         |\n|:------------|:--------------------------|:--------------------------------|:--------------------------------|:---------------------------------|:--------------------------------|:---------------------------------|:---------------------------------|:---------------------------------|:--------------------------------- |\n| **`0`**     | `5.86 ns` (1.00x)         | `0.73 ns` (🚀 **8.08x faster**)  | `4.49 ns` (✅ **1.30x faster**)  | `1.28 ns` (🚀 **4.57x faster**)   | `2.47 ns` (🚀 **2.37x faster**)  | `3.47 ns` (✅ **1.69x faster**)   | `14.71 ns` (❌ *2.51x slower*)    | `4.21 ns` (✅ **1.39x faster**)   | `12.08 ns` (❌ *2.06x slower*)     |\n| **`10`**    | `12.26 ns` (1.00x)        | `0.73 ns` (🚀 **16.85x faster**) | `4.71 ns` (🚀 **2.60x faster**)  | `1.11 ns` (🚀 **11.02x faster**)  | `2.32 ns` (🚀 **5.28x faster**)  | `3.43 ns` (🚀 **3.57x faster**)   | `14.80 ns` (❌ *1.21x slower*)    | `4.12 ns` (🚀 **2.98x faster**)   | `12.14 ns` (✅ **1.01x faster**)   |\n| **`20`**    | `11.51 ns` (1.00x)        | `0.76 ns` (🚀 **15.23x faster**) | `4.73 ns` (🚀 **2.43x faster**)  | `0.87 ns` (🚀 **13.19x faster**)  | `2.29 ns` (🚀 **5.04x faster**)  | `3.44 ns` (🚀 **3.35x faster**)   | `15.49 ns` (❌ *1.35x slower*)    | `4.02 ns` (🚀 **2.86x faster**)   | `12.17 ns` (❌ *1.06x slower*)     |\n| **`100`**   | `12.93 ns` (1.00x)        | `1.33 ns` (🚀 **9.74x faster**)  | `5.12 ns` (🚀 **2.52x faster**)  | `1.64 ns` (🚀 **7.86x faster**)   | `5.43 ns` (🚀 **2.38x faster**)  | `15.12 ns` (❌ *1.17x slower*)    | `17.51 ns` (❌ *1.35x slower*)    | `16.70 ns` (❌ *1.29x slower*)    | `16.27 ns` (❌ *1.26x slower*)     |\n| **`1000`**  | `55.12 ns` (1.00x)        | `3.05 ns` (🚀 **18.06x faster**) | `7.46 ns` (🚀 **7.38x faster**)  | `3.08 ns` (🚀 **17.87x faster**)  | `5.77 ns` (🚀 **9.55x faster**)  | `40.18 ns` (✅ **1.37x faster**)  | `54.93 ns` (✅ **1.00x faster**)  | `55.64 ns` (❌ *1.01x slower*)    | `16.39 ns` (🚀 **3.36x faster**)   |\n| **`16384`** | `484.42 ns` (1.00x)       | `5.73 ns` (🚀 **84.48x faster**) | `7.41 ns` (🚀 **65.36x faster**) | `2.49 ns` (🚀 **194.42x faster**) | `6.29 ns` (🚀 **77.02x faster**) | `452.33 ns` (✅ **1.07x faster**) | `500.87 ns` (❌ *1.03x slower*)   | `497.66 ns` (❌ *1.03x slower*)   | `17.57 ns` (🚀 **27.56x faster**)  |\n\n### Convert\n\nThanks mostly to `ryu` and `itoa`, our primitive conversions handily outperforms `String`\n\n|            | `String`                  | `AFlexStr`                      | `FlexStr`                        |\n|:-----------|:--------------------------|:--------------------------------|:-------------------------------- |\n| **`bool`** | `17.02 ns` (1.00x)        | `1.07 ns` (🚀 **15.87x faster**) | `0.86 ns` (🚀 **19.84x faster**)  |\n| **`char`** | `10.55 ns` (1.00x)        | `10.04 ns` (✅ **1.05x faster**) | `10.28 ns` (✅ **1.03x faster**)  |\n| **`i8`**   | `12.69 ns` (1.00x)        | `10.01 ns` (✅ **1.27x faster**) | `10.20 ns` (✅ **1.24x faster**)  |\n| **`i16`**  | `21.17 ns` (1.00x)        | `10.61 ns` (✅ **1.99x faster**) | `10.63 ns` (✅ **1.99x faster**)  |\n| **`i32`**  | `38.49 ns` (1.00x)        | `12.68 ns` (🚀 **3.04x faster**) | `12.67 ns` (🚀 **3.04x faster**)  |\n| **`i64`**  | `35.91 ns` (1.00x)        | `12.10 ns` (🚀 **2.97x faster**) | `12.12 ns` (🚀 **2.96x faster**)  |\n| **`i128`** | `63.06 ns` (1.00x)        | `34.05 ns` (✅ **1.85x faster**) | `33.45 ns` (✅ **1.89x faster**)  |\n| **`f32`**  | `118.53 ns` (1.00x)       | `18.47 ns` (🚀 **6.42x faster**) | `17.36 ns` (🚀 **6.83x faster**)  |\n| **`f64`**  | `191.93 ns` (1.00x)       | `30.56 ns` (🚀 **6.28x faster**) | `30.14 ns` (🚀 **6.37x faster**)  |\n\n---\nMade with [criterion-table](https://github.com/nu11ptr/criterion-table)\n\n"
  },
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Computed/SmolStr/16384\",\"report_directory\":\"/home/scott/IdeaProjects/flexstr/benchmarks/target/criterion/reports/Create and Destroy - Computed/SmolStr/16384\",\"iteration_count\":[4911,9822,14733,19644,24555,29466,34377,39288,44199,49110,54021,58932,63843,68754,73665,78576,83487,88398,93309,98220,103131,108042,112953,117864,122775,127686,132597,137508,142419,147330,152241,157152,162063,166974,171885,176796,181707,186618,191529,196440,201351,206262,211173,216084,220995,225906,230817,235728,240639,245550,250461,255372,260283,265194,270105,275016,279927,284838,289749,294660,299571,304482,309393,314304,319215,324126,329037,333948,338859,343770,348681,353592,358503,363414,368325,373236,378147,383058,387969,392880,397791,402702,407613,412524,417435,422346,427257,432168,437079,441990,446901,451812,456723,461634,466545,471456,476367,481278,486189,491100],\"measured_values\":[986278.0,1972456.0,2957121.0,3945413.0,4922444.0,5930353.0,6910008.0,7883833.0,8878617.0,9841731.0,10837517.0,11777548.0,12764177.0,13662337.0,14697007.0,15669649.0,16663894.0,17696588.0,18687746.0,19580517.0,20610719.0,21559345.0,22454180.0,23521612.0,24408882.0,25444475.0,26369767.0,27352087.0,28507044.0,29445172.0,30290733.0,31422708.0,32378327.0,33268994.0,34168938.0,35261948.0,36305486.0,37292966.0,38308910.0,39124154.0,40227815.0,41142748.0,42199068.0,43083824.0,44155915.0,45138657.0,46051805.0,47099971.0,48326304.0,49000851.0,49957634.0,50812153.0,51961439.0,52941135.0,53942171.0,54988302.0,55776556.0,56894422.0,57867757.0,59120088.0,59782733.0,61179348.0,61806577.0,62851927.0,63599001.0,64658598.0,65805141.0,66558477.0,67443343.0,68741752.0,69761764.0,70699390.0,71323723.0,72584972.0,73665118.0,74341799.0,75631442.0,76484759.0,77336841.0,78377364.0,79262550.0,80346833.0,81316580.0,82431531.0,83395598.0,84350336.0,85528237.0,86301632.0,87296356.0,88340994.0,89319207.0,90497369.0,91056027.0,92245289.0,93314053.0,94308717.0,95053468.0,96405118.0,97228088.0,98522930.0],\"unit\":\"ns\",\"throughput\":[],\"typical\":{\"estimate\":199.76618616998053,\"lower_bound\":199.66454621579155,\"upper_bound\":199.86833663714106,\"unit\":\"ns\"},\"mean\":{\"estimate\":199.79061400843605,\"lower_bound\":199.68473203862808,\"upper_bound\":199.8993105625165,\"unit\":\"ns\"},\"median\":{\"estimate\":199.78477973888874,\"lower_bound\":199.6645156862478,\"upper_bound\":199.84076641742394,\"unit\":\"ns\"},\"median_abs_dev\":{\"estimate\":0.42902491641801577,\"lower_bound\":0.33034947119036373,\"upper_bound\":0.5796949156012581,\"unit\":\"ns\"},\"slope\":{\"estimate\":199.76618616998053,\"lower_bound\":199.66454621579155,\"upper_bound\":199.86833663714106,\"unit\":\"ns\"},\"change\":{\"mean\":{\"estimate\":-0.03157420638672437,\"lower_bound\":-0.03228577708937922,\"upper_bound\":-0.030892083125689827,\"unit\":\"%\"},\"median\":{\"estimate\":-0.03123688003669456,\"lower_bound\":-0.0320674067711212,\"upper_bound\":-0.03090397631704833,\"unit\":\"%\"},\"change\":\"Improved\"}}\n{\"reason\":\"group-complete\",\"group_name\":\"Create and Destroy - Computed\",\"benchmarks\":[\"Create and Destroy - Computed/String/0\",\"Create and Destroy - Computed/Rc<str>/0\",\"Create and Destroy - Computed/Arc<str>/0\",\"Create and Destroy - Computed/FlexStr/0\",\"Create and Destroy - Computed/AFlexStr/0\",\"Create and Destroy - Computed/CompactStr/0\",\"Create and Destroy - Computed/KString/0\",\"Create and Destroy - Computed/SmartString/0\",\"Create and Destroy - Computed/SmolStr/0\",\"Create and Destroy - Computed/String/10\",\"Create and Destroy - Computed/Rc<str>/10\",\"Create and Destroy - Computed/Arc<str>/10\",\"Create and Destroy - Computed/FlexStr/10\",\"Create and Destroy - Computed/AFlexStr/10\",\"Create and Destroy - Computed/CompactStr/10\",\"Create and Destroy - Computed/KString/10\",\"Create and Destroy - Computed/SmartString/10\",\"Create and Destroy - Computed/SmolStr/10\",\"Create and Destroy - Computed/String/20\",\"Create and Destroy - Computed/Rc<str>/20\",\"Create and Destroy - Computed/Arc<str>/20\",\"Create and Destroy - Computed/FlexStr/20\",\"Create and Destroy - Computed/AFlexStr/20\",\"Create and Destroy - Computed/CompactStr/20\",\"Create and Destroy - Computed/KString/20\",\"Create and Destroy - Computed/SmartString/20\",\"Create and Destroy - Computed/SmolStr/20\",\"Create and Destroy - Computed/String/100\",\"Create and Destroy - Computed/Rc<str>/100\",\"Create and Destroy - Computed/Arc<str>/100\",\"Create and Destroy - Computed/FlexStr/100\",\"Create and Destroy - Computed/AFlexStr/100\",\"Create and Destroy - Computed/CompactStr/100\",\"Create and Destroy - Computed/KString/100\",\"Create and Destroy - Computed/SmartString/100\",\"Create and Destroy - Computed/SmolStr/100\",\"Create and Destroy - Computed/String/1000\",\"Create and Destroy - Computed/Rc<str>/1000\",\"Create and Destroy - Computed/Arc<str>/1000\",\"Create and Destroy - Computed/FlexStr/1000\",\"Create and Destroy - Computed/AFlexStr/1000\",\"Create and Destroy - Computed/CompactStr/1000\",\"Create and Destroy - Computed/KString/1000\",\"Create and Destroy - Computed/SmartString/1000\",\"Create and Destroy - Computed/SmolStr/1000\",\"Create and Destroy - Computed/String/16384\",\"Create and Destroy - Computed/Rc<str>/16384\",\"Create and Destroy - Computed/Arc<str>/16384\",\"Create and Destroy - Computed/FlexStr/16384\",\"Create and Destroy - Computed/AFlexStr/16384\",\"Create and Destroy - Computed/CompactStr/16384\",\"Create and Destroy - Computed/KString/16384\",\"Create and Destroy - Computed/SmartString/16384\",\"Create and Destroy - Computed/SmolStr/16384\"],\"report_directory\":\"/home/scott/IdeaProjects/flexstr/benchmarks/target/criterion/reports/Create and Destroy - Computed\"}\n"
  },
  {
    "path": "benchmarks/benches/clone.rs",
    "content": "use std::hint::black_box;\nuse std::rc::Rc;\nuse std::sync::Arc;\n\nuse criterion::{BatchSize, BenchmarkId, Criterion, criterion_group, criterion_main};\n\nconst ITERATIONS: usize = 10_000;\n\nmacro_rules! clone {\n    ($($name:expr, $setup:expr),+) => {\n        fn clone(c: &mut Criterion) {\n            let mut group = c.benchmark_group(\"Clone\");\n            let lengths = vec![0usize, 10, 20, 100, 500];\n\n            for len in lengths {\n                $(\n                    let id = BenchmarkId::new($name, len);\n\n                    group.bench_function(id, |b| {\n                        b.iter_batched(|| $setup(len), |s| {\n                            for _ in 0..ITERATIONS {\n                                let s2 = s.clone();\n                                black_box(&s);\n                                black_box(&s2);\n                            }\n                        }, BatchSize::SmallInput)\n                    });\n                )+\n            }\n\n            group.finish();\n        }\n    };\n}\n\nclone!(\n    \"String\",\n    |len| \"x\".repeat(len),\n    \"Rc<str>\",\n    |len| -> Rc<str> { \"x\".repeat(len).into() },\n    \"Arc<str>\",\n    |len| -> Arc<str> { \"x\".repeat(len).into() },\n    \"FlexStr 0.9 (LocalStr)\",\n    |len| -> flexstr09::LocalStr { \"x\".repeat(len).into() },\n    \"FlexStr 0.9 (SharedStr)\",\n    |len| -> flexstr09::SharedStr { \"x\".repeat(len).into() },\n    \"InlineFlexStr 0.1 (InlineStr)\",\n    |len| -> inline_flexstr::InlineStr {\n        let len = std::cmp::min(len, inline_flexstr::INLINE_CAPACITY);\n        \"x\".repeat(len).as_str().try_into().unwrap()\n    },\n    \"FlexStr 0.10 (LocalStr - Boxed)\",\n    |len| -> flexstr::LocalStr { \"x\".repeat(len).into() },\n    \"FlexStr 0.10 (SharedStr - Boxed)\",\n    |len| -> flexstr::SharedStr { \"x\".repeat(len).into() },\n    \"FlexStr 0.10 (LocalStr - Optimized)\",\n    |len| {\n        let s: flexstr::LocalStr = \"x\".repeat(len).into();\n        s.optimize()\n    },\n    \"FlexStr 0.10 (SharedStr - Optimized)\",\n    |len| {\n        let s: flexstr::SharedStr = \"x\".repeat(len).into();\n        s.optimize()\n    }\n);\n\ncriterion_group!(benches, clone);\ncriterion_main!(benches);\n"
  },
  {
    "path": "benchmarks/benches/import.rs",
    "content": "use std::borrow::Cow;\nuse std::hint::black_box;\nuse std::rc::Rc;\nuse std::sync::Arc;\n\nuse criterion::{BatchSize, BenchmarkId, Criterion, criterion_group, criterion_main};\n\nmacro_rules! import {\n    ($func:ident, $group:expr,$($name:expr, $op:expr),+) => {\n        fn $func(c: &mut Criterion) {\n            let mut group = c.benchmark_group($group);\n\n            let strings: Vec<String> = vec![0usize, 10, 20, 100, 500]\n                .into_iter()\n                .map(|n| String::from(\"x\").repeat(n))\n                .collect();\n\n            for string in strings {\n                let len = string.len();\n            $(\n                let id = BenchmarkId::new($name, len);\n\n                group.bench_function(id, |b|\n                    b.iter_batched(|| string.clone(), |s| {\n                        let s = $op(s);\n                        black_box(&s);\n                    }, BatchSize::SmallInput)\n                );\n            )+\n            }\n\n            group.finish();\n        }\n    };\n}\n\nimport!(\n    import_owned_and_destroy,\n    \"Import as owned and destroy\",\n    \"Rc<str>\",\n    |s: String| -> Rc<str> { s.into() },\n    \"Arc<str>\",\n    |s: String| -> Arc<str> { s.into() },\n    \"Cow<'_, str>\",\n    |s: String| -> Cow<'_, str> { s.into() },\n    \"FlexStr 0.9 (SharedStr)\",\n    |s: String| -> flexstr09::SharedStr { s.into() },\n    \"FlexStr 0.9 (LocalStr)\",\n    |s: String| -> flexstr09::LocalStr { s.into() },\n    \"InlineFlexStr 0.1 (InlineStr)\",\n    |s: String| -> Result<inline_flexstr::InlineFlexStr<str>, _> { s.as_str().try_into() },\n    \"FlexStr 0.10 (SharedStr - As is)\",\n    |s: String| -> flexstr::SharedStr { s.into() },\n    \"FlexStr 0.10 (LocalStr - As is)\",\n    |s: String| -> flexstr::LocalStr { s.into() },\n    \"FlexStr 0.10 (SharedStr - Optimized)\",\n    |s: String| {\n        let s: flexstr::SharedStr = s.into();\n        s.optimize()\n    },\n    \"FlexStr 0.10 (LocalStr - Optimized)\",\n    |s: String| {\n        let s: flexstr::LocalStr = s.into();\n        s.optimize()\n    }\n);\n\nimport!(\n    import_borrowed_own_and_destroy,\n    \"Import as borrowed, own and destroy\",\n    \"Cow<'_, str>\",\n    |s: String| {\n        let s: Cow<'_, str> = s.as_str().into();\n        s.into_owned()\n    },\n    \"FlexStr 0.10 (SharedStr)\",\n    |s: String| {\n        let s: flexstr::SharedStr = s.as_str().into();\n        s.into_owned()\n    },\n    \"FlexStr 0.10 (LocalStr)\",\n    |s: String| {\n        let s: flexstr::LocalStr = s.as_str().into();\n        s.into_owned()\n    }\n);\n\ncriterion_group!(\n    benches,\n    import_owned_and_destroy,\n    import_borrowed_own_and_destroy\n);\ncriterion_main!(benches);\n"
  },
  {
    "path": "benchmarks/criterion.toml",
    "content": "criterion_home = \"../docs/criterion\"\n"
  },
  {
    "path": "benchmarks/src/lib.rs",
    "content": "\n"
  },
  {
    "path": "boxed_flexstr/Cargo.toml",
    "content": "[package]\nname = \"boxed_flexstr\"\nversion = \"0.1.0\"\nauthors = [\"Scott Meeuwsen <smeeuwsen@gmail.com>\"]\nlicense = \"MIT OR Apache-2.0\"\ndescription = \"A simple to use, compact, mutable boxed string type for Rust\"\nrepository = \"https://github.com/nu11ptr/flexstr/boxed_flexstr\"\ndocumentation = \"https://docs.rs/boxed_flexstr\"\nkeywords = [\"string\", \"boxed\"]\ncategories = [\n    \"data-structures\",\n    \"memory-management\",\n    \"no-std\",\n    \"text-processing\",\n]\nreadme = \"README.md\"\nedition = \"2024\"\n\n\n[features]\ndefault = [\"std\", \"str\"]\nlarge_strings = []\nsqlx_pg_arrays = [\"sqlx\", \"sqlx/postgres\"]\n# Does not use and forbids all unsafe code (unless windows_min_unsafe is also enabled, but that only impacts Windows)\nsafe = [\"flexstr_support/safe\"]\nstd = [\"flexstr_support/std\", \"serde?/std\"]\n# Uses the minimum unsafe code possible to support OsStr/Path on Windows. Doesn't impact any other string types or operating systems.\nwin_min_unsafe = [\"flexstr_support/win_min_unsafe\", \"safe\"]\n\n# String type features\nbytes = [\"flexstr_support/bytes\"]\ncstr = [\"flexstr_support/cstr\"]\nosstr = [\"flexstr_support/osstr\", \"std\"]\npath = [\"flexstr_support/path\", \"osstr\"]\nstr = [\"flexstr_support/str\"]\n\n[dependencies.flexstr_support]\npath = \"../flexstr_support\"\nversion = \"0.1.3\"\ndefault-features = false\n\n[dependencies.serde]\nversion = \"1\"\ndefault-features = false\noptional = true\n\n[dependencies.sqlx]\nversion = \"0.8\"\ndefault-features = false\noptional = true\n\n[dev-dependencies.serde_json]\nversion = \"1\"\n\n[package.metadata.docs.rs]\nfeatures = [\"bytes\", \"cstr\", \"osstr\", \"path\", \"serde\", \"std\", \"str\"]\nrustdoc-args = [\"--cfg\", \"docsrs\"]\n"
  },
  {
    "path": "boxed_flexstr/src/boxed.rs",
    "content": "use core::marker::PhantomData;\n\nuse flexstr_support::StringToFromBytes;\n\n// *** OwnedToFromBoxedInner ***\n\npub trait OwnedToFromBoxed<S: ?Sized + StringToFromBytes>\nwhere\n    S::Owned: OwnedToFromBoxed<S>,\n{\n    type BoxType;\n\n    fn into_boxed(self) -> Self::BoxType;\n\n    fn from_boxed(boxed: &mut Self::BoxType) -> Self;\n\n    fn clone_boxed(boxed: &Self::BoxType) -> Self::BoxType;\n}\n\n// *** OwnedOpsMut ***\n\npub trait OwnedOpsMut<S: ?Sized + StringToFromBytes> {\n    fn push_str(&mut self, s: &S);\n}\n\n// *** BoxedFlexStr ***\n\n#[cfg(feature = \"safe\")]\npub type BoxedFlexStr<S> = Boxed<S, Option<alloc::boxed::Box<S>>>;\n\n#[cfg(not(feature = \"safe\"))]\npub type BoxedFlexStr<S> = Boxed<S, crate::small_box::SmallBox<S>>;\n\npub struct Boxed<S: ?Sized + StringToFromBytes, B>\nwhere\n    S::Owned: OwnedToFromBoxed<S, BoxType = B>,\n{\n    inner: B,\n    _marker: PhantomData<S>,\n}\n\nimpl<S: ?Sized + StringToFromBytes, B> Boxed<S, B>\nwhere\n    S::Owned: OwnedToFromBoxed<S, BoxType = B>,\n{\n    pub fn new(s: S::Owned) -> Self {\n        Self {\n            inner: s.into_boxed(),\n            _marker: PhantomData,\n        }\n    }\n}\n\nimpl<S: ?Sized + StringToFromBytes, B> Boxed<S, B>\nwhere\n    S::Owned: OwnedToFromBoxed<S, BoxType = B> + OwnedOpsMut<S>,\n{\n    pub fn with_mut_str<F>(&mut self, f: F)\n    where\n        F: FnOnce(&mut S::Owned),\n    {\n        let mut str: S::Owned = S::Owned::from_boxed(&mut self.inner);\n        f(&mut str);\n        self.inner = str.into_boxed();\n    }\n\n    pub fn push_str(&mut self, s: &S) {\n        self.with_mut_str(|str| str.push_str(s));\n    }\n}\n\nimpl<S: ?Sized + StringToFromBytes, B> Clone for Boxed<S, B>\nwhere\n    S::Owned: OwnedToFromBoxed<S, BoxType = B>,\n{\n    fn clone(&self) -> Self {\n        Self {\n            inner: S::Owned::clone_boxed(&self.inner),\n            _marker: PhantomData,\n        }\n    }\n}\n"
  },
  {
    "path": "boxed_flexstr/src/bytes.rs",
    "content": "#[cfg(not(feature = \"std\"))]\nuse alloc::vec::Vec;\n\nuse crate::boxed::{BoxedFlexStr, OwnedOpsMut, OwnedToFromBoxed};\n#[cfg(not(feature = \"safe\"))]\nuse crate::small_box::SmallBox;\n\npub type BoxedBytes = BoxedFlexStr<[u8]>;\n\n#[cfg(not(feature = \"large_strings\"))]\nconst _: () = assert!(\n    size_of::<BoxedBytes>() <= size_of::<alloc::boxed::Box<[u8]>>(),\n    \"BoxedBytes must be less than or equal to the size of Box<[u8]>\"\n);\n\nconst _: () = assert!(\n    size_of::<Option<BoxedBytes>>() <= size_of::<Vec<u8>>(),\n    \"Option<BoxedBytes> must be less than or equal to the size of Vec<u8>\"\n);\n\n#[cfg(not(feature = \"safe\"))]\nimpl OwnedToFromBoxed<[u8]> for Vec<u8> {\n    type BoxType = SmallBox<[u8]>;\n\n    #[inline]\n    fn into_boxed(self) -> SmallBox<[u8]> {\n        let ptr = self.as_ptr();\n        let len = self.len();\n        let cap = self.capacity();\n        core::mem::forget(self);\n        // SAFETY: The raw parts are valid as they are not modified\n        unsafe { SmallBox::new(ptr, len, cap) }\n    }\n\n    #[inline]\n    fn from_boxed(boxed: &mut SmallBox<[u8]>) -> Self {\n        // SAFETY: The raw parts are valid as they are not modified\n        unsafe { Vec::from_raw_parts(boxed.ptr() as *mut u8, boxed.len(), boxed.cap()) }\n    }\n\n    #[inline]\n    fn clone_boxed(boxed: &SmallBox<[u8]>) -> SmallBox<[u8]> {\n        // SAFETY: The raw parts are valid as they are not modified\n        let v = unsafe { Vec::from_raw_parts(boxed.ptr() as *mut u8, boxed.len(), boxed.cap()) };\n        let v2 = v.clone();\n        core::mem::forget(v);\n        v2.into_boxed()\n    }\n}\n\n#[cfg(feature = \"safe\")]\nimpl OwnedToFromBoxed<[u8]> for Vec<u8> {\n    type BoxType = Option<alloc::boxed::Box<[u8]>>;\n\n    #[inline]\n    fn into_boxed(self) -> Self::BoxType {\n        Some(self.into_boxed_slice())\n    }\n\n    #[inline]\n    fn from_boxed(boxed: &mut Self::BoxType) -> Self {\n        boxed\n            .take()\n            .expect(\"Expected a vector of bytes, but got None\")\n            .into_vec()\n    }\n\n    #[inline]\n    fn clone_boxed(boxed: &Self::BoxType) -> Self::BoxType {\n        boxed.clone()\n    }\n}\n\nimpl OwnedOpsMut<[u8]> for Vec<u8> {\n    #[inline]\n    fn push_str(&mut self, s: &[u8]) {\n        self.extend_from_slice(s);\n    }\n}\n"
  },
  {
    "path": "boxed_flexstr/src/cstr.rs",
    "content": "use alloc::ffi::CString;\n#[cfg(all(not(feature = \"std\"), not(feature = \"safe\")))]\nuse alloc::vec::Vec;\nuse core::ffi::CStr;\n\nuse crate::boxed::{BoxedFlexStr, OwnedToFromBoxed};\n#[cfg(not(feature = \"safe\"))]\nuse crate::small_box::SmallBox;\n\npub type BoxedCStr = BoxedFlexStr<CStr>;\n\n#[cfg(not(feature = \"large_strings\"))]\nconst _: () = assert!(\n    size_of::<BoxedCStr>() <= size_of::<alloc::boxed::Box<CStr>>(),\n    \"BoxedCStr must be less than or equal to the size of Box<CStr>\"\n);\n\n// NOTE: We need to manually add an extra word due to `CString` being a `Box<[u8]>`, it is only 2 words vs the needed 3.\nconst _: () = assert!(\n    size_of::<Option<BoxedCStr>>() <= size_of::<CString>() + size_of::<usize>(),\n    \"Option<BoxedCStr> must be less than or equal to the size of CString\"\n);\n\n#[cfg(not(feature = \"safe\"))]\nimpl OwnedToFromBoxed<CStr> for CString {\n    type BoxType = SmallBox<CStr>;\n\n    #[inline]\n    fn into_boxed(self) -> SmallBox<CStr> {\n        let bytes = self.into_bytes_with_nul();\n        let ptr = bytes.as_ptr();\n        let len = bytes.len() - 1;\n        let cap = bytes.len();\n        core::mem::forget(bytes);\n        // SAFETY: The raw parts are valid as they are not modified\n        unsafe { SmallBox::new(ptr, len, cap - 1) }\n    }\n\n    #[inline]\n    fn from_boxed(boxed: &mut SmallBox<CStr>) -> Self {\n        // SAFETY: The raw parts are valid as they are not modified. This was previously a CString.\n        unsafe {\n            let bytes = Vec::from_raw_parts(boxed.ptr() as *mut u8, boxed.len(), boxed.cap());\n            CString::from_vec_with_nul_unchecked(bytes)\n        }\n    }\n\n    #[inline]\n    fn clone_boxed(boxed: &SmallBox<CStr>) -> SmallBox<CStr> {\n        // SAFETY: The raw parts are valid as they are not modified. This was previously a CString.\n        let s = unsafe {\n            let bytes = Vec::from_raw_parts(boxed.ptr() as *mut u8, boxed.len(), boxed.cap());\n            CString::from_vec_with_nul_unchecked(bytes)\n        };\n        let s2 = s.clone();\n        core::mem::forget(s);\n        s2.into_boxed()\n    }\n}\n\n#[cfg(feature = \"safe\")]\nimpl OwnedToFromBoxed<CStr> for CString {\n    type BoxType = Option<alloc::boxed::Box<CStr>>;\n\n    #[inline]\n    fn into_boxed(self) -> Self::BoxType {\n        Some(self.into_boxed_c_str())\n    }\n\n    #[inline]\n    fn from_boxed(boxed: &mut Self::BoxType) -> Self {\n        boxed\n            .take()\n            .expect(\"Expected a string, but got None\")\n            .into_c_string()\n    }\n\n    #[inline]\n    fn clone_boxed(boxed: &Self::BoxType) -> Self::BoxType {\n        boxed.clone()\n    }\n}\n"
  },
  {
    "path": "boxed_flexstr/src/lib.rs",
    "content": "#![cfg_attr(not(feature = \"std\"), no_std)]\n\nextern crate alloc;\n\nmod boxed;\n#[cfg(feature = \"bytes\")]\nmod bytes;\n#[cfg(feature = \"cstr\")]\nmod cstr;\n#[cfg(all(feature = \"std\", feature = \"osstr\"))]\nmod osstr;\n#[cfg(all(feature = \"std\", feature = \"path\"))]\nmod path;\n#[cfg(not(feature = \"safe\"))]\nmod small_box;\n#[cfg(feature = \"str\")]\nmod str;\n\npub use boxed::BoxedFlexStr;\n#[cfg(feature = \"bytes\")]\npub use bytes::BoxedBytes;\n#[cfg(feature = \"cstr\")]\npub use cstr::BoxedCStr;\n#[cfg(all(feature = \"std\", feature = \"osstr\"))]\npub use osstr::BoxedOsStr;\n#[cfg(all(feature = \"std\", feature = \"path\"))]\npub use path::BoxedPath;\n#[cfg(feature = \"str\")]\npub use str::BoxedStr;\n"
  },
  {
    "path": "boxed_flexstr/src/osstr.rs",
    "content": "use std::ffi::{OsStr, OsString};\n\nuse crate::boxed::{BoxedFlexStr, OwnedOpsMut, OwnedToFromBoxed};\n#[cfg(not(feature = \"safe\"))]\nuse crate::small_box::SmallBox;\n\npub type BoxedOsStr = BoxedFlexStr<OsStr>;\n\n#[cfg(not(feature = \"large_strings\"))]\nconst _: () = assert!(\n    size_of::<BoxedOsStr>() <= size_of::<Box<OsStr>>(),\n    \"BoxedOsStr must be less than or equal to the size of Box<OsStr>\"\n);\n\nconst _: () = assert!(\n    size_of::<Option<BoxedOsStr>>() <= size_of::<OsString>(),\n    \"Option<BoxedOsStr> must be less than or equal to the size of OsString\"\n);\n\n#[cfg(not(feature = \"safe\"))]\nimpl OwnedToFromBoxed<OsStr> for OsString {\n    type BoxType = SmallBox<OsStr>;\n\n    #[inline]\n    fn into_boxed(self) -> SmallBox<OsStr> {\n        let bytes = self.into_encoded_bytes();\n        let ptr = bytes.as_ptr();\n        let len = bytes.len();\n        let cap = bytes.capacity();\n        core::mem::forget(bytes);\n        // SAFETY: The raw parts are valid as they are not modified\n        unsafe { SmallBox::new(ptr, len, cap) }\n    }\n\n    #[inline]\n    fn from_boxed(boxed: &mut SmallBox<OsStr>) -> Self {\n        // SAFETY: The raw parts are valid as they are not modified. This was previously an OsString.\n        unsafe {\n            let bytes = Vec::from_raw_parts(boxed.ptr() as *mut u8, boxed.len(), boxed.cap());\n            OsString::from_encoded_bytes_unchecked(bytes)\n        }\n    }\n\n    #[inline]\n    fn clone_boxed(boxed: &SmallBox<OsStr>) -> SmallBox<OsStr> {\n        // SAFETY: The raw parts are valid as they are not modified. This was previously an OsString.\n        let s = unsafe {\n            let bytes = Vec::from_raw_parts(boxed.ptr() as *mut u8, boxed.len(), boxed.cap());\n            OsString::from_encoded_bytes_unchecked(bytes)\n        };\n        let s2 = s.clone();\n        core::mem::forget(s);\n        s2.into_boxed()\n    }\n}\n\n#[cfg(feature = \"safe\")]\nimpl OwnedToFromBoxed<OsStr> for OsString {\n    type BoxType = Option<Box<OsStr>>;\n\n    #[inline]\n    fn into_boxed(self) -> Self::BoxType {\n        Some(self.into_boxed_os_str())\n    }\n\n    #[inline]\n    fn from_boxed(boxed: &mut Self::BoxType) -> Self {\n        boxed\n            .take()\n            .expect(\"Expected a string, but got None\")\n            .into_os_string()\n    }\n\n    #[inline]\n    fn clone_boxed(boxed: &Self::BoxType) -> Self::BoxType {\n        boxed.clone()\n    }\n}\n\nimpl OwnedOpsMut<OsStr> for OsString {\n    #[inline]\n    fn push_str(&mut self, s: &OsStr) {\n        self.push(s);\n    }\n}\n"
  },
  {
    "path": "boxed_flexstr/src/path.rs",
    "content": "use std::path::{Path, PathBuf};\n\nuse crate::boxed::{BoxedFlexStr, OwnedOpsMut, OwnedToFromBoxed};\n#[cfg(not(feature = \"safe\"))]\nuse crate::small_box::SmallBox;\n\npub type BoxedPath = BoxedFlexStr<Path>;\n\n#[cfg(not(feature = \"large_strings\"))]\nconst _: () = assert!(\n    size_of::<BoxedPath>() <= size_of::<Box<Path>>(),\n    \"BoxedPath must be less than or equal to the size of Box<Path>\"\n);\n\nconst _: () = assert!(\n    size_of::<Option<BoxedPath>>() <= size_of::<PathBuf>(),\n    \"Option<BoxedPath> must be less than or equal to the size of PathBuf\"\n);\n\n#[cfg(not(feature = \"safe\"))]\nimpl OwnedToFromBoxed<Path> for PathBuf {\n    type BoxType = SmallBox<Path>;\n\n    #[inline]\n    fn into_boxed(self) -> SmallBox<Path> {\n        let bytes = self.into_os_string().into_encoded_bytes();\n        let ptr = bytes.as_ptr();\n        let len = bytes.len();\n        let cap = bytes.capacity();\n        core::mem::forget(bytes);\n        // SAFETY: The raw parts are valid as they are not modified\n        unsafe { SmallBox::new(ptr, len, cap) }\n    }\n\n    #[inline]\n    fn from_boxed(boxed: &mut SmallBox<Path>) -> Self {\n        // SAFETY: The raw parts are valid as they are not modified. This was previously an OsString.\n        unsafe {\n            let bytes = Vec::from_raw_parts(boxed.ptr() as *mut u8, boxed.len(), boxed.cap());\n            std::ffi::OsString::from_encoded_bytes_unchecked(bytes).into()\n        }\n    }\n\n    #[inline]\n    fn clone_boxed(boxed: &SmallBox<Path>) -> SmallBox<Path> {\n        // SAFETY: The raw parts are valid as they are not modified. This was previously an OsString.\n        let s: PathBuf = unsafe {\n            let bytes = Vec::from_raw_parts(boxed.ptr() as *mut u8, boxed.len(), boxed.cap());\n            std::ffi::OsString::from_encoded_bytes_unchecked(bytes).into()\n        };\n        let s2 = s.clone();\n        core::mem::forget(s);\n        s2.into_boxed()\n    }\n}\n\n#[cfg(feature = \"safe\")]\nimpl OwnedToFromBoxed<Path> for PathBuf {\n    type BoxType = Option<Box<Path>>;\n\n    #[inline]\n    fn into_boxed(self) -> Self::BoxType {\n        Some(self.into_boxed_path())\n    }\n\n    #[inline]\n    fn from_boxed(boxed: &mut Self::BoxType) -> Self {\n        boxed\n            .take()\n            .expect(\"Expected a string, but got None\")\n            .into_path_buf()\n    }\n\n    #[inline]\n    fn clone_boxed(boxed: &Self::BoxType) -> Self::BoxType {\n        boxed.clone()\n    }\n}\n\nimpl OwnedOpsMut<Path> for PathBuf {\n    #[inline]\n    fn push_str(&mut self, s: &Path) {\n        self.push(s);\n    }\n}\n"
  },
  {
    "path": "boxed_flexstr/src/small_box.rs",
    "content": "use core::marker::PhantomData;\nuse core::ptr::NonNull;\n\nuse flexstr_support::StringToFromBytes;\n\nuse crate::boxed::OwnedToFromBoxed;\n\n// *** LengthCapacity - 32-bit (16-bit length/capacity) ***\n\n#[cfg(all(not(feature = \"large_strings\"), target_pointer_width = \"32\"))]\n#[derive(Clone, Copy)]\nstruct LengthCapacity {\n    len: u16,\n    cap: u16,\n}\n\n#[cfg(all(not(feature = \"large_strings\"), target_pointer_width = \"32\"))]\nimpl LengthCapacity {\n    const MAX_CAPACITY: usize = u16::MAX as usize;\n\n    #[inline]\n    pub fn new(len: usize, cap: usize) -> Self {\n        if cap > Self::MAX_CAPACITY {\n            panic!(\"String is too large after mutation\");\n        }\n        Self {\n            len: len as u16,\n            cap: cap as u16,\n        }\n    }\n    #[inline]\n    pub fn len(&self) -> usize {\n        self.len as usize\n    }\n\n    #[inline]\n    pub fn cap(&self) -> usize {\n        self.cap as usize\n    }\n}\n\n// *** LengthCapacity - 32-bit (24-bit length/capacity) ***\n\n#[cfg(all(feature = \"large_strings\", target_pointer_width = \"32\"))]\n#[derive(Clone, Copy)]\nstruct LengthCapacity {\n    len: u16,\n    cap: u16,\n    len_extra: u8,\n    cap_extra: u8,\n}\n\n#[cfg(all(feature = \"large_strings\", target_pointer_width = \"32\"))]\nimpl LengthCapacity {\n    const MAX_CAPACITY: usize = u16::MAX as usize + ((u8::MAX as usize) << 16);\n\n    #[inline]\n    pub fn new(len: usize, cap: usize) -> Self {\n        if cap > Self::MAX_CAPACITY {\n            panic!(\"String is too large after mutation\");\n        }\n        Self {\n            len: len as u16,\n            cap: cap as u16,\n            len_extra: (len >> 16) as u8,\n            cap_extra: (cap >> 16) as u8,\n        }\n    }\n\n    #[inline]\n    pub fn len(&self) -> usize {\n        self.len as usize + ((self.len_extra as usize) << 16)\n    }\n\n    #[inline]\n    pub fn cap(&self) -> usize {\n        self.cap as usize + ((self.cap_extra as usize) << 16)\n    }\n}\n\n// *** LengthCapacity - 64-bit (32-bit length/capacity) ***\n\n#[cfg(all(not(feature = \"large_strings\"), target_pointer_width = \"64\"))]\n#[derive(Clone, Copy)]\nstruct LengthCapacity {\n    len: u32,\n    cap: u32,\n}\n\n#[cfg(all(not(feature = \"large_strings\"), target_pointer_width = \"64\"))]\nimpl LengthCapacity {\n    const MAX_CAPACITY: usize = u32::MAX as usize;\n\n    #[inline]\n    pub fn new(len: usize, cap: usize) -> Self {\n        if cap > Self::MAX_CAPACITY {\n            panic!(\"String is too large after mutation\");\n        }\n        Self {\n            len: len as u32,\n            cap: cap as u32,\n        }\n    }\n\n    #[inline]\n    pub fn len(&self) -> usize {\n        self.len as usize\n    }\n\n    #[inline]\n    pub fn cap(&self) -> usize {\n        self.cap as usize\n    }\n}\n\n// *** LengthCapacity - 64-bit (48-bit length/capacity) ***\n\n#[cfg(all(feature = \"large_strings\", target_pointer_width = \"64\"))]\n#[derive(Clone, Copy)]\nstruct LengthCapacity {\n    len: u32,\n    cap: u32,\n    len_extra: u16,\n    cap_extra: u16,\n}\n\n#[cfg(all(feature = \"large_strings\", target_pointer_width = \"64\"))]\nimpl LengthCapacity {\n    const MAX_CAPACITY: usize = u32::MAX as usize + ((u16::MAX as usize) << 32);\n\n    #[inline]\n    pub fn new(len: usize, cap: usize) -> Self {\n        if cap > Self::MAX_CAPACITY {\n            panic!(\"String is too large after mutation\");\n        }\n        Self {\n            len: len as u32,\n            cap: cap as u32,\n            len_extra: (len >> 32) as u16,\n            cap_extra: (cap >> 32) as u16,\n        }\n    }\n\n    #[inline]\n    pub fn len(&self) -> usize {\n        self.len as usize + ((self.len_extra as usize) << 32)\n    }\n\n    #[inline]\n    pub fn cap(&self) -> usize {\n        self.cap as usize + ((self.cap_extra as usize) << 32)\n    }\n}\n\n// *** SmallBox ***\n\npub struct SmallBox<S: ?Sized + StringToFromBytes>\nwhere\n    S::Owned: OwnedToFromBoxed<S, BoxType = SmallBox<S>>,\n{\n    ptr: NonNull<u8>,\n    len_cap: LengthCapacity,\n    _marker: PhantomData<S>,\n}\n\nimpl<S: ?Sized + StringToFromBytes> SmallBox<S>\nwhere\n    S::Owned: OwnedToFromBoxed<S, BoxType = SmallBox<S>>,\n{\n    pub(crate) unsafe fn new(ptr: *const u8, len: usize, cap: usize) -> Self {\n        Self {\n            // SAFETY: The caller is responsible for ensuring the pointer is valid\n            ptr: unsafe { NonNull::new_unchecked(ptr as *mut u8) },\n            len_cap: LengthCapacity::new(len, cap),\n            _marker: PhantomData,\n        }\n    }\n\n    pub fn ptr(&self) -> *const u8 {\n        self.ptr.as_ptr()\n    }\n\n    pub fn len(&self) -> usize {\n        self.len_cap.len()\n    }\n\n    pub fn cap(&self) -> usize {\n        self.len_cap.cap()\n    }\n}\n\nimpl<S: ?Sized + StringToFromBytes> Drop for SmallBox<S>\nwhere\n    S::Owned: OwnedToFromBoxed<S, BoxType = SmallBox<S>>,\n{\n    fn drop(&mut self) {\n        S::Owned::from_boxed(self);\n    }\n}\n"
  },
  {
    "path": "boxed_flexstr/src/str.rs",
    "content": "#[cfg(not(feature = \"std\"))]\nuse alloc::string::String;\n\nuse crate::boxed::{BoxedFlexStr, OwnedOpsMut, OwnedToFromBoxed};\n#[cfg(not(feature = \"safe\"))]\nuse crate::small_box::SmallBox;\n\npub type BoxedStr = BoxedFlexStr<str>;\n\n#[cfg(not(feature = \"large_strings\"))]\nconst _: () = assert!(\n    size_of::<BoxedStr>() <= size_of::<alloc::boxed::Box<str>>(),\n    \"BoxedStr must be less than or equal to the size of Box<str>\"\n);\n\nconst _: () = assert!(\n    size_of::<Option<BoxedStr>>() <= size_of::<String>(),\n    \"Option<BoxedStr> must be less than or equal to the size of String\"\n);\n\n#[cfg(not(feature = \"safe\"))]\nimpl OwnedToFromBoxed<str> for String {\n    type BoxType = SmallBox<str>;\n\n    #[inline]\n    fn into_boxed(self) -> SmallBox<str> {\n        let ptr = self.as_str().as_ptr();\n        let len = self.len();\n        let cap = self.capacity();\n        core::mem::forget(self);\n        // SAFETY: The raw parts are valid as they are not modified\n        unsafe { SmallBox::new(ptr, len, cap) }\n    }\n\n    #[inline]\n    fn from_boxed(boxed: &mut SmallBox<str>) -> Self {\n        // SAFETY: The raw parts are valid as they are not modified\n        unsafe { String::from_raw_parts(boxed.ptr() as *mut u8, boxed.len(), boxed.cap()) }\n    }\n\n    #[inline]\n    fn clone_boxed(boxed: &SmallBox<str>) -> SmallBox<str> {\n        // SAFETY: The raw parts are valid as they are not modified\n        let s = unsafe { String::from_raw_parts(boxed.ptr() as *mut u8, boxed.len(), boxed.cap()) };\n        let s2 = s.clone();\n        core::mem::forget(s);\n        s2.into_boxed()\n    }\n}\n\n#[cfg(feature = \"safe\")]\nimpl OwnedToFromBoxed<str> for String {\n    type BoxType = Option<alloc::boxed::Box<str>>;\n\n    #[inline]\n    fn into_boxed(self) -> Self::BoxType {\n        Some(self.into_boxed_str())\n    }\n\n    #[inline]\n    fn from_boxed(boxed: &mut Self::BoxType) -> Self {\n        boxed\n            .take()\n            .expect(\"Expected a string, but got None\")\n            .into_string()\n    }\n\n    #[inline]\n    fn clone_boxed(boxed: &Self::BoxType) -> Self::BoxType {\n        boxed.clone()\n    }\n}\n\nimpl OwnedOpsMut<str> for String {\n    #[inline]\n    fn push_str(&mut self, s: &str) {\n        self.push_str(s);\n    }\n}\n"
  },
  {
    "path": "docs/criterion/Clone/0/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/0 Summary - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/0</h2>\n        <h3>Violin Plot</h3>\n        <a href=\"violin.svg\">\n            <img src=\"violin.svg\" alt=\"Violin Plot\" />\n        </a>\n        <p>This chart shows the relationship between function/parameter and iteration time. The thickness of the shaded\n            region indicates the probability that a measurement of the given function/parameter would take a particular\n            length of time.</p>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/String/0/report/index.html\">\n                <h4>Clone/String/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/String/0/report/pdf.svg\">\n                                <img src=\"../../../Clone/String/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/String/0/report/regression.svg\">\n                                <img src=\"../../../Clone/String/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/Rc_str_/0/report/index.html\">\n                <h4>Clone/Rc&lt;str&gt;/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/Rc_str_/0/report/pdf.svg\">\n                                <img src=\"../../../Clone/Rc_str_/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/Rc_str_/0/report/regression.svg\">\n                                <img src=\"../../../Clone/Rc_str_/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/Arc_str_/0/report/index.html\">\n                <h4>Clone/Arc&lt;str&gt;/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/Arc_str_/0/report/pdf.svg\">\n                                <img src=\"../../../Clone/Arc_str_/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/Arc_str_/0/report/regression.svg\">\n                                <img src=\"../../../Clone/Arc_str_/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/FlexStr 0.9 (LocalStr)/0/report/index.html\">\n                <h4>Clone/FlexStr 0.9 (LocalStr)/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.9 (LocalStr)/0/report/pdf.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.9 (LocalStr)/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.9 (LocalStr)/0/report/regression.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.9 (LocalStr)/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/FlexStr 0.9 (SharedStr)/0/report/index.html\">\n                <h4>Clone/FlexStr 0.9 (SharedStr)/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.9 (SharedStr)/0/report/pdf.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.9 (SharedStr)/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.9 (SharedStr)/0/report/regression.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.9 (SharedStr)/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/InlineFlexStr 0.1 (InlineStr)/0/report/index.html\">\n                <h4>Clone/InlineFlexStr 0.1 (InlineStr)/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/InlineFlexStr 0.1 (InlineStr)/0/report/pdf.svg\">\n                                <img src=\"../../../Clone/InlineFlexStr 0.1 (InlineStr)/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/InlineFlexStr 0.1 (InlineStr)/0/report/regression.svg\">\n                                <img src=\"../../../Clone/InlineFlexStr 0.1 (InlineStr)/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/FlexStr 0.10 (LocalStr - Boxed)/0/report/index.html\">\n                <h4>Clone/FlexStr 0.10 (LocalStr - Boxed)/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (LocalStr - Boxed)/0/report/pdf.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (LocalStr - Boxed)/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (LocalStr - Boxed)/0/report/regression.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (LocalStr - Boxed)/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/FlexStr 0.10 (SharedStr - Boxed)/0/report/index.html\">\n                <h4>Clone/FlexStr 0.10 (SharedStr - Boxed)/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (SharedStr - Boxed)/0/report/pdf.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (SharedStr - Boxed)/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (SharedStr - Boxed)/0/report/regression.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (SharedStr - Boxed)/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/FlexStr 0.10 (LocalStr - Optimized)/0/report/index.html\">\n                <h4>Clone/FlexStr 0.10 (LocalStr - Optimized)/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (LocalStr - Optimized)/0/report/pdf.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (LocalStr - Optimized)/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (LocalStr - Optimized)/0/report/regression.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (LocalStr - Optimized)/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/FlexStr 0.10 (SharedStr - Optimized)/0/report/index.html\">\n                <h4>Clone/FlexStr 0.10 (SharedStr - Optimized)/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (SharedStr - Optimized)/0/report/pdf.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (SharedStr - Optimized)/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (SharedStr - Optimized)/0/report/regression.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (SharedStr - Optimized)/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Clone/10/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/10 Summary - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/10</h2>\n        <h3>Violin Plot</h3>\n        <a href=\"violin.svg\">\n            <img src=\"violin.svg\" alt=\"Violin Plot\" />\n        </a>\n        <p>This chart shows the relationship between function/parameter and iteration time. The thickness of the shaded\n            region indicates the probability that a measurement of the given function/parameter would take a particular\n            length of time.</p>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/String/10/report/index.html\">\n                <h4>Clone/String/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/String/10/report/pdf.svg\">\n                                <img src=\"../../../Clone/String/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/String/10/report/regression.svg\">\n                                <img src=\"../../../Clone/String/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/Rc_str_/10/report/index.html\">\n                <h4>Clone/Rc&lt;str&gt;/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/Rc_str_/10/report/pdf.svg\">\n                                <img src=\"../../../Clone/Rc_str_/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/Rc_str_/10/report/regression.svg\">\n                                <img src=\"../../../Clone/Rc_str_/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/Arc_str_/10/report/index.html\">\n                <h4>Clone/Arc&lt;str&gt;/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/Arc_str_/10/report/pdf.svg\">\n                                <img src=\"../../../Clone/Arc_str_/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/Arc_str_/10/report/regression.svg\">\n                                <img src=\"../../../Clone/Arc_str_/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/FlexStr 0.9 (LocalStr)/10/report/index.html\">\n                <h4>Clone/FlexStr 0.9 (LocalStr)/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.9 (LocalStr)/10/report/pdf.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.9 (LocalStr)/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.9 (LocalStr)/10/report/regression.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.9 (LocalStr)/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/FlexStr 0.9 (SharedStr)/10/report/index.html\">\n                <h4>Clone/FlexStr 0.9 (SharedStr)/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.9 (SharedStr)/10/report/pdf.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.9 (SharedStr)/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.9 (SharedStr)/10/report/regression.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.9 (SharedStr)/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/InlineFlexStr 0.1 (InlineStr)/10/report/index.html\">\n                <h4>Clone/InlineFlexStr 0.1 (InlineStr)/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/InlineFlexStr 0.1 (InlineStr)/10/report/pdf.svg\">\n                                <img src=\"../../../Clone/InlineFlexStr 0.1 (InlineStr)/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/InlineFlexStr 0.1 (InlineStr)/10/report/regression.svg\">\n                                <img src=\"../../../Clone/InlineFlexStr 0.1 (InlineStr)/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/FlexStr 0.10 (LocalStr - Boxed)/10/report/index.html\">\n                <h4>Clone/FlexStr 0.10 (LocalStr - Boxed)/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (LocalStr - Boxed)/10/report/pdf.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (LocalStr - Boxed)/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (LocalStr - Boxed)/10/report/regression.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (LocalStr - Boxed)/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/FlexStr 0.10 (SharedStr - Boxed)/10/report/index.html\">\n                <h4>Clone/FlexStr 0.10 (SharedStr - Boxed)/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (SharedStr - Boxed)/10/report/pdf.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (SharedStr - Boxed)/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (SharedStr - Boxed)/10/report/regression.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (SharedStr - Boxed)/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/FlexStr 0.10 (LocalStr - Optimized)/10/report/index.html\">\n                <h4>Clone/FlexStr 0.10 (LocalStr - Optimized)/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (LocalStr - Optimized)/10/report/pdf.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (LocalStr - Optimized)/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (LocalStr - Optimized)/10/report/regression.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (LocalStr - Optimized)/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/FlexStr 0.10 (SharedStr - Optimized)/10/report/index.html\">\n                <h4>Clone/FlexStr 0.10 (SharedStr - Optimized)/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (SharedStr - Optimized)/10/report/pdf.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (SharedStr - Optimized)/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (SharedStr - Optimized)/10/report/regression.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (SharedStr - Optimized)/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Clone/100/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/100 Summary - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/100</h2>\n        <h3>Violin Plot</h3>\n        <a href=\"violin.svg\">\n            <img src=\"violin.svg\" alt=\"Violin Plot\" />\n        </a>\n        <p>This chart shows the relationship between function/parameter and iteration time. The thickness of the shaded\n            region indicates the probability that a measurement of the given function/parameter would take a particular\n            length of time.</p>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/String/100/report/index.html\">\n                <h4>Clone/String/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/String/100/report/pdf.svg\">\n                                <img src=\"../../../Clone/String/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/String/100/report/regression.svg\">\n                                <img src=\"../../../Clone/String/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/Rc_str_/100/report/index.html\">\n                <h4>Clone/Rc&lt;str&gt;/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/Rc_str_/100/report/pdf.svg\">\n                                <img src=\"../../../Clone/Rc_str_/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/Rc_str_/100/report/regression.svg\">\n                                <img src=\"../../../Clone/Rc_str_/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/Arc_str_/100/report/index.html\">\n                <h4>Clone/Arc&lt;str&gt;/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/Arc_str_/100/report/pdf.svg\">\n                                <img src=\"../../../Clone/Arc_str_/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/Arc_str_/100/report/regression.svg\">\n                                <img src=\"../../../Clone/Arc_str_/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/FlexStr 0.9 (LocalStr)/100/report/index.html\">\n                <h4>Clone/FlexStr 0.9 (LocalStr)/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.9 (LocalStr)/100/report/pdf.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.9 (LocalStr)/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.9 (LocalStr)/100/report/regression.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.9 (LocalStr)/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/FlexStr 0.9 (SharedStr)/100/report/index.html\">\n                <h4>Clone/FlexStr 0.9 (SharedStr)/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.9 (SharedStr)/100/report/pdf.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.9 (SharedStr)/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.9 (SharedStr)/100/report/regression.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.9 (SharedStr)/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/InlineFlexStr 0.1 (InlineStr)/100/report/index.html\">\n                <h4>Clone/InlineFlexStr 0.1 (InlineStr)/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/InlineFlexStr 0.1 (InlineStr)/100/report/pdf.svg\">\n                                <img src=\"../../../Clone/InlineFlexStr 0.1 (InlineStr)/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/InlineFlexStr 0.1 (InlineStr)/100/report/regression.svg\">\n                                <img src=\"../../../Clone/InlineFlexStr 0.1 (InlineStr)/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/FlexStr 0.10 (LocalStr - Boxed)/100/report/index.html\">\n                <h4>Clone/FlexStr 0.10 (LocalStr - Boxed)/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (LocalStr - Boxed)/100/report/pdf.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (LocalStr - Boxed)/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (LocalStr - Boxed)/100/report/regression.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (LocalStr - Boxed)/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/FlexStr 0.10 (SharedStr - Boxed)/100/report/index.html\">\n                <h4>Clone/FlexStr 0.10 (SharedStr - Boxed)/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (SharedStr - Boxed)/100/report/pdf.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (SharedStr - Boxed)/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (SharedStr - Boxed)/100/report/regression.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (SharedStr - Boxed)/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/FlexStr 0.10 (LocalStr - Optimized)/100/report/index.html\">\n                <h4>Clone/FlexStr 0.10 (LocalStr - Optimized)/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (LocalStr - Optimized)/100/report/pdf.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (LocalStr - Optimized)/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (LocalStr - Optimized)/100/report/regression.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (LocalStr - Optimized)/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/FlexStr 0.10 (SharedStr - Optimized)/100/report/index.html\">\n                <h4>Clone/FlexStr 0.10 (SharedStr - Optimized)/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (SharedStr - Optimized)/100/report/pdf.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (SharedStr - Optimized)/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (SharedStr - Optimized)/100/report/regression.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (SharedStr - Optimized)/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Clone/20/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/20 Summary - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/20</h2>\n        <h3>Violin Plot</h3>\n        <a href=\"violin.svg\">\n            <img src=\"violin.svg\" alt=\"Violin Plot\" />\n        </a>\n        <p>This chart shows the relationship between function/parameter and iteration time. The thickness of the shaded\n            region indicates the probability that a measurement of the given function/parameter would take a particular\n            length of time.</p>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/String/20/report/index.html\">\n                <h4>Clone/String/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/String/20/report/pdf.svg\">\n                                <img src=\"../../../Clone/String/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/String/20/report/regression.svg\">\n                                <img src=\"../../../Clone/String/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/Rc_str_/20/report/index.html\">\n                <h4>Clone/Rc&lt;str&gt;/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/Rc_str_/20/report/pdf.svg\">\n                                <img src=\"../../../Clone/Rc_str_/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/Rc_str_/20/report/regression.svg\">\n                                <img src=\"../../../Clone/Rc_str_/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/Arc_str_/20/report/index.html\">\n                <h4>Clone/Arc&lt;str&gt;/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/Arc_str_/20/report/pdf.svg\">\n                                <img src=\"../../../Clone/Arc_str_/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/Arc_str_/20/report/regression.svg\">\n                                <img src=\"../../../Clone/Arc_str_/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/FlexStr 0.9 (LocalStr)/20/report/index.html\">\n                <h4>Clone/FlexStr 0.9 (LocalStr)/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.9 (LocalStr)/20/report/pdf.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.9 (LocalStr)/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.9 (LocalStr)/20/report/regression.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.9 (LocalStr)/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/FlexStr 0.9 (SharedStr)/20/report/index.html\">\n                <h4>Clone/FlexStr 0.9 (SharedStr)/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.9 (SharedStr)/20/report/pdf.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.9 (SharedStr)/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.9 (SharedStr)/20/report/regression.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.9 (SharedStr)/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/InlineFlexStr 0.1 (InlineStr)/20/report/index.html\">\n                <h4>Clone/InlineFlexStr 0.1 (InlineStr)/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/InlineFlexStr 0.1 (InlineStr)/20/report/pdf.svg\">\n                                <img src=\"../../../Clone/InlineFlexStr 0.1 (InlineStr)/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/InlineFlexStr 0.1 (InlineStr)/20/report/regression.svg\">\n                                <img src=\"../../../Clone/InlineFlexStr 0.1 (InlineStr)/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/FlexStr 0.10 (LocalStr - Boxed)/20/report/index.html\">\n                <h4>Clone/FlexStr 0.10 (LocalStr - Boxed)/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (LocalStr - Boxed)/20/report/pdf.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (LocalStr - Boxed)/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (LocalStr - Boxed)/20/report/regression.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (LocalStr - Boxed)/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/FlexStr 0.10 (SharedStr - Boxed)/20/report/index.html\">\n                <h4>Clone/FlexStr 0.10 (SharedStr - Boxed)/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (SharedStr - Boxed)/20/report/pdf.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (SharedStr - Boxed)/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (SharedStr - Boxed)/20/report/regression.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (SharedStr - Boxed)/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/FlexStr 0.10 (LocalStr - Optimized)/20/report/index.html\">\n                <h4>Clone/FlexStr 0.10 (LocalStr - Optimized)/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (LocalStr - Optimized)/20/report/pdf.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (LocalStr - Optimized)/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (LocalStr - Optimized)/20/report/regression.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (LocalStr - Optimized)/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/FlexStr 0.10 (SharedStr - Optimized)/20/report/index.html\">\n                <h4>Clone/FlexStr 0.10 (SharedStr - Optimized)/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (SharedStr - Optimized)/20/report/pdf.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (SharedStr - Optimized)/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (SharedStr - Optimized)/20/report/regression.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (SharedStr - Optimized)/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Clone/500/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/500 Summary - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/500</h2>\n        <h3>Violin Plot</h3>\n        <a href=\"violin.svg\">\n            <img src=\"violin.svg\" alt=\"Violin Plot\" />\n        </a>\n        <p>This chart shows the relationship between function/parameter and iteration time. The thickness of the shaded\n            region indicates the probability that a measurement of the given function/parameter would take a particular\n            length of time.</p>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/String/500/report/index.html\">\n                <h4>Clone/String/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/String/500/report/pdf.svg\">\n                                <img src=\"../../../Clone/String/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/String/500/report/regression.svg\">\n                                <img src=\"../../../Clone/String/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/Rc_str_/500/report/index.html\">\n                <h4>Clone/Rc&lt;str&gt;/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/Rc_str_/500/report/pdf.svg\">\n                                <img src=\"../../../Clone/Rc_str_/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/Rc_str_/500/report/regression.svg\">\n                                <img src=\"../../../Clone/Rc_str_/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/Arc_str_/500/report/index.html\">\n                <h4>Clone/Arc&lt;str&gt;/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/Arc_str_/500/report/pdf.svg\">\n                                <img src=\"../../../Clone/Arc_str_/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/Arc_str_/500/report/regression.svg\">\n                                <img src=\"../../../Clone/Arc_str_/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/FlexStr 0.9 (LocalStr)/500/report/index.html\">\n                <h4>Clone/FlexStr 0.9 (LocalStr)/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.9 (LocalStr)/500/report/pdf.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.9 (LocalStr)/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.9 (LocalStr)/500/report/regression.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.9 (LocalStr)/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/FlexStr 0.9 (SharedStr)/500/report/index.html\">\n                <h4>Clone/FlexStr 0.9 (SharedStr)/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.9 (SharedStr)/500/report/pdf.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.9 (SharedStr)/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.9 (SharedStr)/500/report/regression.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.9 (SharedStr)/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/InlineFlexStr 0.1 (InlineStr)/500/report/index.html\">\n                <h4>Clone/InlineFlexStr 0.1 (InlineStr)/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/InlineFlexStr 0.1 (InlineStr)/500/report/pdf.svg\">\n                                <img src=\"../../../Clone/InlineFlexStr 0.1 (InlineStr)/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/InlineFlexStr 0.1 (InlineStr)/500/report/regression.svg\">\n                                <img src=\"../../../Clone/InlineFlexStr 0.1 (InlineStr)/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/FlexStr 0.10 (LocalStr - Boxed)/500/report/index.html\">\n                <h4>Clone/FlexStr 0.10 (LocalStr - Boxed)/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (LocalStr - Boxed)/500/report/pdf.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (LocalStr - Boxed)/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (LocalStr - Boxed)/500/report/regression.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (LocalStr - Boxed)/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/FlexStr 0.10 (SharedStr - Boxed)/500/report/index.html\">\n                <h4>Clone/FlexStr 0.10 (SharedStr - Boxed)/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (SharedStr - Boxed)/500/report/pdf.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (SharedStr - Boxed)/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (SharedStr - Boxed)/500/report/regression.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (SharedStr - Boxed)/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/FlexStr 0.10 (LocalStr - Optimized)/500/report/index.html\">\n                <h4>Clone/FlexStr 0.10 (LocalStr - Optimized)/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (LocalStr - Optimized)/500/report/pdf.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (LocalStr - Optimized)/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (LocalStr - Optimized)/500/report/regression.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (LocalStr - Optimized)/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/FlexStr 0.10 (SharedStr - Optimized)/500/report/index.html\">\n                <h4>Clone/FlexStr 0.10 (SharedStr - Optimized)/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (SharedStr - Optimized)/500/report/pdf.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (SharedStr - Optimized)/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (SharedStr - Optimized)/500/report/regression.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (SharedStr - Optimized)/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
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  {
    "path": "docs/criterion/Clone/Arc_str_/0/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/Arc&lt;str&gt;/0 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/Arc&lt;str&gt;/0</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">94.512 µs</td>\n                                <td>94.568 µs</td>\n                                <td class=\"ci-bound\">94.639 µs</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.9971762</td>\n                                <td>0.9972238</td>\n                                <td class=\"ci-bound\">0.9971455</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">94.665 µs</td>\n                                <td>94.802 µs</td>\n                                <td class=\"ci-bound\">94.963 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">484.03 ns</td>\n                                <td>770.29 ns</td>\n                                <td class=\"ci-bound\">1.0266 µs</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">94.490 µs</td>\n                                <td>94.549 µs</td>\n                                <td class=\"ci-bound\">94.599 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">128.45 ns</td>\n                                <td>175.07 ns</td>\n                                <td class=\"ci-bound\">242.56 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−0.3508%</td>\n                            <td>−0.1019%</td>\n                            <td class=\"ci-bound\">+0.1583%</td>\n                            <td>(p = 0.45 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Clone/Arc_str_/10/base/benchmark.json",
    "content": "{\"group_id\":\"Clone\",\"function_id\":\"Arc<str>\",\"value_str\":\"10\",\"throughput\":null,\"full_id\":\"Clone/Arc<str>/10\",\"directory_name\":\"Clone/Arc_str_/10\",\"title\":\"Clone/Arc<str>/10\"}"
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    "path": "docs/criterion/Clone/Arc_str_/10/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":94657.04291262414,\"upper_bound\":94882.48374840121},\"point_estimate\":94759.97755355037,\"standard_error\":57.656060400096756},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":94557.17965367965,\"upper_bound\":94611.5646002596},\"point_estimate\":94581.08243870294,\"standard_error\":14.011081679489106},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":103.10036036170625,\"upper_bound\":181.55105382842055},\"point_estimate\":140.20897423945428,\"standard_error\":19.55064984006466},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":94579.15155031881,\"upper_bound\":94757.74425079688},\"point_estimate\":94655.17162889423,\"standard_error\":46.60456770857712},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":336.3257252572358,\"upper_bound\":800.834220007082},\"point_estimate\":580.7406123848888,\"standard_error\":120.49519720385945}}"
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    "path": "docs/criterion/Clone/Arc_str_/10/base/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[11.0,22.0,33.0,44.0,55.0,66.0,77.0,88.0,99.0,110.0,121.0,132.0,143.0,154.0,165.0,176.0,187.0,198.0,209.0,220.0,231.0,242.0,253.0,264.0,275.0,286.0,297.0,308.0,319.0,330.0,341.0,352.0,363.0,374.0,385.0,396.0,407.0,418.0,429.0,440.0,451.0,462.0,473.0,484.0,495.0,506.0,517.0,528.0,539.0,550.0,561.0,572.0,583.0,594.0,605.0,616.0,627.0,638.0,649.0,660.0,671.0,682.0,693.0,704.0,715.0,726.0,737.0,748.0,759.0,770.0,781.0,792.0,803.0,814.0,825.0,836.0,847.0,858.0,869.0,880.0,891.0,902.0,913.0,924.0,935.0,946.0,957.0,968.0,979.0,990.0,1001.0,1012.0,1023.0,1034.0,1045.0,1056.0,1067.0,1078.0,1089.0,1100.0],\"times\":[1051292.0,2072252.0,3107874.0,4324458.0,5319335.0,6320207.0,7347292.0,8381292.0,9372957.0,10458875.0,11470541.0,12806374.0,13537082.0,14745710.0,15666417.0,16651583.0,17794084.0,18771166.0,19768750.0,20811876.0,21846709.0,22874918.0,23926875.0,24960208.0,26007125.0,27046583.0,28032916.0,29091375.0,30261875.0,31224207.0,32497793.0,33280750.0,34327292.0,35332291.0,36361168.0,37450250.0,38538627.0,39485917.0,40523834.0,41572167.0,42829459.0,43685417.0,44735625.0,45703084.0,47173127.0,47928124.0,48882290.0,49903793.0,50898459.0,51998958.0,52979458.0,54121627.0,55091499.0,56111002.0,57118374.0,58215250.0,59310541.0,60224333.0,61284206.0,62489876.0,63486001.0,64523419.0,65513584.0,66630290.0,67524583.0,68559041.0,69779083.0,71882542.0,72094333.0,72806085.0,73781626.0,74853835.0,75805500.0,77069915.0,78052123.0,79003336.0,80112374.0,81231125.0,82255165.0,83193165.0,84262706.0,85275958.0,86270708.0,87462127.0,88481957.0,89479333.0,90661125.0,91652750.0,92652958.0,93516958.0,94631125.0,95725250.0,96682874.0,97713540.0,99245875.0,99815542.0,101004166.0,101944458.0,103022333.0,105549418.0]}"
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    "path": "docs/criterion/Clone/Arc_str_/10/new/benchmark.json",
    "content": "{\"group_id\":\"Clone\",\"function_id\":\"Arc<str>\",\"value_str\":\"10\",\"throughput\":null,\"full_id\":\"Clone/Arc<str>/10\",\"directory_name\":\"Clone/Arc_str_/10\",\"title\":\"Clone/Arc<str>/10\"}"
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    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":94657.04291262414,\"upper_bound\":94882.48374840121},\"point_estimate\":94759.97755355037,\"standard_error\":57.656060400096756},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":94557.17965367965,\"upper_bound\":94611.5646002596},\"point_estimate\":94581.08243870294,\"standard_error\":14.011081679489106},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":103.10036036170625,\"upper_bound\":181.55105382842055},\"point_estimate\":140.20897423945428,\"standard_error\":19.55064984006466},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":94579.15155031881,\"upper_bound\":94757.74425079688},\"point_estimate\":94655.17162889423,\"standard_error\":46.60456770857712},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":336.3257252572358,\"upper_bound\":800.834220007082},\"point_estimate\":580.7406123848888,\"standard_error\":120.49519720385945}}"
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    "path": "docs/criterion/Clone/Arc_str_/10/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[11.0,22.0,33.0,44.0,55.0,66.0,77.0,88.0,99.0,110.0,121.0,132.0,143.0,154.0,165.0,176.0,187.0,198.0,209.0,220.0,231.0,242.0,253.0,264.0,275.0,286.0,297.0,308.0,319.0,330.0,341.0,352.0,363.0,374.0,385.0,396.0,407.0,418.0,429.0,440.0,451.0,462.0,473.0,484.0,495.0,506.0,517.0,528.0,539.0,550.0,561.0,572.0,583.0,594.0,605.0,616.0,627.0,638.0,649.0,660.0,671.0,682.0,693.0,704.0,715.0,726.0,737.0,748.0,759.0,770.0,781.0,792.0,803.0,814.0,825.0,836.0,847.0,858.0,869.0,880.0,891.0,902.0,913.0,924.0,935.0,946.0,957.0,968.0,979.0,990.0,1001.0,1012.0,1023.0,1034.0,1045.0,1056.0,1067.0,1078.0,1089.0,1100.0],\"times\":[1051292.0,2072252.0,3107874.0,4324458.0,5319335.0,6320207.0,7347292.0,8381292.0,9372957.0,10458875.0,11470541.0,12806374.0,13537082.0,14745710.0,15666417.0,16651583.0,17794084.0,18771166.0,19768750.0,20811876.0,21846709.0,22874918.0,23926875.0,24960208.0,26007125.0,27046583.0,28032916.0,29091375.0,30261875.0,31224207.0,32497793.0,33280750.0,34327292.0,35332291.0,36361168.0,37450250.0,38538627.0,39485917.0,40523834.0,41572167.0,42829459.0,43685417.0,44735625.0,45703084.0,47173127.0,47928124.0,48882290.0,49903793.0,50898459.0,51998958.0,52979458.0,54121627.0,55091499.0,56111002.0,57118374.0,58215250.0,59310541.0,60224333.0,61284206.0,62489876.0,63486001.0,64523419.0,65513584.0,66630290.0,67524583.0,68559041.0,69779083.0,71882542.0,72094333.0,72806085.0,73781626.0,74853835.0,75805500.0,77069915.0,78052123.0,79003336.0,80112374.0,81231125.0,82255165.0,83193165.0,84262706.0,85275958.0,86270708.0,87462127.0,88481957.0,89479333.0,90661125.0,91652750.0,92652958.0,93516958.0,94631125.0,95725250.0,96682874.0,97713540.0,99245875.0,99815542.0,101004166.0,101944458.0,103022333.0,105549418.0]}"
  },
  {
    "path": "docs/criterion/Clone/Arc_str_/10/new/tukey.json",
    "content": "[93971.81309497921,94238.0847985149,94948.14267461008,95214.41437814577]"
  },
  {
    "path": "docs/criterion/Clone/Arc_str_/10/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/Arc&lt;str&gt;/10 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/Arc&lt;str&gt;/10</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">94.579 µs</td>\n                                <td>94.655 µs</td>\n                                <td class=\"ci-bound\">94.758 µs</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.9983808</td>\n                                <td>0.9984649</td>\n                                <td class=\"ci-bound\">0.9983118</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">94.657 µs</td>\n                                <td>94.760 µs</td>\n                                <td class=\"ci-bound\">94.882 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">336.33 ns</td>\n                                <td>580.74 ns</td>\n                                <td class=\"ci-bound\">800.83 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">94.557 µs</td>\n                                <td>94.581 µs</td>\n                                <td class=\"ci-bound\">94.612 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">103.10 ns</td>\n                                <td>140.21 ns</td>\n                                <td class=\"ci-bound\">181.55 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−0.3885%</td>\n                            <td>−0.1514%</td>\n                            <td class=\"ci-bound\">+0.0522%</td>\n                            <td>(p = 0.19 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
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    "path": "docs/criterion/Clone/Arc_str_/100/base/benchmark.json",
    "content": "{\"group_id\":\"Clone\",\"function_id\":\"Arc<str>\",\"value_str\":\"100\",\"throughput\":null,\"full_id\":\"Clone/Arc<str>/100\",\"directory_name\":\"Clone/Arc_str_/100\",\"title\":\"Clone/Arc<str>/100\"}"
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    "path": "docs/criterion/Clone/Arc_str_/100/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":94634.31548947081,\"upper_bound\":94837.45006006242},\"point_estimate\":94727.49400273277,\"standard_error\":51.84915142687652},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":94505.52958152958,\"upper_bound\":94615.75757575757},\"point_estimate\":94562.46992500254,\"standard_error\":26.157098737445438},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":122.09634136382172,\"upper_bound\":236.57624501321962},\"point_estimate\":177.76278184335294,\"standard_error\":29.313836078363362},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":94550.60411184789,\"upper_bound\":94741.40368891665},\"point_estimate\":94634.6966726225,\"standard_error\":49.35480713258903},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":310.2355101630091,\"upper_bound\":708.4817668609605},\"point_estimate\":519.7403912635331,\"standard_error\":102.64212815160707}}"
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    "path": "docs/criterion/Clone/Arc_str_/100/base/sample.json",
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    "path": "docs/criterion/Clone/Arc_str_/100/base/tukey.json",
    "content": "[93603.72474526693,94030.70458916845,95169.3175062392,95596.29735014073]"
  },
  {
    "path": "docs/criterion/Clone/Arc_str_/100/change/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.032170708907577054,\"upper_bound\":-0.00466939262542867},\"point_estimate\":-0.016953021263033108,\"standard_error\":0.007114655688548438},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.0021255888153087765,\"upper_bound\":-0.0005531302679327276},\"point_estimate\":-0.0012808932087639002,\"standard_error\":0.00039702483246218225}}"
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    "path": "docs/criterion/Clone/Arc_str_/100/new/benchmark.json",
    "content": "{\"group_id\":\"Clone\",\"function_id\":\"Arc<str>\",\"value_str\":\"100\",\"throughput\":null,\"full_id\":\"Clone/Arc<str>/100\",\"directory_name\":\"Clone/Arc_str_/100\",\"title\":\"Clone/Arc<str>/100\"}"
  },
  {
    "path": "docs/criterion/Clone/Arc_str_/100/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":94634.31548947081,\"upper_bound\":94837.45006006242},\"point_estimate\":94727.49400273277,\"standard_error\":51.84915142687652},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":94505.52958152958,\"upper_bound\":94615.75757575757},\"point_estimate\":94562.46992500254,\"standard_error\":26.157098737445438},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":122.09634136382172,\"upper_bound\":236.57624501321962},\"point_estimate\":177.76278184335294,\"standard_error\":29.313836078363362},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":94550.60411184789,\"upper_bound\":94741.40368891665},\"point_estimate\":94634.6966726225,\"standard_error\":49.35480713258903},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":310.2355101630091,\"upper_bound\":708.4817668609605},\"point_estimate\":519.7403912635331,\"standard_error\":102.64212815160707}}"
  },
  {
    "path": "docs/criterion/Clone/Arc_str_/100/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[11.0,22.0,33.0,44.0,55.0,66.0,77.0,88.0,99.0,110.0,121.0,132.0,143.0,154.0,165.0,176.0,187.0,198.0,209.0,220.0,231.0,242.0,253.0,264.0,275.0,286.0,297.0,308.0,319.0,330.0,341.0,352.0,363.0,374.0,385.0,396.0,407.0,418.0,429.0,440.0,451.0,462.0,473.0,484.0,495.0,506.0,517.0,528.0,539.0,550.0,561.0,572.0,583.0,594.0,605.0,616.0,627.0,638.0,649.0,660.0,671.0,682.0,693.0,704.0,715.0,726.0,737.0,748.0,759.0,770.0,781.0,792.0,803.0,814.0,825.0,836.0,847.0,858.0,869.0,880.0,891.0,902.0,913.0,924.0,935.0,946.0,957.0,968.0,979.0,990.0,1001.0,1012.0,1023.0,1034.0,1045.0,1056.0,1067.0,1078.0,1089.0,1100.0],\"times\":[1052083.0,2078792.0,3111833.0,4253417.0,5377289.0,6370916.0,7330167.0,8399041.0,9366960.0,10475041.0,11478792.0,12459957.0,13631083.0,14590251.0,15839333.0,16708168.0,17673747.0,18759249.0,19775707.0,20813455.0,21850875.0,22857542.0,23900040.0,24952001.0,25957877.0,27045667.0,28204166.0,29278418.0,30170001.0,31232123.0,32354749.0,33298291.0,34407832.0,35343082.0,36533041.0,37412085.0,38450001.0,39461083.0,40511334.0,41601126.0,42642253.0,43732334.0,44679126.0,45714960.0,46860249.0,47797374.0,48837877.0,49850875.0,50894002.0,52087582.0,53045458.0,54099501.0,55195168.0,56211749.0,57207709.0,58366709.0,59222418.0,60248792.0,61485959.0,62600915.0,63549292.0,64403709.0,65492332.0,66485750.0,67508375.0,68536792.0,69695084.0,70805834.0,71770790.0,72754541.0,73726122.0,74859042.0,75841540.0,76945959.0,77923834.0,78921542.0,80044208.0,81060001.0,82049750.0,83145208.0,84187750.0,85320915.0,86198000.0,87761168.0,88251751.0,89703001.0,90509208.0,91698708.0,92460666.0,94495041.0,94952292.0,96042540.0,96801001.0,97712625.0,98993292.0,99735792.0,102509042.0,102069124.0,102909247.0,103864792.0]}"
  },
  {
    "path": "docs/criterion/Clone/Arc_str_/100/new/tukey.json",
    "content": "[93603.72474526693,94030.70458916845,95169.3175062392,95596.29735014073]"
  },
  {
    "path": "docs/criterion/Clone/Arc_str_/100/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/Arc&lt;str&gt;/100 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/Arc&lt;str&gt;/100</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">94.551 µs</td>\n                                <td>94.635 µs</td>\n                                <td class=\"ci-bound\">94.741 µs</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.9982790</td>\n                                <td>0.9983887</td>\n                                <td class=\"ci-bound\">0.9982121</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">94.634 µs</td>\n                                <td>94.727 µs</td>\n                                <td class=\"ci-bound\">94.837 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">310.24 ns</td>\n                                <td>519.74 ns</td>\n                                <td class=\"ci-bound\">708.48 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">94.506 µs</td>\n                                <td>94.562 µs</td>\n                                <td class=\"ci-bound\">94.616 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">122.10 ns</td>\n                                <td>177.76 ns</td>\n                                <td class=\"ci-bound\">236.58 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−3.2171%</td>\n                            <td>−1.6953%</td>\n                            <td class=\"ci-bound\">−0.4669%</td>\n                            <td>(p = 0.01 &lt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                Change within noise threshold.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Clone/Arc_str_/20/base/benchmark.json",
    "content": "{\"group_id\":\"Clone\",\"function_id\":\"Arc<str>\",\"value_str\":\"20\",\"throughput\":null,\"full_id\":\"Clone/Arc<str>/20\",\"directory_name\":\"Clone/Arc_str_/20\",\"title\":\"Clone/Arc<str>/20\"}"
  },
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  {
    "path": "docs/criterion/Clone/Arc_str_/20/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/Arc&lt;str&gt;/20 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/Arc&lt;str&gt;/20</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">94.586 µs</td>\n                                <td>94.646 µs</td>\n                                <td class=\"ci-bound\">94.716 µs</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.9983540</td>\n                                <td>0.9984088</td>\n                                <td class=\"ci-bound\">0.9983329</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">94.699 µs</td>\n                                <td>94.840 µs</td>\n                                <td class=\"ci-bound\">95.028 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">374.68 ns</td>\n                                <td>847.37 ns</td>\n                                <td class=\"ci-bound\">1.3003 µs</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">94.549 µs</td>\n                                <td>94.604 µs</td>\n                                <td class=\"ci-bound\">94.662 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">123.84 ns</td>\n                                <td>182.70 ns</td>\n                                <td class=\"ci-bound\">264.82 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−0.1178%</td>\n                            <td>+0.0666%</td>\n                            <td class=\"ci-bound\">+0.2753%</td>\n                            <td>(p = 0.54 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
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    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.12925172175803223,\"upper_bound\":-0.05164101901232282},\"point_estimate\":-0.08924380179368074,\"standard_error\":0.01985594631528621},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.0036676245848047406,\"upper_bound\":-0.000562158997199691},\"point_estimate\":-0.00158680547499368,\"standard_error\":0.0007654811268340382}}"
  },
  {
    "path": "docs/criterion/Clone/Arc_str_/500/new/benchmark.json",
    "content": "{\"group_id\":\"Clone\",\"function_id\":\"Arc<str>\",\"value_str\":\"500\",\"throughput\":null,\"full_id\":\"Clone/Arc<str>/500\",\"directory_name\":\"Clone/Arc_str_/500\",\"title\":\"Clone/Arc<str>/500\"}"
  },
  {
    "path": "docs/criterion/Clone/Arc_str_/500/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":94582.72281749973,\"upper_bound\":94847.47355562466},\"point_estimate\":94701.5959613957,\"standard_error\":67.99477910628413},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":94450.83363636363,\"upper_bound\":94545.19925629925},\"point_estimate\":94497.453568468,\"standard_error\":29.553230763631902},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":114.41075391285636,\"upper_bound\":223.24722532728757},\"point_estimate\":157.36641608070985,\"standard_error\":30.053624054685976},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":94457.3815541126,\"upper_bound\":94565.27385895974},\"point_estimate\":94502.61858672435,\"standard_error\":27.78968055315097},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":358.1188178284059,\"upper_bound\":957.2218918060827},\"point_estimate\":680.7591671553954,\"standard_error\":154.68552997810497}}"
  },
  {
    "path": "docs/criterion/Clone/Arc_str_/500/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[11.0,22.0,33.0,44.0,55.0,66.0,77.0,88.0,99.0,110.0,121.0,132.0,143.0,154.0,165.0,176.0,187.0,198.0,209.0,220.0,231.0,242.0,253.0,264.0,275.0,286.0,297.0,308.0,319.0,330.0,341.0,352.0,363.0,374.0,385.0,396.0,407.0,418.0,429.0,440.0,451.0,462.0,473.0,484.0,495.0,506.0,517.0,528.0,539.0,550.0,561.0,572.0,583.0,594.0,605.0,616.0,627.0,638.0,649.0,660.0,671.0,682.0,693.0,704.0,715.0,726.0,737.0,748.0,759.0,770.0,781.0,792.0,803.0,814.0,825.0,836.0,847.0,858.0,869.0,880.0,891.0,902.0,913.0,924.0,935.0,946.0,957.0,968.0,979.0,990.0,1001.0,1012.0,1023.0,1034.0,1045.0,1056.0,1067.0,1078.0,1089.0,1100.0],\"times\":[1046084.0,2075291.0,3120292.0,4355083.0,5359708.0,6392001.0,7298499.0,8424458.0,9362458.0,10435834.0,11446085.0,12465419.0,13560666.0,14767041.0,15768416.0,16676750.0,17643459.0,18742709.0,19832833.0,20804084.0,21871792.0,22859210.0,23888085.0,24916334.0,25946377.0,27182288.0,28104207.0,29055166.0,30133291.0,31152499.0,32325668.0,33249791.0,34260667.0,35357083.0,36353043.0,37392331.0,38800709.0,39519169.0,40667627.0,42138123.0,42775209.0,43659542.0,44672165.0,45766583.0,46759252.0,47864500.0,48853667.0,50088666.0,51044710.0,51951207.0,53034125.0,54098540.0,55211665.0,57589250.0,57144915.0,58494458.0,59252373.0,60177249.0,61367126.0,62384082.0,63332917.0,64468626.0,65515084.0,66641793.0,67604707.0,68470209.0,69581666.0,70603958.0,71692833.0,72669501.0,73696208.0,74703918.0,75842208.0,76862501.0,77881627.0,78942417.0,79957875.0,81112501.0,82007875.0,83238416.0,84133376.0,85134331.0,86221126.0,87184042.0,88168624.0,89633499.0,90332708.0,91397083.0,92383540.0,93705832.0,94500832.0,95628125.0,96610710.0,97600375.0,98840084.0,99694208.0,100688876.0,101871417.0,102746458.0,103895917.0]}"
  },
  {
    "path": "docs/criterion/Clone/Arc_str_/500/new/tukey.json",
    "content": "[93620.25214197263,94012.78217654742,95059.52893541355,95452.05896998834]"
  },
  {
    "path": "docs/criterion/Clone/Arc_str_/500/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/Arc&lt;str&gt;/500 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/Arc&lt;str&gt;/500</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">94.457 µs</td>\n                                <td>94.503 µs</td>\n                                <td class=\"ci-bound\">94.565 µs</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.9986790</td>\n                                <td>0.9987107</td>\n                                <td class=\"ci-bound\">0.9986499</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">94.583 µs</td>\n                                <td>94.702 µs</td>\n                                <td class=\"ci-bound\">94.847 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">358.12 ns</td>\n                                <td>680.76 ns</td>\n                                <td class=\"ci-bound\">957.22 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">94.451 µs</td>\n                                <td>94.497 µs</td>\n                                <td class=\"ci-bound\">94.545 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">114.41 ns</td>\n                                <td>157.37 ns</td>\n                                <td class=\"ci-bound\">223.25 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−12.925%</td>\n                            <td>−8.9244%</td>\n                            <td class=\"ci-bound\">−5.1641%</td>\n                            <td>(p = 0.00 &lt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                Performance has improved.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Clone/Arc_str_/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/Arc&lt;str&gt; Summary - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/Arc&lt;str&gt;</h2>\n        <h3>Violin Plot</h3>\n        <a href=\"violin.svg\">\n            <img src=\"violin.svg\" alt=\"Violin Plot\" />\n        </a>\n        <p>This chart shows the relationship between function/parameter and iteration time. The thickness of the shaded\n            region indicates the probability that a measurement of the given function/parameter would take a particular\n            length of time.</p>\n        <h3>Line Chart</h3>\n        <img src=\"lines.svg\" alt=\"Line Chart\" />\n        <p>This chart shows the mean measured time for each function as the input (or the size of the input) increases.</p>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/Arc_str_/0/report/index.html\">\n                <h4>Clone/Arc&lt;str&gt;/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/Arc_str_/0/report/pdf.svg\">\n                                <img src=\"../../../Clone/Arc_str_/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/Arc_str_/0/report/regression.svg\">\n                                <img src=\"../../../Clone/Arc_str_/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/Arc_str_/10/report/index.html\">\n                <h4>Clone/Arc&lt;str&gt;/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/Arc_str_/10/report/pdf.svg\">\n                                <img src=\"../../../Clone/Arc_str_/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/Arc_str_/10/report/regression.svg\">\n                                <img src=\"../../../Clone/Arc_str_/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/Arc_str_/20/report/index.html\">\n                <h4>Clone/Arc&lt;str&gt;/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/Arc_str_/20/report/pdf.svg\">\n                                <img src=\"../../../Clone/Arc_str_/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/Arc_str_/20/report/regression.svg\">\n                                <img src=\"../../../Clone/Arc_str_/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/Arc_str_/100/report/index.html\">\n                <h4>Clone/Arc&lt;str&gt;/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/Arc_str_/100/report/pdf.svg\">\n                                <img src=\"../../../Clone/Arc_str_/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/Arc_str_/100/report/regression.svg\">\n                                <img src=\"../../../Clone/Arc_str_/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/Arc_str_/500/report/index.html\">\n                <h4>Clone/Arc&lt;str&gt;/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/Arc_str_/500/report/pdf.svg\">\n                                <img src=\"../../../Clone/Arc_str_/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/Arc_str_/500/report/regression.svg\">\n                                <img src=\"../../../Clone/Arc_str_/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Clone/FlexStr 0.10 (LocalStr - Boxed)/0/base/benchmark.json",
    "content": "{\"group_id\":\"Clone\",\"function_id\":\"FlexStr 0.10 (LocalStr - Boxed)\",\"value_str\":\"0\",\"throughput\":null,\"full_id\":\"Clone/FlexStr 0.10 (LocalStr - Boxed)/0\",\"directory_name\":\"Clone/FlexStr 0.10 (LocalStr - Boxed)/0\",\"title\":\"Clone/FlexStr 0.10 (LocalStr - Boxed)/0\"}"
  },
  {
    "path": "docs/criterion/Clone/FlexStr 0.10 (LocalStr - Boxed)/0/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":81234.30064113844,\"upper_bound\":81701.69620123917},\"point_estimate\":81456.2170145982,\"standard_error\":119.50611223378769},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":80870.08479020979,\"upper_bound\":80991.92985658409},\"point_estimate\":80918.70158862876,\"standard_error\":32.41015694270174},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":136.94253245340204,\"upper_bound\":314.8897194445446},\"point_estimate\":200.52670283404845,\"standard_error\":44.16685932038463},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":81000.14653818964,\"upper_bound\":81461.20698048394},\"point_estimate\":81204.03299360017,\"standard_error\":118.2356803599473},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":891.5122978957675,\"upper_bound\":1447.4638005653862},\"point_estimate\":1199.5308901100998,\"standard_error\":141.82632647636134}}"
  },
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    "path": "docs/criterion/Clone/FlexStr 0.10 (LocalStr - Boxed)/0/base/sample.json",
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  {
    "path": "docs/criterion/Clone/FlexStr 0.10 (LocalStr - Boxed)/0/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/FlexStr 0.10 (LocalStr - Boxed)/0 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/FlexStr 0.10 (LocalStr - Boxed)/0</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">81.000 µs</td>\n                                <td>81.204 µs</td>\n                                <td class=\"ci-bound\">81.461 µs</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.9763825</td>\n                                <td>0.9772353</td>\n                                <td class=\"ci-bound\">0.9758791</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">81.234 µs</td>\n                                <td>81.456 µs</td>\n                                <td class=\"ci-bound\">81.702 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">891.51 ns</td>\n                                <td>1.1995 µs</td>\n                                <td class=\"ci-bound\">1.4475 µs</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">80.870 µs</td>\n                                <td>80.919 µs</td>\n                                <td class=\"ci-bound\">80.992 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">136.94 ns</td>\n                                <td>200.53 ns</td>\n                                <td class=\"ci-bound\">314.89 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">+0.0807%</td>\n                            <td>+0.4128%</td>\n                            <td class=\"ci-bound\">+0.7614%</td>\n                            <td>(p = 0.02 &lt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                Change within noise threshold.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
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    "content": "{\"group_id\":\"Clone\",\"function_id\":\"FlexStr 0.10 (LocalStr - Boxed)\",\"value_str\":\"10\",\"throughput\":null,\"full_id\":\"Clone/FlexStr 0.10 (LocalStr - Boxed)/10\",\"directory_name\":\"Clone/FlexStr 0.10 (LocalStr - Boxed)/10\",\"title\":\"Clone/FlexStr 0.10 (LocalStr - Boxed)/10\"}"
  },
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    "path": "docs/criterion/Clone/FlexStr 0.10 (LocalStr - Boxed)/10/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":68495.68172554189,\"upper_bound\":68619.96710697256},\"point_estimate\":68552.12586360055,\"standard_error\":31.865664603842557},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":68423.5943968254,\"upper_bound\":68487.68562658},\"point_estimate\":68450.73150584794,\"standard_error\":17.31131240823833},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":81.88466138259345,\"upper_bound\":158.69836390968248},\"point_estimate\":121.20881927501055,\"standard_error\":20.35900850248473},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":68431.55689345225,\"upper_bound\":68532.7540648748},\"point_estimate\":68474.7873308704,\"standard_error\":26.31071333388616},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":187.87201498582579,\"upper_bound\":451.2035511952392},\"point_estimate\":319.63231399262133,\"standard_error\":71.42071813388718}}"
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    "path": "docs/criterion/Clone/FlexStr 0.10 (LocalStr - Boxed)/10/new/benchmark.json",
    "content": "{\"group_id\":\"Clone\",\"function_id\":\"FlexStr 0.10 (LocalStr - Boxed)\",\"value_str\":\"10\",\"throughput\":null,\"full_id\":\"Clone/FlexStr 0.10 (LocalStr - Boxed)/10\",\"directory_name\":\"Clone/FlexStr 0.10 (LocalStr - Boxed)/10\",\"title\":\"Clone/FlexStr 0.10 (LocalStr - Boxed)/10\"}"
  },
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    "path": "docs/criterion/Clone/FlexStr 0.10 (LocalStr - Boxed)/10/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":68495.68172554189,\"upper_bound\":68619.96710697256},\"point_estimate\":68552.12586360055,\"standard_error\":31.865664603842557},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":68423.5943968254,\"upper_bound\":68487.68562658},\"point_estimate\":68450.73150584794,\"standard_error\":17.31131240823833},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":81.88466138259345,\"upper_bound\":158.69836390968248},\"point_estimate\":121.20881927501055,\"standard_error\":20.35900850248473},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":68431.55689345225,\"upper_bound\":68532.7540648748},\"point_estimate\":68474.7873308704,\"standard_error\":26.31071333388616},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":187.87201498582579,\"upper_bound\":451.2035511952392},\"point_estimate\":319.63231399262133,\"standard_error\":71.42071813388718}}"
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    "path": "docs/criterion/Clone/FlexStr 0.10 (LocalStr - Boxed)/10/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[15.0,30.0,45.0,60.0,75.0,90.0,105.0,120.0,135.0,150.0,165.0,180.0,195.0,210.0,225.0,240.0,255.0,270.0,285.0,300.0,315.0,330.0,345.0,360.0,375.0,390.0,405.0,420.0,435.0,450.0,465.0,480.0,495.0,510.0,525.0,540.0,555.0,570.0,585.0,600.0,615.0,630.0,645.0,660.0,675.0,690.0,705.0,720.0,735.0,750.0,765.0,780.0,795.0,810.0,825.0,840.0,855.0,870.0,885.0,900.0,915.0,930.0,945.0,960.0,975.0,990.0,1005.0,1020.0,1035.0,1050.0,1065.0,1080.0,1095.0,1110.0,1125.0,1140.0,1155.0,1170.0,1185.0,1200.0,1215.0,1230.0,1245.0,1260.0,1275.0,1290.0,1305.0,1320.0,1335.0,1350.0,1365.0,1380.0,1395.0,1410.0,1425.0,1440.0,1455.0,1470.0,1485.0,1500.0],\"times\":[1029041.0,2080376.0,3081790.0,4162500.0,5299705.0,6200711.0,7266295.0,8226416.0,9229958.0,10307707.0,11327251.0,12349458.0,13354292.0,14453125.0,15487583.0,16480373.0,17482042.0,18529959.0,19490377.0,20683917.0,21554959.0,22892583.0,23663499.0,24605250.0,25658333.0,26707667.0,27724542.0,28904000.0,29815919.0,30849417.0,31838917.0,32907541.0,33887335.0,34963792.0,35906792.0,36934291.0,37948375.0,39018751.0,40014875.0,41002085.0,42077749.0,43069917.0,44167168.0,45220874.0,46209792.0,47185917.0,48218041.0,49282210.0,50217710.0,51286623.0,52355583.0,53544125.0,54542959.0,55405919.0,56397377.0,57713790.0,58416416.0,59506167.0,60529165.0,61502835.0,62835251.0,63670041.0,64642960.0,65637208.0,66618292.0,67669667.0,68784751.0,69765750.0,71571169.0,71991041.0,72943791.0,73835914.0,74893542.0,76243625.0,76977542.0,78226708.0,79043000.0,80006334.0,80959583.0,82072000.0,83061211.0,84346750.0,85102668.0,86215459.0,87185958.0,88220626.0,89209168.0,91615375.0,91354959.0,92301833.0,93270042.0,94334875.0,95588376.0,96443833.0,97660334.0,98540501.0,99659042.0,100599500.0,101717792.0,102743875.0]}"
  },
  {
    "path": "docs/criterion/Clone/FlexStr 0.10 (LocalStr - Boxed)/10/new/tukey.json",
    "content": "[67816.30973463772,68102.09664618463,68864.19507697638,69149.98198852329]"
  },
  {
    "path": "docs/criterion/Clone/FlexStr 0.10 (LocalStr - Boxed)/10/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/FlexStr 0.10 (LocalStr - Boxed)/10 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/FlexStr 0.10 (LocalStr - Boxed)/10</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">68.432 µs</td>\n                                <td>68.475 µs</td>\n                                <td class=\"ci-bound\">68.533 µs</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.9988423</td>\n                                <td>0.9988972</td>\n                                <td class=\"ci-bound\">0.9987985</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">68.496 µs</td>\n                                <td>68.552 µs</td>\n                                <td class=\"ci-bound\">68.620 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">187.87 ns</td>\n                                <td>319.63 ns</td>\n                                <td class=\"ci-bound\">451.20 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">68.424 µs</td>\n                                <td>68.451 µs</td>\n                                <td class=\"ci-bound\">68.488 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">81.885 ns</td>\n                                <td>121.21 ns</td>\n                                <td class=\"ci-bound\">158.70 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−0.2255%</td>\n                            <td>−0.0476%</td>\n                            <td class=\"ci-bound\">+0.1198%</td>\n                            <td>(p = 0.61 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Clone/FlexStr 0.10 (LocalStr - Boxed)/100/base/benchmark.json",
    "content": "{\"group_id\":\"Clone\",\"function_id\":\"FlexStr 0.10 (LocalStr - Boxed)\",\"value_str\":\"100\",\"throughput\":null,\"full_id\":\"Clone/FlexStr 0.10 (LocalStr - Boxed)/100\",\"directory_name\":\"Clone/FlexStr 0.10 (LocalStr - Boxed)/100\",\"title\":\"Clone/FlexStr 0.10 (LocalStr - Boxed)/100\"}"
  },
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    "path": "docs/criterion/Clone/FlexStr 0.10 (LocalStr - Boxed)/100/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":261050.2606847989,\"upper_bound\":261683.86380321268},\"point_estimate\":261350.80681349192,\"standard_error\":161.6681780923026},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":260963.18023255814,\"upper_bound\":261205.91346153847},\"point_estimate\":261082.1755616215,\"standard_error\":67.42656577355906},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":405.47087552874024,\"upper_bound\":759.2586751998869},\"point_estimate\":586.5485021729085,\"standard_error\":88.91001762172088},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":260785.98454825024,\"upper_bound\":261285.0644783419},\"point_estimate\":261038.85993350082,\"standard_error\":126.95413750100478},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":1110.7229339867692,\"upper_bound\":2085.7979690657658},\"point_estimate\":1627.8834190274483,\"standard_error\":249.4813373902682}}"
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    "path": "docs/criterion/Clone/FlexStr 0.10 (LocalStr - Boxed)/100/base/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[4.0,8.0,12.0,16.0,20.0,24.0,28.0,32.0,36.0,40.0,44.0,48.0,52.0,56.0,60.0,64.0,68.0,72.0,76.0,80.0,84.0,88.0,92.0,96.0,100.0,104.0,108.0,112.0,116.0,120.0,124.0,128.0,132.0,136.0,140.0,144.0,148.0,152.0,156.0,160.0,164.0,168.0,172.0,176.0,180.0,184.0,188.0,192.0,196.0,200.0,204.0,208.0,212.0,216.0,220.0,224.0,228.0,232.0,236.0,240.0,244.0,248.0,252.0,256.0,260.0,264.0,268.0,272.0,276.0,280.0,284.0,288.0,292.0,296.0,300.0,304.0,308.0,312.0,316.0,320.0,324.0,328.0,332.0,336.0,340.0,344.0,348.0,352.0,356.0,360.0,364.0,368.0,372.0,376.0,380.0,384.0,388.0,392.0,396.0,400.0],\"times\":[1051458.0,2091084.0,3144791.0,4284833.0,5384126.0,6343249.0,7314294.0,8371167.0,9429334.0,10446790.0,11494583.0,12535707.0,13550122.0,14808751.0,15852916.0,16737917.0,17794043.0,18827790.0,19854167.0,20902502.0,21959542.0,22945417.0,24021333.0,25072043.0,26238416.0,27165415.0,28150332.0,29162835.0,30189542.0,31248751.0,32449040.0,33361000.0,34452375.0,35482749.0,36528332.0,38280501.0,39404083.0,39632459.0,40680418.0,41876085.0,42388750.0,43552334.0,44885667.0,45904000.0,46951749.0,47578292.0,49109541.0,49792957.0,50909333.0,52138710.0,53434792.0,54616459.0,55321084.0,56379666.0,57429666.0,58498708.0,59543458.0,60506916.0,61970583.0,63152875.0,63228125.0,64885083.0,65768373.0,66804917.0,67803623.0,68430415.0,69756751.0,70902043.0,72159417.0,72587958.0,74120916.0,75153123.0,76183125.0,76753126.0,78193042.0,79262250.0,80604710.0,81449126.0,82687248.0,83611541.0,84448125.0,85309627.0,86674792.0,87782292.0,88807874.0,89732001.0,90996708.0,90914330.0,93530585.0,94146376.0,95805084.0,95938959.0,97010248.0,98652293.0,99133582.0,100260749.0,101428667.0,102319540.0,103396125.0,104390207.0]}"
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    "path": "docs/criterion/Clone/FlexStr 0.10 (LocalStr - Boxed)/100/base/tukey.json",
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    "path": "docs/criterion/Clone/FlexStr 0.10 (LocalStr - Boxed)/100/change/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.061671786468449216,\"upper_bound\":-0.009775105677100344},\"point_estimate\":-0.033102621322935066,\"standard_error\":0.013273871619754216},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.004154144230417489,\"upper_bound\":-0.0010300497154547283},\"point_estimate\":-0.0022299635362788006,\"standard_error\":0.0008631461131242063}}"
  },
  {
    "path": "docs/criterion/Clone/FlexStr 0.10 (LocalStr - Boxed)/100/new/benchmark.json",
    "content": "{\"group_id\":\"Clone\",\"function_id\":\"FlexStr 0.10 (LocalStr - Boxed)\",\"value_str\":\"100\",\"throughput\":null,\"full_id\":\"Clone/FlexStr 0.10 (LocalStr - Boxed)/100\",\"directory_name\":\"Clone/FlexStr 0.10 (LocalStr - Boxed)/100\",\"title\":\"Clone/FlexStr 0.10 (LocalStr - Boxed)/100\"}"
  },
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    "path": "docs/criterion/Clone/FlexStr 0.10 (LocalStr - Boxed)/100/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":261050.2606847989,\"upper_bound\":261683.86380321268},\"point_estimate\":261350.80681349192,\"standard_error\":161.6681780923026},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":260963.18023255814,\"upper_bound\":261205.91346153847},\"point_estimate\":261082.1755616215,\"standard_error\":67.42656577355906},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":405.47087552874024,\"upper_bound\":759.2586751998869},\"point_estimate\":586.5485021729085,\"standard_error\":88.91001762172088},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":260785.98454825024,\"upper_bound\":261285.0644783419},\"point_estimate\":261038.85993350082,\"standard_error\":126.95413750100478},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":1110.7229339867692,\"upper_bound\":2085.7979690657658},\"point_estimate\":1627.8834190274483,\"standard_error\":249.4813373902682}}"
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  {
    "path": "docs/criterion/Clone/FlexStr 0.10 (LocalStr - Boxed)/100/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/FlexStr 0.10 (LocalStr - Boxed)/100 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/FlexStr 0.10 (LocalStr - Boxed)/100</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">260.79 µs</td>\n                                <td>261.04 µs</td>\n                                <td class=\"ci-bound\">261.29 µs</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.9976189</td>\n                                <td>0.9977481</td>\n                                <td class=\"ci-bound\">0.9976256</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">261.05 µs</td>\n                                <td>261.35 µs</td>\n                                <td class=\"ci-bound\">261.68 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">1.1107 µs</td>\n                                <td>1.6279 µs</td>\n                                <td class=\"ci-bound\">2.0858 µs</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">260.96 µs</td>\n                                <td>261.08 µs</td>\n                                <td class=\"ci-bound\">261.21 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">405.47 ns</td>\n                                <td>586.55 ns</td>\n                                <td class=\"ci-bound\">759.26 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−6.1672%</td>\n                            <td>−3.3103%</td>\n                            <td class=\"ci-bound\">−0.9775%</td>\n                            <td>(p = 0.00 &lt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                Change within noise threshold.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
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    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/FlexStr 0.10 (LocalStr - Boxed)/20 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/FlexStr 0.10 (LocalStr - Boxed)/20</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">74.662 µs</td>\n                                <td>75.015 µs</td>\n                                <td class=\"ci-bound\">75.779 µs</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.8197703</td>\n                                <td>0.8218882</td>\n                                <td class=\"ci-bound\">0.8121110</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">74.740 µs</td>\n                                <td>75.090 µs</td>\n                                <td class=\"ci-bound\">75.702 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">242.01 ns</td>\n                                <td>2.7408 µs</td>\n                                <td class=\"ci-bound\">4.6405 µs</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">74.652 µs</td>\n                                <td>74.675 µs</td>\n                                <td class=\"ci-bound\">74.703 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">83.636 ns</td>\n                                <td>109.93 ns</td>\n                                <td class=\"ci-bound\">153.40 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−0.3130%</td>\n                            <td>+0.2147%</td>\n                            <td class=\"ci-bound\">+1.0122%</td>\n                            <td>(p = 0.68 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
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    "path": "docs/criterion/Clone/FlexStr 0.10 (LocalStr - Boxed)/500/base/benchmark.json",
    "content": "{\"group_id\":\"Clone\",\"function_id\":\"FlexStr 0.10 (LocalStr - Boxed)\",\"value_str\":\"500\",\"throughput\":null,\"full_id\":\"Clone/FlexStr 0.10 (LocalStr - Boxed)/500\",\"directory_name\":\"Clone/FlexStr 0.10 (LocalStr - Boxed)/500\",\"title\":\"Clone/FlexStr 0.10 (LocalStr - Boxed)/500\"}"
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    "path": "docs/criterion/Clone/FlexStr 0.10 (LocalStr - Boxed)/500/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":541141.4350854007,\"upper_bound\":544749.3055706545},\"point_estimate\":542941.7689889929,\"standard_error\":920.5208213190151},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":540286.2131147541,\"upper_bound\":544488.1654007334},\"point_estimate\":542306.260330948,\"standard_error\":1088.0826633944248},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":6858.206973774259,\"upper_bound\":11593.977974302703},\"point_estimate\":9052.800518334687,\"standard_error\":1217.2868728112187},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":541562.8912921556,\"upper_bound\":546604.4789066693},\"point_estimate\":544025.143647111,\"standard_error\":1287.48564545301},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":7971.153465942713,\"upper_bound\":10356.103570610363},\"point_estimate\":9222.86466450478,\"standard_error\":609.2579578065763}}"
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    "path": "docs/criterion/Clone/FlexStr 0.10 (LocalStr - Boxed)/500/base/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[2.0,4.0,6.0,8.0,10.0,12.0,14.0,16.0,18.0,20.0,22.0,24.0,26.0,28.0,30.0,32.0,34.0,36.0,38.0,40.0,42.0,44.0,46.0,48.0,50.0,52.0,54.0,56.0,58.0,60.0,62.0,64.0,66.0,68.0,70.0,72.0,74.0,76.0,78.0,80.0,82.0,84.0,86.0,88.0,90.0,92.0,94.0,96.0,98.0,100.0,102.0,104.0,106.0,108.0,110.0,112.0,114.0,116.0,118.0,120.0,122.0,124.0,126.0,128.0,130.0,132.0,134.0,136.0,138.0,140.0,142.0,144.0,146.0,148.0,150.0,152.0,154.0,156.0,158.0,160.0,162.0,164.0,166.0,168.0,170.0,172.0,174.0,176.0,178.0,180.0,182.0,184.0,186.0,188.0,190.0,192.0,194.0,196.0,198.0,200.0],\"times\":[1061833.0,2111751.0,3127125.0,4298251.0,5248417.0,6329625.0,7330625.0,8425584.0,9577041.0,10456999.0,11894459.0,13049165.0,14097082.0,15301288.0,16338045.0,17651417.0,18672626.0,19976792.0,20854956.0,21965542.0,22709835.0,23892001.0,25042459.0,26278580.0,27300290.0,28205294.0,29469044.0,30274458.0,31576334.0,32546291.0,33392918.0,34438918.0,35604999.0,36725918.0,38022792.0,38893125.0,39922749.0,40977209.0,42264918.0,43310623.0,44097916.0,45249875.0,46273250.0,47798334.0,49675710.0,50762499.0,52523583.0,53115040.0,52852374.0,53679665.0,55211914.0,58568707.0,58822457.0,58258291.0,59042958.0,61152835.0,63621001.0,64428415.0,63374664.0,64461916.0,65914918.0,68841002.0,69364500.0,68637792.0,70499791.0,73810250.0,74000665.0,72532041.0,73834625.0,76456415.0,79067374.0,79002666.0,78091289.0,81169832.0,84982002.0,83268415.0,83263334.0,86462459.0,87530209.0,85975834.0,88754375.0,90843877.0,90399458.0,91400626.0,94196543.0,93276707.0,93001457.0,96779585.0,99101544.0,98513083.0,100591625.0,102417499.0,99476873.0,100122751.0,101678750.0,102585459.0,103436250.0,104408875.0,105179374.0,106447416.0]}"
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    "path": "docs/criterion/Clone/FlexStr 0.10 (LocalStr - Boxed)/500/base/tukey.json",
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    "path": "docs/criterion/Clone/FlexStr 0.10 (LocalStr - Boxed)/500/change/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.008289338428069259,\"upper_bound\":0.016566326510021136},\"point_estimate\":0.012398867302167549,\"standard_error\":0.0021142514089612214},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.009864360028446484,\"upper_bound\":0.018742222146273413},\"point_estimate\":0.014259555773278754,\"standard_error\":0.0022624648517378166}}"
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    "path": "docs/criterion/Clone/FlexStr 0.10 (LocalStr - Boxed)/500/new/benchmark.json",
    "content": "{\"group_id\":\"Clone\",\"function_id\":\"FlexStr 0.10 (LocalStr - Boxed)\",\"value_str\":\"500\",\"throughput\":null,\"full_id\":\"Clone/FlexStr 0.10 (LocalStr - Boxed)/500\",\"directory_name\":\"Clone/FlexStr 0.10 (LocalStr - Boxed)/500\",\"title\":\"Clone/FlexStr 0.10 (LocalStr - Boxed)/500\"}"
  },
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    "path": "docs/criterion/Clone/FlexStr 0.10 (LocalStr - Boxed)/500/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":541141.4350854007,\"upper_bound\":544749.3055706545},\"point_estimate\":542941.7689889929,\"standard_error\":920.5208213190151},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":540286.2131147541,\"upper_bound\":544488.1654007334},\"point_estimate\":542306.260330948,\"standard_error\":1088.0826633944248},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":6858.206973774259,\"upper_bound\":11593.977974302703},\"point_estimate\":9052.800518334687,\"standard_error\":1217.2868728112187},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":541562.8912921556,\"upper_bound\":546604.4789066693},\"point_estimate\":544025.143647111,\"standard_error\":1287.48564545301},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":7971.153465942713,\"upper_bound\":10356.103570610363},\"point_estimate\":9222.86466450478,\"standard_error\":609.2579578065763}}"
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    "path": "docs/criterion/Clone/FlexStr 0.10 (LocalStr - Boxed)/500/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[2.0,4.0,6.0,8.0,10.0,12.0,14.0,16.0,18.0,20.0,22.0,24.0,26.0,28.0,30.0,32.0,34.0,36.0,38.0,40.0,42.0,44.0,46.0,48.0,50.0,52.0,54.0,56.0,58.0,60.0,62.0,64.0,66.0,68.0,70.0,72.0,74.0,76.0,78.0,80.0,82.0,84.0,86.0,88.0,90.0,92.0,94.0,96.0,98.0,100.0,102.0,104.0,106.0,108.0,110.0,112.0,114.0,116.0,118.0,120.0,122.0,124.0,126.0,128.0,130.0,132.0,134.0,136.0,138.0,140.0,142.0,144.0,146.0,148.0,150.0,152.0,154.0,156.0,158.0,160.0,162.0,164.0,166.0,168.0,170.0,172.0,174.0,176.0,178.0,180.0,182.0,184.0,186.0,188.0,190.0,192.0,194.0,196.0,198.0,200.0],\"times\":[1061833.0,2111751.0,3127125.0,4298251.0,5248417.0,6329625.0,7330625.0,8425584.0,9577041.0,10456999.0,11894459.0,13049165.0,14097082.0,15301288.0,16338045.0,17651417.0,18672626.0,19976792.0,20854956.0,21965542.0,22709835.0,23892001.0,25042459.0,26278580.0,27300290.0,28205294.0,29469044.0,30274458.0,31576334.0,32546291.0,33392918.0,34438918.0,35604999.0,36725918.0,38022792.0,38893125.0,39922749.0,40977209.0,42264918.0,43310623.0,44097916.0,45249875.0,46273250.0,47798334.0,49675710.0,50762499.0,52523583.0,53115040.0,52852374.0,53679665.0,55211914.0,58568707.0,58822457.0,58258291.0,59042958.0,61152835.0,63621001.0,64428415.0,63374664.0,64461916.0,65914918.0,68841002.0,69364500.0,68637792.0,70499791.0,73810250.0,74000665.0,72532041.0,73834625.0,76456415.0,79067374.0,79002666.0,78091289.0,81169832.0,84982002.0,83268415.0,83263334.0,86462459.0,87530209.0,85975834.0,88754375.0,90843877.0,90399458.0,91400626.0,94196543.0,93276707.0,93001457.0,96779585.0,99101544.0,98513083.0,100591625.0,102417499.0,99476873.0,100122751.0,101678750.0,102585459.0,103436250.0,104408875.0,105179374.0,106447416.0]}"
  },
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    "path": "docs/criterion/Clone/FlexStr 0.10 (LocalStr - Boxed)/500/new/tukey.json",
    "content": "[501163.4244641075,519159.3776981554,567148.5863222831,585144.5395563311]"
  },
  {
    "path": "docs/criterion/Clone/FlexStr 0.10 (LocalStr - Boxed)/500/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/FlexStr 0.10 (LocalStr - Boxed)/500 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/FlexStr 0.10 (LocalStr - Boxed)/500</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">541.56 µs</td>\n                                <td>544.03 µs</td>\n                                <td class=\"ci-bound\">546.60 µs</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.9558182</td>\n                                <td>0.9586553</td>\n                                <td class=\"ci-bound\">0.9555429</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">541.14 µs</td>\n                                <td>542.94 µs</td>\n                                <td class=\"ci-bound\">544.75 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">7.9712 µs</td>\n                                <td>9.2229 µs</td>\n                                <td class=\"ci-bound\">10.356 µs</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">540.29 µs</td>\n                                <td>542.31 µs</td>\n                                <td class=\"ci-bound\">544.49 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">6.8582 µs</td>\n                                <td>9.0528 µs</td>\n                                <td class=\"ci-bound\">11.594 µs</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">+0.8289%</td>\n                            <td>+1.2399%</td>\n                            <td class=\"ci-bound\">+1.6566%</td>\n                            <td>(p = 0.00 &lt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                Change within noise threshold.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Clone/FlexStr 0.10 (LocalStr - Boxed)/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/FlexStr 0.10 (LocalStr - Boxed) Summary - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/FlexStr 0.10 (LocalStr - Boxed)</h2>\n        <h3>Violin Plot</h3>\n        <a href=\"violin.svg\">\n            <img src=\"violin.svg\" alt=\"Violin Plot\" />\n        </a>\n        <p>This chart shows the relationship between function/parameter and iteration time. The thickness of the shaded\n            region indicates the probability that a measurement of the given function/parameter would take a particular\n            length of time.</p>\n        <h3>Line Chart</h3>\n        <img src=\"lines.svg\" alt=\"Line Chart\" />\n        <p>This chart shows the mean measured time for each function as the input (or the size of the input) increases.</p>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/FlexStr 0.10 (LocalStr - Boxed)/0/report/index.html\">\n                <h4>Clone/FlexStr 0.10 (LocalStr - Boxed)/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (LocalStr - Boxed)/0/report/pdf.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (LocalStr - Boxed)/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (LocalStr - Boxed)/0/report/regression.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (LocalStr - Boxed)/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/FlexStr 0.10 (LocalStr - Boxed)/10/report/index.html\">\n                <h4>Clone/FlexStr 0.10 (LocalStr - Boxed)/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (LocalStr - Boxed)/10/report/pdf.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (LocalStr - Boxed)/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (LocalStr - Boxed)/10/report/regression.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (LocalStr - Boxed)/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/FlexStr 0.10 (LocalStr - Boxed)/20/report/index.html\">\n                <h4>Clone/FlexStr 0.10 (LocalStr - Boxed)/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (LocalStr - Boxed)/20/report/pdf.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (LocalStr - Boxed)/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (LocalStr - Boxed)/20/report/regression.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (LocalStr - Boxed)/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/FlexStr 0.10 (LocalStr - Boxed)/100/report/index.html\">\n                <h4>Clone/FlexStr 0.10 (LocalStr - Boxed)/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (LocalStr - Boxed)/100/report/pdf.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (LocalStr - Boxed)/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (LocalStr - Boxed)/100/report/regression.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (LocalStr - Boxed)/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/FlexStr 0.10 (LocalStr - Boxed)/500/report/index.html\">\n                <h4>Clone/FlexStr 0.10 (LocalStr - Boxed)/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (LocalStr - Boxed)/500/report/pdf.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (LocalStr - Boxed)/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (LocalStr - Boxed)/500/report/regression.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (LocalStr - Boxed)/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Clone/FlexStr 0.10 (LocalStr - Optimized)/0/base/benchmark.json",
    "content": "{\"group_id\":\"Clone\",\"function_id\":\"FlexStr 0.10 (LocalStr - Optimized)\",\"value_str\":\"0\",\"throughput\":null,\"full_id\":\"Clone/FlexStr 0.10 (LocalStr - Optimized)/0\",\"directory_name\":\"Clone/FlexStr 0.10 (LocalStr - Optimized)/0\",\"title\":\"Clone/FlexStr 0.10 (LocalStr - Optimized)/0\"}"
  },
  {
    "path": "docs/criterion/Clone/FlexStr 0.10 (LocalStr - Optimized)/0/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":12470.671286058832,\"upper_bound\":12525.183963122074},\"point_estimate\":12495.089098122888,\"standard_error\":13.927910106166875},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":12444.717929292929,\"upper_bound\":12458.136817528735},\"point_estimate\":12453.043359374999,\"standard_error\":3.8947342803415825},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":20.898719261731777,\"upper_bound\":36.58192514888553},\"point_estimate\":30.30467497006427,\"standard_error\":4.006630240641267},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":12450.02028312689,\"upper_bound\":12490.622543249508},\"point_estimate\":12467.847771168908,\"standard_error\":10.469192077427335},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":74.53211436566595,\"upper_bound\":199.38752302889318},\"point_estimate\":139.93517296509944,\"standard_error\":32.59097109410112}}"
  },
  {
    "path": "docs/criterion/Clone/FlexStr 0.10 (LocalStr - Optimized)/0/base/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[80.0,160.0,240.0,320.0,400.0,480.0,560.0,640.0,720.0,800.0,880.0,960.0,1040.0,1120.0,1200.0,1280.0,1360.0,1440.0,1520.0,1600.0,1680.0,1760.0,1840.0,1920.0,2000.0,2080.0,2160.0,2240.0,2320.0,2400.0,2480.0,2560.0,2640.0,2720.0,2800.0,2880.0,2960.0,3040.0,3120.0,3200.0,3280.0,3360.0,3440.0,3520.0,3600.0,3680.0,3760.0,3840.0,3920.0,4000.0,4080.0,4160.0,4240.0,4320.0,4400.0,4480.0,4560.0,4640.0,4720.0,4800.0,4880.0,4960.0,5040.0,5120.0,5200.0,5280.0,5360.0,5440.0,5520.0,5600.0,5680.0,5760.0,5840.0,5920.0,6000.0,6080.0,6160.0,6240.0,6320.0,6400.0,6480.0,6560.0,6640.0,6720.0,6800.0,6880.0,6960.0,7040.0,7120.0,7200.0,7280.0,7360.0,7440.0,7520.0,7600.0,7680.0,7760.0,7840.0,7920.0,8000.0],\"times\":[1005001.0,1996542.0,3007249.0,4100585.0,5216290.0,6179000.0,6980666.0,8168417.0,9032414.0,10021414.0,11026165.0,11957248.0,12955084.0,15016540.0,15003584.0,15990502.0,16971667.0,17931750.0,18967126.0,19929540.0,20919291.0,21902041.0,22896832.0,24082375.0,24862042.0,25866417.0,26883667.0,27837459.0,29082749.0,30851750.0,30893502.0,31887749.0,33030543.0,33822546.0,34802666.0,35850500.0,36769419.0,37824665.0,38919624.0,39769792.0,40767957.0,41905207.0,42744584.0,43915583.0,44958622.0,45796125.0,46784833.0,47821373.0,48737792.0,49831082.0,50818207.0,51864418.0,52740208.0,53886543.0,54865917.0,55858293.0,56714541.0,57687876.0,58665833.0,59675877.0,60716500.0,61839918.0,62782250.0,63783584.0,64727625.0,65698624.0,66631582.0,67613043.0,68642960.0,69582082.0,70696250.0,71650374.0,72588582.0,73594041.0,74554375.0,75780210.0,76674294.0,77613458.0,78687168.0,79578249.0,80470750.0,81480873.0,82503501.0,84966794.0,85494333.0,85814544.0,86711455.0,88620459.0,91212293.0,90423583.0,90825790.0,91703542.0,92694040.0,93611250.0,94504084.0,95474249.0,96453251.0,97384082.0,98562166.0,99481542.0]}"
  },
  {
    "path": "docs/criterion/Clone/FlexStr 0.10 (LocalStr - Optimized)/0/base/tukey.json",
    "content": "[12309.089671265265,12371.923157033561,12539.479119082353,12602.31260485065]"
  },
  {
    "path": "docs/criterion/Clone/FlexStr 0.10 (LocalStr - Optimized)/0/change/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.011563454230334442,\"upper_bound\":-0.00309208930288829},\"point_estimate\":-0.007332598511719746,\"standard_error\":0.002157024364882625},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.0026990647938627266,\"upper_bound\":-0.000037086056826729497},\"point_estimate\":-0.0013990893600346332,\"standard_error\":0.0007364623085415503}}"
  },
  {
    "path": "docs/criterion/Clone/FlexStr 0.10 (LocalStr - Optimized)/0/new/benchmark.json",
    "content": "{\"group_id\":\"Clone\",\"function_id\":\"FlexStr 0.10 (LocalStr - Optimized)\",\"value_str\":\"0\",\"throughput\":null,\"full_id\":\"Clone/FlexStr 0.10 (LocalStr - Optimized)/0\",\"directory_name\":\"Clone/FlexStr 0.10 (LocalStr - Optimized)/0\",\"title\":\"Clone/FlexStr 0.10 (LocalStr - Optimized)/0\"}"
  },
  {
    "path": "docs/criterion/Clone/FlexStr 0.10 (LocalStr - Optimized)/0/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":12470.671286058832,\"upper_bound\":12525.183963122074},\"point_estimate\":12495.089098122888,\"standard_error\":13.927910106166875},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":12444.717929292929,\"upper_bound\":12458.136817528735},\"point_estimate\":12453.043359374999,\"standard_error\":3.8947342803415825},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":20.898719261731777,\"upper_bound\":36.58192514888553},\"point_estimate\":30.30467497006427,\"standard_error\":4.006630240641267},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":12450.02028312689,\"upper_bound\":12490.622543249508},\"point_estimate\":12467.847771168908,\"standard_error\":10.469192077427335},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":74.53211436566595,\"upper_bound\":199.38752302889318},\"point_estimate\":139.93517296509944,\"standard_error\":32.59097109410112}}"
  },
  {
    "path": "docs/criterion/Clone/FlexStr 0.10 (LocalStr - Optimized)/0/new/sample.json",
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  {
    "path": "docs/criterion/Clone/FlexStr 0.10 (LocalStr - Optimized)/0/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/FlexStr 0.10 (LocalStr - Optimized)/0 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/FlexStr 0.10 (LocalStr - Optimized)/0</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">12.450 µs</td>\n                                <td>12.468 µs</td>\n                                <td class=\"ci-bound\">12.491 µs</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.9944329</td>\n                                <td>0.9947153</td>\n                                <td class=\"ci-bound\">0.9942545</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">12.471 µs</td>\n                                <td>12.495 µs</td>\n                                <td class=\"ci-bound\">12.525 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">74.532 ns</td>\n                                <td>139.94 ns</td>\n                                <td class=\"ci-bound\">199.39 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">12.445 µs</td>\n                                <td>12.453 µs</td>\n                                <td class=\"ci-bound\">12.458 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">20.899 ns</td>\n                                <td>30.305 ns</td>\n                                <td class=\"ci-bound\">36.582 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−1.1563%</td>\n                            <td>−0.7333%</td>\n                            <td class=\"ci-bound\">−0.3092%</td>\n                            <td>(p = 0.00 &lt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                Change within noise threshold.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
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    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/FlexStr 0.10 (LocalStr - Optimized)/10 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/FlexStr 0.10 (LocalStr - Optimized)/10</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">12.438 µs</td>\n                                <td>12.449 µs</td>\n                                <td class=\"ci-bound\">12.463 µs</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.9967535</td>\n                                <td>0.9968535</td>\n                                <td class=\"ci-bound\">0.9966622</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">12.455 µs</td>\n                                <td>12.470 µs</td>\n                                <td class=\"ci-bound\">12.488 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">44.984 ns</td>\n                                <td>85.587 ns</td>\n                                <td class=\"ci-bound\">120.17 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">12.436 µs</td>\n                                <td>12.440 µs</td>\n                                <td class=\"ci-bound\">12.446 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">14.262 ns</td>\n                                <td>22.706 ns</td>\n                                <td class=\"ci-bound\">31.607 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−0.6391%</td>\n                            <td>−0.2491%</td>\n                            <td class=\"ci-bound\">+0.0437%</td>\n                            <td>(p = 0.17 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
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    "path": "docs/criterion/Clone/FlexStr 0.10 (LocalStr - Optimized)/100/base/benchmark.json",
    "content": "{\"group_id\":\"Clone\",\"function_id\":\"FlexStr 0.10 (LocalStr - Optimized)\",\"value_str\":\"100\",\"throughput\":null,\"full_id\":\"Clone/FlexStr 0.10 (LocalStr - Optimized)/100\",\"directory_name\":\"Clone/FlexStr 0.10 (LocalStr - Optimized)/100\",\"title\":\"Clone/FlexStr 0.10 (LocalStr - Optimized)/100\"}"
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    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":40277.08704669481,\"upper_bound\":40616.053817665845},\"point_estimate\":40403.275214359535,\"standard_error\":92.77886735887995},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":40219.287142857145,\"upper_bound\":40280.731339743594},\"point_estimate\":40250.72680851064,\"standard_error\":15.291605041829946},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":74.63920224674516,\"upper_bound\":128.70242047200577},\"point_estimate\":92.84539389832358,\"standard_error\":14.259774730900363},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":40251.84369422597,\"upper_bound\":40931.192872362575},\"point_estimate\":40475.34190418206,\"standard_error\":198.10552759580435},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":161.38833589422666,\"upper_bound\":1560.0966769900256},\"point_estimate\":930.3746802720026,\"standard_error\":460.16564663111166}}"
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    "path": "docs/criterion/Clone/FlexStr 0.10 (LocalStr - Optimized)/100/base/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[25.0,50.0,75.0,100.0,125.0,150.0,175.0,200.0,225.0,250.0,275.0,300.0,325.0,350.0,375.0,400.0,425.0,450.0,475.0,500.0,525.0,550.0,575.0,600.0,625.0,650.0,675.0,700.0,725.0,750.0,775.0,800.0,825.0,850.0,875.0,900.0,925.0,950.0,975.0,1000.0,1025.0,1050.0,1075.0,1100.0,1125.0,1150.0,1175.0,1200.0,1225.0,1250.0,1275.0,1300.0,1325.0,1350.0,1375.0,1400.0,1425.0,1450.0,1475.0,1500.0,1525.0,1550.0,1575.0,1600.0,1625.0,1650.0,1675.0,1700.0,1725.0,1750.0,1775.0,1800.0,1825.0,1850.0,1875.0,1900.0,1925.0,1950.0,1975.0,2000.0,2025.0,2050.0,2075.0,2100.0,2125.0,2150.0,2175.0,2200.0,2225.0,2250.0,2275.0,2300.0,2325.0,2350.0,2375.0,2400.0,2425.0,2450.0,2475.0,2500.0],\"times\":[1016622.0,2007333.0,3016583.0,4144583.0,5260749.0,6156581.0,7158751.0,8031291.0,9077207.0,10020624.0,11154663.0,12059292.0,13061958.0,14044252.0,15291626.0,16123084.0,17121668.0,18134250.0,19116124.0,20056000.0,21139248.0,22259875.0,23136001.0,24117709.0,25112251.0,26189710.0,27262042.0,28473874.0,29092874.0,30135334.0,31187751.0,32192124.0,33146125.0,34174417.0,35145126.0,36142791.0,37172082.0,38220582.0,39266373.0,40144251.0,41193292.0,42213793.0,43214417.0,44191084.0,45211083.0,46227127.0,47345706.0,48212253.0,49169500.0,50367374.0,51247916.0,52348957.0,53386834.0,54680501.0,55308875.0,56307002.0,57279582.0,58204709.0,59378166.0,60257165.0,61462084.0,62385082.0,63429251.0,64244336.0,65455458.0,66589584.0,67609877.0,68556250.0,69663999.0,70460584.0,71451375.0,72572458.0,73658998.0,74538333.0,75356126.0,76406252.0,77588706.0,78553584.0,79769625.0,80779832.0,81639332.0,82407751.0,83755043.0,84514251.0,85926375.0,86397915.0,107067335.0,89361959.0,89634874.0,90462500.0,91637877.0,92703375.0,93476000.0,94594582.0,96415791.0,96674834.0,97336292.0,98282916.0,99533919.0,100352167.0]}"
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    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.05040104337210119,\"upper_bound\":-0.0038619107959158815},\"point_estimate\":-0.024950674579305887,\"standard_error\":0.011951362656517445},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.0022699237224418356,\"upper_bound\":0.0009225106309479642},\"point_estimate\":-0.0006156672052086698,\"standard_error\":0.0008870087498302985}}"
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    "path": "docs/criterion/Clone/FlexStr 0.10 (LocalStr - Optimized)/100/new/benchmark.json",
    "content": "{\"group_id\":\"Clone\",\"function_id\":\"FlexStr 0.10 (LocalStr - Optimized)\",\"value_str\":\"100\",\"throughput\":null,\"full_id\":\"Clone/FlexStr 0.10 (LocalStr - Optimized)/100\",\"directory_name\":\"Clone/FlexStr 0.10 (LocalStr - Optimized)/100\",\"title\":\"Clone/FlexStr 0.10 (LocalStr - Optimized)/100\"}"
  },
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    "path": "docs/criterion/Clone/FlexStr 0.10 (LocalStr - Optimized)/100/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":40277.08704669481,\"upper_bound\":40616.053817665845},\"point_estimate\":40403.275214359535,\"standard_error\":92.77886735887995},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":40219.287142857145,\"upper_bound\":40280.731339743594},\"point_estimate\":40250.72680851064,\"standard_error\":15.291605041829946},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":74.63920224674516,\"upper_bound\":128.70242047200577},\"point_estimate\":92.84539389832358,\"standard_error\":14.259774730900363},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":40251.84369422597,\"upper_bound\":40931.192872362575},\"point_estimate\":40475.34190418206,\"standard_error\":198.10552759580435},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":161.38833589422666,\"upper_bound\":1560.0966769900256},\"point_estimate\":930.3746802720026,\"standard_error\":460.16564663111166}}"
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    "path": "docs/criterion/Clone/FlexStr 0.10 (LocalStr - Optimized)/100/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[25.0,50.0,75.0,100.0,125.0,150.0,175.0,200.0,225.0,250.0,275.0,300.0,325.0,350.0,375.0,400.0,425.0,450.0,475.0,500.0,525.0,550.0,575.0,600.0,625.0,650.0,675.0,700.0,725.0,750.0,775.0,800.0,825.0,850.0,875.0,900.0,925.0,950.0,975.0,1000.0,1025.0,1050.0,1075.0,1100.0,1125.0,1150.0,1175.0,1200.0,1225.0,1250.0,1275.0,1300.0,1325.0,1350.0,1375.0,1400.0,1425.0,1450.0,1475.0,1500.0,1525.0,1550.0,1575.0,1600.0,1625.0,1650.0,1675.0,1700.0,1725.0,1750.0,1775.0,1800.0,1825.0,1850.0,1875.0,1900.0,1925.0,1950.0,1975.0,2000.0,2025.0,2050.0,2075.0,2100.0,2125.0,2150.0,2175.0,2200.0,2225.0,2250.0,2275.0,2300.0,2325.0,2350.0,2375.0,2400.0,2425.0,2450.0,2475.0,2500.0],\"times\":[1016622.0,2007333.0,3016583.0,4144583.0,5260749.0,6156581.0,7158751.0,8031291.0,9077207.0,10020624.0,11154663.0,12059292.0,13061958.0,14044252.0,15291626.0,16123084.0,17121668.0,18134250.0,19116124.0,20056000.0,21139248.0,22259875.0,23136001.0,24117709.0,25112251.0,26189710.0,27262042.0,28473874.0,29092874.0,30135334.0,31187751.0,32192124.0,33146125.0,34174417.0,35145126.0,36142791.0,37172082.0,38220582.0,39266373.0,40144251.0,41193292.0,42213793.0,43214417.0,44191084.0,45211083.0,46227127.0,47345706.0,48212253.0,49169500.0,50367374.0,51247916.0,52348957.0,53386834.0,54680501.0,55308875.0,56307002.0,57279582.0,58204709.0,59378166.0,60257165.0,61462084.0,62385082.0,63429251.0,64244336.0,65455458.0,66589584.0,67609877.0,68556250.0,69663999.0,70460584.0,71451375.0,72572458.0,73658998.0,74538333.0,75356126.0,76406252.0,77588706.0,78553584.0,79769625.0,80779832.0,81639332.0,82407751.0,83755043.0,84514251.0,85926375.0,86397915.0,107067335.0,89361959.0,89634874.0,90462500.0,91637877.0,92703375.0,93476000.0,94594582.0,96415791.0,96674834.0,97336292.0,98282916.0,99533919.0,100352167.0]}"
  },
  {
    "path": "docs/criterion/Clone/FlexStr 0.10 (LocalStr - Optimized)/100/new/tukey.json",
    "content": "[39809.486105420045,39999.54044783197,40506.35202759711,40696.40637000904]"
  },
  {
    "path": "docs/criterion/Clone/FlexStr 0.10 (LocalStr - Optimized)/100/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/FlexStr 0.10 (LocalStr - Optimized)/100 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/FlexStr 0.10 (LocalStr - Optimized)/100</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">40.252 µs</td>\n                                <td>40.475 µs</td>\n                                <td class=\"ci-bound\">40.931 µs</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.8636493</td>\n                                <td>0.8669019</td>\n                                <td class=\"ci-bound\">0.8535294</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">40.277 µs</td>\n                                <td>40.403 µs</td>\n                                <td class=\"ci-bound\">40.616 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">161.39 ns</td>\n                                <td>930.37 ns</td>\n                                <td class=\"ci-bound\">1.5601 µs</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">40.219 µs</td>\n                                <td>40.251 µs</td>\n                                <td class=\"ci-bound\">40.281 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">74.639 ns</td>\n                                <td>92.845 ns</td>\n                                <td class=\"ci-bound\">128.70 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−5.0401%</td>\n                            <td>−2.4951%</td>\n                            <td class=\"ci-bound\">−0.3862%</td>\n                            <td>(p = 0.03 &lt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                Change within noise threshold.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
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    "path": "docs/criterion/Clone/FlexStr 0.10 (LocalStr - Optimized)/20/base/benchmark.json",
    "content": "{\"group_id\":\"Clone\",\"function_id\":\"FlexStr 0.10 (LocalStr - Optimized)\",\"value_str\":\"20\",\"throughput\":null,\"full_id\":\"Clone/FlexStr 0.10 (LocalStr - Optimized)/20\",\"directory_name\":\"Clone/FlexStr 0.10 (LocalStr - Optimized)/20\",\"title\":\"Clone/FlexStr 0.10 (LocalStr - Optimized)/20\"}"
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    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":12462.723009524088,\"upper_bound\":12506.501875939757},\"point_estimate\":12482.356565024702,\"standard_error\":11.212420570013078},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":12439.40311587147,\"upper_bound\":12450.604067233866},\"point_estimate\":12444.102299147507,\"standard_error\":3.0966209981463355},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":16.491179521389938,\"upper_bound\":31.5983973920359},\"point_estimate\":22.946097335234256,\"standard_error\":3.87224227280651},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":12445.249205461105,\"upper_bound\":12468.47577263211},\"point_estimate\":12455.56286778914,\"standard_error\":5.939886157738566},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":60.31377083471497,\"upper_bound\":161.4636195474016},\"point_estimate\":112.67859019076569,\"standard_error\":26.56779974910198}}"
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    "content": "{\"group_id\":\"Clone\",\"function_id\":\"FlexStr 0.10 (LocalStr - Optimized)\",\"value_str\":\"20\",\"throughput\":null,\"full_id\":\"Clone/FlexStr 0.10 (LocalStr - Optimized)/20\",\"directory_name\":\"Clone/FlexStr 0.10 (LocalStr - Optimized)/20\",\"title\":\"Clone/FlexStr 0.10 (LocalStr - Optimized)/20\"}"
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    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":12462.723009524088,\"upper_bound\":12506.501875939757},\"point_estimate\":12482.356565024702,\"standard_error\":11.212420570013078},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":12439.40311587147,\"upper_bound\":12450.604067233866},\"point_estimate\":12444.102299147507,\"standard_error\":3.0966209981463355},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":16.491179521389938,\"upper_bound\":31.5983973920359},\"point_estimate\":22.946097335234256,\"standard_error\":3.87224227280651},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":12445.249205461105,\"upper_bound\":12468.47577263211},\"point_estimate\":12455.56286778914,\"standard_error\":5.939886157738566},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":60.31377083471497,\"upper_bound\":161.4636195474016},\"point_estimate\":112.67859019076569,\"standard_error\":26.56779974910198}}"
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    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[79.0,158.0,237.0,316.0,395.0,474.0,553.0,632.0,711.0,790.0,869.0,948.0,1027.0,1106.0,1185.0,1264.0,1343.0,1422.0,1501.0,1580.0,1659.0,1738.0,1817.0,1896.0,1975.0,2054.0,2133.0,2212.0,2291.0,2370.0,2449.0,2528.0,2607.0,2686.0,2765.0,2844.0,2923.0,3002.0,3081.0,3160.0,3239.0,3318.0,3397.0,3476.0,3555.0,3634.0,3713.0,3792.0,3871.0,3950.0,4029.0,4108.0,4187.0,4266.0,4345.0,4424.0,4503.0,4582.0,4661.0,4740.0,4819.0,4898.0,4977.0,5056.0,5135.0,5214.0,5293.0,5372.0,5451.0,5530.0,5609.0,5688.0,5767.0,5846.0,5925.0,6004.0,6083.0,6162.0,6241.0,6320.0,6399.0,6478.0,6557.0,6636.0,6715.0,6794.0,6873.0,6952.0,7031.0,7110.0,7189.0,7268.0,7347.0,7426.0,7505.0,7584.0,7663.0,7742.0,7821.0,7900.0],\"times\":[1000626.0,1969543.0,3056334.0,4047290.0,5225373.0,6079083.0,6972629.0,7935376.0,8841959.0,9888623.0,10839416.0,11803666.0,12774375.0,13907668.0,14824293.0,15777249.0,16738668.0,17894958.0,18665500.0,19670458.0,20650790.0,21619332.0,22629960.0,23589834.0,24573584.0,25548334.0,26555959.0,27480044.0,28487918.0,29451582.0,30469666.0,31472457.0,32443915.0,33427458.0,34607959.0,35370584.0,36399125.0,37441084.0,38364375.0,39284876.0,40250668.0,41269875.0,42216251.0,43196206.0,44253378.0,45199834.0,46155458.0,47148000.0,48169752.0,49169751.0,50060250.0,51067373.0,52459748.0,53028625.0,54735585.0,55684459.0,56110793.0,57008583.0,57917874.0,58900999.0,59999461.0,60857793.0,61860331.0,63103707.0,63876335.0,65275168.0,65792164.0,66767416.0,67747584.0,68719253.0,70786627.0,70772916.0,72024625.0,73040833.0,73822041.0,74802957.0,75699624.0,78049083.0,77776833.0,78775248.0,79615834.0,80525878.0,81458335.0,82759417.0,84074956.0,84665625.0,85459333.0,86338875.0,87351126.0,88459750.0,89404374.0,90360625.0,91322624.0,92291957.0,93478373.0,94349333.0,95574249.0,96215751.0,97230957.0,98146875.0]}"
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    "content": "[12310.735744925008,12371.239020222973,12532.581087684208,12593.08436298217]"
  },
  {
    "path": "docs/criterion/Clone/FlexStr 0.10 (LocalStr - Optimized)/20/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/FlexStr 0.10 (LocalStr - Optimized)/20 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/FlexStr 0.10 (LocalStr - Optimized)/20</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">12.445 µs</td>\n                                <td>12.456 µs</td>\n                                <td class=\"ci-bound\">12.468 µs</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.9978432</td>\n                                <td>0.9979385</td>\n                                <td class=\"ci-bound\">0.9977891</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">12.463 µs</td>\n                                <td>12.482 µs</td>\n                                <td class=\"ci-bound\">12.507 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">60.314 ns</td>\n                                <td>112.68 ns</td>\n                                <td class=\"ci-bound\">161.46 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">12.439 µs</td>\n                                <td>12.444 µs</td>\n                                <td class=\"ci-bound\">12.451 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">16.491 ns</td>\n                                <td>22.946 ns</td>\n                                <td class=\"ci-bound\">31.598 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−0.1060%</td>\n                            <td>+0.0918%</td>\n                            <td class=\"ci-bound\">+0.2920%</td>\n                            <td>(p = 0.39 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
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  },
  {
    "path": "docs/criterion/Clone/FlexStr 0.10 (LocalStr - Optimized)/500/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/FlexStr 0.10 (LocalStr - Optimized)/500 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/FlexStr 0.10 (LocalStr - Optimized)/500</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">40.212 µs</td>\n                                <td>40.225 µs</td>\n                                <td class=\"ci-bound\">40.240 µs</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.9993198</td>\n                                <td>0.9993350</td>\n                                <td class=\"ci-bound\">0.9993145</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">40.266 µs</td>\n                                <td>40.312 µs</td>\n                                <td class=\"ci-bound\">40.366 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">153.63 ns</td>\n                                <td>258.53 ns</td>\n                                <td class=\"ci-bound\">346.33 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">40.214 µs</td>\n                                <td>40.223 µs</td>\n                                <td class=\"ci-bound\">40.241 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">37.367 ns</td>\n                                <td>60.418 ns</td>\n                                <td class=\"ci-bound\">83.182 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−2.1413%</td>\n                            <td>−0.9583%</td>\n                            <td class=\"ci-bound\">−0.2165%</td>\n                            <td>(p = 0.03 &lt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                Change within noise threshold.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Clone/FlexStr 0.10 (LocalStr - Optimized)/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/FlexStr 0.10 (LocalStr - Optimized) Summary - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/FlexStr 0.10 (LocalStr - Optimized)</h2>\n        <h3>Violin Plot</h3>\n        <a href=\"violin.svg\">\n            <img src=\"violin.svg\" alt=\"Violin Plot\" />\n        </a>\n        <p>This chart shows the relationship between function/parameter and iteration time. The thickness of the shaded\n            region indicates the probability that a measurement of the given function/parameter would take a particular\n            length of time.</p>\n        <h3>Line Chart</h3>\n        <img src=\"lines.svg\" alt=\"Line Chart\" />\n        <p>This chart shows the mean measured time for each function as the input (or the size of the input) increases.</p>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/FlexStr 0.10 (LocalStr - Optimized)/0/report/index.html\">\n                <h4>Clone/FlexStr 0.10 (LocalStr - Optimized)/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (LocalStr - Optimized)/0/report/pdf.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (LocalStr - Optimized)/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (LocalStr - Optimized)/0/report/regression.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (LocalStr - Optimized)/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/FlexStr 0.10 (LocalStr - Optimized)/10/report/index.html\">\n                <h4>Clone/FlexStr 0.10 (LocalStr - Optimized)/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (LocalStr - Optimized)/10/report/pdf.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (LocalStr - Optimized)/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (LocalStr - Optimized)/10/report/regression.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (LocalStr - Optimized)/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/FlexStr 0.10 (LocalStr - Optimized)/20/report/index.html\">\n                <h4>Clone/FlexStr 0.10 (LocalStr - Optimized)/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (LocalStr - Optimized)/20/report/pdf.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (LocalStr - Optimized)/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (LocalStr - Optimized)/20/report/regression.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (LocalStr - Optimized)/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/FlexStr 0.10 (LocalStr - Optimized)/100/report/index.html\">\n                <h4>Clone/FlexStr 0.10 (LocalStr - Optimized)/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (LocalStr - Optimized)/100/report/pdf.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (LocalStr - Optimized)/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (LocalStr - Optimized)/100/report/regression.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (LocalStr - Optimized)/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/FlexStr 0.10 (LocalStr - Optimized)/500/report/index.html\">\n                <h4>Clone/FlexStr 0.10 (LocalStr - Optimized)/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (LocalStr - Optimized)/500/report/pdf.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (LocalStr - Optimized)/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (LocalStr - Optimized)/500/report/regression.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (LocalStr - Optimized)/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Clone/FlexStr 0.10 (SharedStr - Boxed)/0/base/benchmark.json",
    "content": "{\"group_id\":\"Clone\",\"function_id\":\"FlexStr 0.10 (SharedStr - Boxed)\",\"value_str\":\"0\",\"throughput\":null,\"full_id\":\"Clone/FlexStr 0.10 (SharedStr - Boxed)/0\",\"directory_name\":\"Clone/FlexStr 0.10 (SharedStr - Boxed)/0\",\"title\":\"Clone/FlexStr 0.10 (SharedStr - Boxed)/0\"}"
  },
  {
    "path": "docs/criterion/Clone/FlexStr 0.10 (SharedStr - Boxed)/0/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":81024.94621305424,\"upper_bound\":81695.39465534729},\"point_estimate\":81289.73330818518,\"standard_error\":177.83252119659394},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":80841.88425925926,\"upper_bound\":80950.64880952382},\"point_estimate\":80871.01089340198,\"standard_error\":29.76604165937697},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":115.58311331415209,\"upper_bound\":240.64155151714218},\"point_estimate\":176.4241800454855,\"standard_error\":31.228518021811148},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":80854.0242749032,\"upper_bound\":82432.8014666018},\"point_estimate\":81375.51226786857,\"standard_error\":463.5769082991296},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":457.4765594424016,\"upper_bound\":2930.0524550137593},\"point_estimate\":1786.3145498205497,\"standard_error\":778.029261868577}}"
  },
  {
    "path": "docs/criterion/Clone/FlexStr 0.10 (SharedStr - Boxed)/0/base/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[12.0,24.0,36.0,48.0,60.0,72.0,84.0,96.0,108.0,120.0,132.0,144.0,156.0,168.0,180.0,192.0,204.0,216.0,228.0,240.0,252.0,264.0,276.0,288.0,300.0,312.0,324.0,336.0,348.0,360.0,372.0,384.0,396.0,408.0,420.0,432.0,444.0,456.0,468.0,480.0,492.0,504.0,516.0,528.0,540.0,552.0,564.0,576.0,588.0,600.0,612.0,624.0,636.0,648.0,660.0,672.0,684.0,696.0,708.0,720.0,732.0,744.0,756.0,768.0,780.0,792.0,804.0,816.0,828.0,840.0,852.0,864.0,876.0,888.0,900.0,912.0,924.0,936.0,948.0,960.0,972.0,984.0,996.0,1008.0,1020.0,1032.0,1044.0,1056.0,1068.0,1080.0,1092.0,1104.0,1116.0,1128.0,1140.0,1152.0,1164.0,1176.0,1188.0,1200.0],\"times\":[975332.0,1993457.0,2916916.0,4044667.0,5128252.0,5906917.0,6863709.0,7935749.0,8816125.0,9746251.0,10939000.0,11666956.0,12650334.0,13599709.0,14763041.0,15554918.0,16624000.0,17756626.0,18711750.0,19524081.0,20465291.0,21411500.0,22512085.0,23269292.0,24257292.0,25210793.0,26242166.0,27234125.0,28120624.0,29070375.0,30049792.0,31109458.0,32023792.0,33144208.0,33930624.0,34958749.0,36020792.0,36873415.0,37904541.0,38822376.0,39820583.0,40745753.0,41715168.0,42637583.0,43629458.0,44641169.0,45719372.0,46522376.0,47656251.0,48597124.0,49475082.0,50389209.0,51353790.0,52385541.0,53306293.0,54327209.0,55402292.0,56247251.0,57232124.0,58174626.0,59238834.0,60159876.0,61046291.0,62026375.0,63012125.0,63927541.0,64964833.0,65922792.0,66913791.0,67824999.0,68831541.0,70242833.0,70738832.0,71932915.0,72786499.0,73753749.0,74685666.0,75526208.0,76568753.0,77520042.0,78577958.0,79476748.0,80472957.0,81439252.0,82400912.0,83463498.0,84571290.0,85420416.0,86320834.0,87204666.0,88163206.0,90665500.0,90336292.0,91313251.0,92057125.0,93723084.0,94287332.0,114679083.0,96013708.0,97015083.0]}"
  },
  {
    "path": "docs/criterion/Clone/FlexStr 0.10 (SharedStr - Boxed)/0/base/tukey.json",
    "content": "[79968.76134427042,80381.72898562727,81482.97602924556,81895.94367060243]"
  },
  {
    "path": "docs/criterion/Clone/FlexStr 0.10 (SharedStr - Boxed)/0/change/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.046104049527195816,\"upper_bound\":-0.0010644310684283698},\"point_estimate\":-0.021346302419605778,\"standard_error\":0.011585988612886183},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.0023650587330023695,\"upper_bound\":0.00029942173996566623},\"point_estimate\":-0.0008038872383331341,\"standard_error\":0.0006513524396761291}}"
  },
  {
    "path": "docs/criterion/Clone/FlexStr 0.10 (SharedStr - Boxed)/0/new/benchmark.json",
    "content": "{\"group_id\":\"Clone\",\"function_id\":\"FlexStr 0.10 (SharedStr - Boxed)\",\"value_str\":\"0\",\"throughput\":null,\"full_id\":\"Clone/FlexStr 0.10 (SharedStr - Boxed)/0\",\"directory_name\":\"Clone/FlexStr 0.10 (SharedStr - Boxed)/0\",\"title\":\"Clone/FlexStr 0.10 (SharedStr - Boxed)/0\"}"
  },
  {
    "path": "docs/criterion/Clone/FlexStr 0.10 (SharedStr - Boxed)/0/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":81024.94621305424,\"upper_bound\":81695.39465534729},\"point_estimate\":81289.73330818518,\"standard_error\":177.83252119659394},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":80841.88425925926,\"upper_bound\":80950.64880952382},\"point_estimate\":80871.01089340198,\"standard_error\":29.76604165937697},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":115.58311331415209,\"upper_bound\":240.64155151714218},\"point_estimate\":176.4241800454855,\"standard_error\":31.228518021811148},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":80854.0242749032,\"upper_bound\":82432.8014666018},\"point_estimate\":81375.51226786857,\"standard_error\":463.5769082991296},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":457.4765594424016,\"upper_bound\":2930.0524550137593},\"point_estimate\":1786.3145498205497,\"standard_error\":778.029261868577}}"
  },
  {
    "path": "docs/criterion/Clone/FlexStr 0.10 (SharedStr - Boxed)/0/new/sample.json",
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  {
    "path": "docs/criterion/Clone/FlexStr 0.10 (SharedStr - Boxed)/0/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/FlexStr 0.10 (SharedStr - Boxed)/0 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/FlexStr 0.10 (SharedStr - Boxed)/0</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">80.854 µs</td>\n                                <td>81.376 µs</td>\n                                <td class=\"ci-bound\">82.433 µs</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.8549298</td>\n                                <td>0.8591939</td>\n                                <td class=\"ci-bound\">0.8419326</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">81.025 µs</td>\n                                <td>81.290 µs</td>\n                                <td class=\"ci-bound\">81.695 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">457.48 ns</td>\n                                <td>1.7863 µs</td>\n                                <td class=\"ci-bound\">2.9301 µs</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">80.842 µs</td>\n                                <td>80.871 µs</td>\n                                <td class=\"ci-bound\">80.951 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">115.58 ns</td>\n                                <td>176.42 ns</td>\n                                <td class=\"ci-bound\">240.64 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−4.6104%</td>\n                            <td>−2.1346%</td>\n                            <td class=\"ci-bound\">−0.1064%</td>\n                            <td>(p = 0.06 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
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    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/FlexStr 0.10 (SharedStr - Boxed)/10 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/FlexStr 0.10 (SharedStr - Boxed)/10</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">68.450 µs</td>\n                                <td>68.497 µs</td>\n                                <td class=\"ci-bound\">68.558 µs</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.9986314</td>\n                                <td>0.9986987</td>\n                                <td class=\"ci-bound\">0.9985893</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">68.532 µs</td>\n                                <td>68.603 µs</td>\n                                <td class=\"ci-bound\">68.684 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">265.20 ns</td>\n                                <td>394.12 ns</td>\n                                <td class=\"ci-bound\">501.57 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">68.451 µs</td>\n                                <td>68.477 µs</td>\n                                <td class=\"ci-bound\">68.497 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">107.47 ns</td>\n                                <td>144.59 ns</td>\n                                <td class=\"ci-bound\">180.55 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−0.1466%</td>\n                            <td>+0.0041%</td>\n                            <td class=\"ci-bound\">+0.1576%</td>\n                            <td>(p = 0.95 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
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    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":250056.12665371134,\"upper_bound\":256174.42605125884},\"point_estimate\":252322.12550116162,\"standard_error\":1716.9240894126626},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":249174.2708333333,\"upper_bound\":250100.44578291557},\"point_estimate\":249582.57738646894,\"standard_error\":231.74146734791674},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":1264.5548666625546,\"upper_bound\":2393.7595862522808},\"point_estimate\":1963.1178322925664,\"standard_error\":290.22049180747507},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":249836.03095106725,\"upper_bound\":254016.66406685536},\"point_estimate\":251388.87338776415,\"standard_error\":1120.7449657984437},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3002.2147452913346,\"upper_bound\":29060.641370816586},\"point_estimate\":17235.823027617604,\"standard_error\":8887.793411239863}}"
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    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[4.0,8.0,12.0,16.0,20.0,24.0,28.0,32.0,36.0,40.0,44.0,48.0,52.0,56.0,60.0,64.0,68.0,72.0,76.0,80.0,84.0,88.0,92.0,96.0,100.0,104.0,108.0,112.0,116.0,120.0,124.0,128.0,132.0,136.0,140.0,144.0,148.0,152.0,156.0,160.0,164.0,168.0,172.0,176.0,180.0,184.0,188.0,192.0,196.0,200.0,204.0,208.0,212.0,216.0,220.0,224.0,228.0,232.0,236.0,240.0,244.0,248.0,252.0,256.0,260.0,264.0,268.0,272.0,276.0,280.0,284.0,288.0,292.0,296.0,300.0,304.0,308.0,312.0,316.0,320.0,324.0,328.0,332.0,336.0,340.0,344.0,348.0,352.0,356.0,360.0,364.0,368.0,372.0,376.0,380.0,384.0,388.0,392.0,396.0,400.0],\"times\":[1005377.0,2010873.0,3013751.0,4123251.0,5070292.0,6544959.0,7483248.0,8117125.0,8948041.0,10013335.0,11306749.0,12156127.0,13002709.0,13986499.0,15060040.0,16056793.0,16966458.0,17990582.0,18842833.0,19975250.0,20893541.0,21814041.0,22894083.0,23872335.0,24873748.0,25733750.0,26710665.0,27558916.0,28464167.0,29398293.0,31021375.0,31958668.0,32863584.0,33907416.0,34835249.0,35821083.0,36882497.0,37895415.0,38846247.0,39814501.0,41848542.0,41742375.0,42592460.0,43685917.0,44630415.0,76918461.0,47245333.0,47897332.0,48771792.0,49698251.0,50811334.0,51922836.0,52426459.0,55582499.0,55355249.0,55553960.0,56636042.0,58258127.0,59103167.0,59714295.0,60360416.0,60911502.0,64756792.0,67100125.0,67102207.0,67786874.0,66428376.0,67108291.0,68052374.0,70305499.0,72799874.0,72378085.0,75320208.0,74923376.0,74705377.0,76229915.0,76923167.0,78014915.0,79959749.0,80396124.0,80411498.0,81761667.0,82845997.0,83628417.0,84792166.0,86314042.0,86560000.0,88316959.0,89054499.0,88458084.0,91078042.0,92213542.0,92739499.0,93926626.0,94591666.0,96561665.0,96981418.0,98895377.0,98752625.0,99579249.0]}"
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    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":250056.12665371134,\"upper_bound\":256174.42605125884},\"point_estimate\":252322.12550116162,\"standard_error\":1716.9240894126626},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":249174.2708333333,\"upper_bound\":250100.44578291557},\"point_estimate\":249582.57738646894,\"standard_error\":231.74146734791674},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":1264.5548666625546,\"upper_bound\":2393.7595862522808},\"point_estimate\":1963.1178322925664,\"standard_error\":290.22049180747507},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":249836.03095106725,\"upper_bound\":254016.66406685536},\"point_estimate\":251388.87338776415,\"standard_error\":1120.7449657984437},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3002.2147452913346,\"upper_bound\":29060.641370816586},\"point_estimate\":17235.823027617604,\"standard_error\":8887.793411239863}}"
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    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[4.0,8.0,12.0,16.0,20.0,24.0,28.0,32.0,36.0,40.0,44.0,48.0,52.0,56.0,60.0,64.0,68.0,72.0,76.0,80.0,84.0,88.0,92.0,96.0,100.0,104.0,108.0,112.0,116.0,120.0,124.0,128.0,132.0,136.0,140.0,144.0,148.0,152.0,156.0,160.0,164.0,168.0,172.0,176.0,180.0,184.0,188.0,192.0,196.0,200.0,204.0,208.0,212.0,216.0,220.0,224.0,228.0,232.0,236.0,240.0,244.0,248.0,252.0,256.0,260.0,264.0,268.0,272.0,276.0,280.0,284.0,288.0,292.0,296.0,300.0,304.0,308.0,312.0,316.0,320.0,324.0,328.0,332.0,336.0,340.0,344.0,348.0,352.0,356.0,360.0,364.0,368.0,372.0,376.0,380.0,384.0,388.0,392.0,396.0,400.0],\"times\":[1005377.0,2010873.0,3013751.0,4123251.0,5070292.0,6544959.0,7483248.0,8117125.0,8948041.0,10013335.0,11306749.0,12156127.0,13002709.0,13986499.0,15060040.0,16056793.0,16966458.0,17990582.0,18842833.0,19975250.0,20893541.0,21814041.0,22894083.0,23872335.0,24873748.0,25733750.0,26710665.0,27558916.0,28464167.0,29398293.0,31021375.0,31958668.0,32863584.0,33907416.0,34835249.0,35821083.0,36882497.0,37895415.0,38846247.0,39814501.0,41848542.0,41742375.0,42592460.0,43685917.0,44630415.0,76918461.0,47245333.0,47897332.0,48771792.0,49698251.0,50811334.0,51922836.0,52426459.0,55582499.0,55355249.0,55553960.0,56636042.0,58258127.0,59103167.0,59714295.0,60360416.0,60911502.0,64756792.0,67100125.0,67102207.0,67786874.0,66428376.0,67108291.0,68052374.0,70305499.0,72799874.0,72378085.0,75320208.0,74923376.0,74705377.0,76229915.0,76923167.0,78014915.0,79959749.0,80396124.0,80411498.0,81761667.0,82845997.0,83628417.0,84792166.0,86314042.0,86560000.0,88316959.0,89054499.0,88458084.0,91078042.0,92213542.0,92739499.0,93926626.0,94591666.0,96561665.0,96981418.0,98895377.0,98752625.0,99579249.0]}"
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  },
  {
    "path": "docs/criterion/Clone/FlexStr 0.10 (SharedStr - Boxed)/100/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/FlexStr 0.10 (SharedStr - Boxed)/100 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/FlexStr 0.10 (SharedStr - Boxed)/100</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">249.84 µs</td>\n                                <td>251.39 µs</td>\n                                <td class=\"ci-bound\">254.02 µs</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.7023705</td>\n                                <td>0.7050955</td>\n                                <td class=\"ci-bound\">0.6973478</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">250.06 µs</td>\n                                <td>252.32 µs</td>\n                                <td class=\"ci-bound\">256.17 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">3.0022 µs</td>\n                                <td>17.236 µs</td>\n                                <td class=\"ci-bound\">29.061 µs</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">249.17 µs</td>\n                                <td>249.58 µs</td>\n                                <td class=\"ci-bound\">250.10 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">1.2646 µs</td>\n                                <td>1.9631 µs</td>\n                                <td class=\"ci-bound\">2.3938 µs</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">+0.0541%</td>\n                            <td>+1.0187%</td>\n                            <td class=\"ci-bound\">+2.8661%</td>\n                            <td>(p = 0.11 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
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  },
  {
    "path": "docs/criterion/Clone/FlexStr 0.10 (SharedStr - Boxed)/20/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/FlexStr 0.10 (SharedStr - Boxed)/20 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/FlexStr 0.10 (SharedStr - Boxed)/20</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">74.702 µs</td>\n                                <td>74.809 µs</td>\n                                <td class=\"ci-bound\">74.946 µs</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.9940861</td>\n                                <td>0.9943683</td>\n                                <td class=\"ci-bound\">0.9939046</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">74.729 µs</td>\n                                <td>74.836 µs</td>\n                                <td class=\"ci-bound\">74.965 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">316.21 ns</td>\n                                <td>606.19 ns</td>\n                                <td class=\"ci-bound\">837.43 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">74.616 µs</td>\n                                <td>74.664 µs</td>\n                                <td class=\"ci-bound\">74.712 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">134.09 ns</td>\n                                <td>199.96 ns</td>\n                                <td class=\"ci-bound\">242.98 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−0.2328%</td>\n                            <td>−0.0193%</td>\n                            <td class=\"ci-bound\">+0.1955%</td>\n                            <td>(p = 0.87 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
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    "path": "docs/criterion/Clone/FlexStr 0.10 (SharedStr - Boxed)/500/base/benchmark.json",
    "content": "{\"group_id\":\"Clone\",\"function_id\":\"FlexStr 0.10 (SharedStr - Boxed)\",\"value_str\":\"500\",\"throughput\":null,\"full_id\":\"Clone/FlexStr 0.10 (SharedStr - Boxed)/500\",\"directory_name\":\"Clone/FlexStr 0.10 (SharedStr - Boxed)/500\",\"title\":\"Clone/FlexStr 0.10 (SharedStr - Boxed)/500\"}"
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    "path": "docs/criterion/Clone/FlexStr 0.10 (SharedStr - Boxed)/500/base/tukey.json",
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    "path": "docs/criterion/Clone/FlexStr 0.10 (SharedStr - Boxed)/500/new/estimates.json",
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    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[2.0,4.0,6.0,8.0,10.0,12.0,14.0,16.0,18.0,20.0,22.0,24.0,26.0,28.0,30.0,32.0,34.0,36.0,38.0,40.0,42.0,44.0,46.0,48.0,50.0,52.0,54.0,56.0,58.0,60.0,62.0,64.0,66.0,68.0,70.0,72.0,74.0,76.0,78.0,80.0,82.0,84.0,86.0,88.0,90.0,92.0,94.0,96.0,98.0,100.0,102.0,104.0,106.0,108.0,110.0,112.0,114.0,116.0,118.0,120.0,122.0,124.0,126.0,128.0,130.0,132.0,134.0,136.0,138.0,140.0,142.0,144.0,146.0,148.0,150.0,152.0,154.0,156.0,158.0,160.0,162.0,164.0,166.0,168.0,170.0,172.0,174.0,176.0,178.0,180.0,182.0,184.0,186.0,188.0,190.0,192.0,194.0,196.0,198.0,200.0],\"times\":[1039042.0,2031293.0,3054083.0,4151873.0,5238708.0,6220416.0,7342876.0,8091041.0,9243875.0,10260541.0,11741706.0,12610957.0,13685957.0,14748791.0,15885333.0,17142625.0,18087124.0,19196250.0,20109958.0,21227791.0,22111916.0,23266086.0,24223332.0,25256542.0,26429378.0,27603707.0,28396501.0,29402168.0,30673082.0,31826208.0,32813667.0,33540084.0,34990792.0,35790624.0,36560250.0,37672623.0,38580665.0,39878294.0,40793876.0,41613791.0,43051333.0,44387124.0,45176710.0,45917751.0,46985542.0,48085461.0,49007125.0,50022041.0,51921586.0,51839667.0,53358333.0,54285917.0,54884749.0,58838499.0,57356251.0,58588999.0,59253125.0,60027918.0,61180751.0,62260830.0,63451666.0,64174498.0,65047623.0,66436667.0,67474874.0,68154666.0,69266165.0,70417165.0,71743127.0,72600874.0,73571542.0,77135791.0,76883208.0,78217125.0,80100999.0,79293497.0,80157583.0,81700834.0,82281207.0,82661374.0,83891626.0,85543251.0,85313498.0,86708375.0,87923041.0,89536834.0,91098792.0,90938958.0,91786543.0,92571749.0,93866957.0,94537416.0,96435837.0,96934209.0,98196959.0,99262999.0,99644918.0,100734124.0,101834044.0,103225667.0]}"
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    "path": "docs/criterion/Clone/FlexStr 0.10 (SharedStr - Boxed)/500/new/tukey.json",
    "content": "[491055.06491564284,504288.8917459193,539579.0966266566,552812.923456933]"
  },
  {
    "path": "docs/criterion/Clone/FlexStr 0.10 (SharedStr - Boxed)/500/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/FlexStr 0.10 (SharedStr - Boxed)/500 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/FlexStr 0.10 (SharedStr - Boxed)/500</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">518.43 µs</td>\n                                <td>519.61 µs</td>\n                                <td class=\"ci-bound\">521.03 µs</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.9839708</td>\n                                <td>0.9846877</td>\n                                <td class=\"ci-bound\">0.9836552</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">520.76 µs</td>\n                                <td>522.02 µs</td>\n                                <td class=\"ci-bound\">523.31 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">5.4590 µs</td>\n                                <td>6.5035 µs</td>\n                                <td class=\"ci-bound\">7.5200 µs</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">519.70 µs</td>\n                                <td>521.39 µs</td>\n                                <td class=\"ci-bound\">523.12 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">4.8623 µs</td>\n                                <td>6.5726 µs</td>\n                                <td class=\"ci-bound\">7.7720 µs</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−0.2259%</td>\n                            <td>+0.1441%</td>\n                            <td class=\"ci-bound\">+0.5063%</td>\n                            <td>(p = 0.43 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Clone/FlexStr 0.10 (SharedStr - Boxed)/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/FlexStr 0.10 (SharedStr - Boxed) Summary - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/FlexStr 0.10 (SharedStr - Boxed)</h2>\n        <h3>Violin Plot</h3>\n        <a href=\"violin.svg\">\n            <img src=\"violin.svg\" alt=\"Violin Plot\" />\n        </a>\n        <p>This chart shows the relationship between function/parameter and iteration time. The thickness of the shaded\n            region indicates the probability that a measurement of the given function/parameter would take a particular\n            length of time.</p>\n        <h3>Line Chart</h3>\n        <img src=\"lines.svg\" alt=\"Line Chart\" />\n        <p>This chart shows the mean measured time for each function as the input (or the size of the input) increases.</p>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/FlexStr 0.10 (SharedStr - Boxed)/0/report/index.html\">\n                <h4>Clone/FlexStr 0.10 (SharedStr - Boxed)/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (SharedStr - Boxed)/0/report/pdf.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (SharedStr - Boxed)/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (SharedStr - Boxed)/0/report/regression.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (SharedStr - Boxed)/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/FlexStr 0.10 (SharedStr - Boxed)/10/report/index.html\">\n                <h4>Clone/FlexStr 0.10 (SharedStr - Boxed)/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (SharedStr - Boxed)/10/report/pdf.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (SharedStr - Boxed)/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (SharedStr - Boxed)/10/report/regression.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (SharedStr - Boxed)/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/FlexStr 0.10 (SharedStr - Boxed)/20/report/index.html\">\n                <h4>Clone/FlexStr 0.10 (SharedStr - Boxed)/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (SharedStr - Boxed)/20/report/pdf.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (SharedStr - Boxed)/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (SharedStr - Boxed)/20/report/regression.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (SharedStr - Boxed)/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/FlexStr 0.10 (SharedStr - Boxed)/100/report/index.html\">\n                <h4>Clone/FlexStr 0.10 (SharedStr - Boxed)/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (SharedStr - Boxed)/100/report/pdf.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (SharedStr - Boxed)/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (SharedStr - Boxed)/100/report/regression.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (SharedStr - Boxed)/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/FlexStr 0.10 (SharedStr - Boxed)/500/report/index.html\">\n                <h4>Clone/FlexStr 0.10 (SharedStr - Boxed)/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (SharedStr - Boxed)/500/report/pdf.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (SharedStr - Boxed)/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (SharedStr - Boxed)/500/report/regression.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (SharedStr - Boxed)/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Clone/FlexStr 0.10 (SharedStr - Optimized)/0/base/benchmark.json",
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  },
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    "path": "docs/criterion/Clone/FlexStr 0.10 (SharedStr - Optimized)/0/base/sample.json",
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    "path": "docs/criterion/Clone/FlexStr 0.10 (SharedStr - Optimized)/0/base/tukey.json",
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  {
    "path": "docs/criterion/Clone/FlexStr 0.10 (SharedStr - Optimized)/0/change/estimates.json",
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  },
  {
    "path": "docs/criterion/Clone/FlexStr 0.10 (SharedStr - Optimized)/0/new/benchmark.json",
    "content": "{\"group_id\":\"Clone\",\"function_id\":\"FlexStr 0.10 (SharedStr - Optimized)\",\"value_str\":\"0\",\"throughput\":null,\"full_id\":\"Clone/FlexStr 0.10 (SharedStr - Optimized)/0\",\"directory_name\":\"Clone/FlexStr 0.10 (SharedStr - Optimized)/0\",\"title\":\"Clone/FlexStr 0.10 (SharedStr - Optimized)/0\"}"
  },
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  },
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    "path": "docs/criterion/Clone/FlexStr 0.10 (SharedStr - Optimized)/0/new/sample.json",
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  },
  {
    "path": "docs/criterion/Clone/FlexStr 0.10 (SharedStr - Optimized)/0/new/tukey.json",
    "content": "[11812.336146386646,12130.40881437291,12978.60259566961,13296.675263655872]"
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  {
    "path": "docs/criterion/Clone/FlexStr 0.10 (SharedStr - Optimized)/0/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/FlexStr 0.10 (SharedStr - Optimized)/0 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/FlexStr 0.10 (SharedStr - Optimized)/0</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">12.524 µs</td>\n                                <td>12.563 µs</td>\n                                <td class=\"ci-bound\">12.608 µs</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.9720283</td>\n                                <td>0.9733696</td>\n                                <td class=\"ci-bound\">0.9716530</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">12.548 µs</td>\n                                <td>12.589 µs</td>\n                                <td class=\"ci-bound\">12.634 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">159.68 ns</td>\n                                <td>218.63 ns</td>\n                                <td class=\"ci-bound\">274.76 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">12.470 µs</td>\n                                <td>12.484 µs</td>\n                                <td class=\"ci-bound\">12.532 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">49.181 ns</td>\n                                <td>76.446 ns</td>\n                                <td class=\"ci-bound\">134.12 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">+0.5193%</td>\n                            <td>+0.8845%</td>\n                            <td class=\"ci-bound\">+1.2489%</td>\n                            <td>(p = 0.00 &lt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                Change within noise threshold.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
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    "content": "{\"group_id\":\"Clone\",\"function_id\":\"FlexStr 0.10 (SharedStr - Optimized)\",\"value_str\":\"10\",\"throughput\":null,\"full_id\":\"Clone/FlexStr 0.10 (SharedStr - Optimized)/10\",\"directory_name\":\"Clone/FlexStr 0.10 (SharedStr - Optimized)/10\",\"title\":\"Clone/FlexStr 0.10 (SharedStr - Optimized)/10\"}"
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    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":12566.49187207371,\"upper_bound\":13111.52861064182},\"point_estimate\":12807.54078100992,\"standard_error\":140.5410796587168},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":12439.724038461538,\"upper_bound\":12452.792944500674},\"point_estimate\":12443.414058139535,\"standard_error\":3.2491731648232585},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":15.346572900619282,\"upper_bound\":35.00039340377634},\"point_estimate\":21.236940564714992,\"standard_error\":4.830250133941574},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":12539.220161222003,\"upper_bound\":13111.732699817172},\"point_estimate\":12784.953107580908,\"standard_error\":147.21170737148017},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":612.543602776595,\"upper_bound\":2007.8288265907802},\"point_estimate\":1415.0033841601726,\"standard_error\":359.04391687582785}}"
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    "path": "docs/criterion/Clone/FlexStr 0.10 (SharedStr - Optimized)/10/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[80.0,160.0,240.0,320.0,400.0,480.0,560.0,640.0,720.0,800.0,880.0,960.0,1040.0,1120.0,1200.0,1280.0,1360.0,1440.0,1520.0,1600.0,1680.0,1760.0,1840.0,1920.0,2000.0,2080.0,2160.0,2240.0,2320.0,2400.0,2480.0,2560.0,2640.0,2720.0,2800.0,2880.0,2960.0,3040.0,3120.0,3200.0,3280.0,3360.0,3440.0,3520.0,3600.0,3680.0,3760.0,3840.0,3920.0,4000.0,4080.0,4160.0,4240.0,4320.0,4400.0,4480.0,4560.0,4640.0,4720.0,4800.0,4880.0,4960.0,5040.0,5120.0,5200.0,5280.0,5360.0,5440.0,5520.0,5600.0,5680.0,5760.0,5840.0,5920.0,6000.0,6080.0,6160.0,6240.0,6320.0,6400.0,6480.0,6560.0,6640.0,6720.0,6800.0,6880.0,6960.0,7040.0,7120.0,7200.0,7280.0,7360.0,7440.0,7520.0,7600.0,7680.0,7760.0,7840.0,7920.0,8000.0],\"times\":[1014833.0,1989833.0,2994832.0,4099124.0,5153666.0,6064834.0,6989416.0,8033417.0,8934124.0,10426210.0,11022417.0,11998917.0,12954709.0,13928083.0,15123084.0,15985248.0,16918124.0,17963584.0,18907917.0,19908002.0,20927372.0,21903000.0,22920080.0,23886042.0,24887876.0,25874626.0,26860833.0,27852665.0,28825625.0,29856750.0,30945499.0,32059084.0,32842167.0,34023792.0,34786627.0,35939792.0,36896876.0,37850165.0,38859206.0,39936207.0,40769415.0,41751125.0,42803542.0,43811375.0,44801207.0,46511375.0,47309000.0,47731249.0,48687626.0,49758627.0,50743293.0,51690751.0,52692584.0,53771043.0,65574083.0,58523208.0,85469248.0,98725375.0,84203834.0,95006794.0,68725208.0,64505919.0,65329376.0,63749085.0,64655123.0,65647958.0,66598625.0,67628500.0,68883833.0,69606251.0,70842167.0,71643375.0,72622708.0,73564793.0,74549043.0,75685417.0,76582500.0,77553166.0,78576753.0,79740960.0,80589166.0,81913209.0,82555127.0,83533956.0,84545542.0,85496918.0,86515165.0,87578960.0,88492833.0,89534166.0,90492041.0,91680416.0,92611957.0,93583206.0,94558584.0,95457584.0,96447542.0,97440251.0,99026958.0,99534916.0]}"
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    "content": "[12284.540419665309,12358.78179335027,12556.758789843498,12631.000163528457]"
  },
  {
    "path": "docs/criterion/Clone/FlexStr 0.10 (SharedStr - Optimized)/10/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/FlexStr 0.10 (SharedStr - Optimized)/10 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/FlexStr 0.10 (SharedStr - Optimized)/10</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">12.539 µs</td>\n                                <td>12.785 µs</td>\n                                <td class=\"ci-bound\">13.112 µs</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.3363882</td>\n                                <td>0.3430293</td>\n                                <td class=\"ci-bound\">0.3314572</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">12.566 µs</td>\n                                <td>12.808 µs</td>\n                                <td class=\"ci-bound\">13.112 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">612.54 ns</td>\n                                <td>1.4150 µs</td>\n                                <td class=\"ci-bound\">2.0078 µs</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">12.440 µs</td>\n                                <td>12.443 µs</td>\n                                <td class=\"ci-bound\">12.453 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">15.347 ns</td>\n                                <td>21.237 ns</td>\n                                <td class=\"ci-bound\">35.000 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">+0.6232%</td>\n                            <td>+2.5793%</td>\n                            <td class=\"ci-bound\">+4.9239%</td>\n                            <td>(p = 0.01 &lt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                Change within noise threshold.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
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    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":94988.75692772212,\"upper_bound\":95173.5607688443},\"point_estimate\":95073.25753206894,\"standard_error\":47.24621464959072},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":94898.7,\"upper_bound\":94974.64685314686},\"point_estimate\":94934.46301834131,\"standard_error\":21.34957316311543},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":110.52281633806729,\"upper_bound\":186.20500850962287},\"point_estimate\":156.7803740397087,\"standard_error\":19.61737635536282},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":94907.9718458255,\"upper_bound\":94990.1925503347},\"point_estimate\":94946.89538724022,\"standard_error\":21.000278742766646},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":278.445380735778,\"upper_bound\":655.8883571758386},\"point_estimate\":476.4792253138015,\"standard_error\":97.84951530802444}}"
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    "path": "docs/criterion/Clone/FlexStr 0.10 (SharedStr - Optimized)/100/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[11.0,22.0,33.0,44.0,55.0,66.0,77.0,88.0,99.0,110.0,121.0,132.0,143.0,154.0,165.0,176.0,187.0,198.0,209.0,220.0,231.0,242.0,253.0,264.0,275.0,286.0,297.0,308.0,319.0,330.0,341.0,352.0,363.0,374.0,385.0,396.0,407.0,418.0,429.0,440.0,451.0,462.0,473.0,484.0,495.0,506.0,517.0,528.0,539.0,550.0,561.0,572.0,583.0,594.0,605.0,616.0,627.0,638.0,649.0,660.0,671.0,682.0,693.0,704.0,715.0,726.0,737.0,748.0,759.0,770.0,781.0,792.0,803.0,814.0,825.0,836.0,847.0,858.0,869.0,880.0,891.0,902.0,913.0,924.0,935.0,946.0,957.0,968.0,979.0,990.0,1001.0,1012.0,1023.0,1034.0,1045.0,1056.0,1067.0,1078.0,1089.0,1100.0],\"times\":[1056875.0,2084376.0,3127585.0,4253166.0,5387958.0,6269417.0,7432417.0,8330917.0,9508250.0,10506666.0,11501920.0,12543874.0,13622958.0,14753876.0,15763292.0,16729501.0,17746749.0,18844749.0,19850625.0,20895667.0,21909959.0,22950041.0,24054208.0,25063291.0,26276251.0,27162749.0,28200667.0,29242166.0,30264544.0,31316417.0,32371001.0,33514333.0,34509960.0,35542499.0,36701498.0,37600585.0,38651373.0,39681667.0,40747082.0,41758124.0,43200666.0,44674792.0,44833417.0,45919042.0,47054332.0,48009750.0,49094706.0,50041292.0,51057791.0,52262250.0,53222793.0,54347959.0,55363083.0,56460457.0,57514376.0,58408835.0,59420750.0,60515669.0,61556876.0,62634250.0,63627125.0,64663376.0,65695874.0,66787832.0,67834708.0,68914168.0,69913333.0,71137293.0,71962794.0,73071999.0,74033293.0,75091581.0,76246625.0,77182500.0,78416833.0,79267499.0,80256378.0,81400957.0,82516834.0,83458252.0,84566377.0,85513877.0,86643708.0,87672376.0,88951624.0,89748583.0,90808958.0,91832664.0,92790960.0,94218708.0,95193081.0,96055248.0,97189082.0,98261667.0,99034502.0,100389957.0,101478377.0,102716084.0,103273249.0,104370958.0]}"
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  },
  {
    "path": "docs/criterion/Clone/FlexStr 0.10 (SharedStr - Optimized)/100/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/FlexStr 0.10 (SharedStr - Optimized)/100 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/FlexStr 0.10 (SharedStr - Optimized)/100</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">94.908 µs</td>\n                                <td>94.947 µs</td>\n                                <td class=\"ci-bound\">94.990 µs</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.9993765</td>\n                                <td>0.9993997</td>\n                                <td class=\"ci-bound\">0.9993710</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">94.989 µs</td>\n                                <td>95.073 µs</td>\n                                <td class=\"ci-bound\">95.174 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">278.45 ns</td>\n                                <td>476.48 ns</td>\n                                <td class=\"ci-bound\">655.89 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">94.899 µs</td>\n                                <td>94.934 µs</td>\n                                <td class=\"ci-bound\">94.975 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">110.52 ns</td>\n                                <td>156.78 ns</td>\n                                <td class=\"ci-bound\">186.21 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−0.1062%</td>\n                            <td>+0.0323%</td>\n                            <td class=\"ci-bound\">+0.1720%</td>\n                            <td>(p = 0.64 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
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  {
    "path": "docs/criterion/Clone/FlexStr 0.10 (SharedStr - Optimized)/20/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/FlexStr 0.10 (SharedStr - Optimized)/20 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/FlexStr 0.10 (SharedStr - Optimized)/20</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">12.468 µs</td>\n                                <td>12.486 µs</td>\n                                <td class=\"ci-bound\">12.509 µs</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.9920884</td>\n                                <td>0.9923770</td>\n                                <td class=\"ci-bound\">0.9919090</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">12.491 µs</td>\n                                <td>12.514 µs</td>\n                                <td class=\"ci-bound\">12.540 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">89.084 ns</td>\n                                <td>126.62 ns</td>\n                                <td class=\"ci-bound\">159.93 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">12.454 µs</td>\n                                <td>12.462 µs</td>\n                                <td class=\"ci-bound\">12.474 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">26.112 ns</td>\n                                <td>40.129 ns</td>\n                                <td class=\"ci-bound\">55.643 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−0.1068%</td>\n                            <td>+0.1559%</td>\n                            <td class=\"ci-bound\">+0.4199%</td>\n                            <td>(p = 0.25 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
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    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[11.0,22.0,33.0,44.0,55.0,66.0,77.0,88.0,99.0,110.0,121.0,132.0,143.0,154.0,165.0,176.0,187.0,198.0,209.0,220.0,231.0,242.0,253.0,264.0,275.0,286.0,297.0,308.0,319.0,330.0,341.0,352.0,363.0,374.0,385.0,396.0,407.0,418.0,429.0,440.0,451.0,462.0,473.0,484.0,495.0,506.0,517.0,528.0,539.0,550.0,561.0,572.0,583.0,594.0,605.0,616.0,627.0,638.0,649.0,660.0,671.0,682.0,693.0,704.0,715.0,726.0,737.0,748.0,759.0,770.0,781.0,792.0,803.0,814.0,825.0,836.0,847.0,858.0,869.0,880.0,891.0,902.0,913.0,924.0,935.0,946.0,957.0,968.0,979.0,990.0,1001.0,1012.0,1023.0,1034.0,1045.0,1056.0,1067.0,1078.0,1089.0,1100.0],\"times\":[1049667.0,2084749.0,3130458.0,4281083.0,5472792.0,6343751.0,7446125.0,8370209.0,9442375.0,10463375.0,11529751.0,12541626.0,13598375.0,14626960.0,15885873.0,16871709.0,17835666.0,18848000.0,19825002.0,20884875.0,21918083.0,22968000.0,24033500.0,25047332.0,26104414.0,27144336.0,28187501.0,29228416.0,30232084.0,31401457.0,32535541.0,33548293.0,34530667.0,35476501.0,36552832.0,37598918.0,38599333.0,39679876.0,40673665.0,41737458.0,42813878.0,43880668.0,45247415.0,46013625.0,47001209.0,47988708.0,49131166.0,50088791.0,51455792.0,52203961.0,53633419.0,54316334.0,55392419.0,56420124.0,57403083.0,58598792.0,59494459.0,60833958.0,62560415.0,62741292.0,63861500.0,64782501.0,65738084.0,66840750.0,67848290.0,68954794.0,70057209.0,70944956.0,72138665.0,72997582.0,74277376.0,75116042.0,76123376.0,77135208.0,78328375.0,79463500.0,80298793.0,81443582.0,84087168.0,83788958.0,84595876.0,85741208.0,86618624.0,87634417.0,88673418.0,89789708.0,90800333.0,91836999.0,92887251.0,93863957.0,94866333.0,96025167.0,97099374.0,98037249.0,99152874.0,100097375.0,101086748.0,102385041.0,103343498.0,104300542.0]}"
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  },
  {
    "path": "docs/criterion/Clone/FlexStr 0.10 (SharedStr - Optimized)/500/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/FlexStr 0.10 (SharedStr - Optimized)/500 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/FlexStr 0.10 (SharedStr - Optimized)/500</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">94.915 µs</td>\n                                <td>94.980 µs</td>\n                                <td class=\"ci-bound\">95.073 µs</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.9982689</td>\n                                <td>0.9983341</td>\n                                <td class=\"ci-bound\">0.9982006</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">95.029 µs</td>\n                                <td>95.136 µs</td>\n                                <td class=\"ci-bound\">95.270 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">323.10 ns</td>\n                                <td>624.63 ns</td>\n                                <td class=\"ci-bound\">910.85 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">94.910 µs</td>\n                                <td>94.943 µs</td>\n                                <td class=\"ci-bound\">94.982 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">99.445 ns</td>\n                                <td>149.68 ns</td>\n                                <td class=\"ci-bound\">199.88 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−0.3806%</td>\n                            <td>−0.1941%</td>\n                            <td class=\"ci-bound\">−0.0160%</td>\n                            <td>(p = 0.05 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Clone/FlexStr 0.10 (SharedStr - Optimized)/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/FlexStr 0.10 (SharedStr - Optimized) Summary - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/FlexStr 0.10 (SharedStr - Optimized)</h2>\n        <h3>Violin Plot</h3>\n        <a href=\"violin.svg\">\n            <img src=\"violin.svg\" alt=\"Violin Plot\" />\n        </a>\n        <p>This chart shows the relationship between function/parameter and iteration time. The thickness of the shaded\n            region indicates the probability that a measurement of the given function/parameter would take a particular\n            length of time.</p>\n        <h3>Line Chart</h3>\n        <img src=\"lines.svg\" alt=\"Line Chart\" />\n        <p>This chart shows the mean measured time for each function as the input (or the size of the input) increases.</p>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/FlexStr 0.10 (SharedStr - Optimized)/0/report/index.html\">\n                <h4>Clone/FlexStr 0.10 (SharedStr - Optimized)/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (SharedStr - Optimized)/0/report/pdf.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (SharedStr - Optimized)/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (SharedStr - Optimized)/0/report/regression.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (SharedStr - Optimized)/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/FlexStr 0.10 (SharedStr - Optimized)/10/report/index.html\">\n                <h4>Clone/FlexStr 0.10 (SharedStr - Optimized)/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (SharedStr - Optimized)/10/report/pdf.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (SharedStr - Optimized)/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (SharedStr - Optimized)/10/report/regression.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (SharedStr - Optimized)/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/FlexStr 0.10 (SharedStr - Optimized)/20/report/index.html\">\n                <h4>Clone/FlexStr 0.10 (SharedStr - Optimized)/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (SharedStr - Optimized)/20/report/pdf.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (SharedStr - Optimized)/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (SharedStr - Optimized)/20/report/regression.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (SharedStr - Optimized)/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/FlexStr 0.10 (SharedStr - Optimized)/100/report/index.html\">\n                <h4>Clone/FlexStr 0.10 (SharedStr - Optimized)/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (SharedStr - Optimized)/100/report/pdf.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (SharedStr - Optimized)/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (SharedStr - Optimized)/100/report/regression.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (SharedStr - Optimized)/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/FlexStr 0.10 (SharedStr - Optimized)/500/report/index.html\">\n                <h4>Clone/FlexStr 0.10 (SharedStr - Optimized)/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (SharedStr - Optimized)/500/report/pdf.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (SharedStr - Optimized)/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.10 (SharedStr - Optimized)/500/report/regression.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.10 (SharedStr - Optimized)/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Clone/FlexStr 0.9 (LocalStr)/0/base/benchmark.json",
    "content": "{\"group_id\":\"Clone\",\"function_id\":\"FlexStr 0.9 (LocalStr)\",\"value_str\":\"0\",\"throughput\":null,\"full_id\":\"Clone/FlexStr 0.9 (LocalStr)/0\",\"directory_name\":\"Clone/FlexStr 0.9 (LocalStr)/0\",\"title\":\"Clone/FlexStr 0.9 (LocalStr)/0\"}"
  },
  {
    "path": "docs/criterion/Clone/FlexStr 0.9 (LocalStr)/0/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":9344.899233586233,\"upper_bound\":9399.862907672914},\"point_estimate\":9365.764967451769,\"standard_error\":14.877532239319558},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":9334.418301886792,\"upper_bound\":9339.91784591195},\"point_estimate\":9337.251572844598,\"standard_error\":1.5800684969738918},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":12.344575425888968,\"upper_bound\":22.804706670122254},\"point_estimate\":18.37626471540026,\"standard_error\":2.7342579888421894},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":9333.672714460317,\"upper_bound\":9343.009046276724},\"point_estimate\":9337.89295858648,\"standard_error\":2.3833050349126697},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":33.45802485190929,\"upper_bound\":248.20956166271245},\"point_estimate\":149.229249668413,\"standard_error\":70.81506899589411}}"
  },
  {
    "path": "docs/criterion/Clone/FlexStr 0.9 (LocalStr)/0/base/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[106.0,212.0,318.0,424.0,530.0,636.0,742.0,848.0,954.0,1060.0,1166.0,1272.0,1378.0,1484.0,1590.0,1696.0,1802.0,1908.0,2014.0,2120.0,2226.0,2332.0,2438.0,2544.0,2650.0,2756.0,2862.0,2968.0,3074.0,3180.0,3286.0,3392.0,3498.0,3604.0,3710.0,3816.0,3922.0,4028.0,4134.0,4240.0,4346.0,4452.0,4558.0,4664.0,4770.0,4876.0,4982.0,5088.0,5194.0,5300.0,5406.0,5512.0,5618.0,5724.0,5830.0,5936.0,6042.0,6148.0,6254.0,6360.0,6466.0,6572.0,6678.0,6784.0,6890.0,6996.0,7102.0,7208.0,7314.0,7420.0,7526.0,7632.0,7738.0,7844.0,7950.0,8056.0,8162.0,8268.0,8374.0,8480.0,8586.0,8692.0,8798.0,8904.0,9010.0,9116.0,9222.0,9328.0,9434.0,9540.0,9646.0,9752.0,9858.0,9964.0,10070.0,10176.0,10282.0,10388.0,10494.0,10600.0],\"times\":[1002708.0,1974792.0,2963125.0,4067291.0,4978416.0,6846208.0,6931126.0,8069041.0,8986666.0,9945749.0,10960460.0,11973833.0,12924124.0,13853583.0,15090540.0,15971166.0,16827583.0,17847460.0,18810334.0,19844542.0,20756459.0,21795459.0,22768292.0,23760751.0,24730292.0,25725252.0,26834709.0,27693583.0,28651792.0,29637667.0,30805666.0,31836583.0,32662583.0,33659082.0,34621330.0,35663749.0,36587082.0,37565210.0,38555375.0,39517083.0,40507373.0,41607831.0,43713125.0,43464833.0,44531959.0,45557834.0,46544956.0,47637626.0,48496961.0,49472417.0,50439625.0,51551833.0,52472000.0,53518458.0,54428749.0,55412709.0,56380834.0,57389958.0,58297542.0,59467039.0,60656958.0,61365333.0,62251083.0,63494334.0,64219707.0,65325959.0,66290043.0,67190833.0,68314125.0,69233584.0,70308792.0,71419791.0,72383627.0,73156167.0,74150543.0,75172749.0,76120542.0,77186917.0,78296166.0,79067917.0,80149583.0,81166499.0,82071167.0,83302750.0,84030708.0,85136749.0,85977709.0,87018375.0,88251334.0,89059749.0,90305166.0,90935499.0,91896707.0,92992624.0,93901832.0,95303710.0,95955875.0,96848789.0,97805542.0,98795209.0]}"
  },
  {
    "path": "docs/criterion/Clone/FlexStr 0.9 (LocalStr)/0/base/tukey.json",
    "content": "[9244.60245344936,9285.769480232178,9395.548218319695,9436.715245102514]"
  },
  {
    "path": "docs/criterion/Clone/FlexStr 0.9 (LocalStr)/0/change/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.0014594764996008506,\"upper_bound\":0.004771485692371462},\"point_estimate\":0.0012509556004187683,\"standard_error\":0.0016870119760289122},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.0007084518475413137,\"upper_bound\":0.0005454196291496682},\"point_estimate\":-0.00006233724852977574,\"standard_error\":0.00030755445348487154}}"
  },
  {
    "path": "docs/criterion/Clone/FlexStr 0.9 (LocalStr)/0/new/benchmark.json",
    "content": "{\"group_id\":\"Clone\",\"function_id\":\"FlexStr 0.9 (LocalStr)\",\"value_str\":\"0\",\"throughput\":null,\"full_id\":\"Clone/FlexStr 0.9 (LocalStr)/0\",\"directory_name\":\"Clone/FlexStr 0.9 (LocalStr)/0\",\"title\":\"Clone/FlexStr 0.9 (LocalStr)/0\"}"
  },
  {
    "path": "docs/criterion/Clone/FlexStr 0.9 (LocalStr)/0/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":9344.899233586233,\"upper_bound\":9399.862907672914},\"point_estimate\":9365.764967451769,\"standard_error\":14.877532239319558},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":9334.418301886792,\"upper_bound\":9339.91784591195},\"point_estimate\":9337.251572844598,\"standard_error\":1.5800684969738918},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":12.344575425888968,\"upper_bound\":22.804706670122254},\"point_estimate\":18.37626471540026,\"standard_error\":2.7342579888421894},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":9333.672714460317,\"upper_bound\":9343.009046276724},\"point_estimate\":9337.89295858648,\"standard_error\":2.3833050349126697},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":33.45802485190929,\"upper_bound\":248.20956166271245},\"point_estimate\":149.229249668413,\"standard_error\":70.81506899589411}}"
  },
  {
    "path": "docs/criterion/Clone/FlexStr 0.9 (LocalStr)/0/new/sample.json",
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    "path": "docs/criterion/Clone/FlexStr 0.9 (LocalStr)/0/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/FlexStr 0.9 (LocalStr)/0 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/FlexStr 0.9 (LocalStr)/0</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">9.3337 µs</td>\n                                <td>9.3379 µs</td>\n                                <td class=\"ci-bound\">9.3430 µs</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.9986932</td>\n                                <td>0.9987215</td>\n                                <td class=\"ci-bound\">0.9986798</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">9.3449 µs</td>\n                                <td>9.3658 µs</td>\n                                <td class=\"ci-bound\">9.3999 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">33.458 ns</td>\n                                <td>149.23 ns</td>\n                                <td class=\"ci-bound\">248.21 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">9.3344 µs</td>\n                                <td>9.3373 µs</td>\n                                <td class=\"ci-bound\">9.3399 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">12.345 ns</td>\n                                <td>18.376 ns</td>\n                                <td class=\"ci-bound\">22.805 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−0.1459%</td>\n                            <td>+0.1251%</td>\n                            <td class=\"ci-bound\">+0.4771%</td>\n                            <td>(p = 0.53 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
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    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/FlexStr 0.9 (LocalStr)/10 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/FlexStr 0.9 (LocalStr)/10</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">7.2694 µs</td>\n                                <td>7.3366 µs</td>\n                                <td class=\"ci-bound\">7.4778 µs</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.7243811</td>\n                                <td>0.7307795</td>\n                                <td class=\"ci-bound\">0.7033100</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">7.2824 µs</td>\n                                <td>7.3100 µs</td>\n                                <td class=\"ci-bound\">7.3588 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">28.996 ns</td>\n                                <td>222.88 ns</td>\n                                <td class=\"ci-bound\">378.63 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">7.2727 µs</td>\n                                <td>7.2763 µs</td>\n                                <td class=\"ci-bound\">7.2804 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">10.133 ns</td>\n                                <td>14.597 ns</td>\n                                <td class=\"ci-bound\">18.996 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−0.1662%</td>\n                            <td>+0.3044%</td>\n                            <td class=\"ci-bound\">+1.0327%</td>\n                            <td>(p = 0.42 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
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    "path": "docs/criterion/Clone/FlexStr 0.9 (LocalStr)/100/base/benchmark.json",
    "content": "{\"group_id\":\"Clone\",\"function_id\":\"FlexStr 0.9 (LocalStr)\",\"value_str\":\"100\",\"throughput\":null,\"full_id\":\"Clone/FlexStr 0.9 (LocalStr)/100\",\"directory_name\":\"Clone/FlexStr 0.9 (LocalStr)/100\",\"title\":\"Clone/FlexStr 0.9 (LocalStr)/100\"}"
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    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":40288.72905338233,\"upper_bound\":40525.9243707278},\"point_estimate\":40388.23303923494,\"standard_error\":61.62292708157086},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":40229.537333333334,\"upper_bound\":40285.35157894737},\"point_estimate\":40260.28523809524,\"standard_error\":13.294876263100237},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":69.90212958586324,\"upper_bound\":125.95195967126493},\"point_estimate\":94.44955524950109,\"standard_error\":14.505872279821146},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":40246.645289761,\"upper_bound\":40390.92496626146},\"point_estimate\":40306.343159450276,\"standard_error\":37.26031379759479},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":184.50226435691764,\"upper_bound\":975.7683936054018},\"point_estimate\":619.4655507995749,\"standard_error\":215.2173400160122}}"
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    "path": "docs/criterion/Clone/FlexStr 0.9 (LocalStr)/100/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[25.0,50.0,75.0,100.0,125.0,150.0,175.0,200.0,225.0,250.0,275.0,300.0,325.0,350.0,375.0,400.0,425.0,450.0,475.0,500.0,525.0,550.0,575.0,600.0,625.0,650.0,675.0,700.0,725.0,750.0,775.0,800.0,825.0,850.0,875.0,900.0,925.0,950.0,975.0,1000.0,1025.0,1050.0,1075.0,1100.0,1125.0,1150.0,1175.0,1200.0,1225.0,1250.0,1275.0,1300.0,1325.0,1350.0,1375.0,1400.0,1425.0,1450.0,1475.0,1500.0,1525.0,1550.0,1575.0,1600.0,1625.0,1650.0,1675.0,1700.0,1725.0,1750.0,1775.0,1800.0,1825.0,1850.0,1875.0,1900.0,1925.0,1950.0,1975.0,2000.0,2025.0,2050.0,2075.0,2100.0,2125.0,2150.0,2175.0,2200.0,2225.0,2250.0,2275.0,2300.0,2325.0,2350.0,2375.0,2400.0,2425.0,2450.0,2475.0,2500.0],\"times\":[1014040.0,2015457.0,3018039.0,4159916.0,5248082.0,6023165.0,7122166.0,8060455.0,9155997.0,10101708.0,11099917.0,12076708.0,13119542.0,14092707.0,15242083.0,16109000.0,17091665.0,18127376.0,19115542.0,20213375.0,21115542.0,22193999.0,23374042.0,24197127.0,25165668.0,26187333.0,27286838.0,28300626.0,29214208.0,30140667.0,31125625.0,32303042.0,33185708.0,34153126.0,35171918.0,36135582.0,37170627.0,38271084.0,39292875.0,40110333.0,41227418.0,42146207.0,43157083.0,49901041.0,48299168.0,46243876.0,47255041.0,48203333.0,49481417.0,50403084.0,51285876.0,52392915.0,53520958.0,54247918.0,55277083.0,56239124.0,57461541.0,58275664.0,59401416.0,60188124.0,61211251.0,62482085.0,63237666.0,64345376.0,65187749.0,66320541.0,67609373.0,68485709.0,69551709.0,70388543.0,71894044.0,72424543.0,73332458.0,74435250.0,75380251.0,76226126.0,77441208.0,78589833.0,79524792.0,80485791.0,81539167.0,82513165.0,83475833.0,84521001.0,85487457.0,86630584.0,88699291.0,88395291.0,89474122.0,90516459.0,91443041.0,92569583.0,93978831.0,94626459.0,95635707.0,96282666.0,97746123.0,98444539.0,99900208.0,100719251.0]}"
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    "content": "[39825.864744190025,40013.06017728982,40512.247998889274,40699.443431989064]"
  },
  {
    "path": "docs/criterion/Clone/FlexStr 0.9 (LocalStr)/100/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/FlexStr 0.9 (LocalStr)/100 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/FlexStr 0.9 (LocalStr)/100</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">40.247 µs</td>\n                                <td>40.306 µs</td>\n                                <td class=\"ci-bound\">40.391 µs</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.9827291</td>\n                                <td>0.9830227</td>\n                                <td class=\"ci-bound\">0.9824336</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">40.289 µs</td>\n                                <td>40.388 µs</td>\n                                <td class=\"ci-bound\">40.526 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">184.50 ns</td>\n                                <td>619.47 ns</td>\n                                <td class=\"ci-bound\">975.77 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">40.230 µs</td>\n                                <td>40.260 µs</td>\n                                <td class=\"ci-bound\">40.285 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">69.902 ns</td>\n                                <td>94.450 ns</td>\n                                <td class=\"ci-bound\">125.95 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−0.0579%</td>\n                            <td>+0.2196%</td>\n                            <td class=\"ci-bound\">+0.5205%</td>\n                            <td>(p = 0.19 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
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    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":7281.677178349198,\"upper_bound\":7299.96797814789},\"point_estimate\":7290.255747810431,\"standard_error\":4.66070047234321},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":7273.497762148338,\"upper_bound\":7280.595208728653},\"point_estimate\":7276.387943011428,\"standard_error\":1.8729321730347561},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":10.155286014524505,\"upper_bound\":19.06194429238169},\"point_estimate\":14.187984385664299,\"standard_error\":2.404705629013086},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":7272.641338264943,\"upper_bound\":7288.88067781517},\"point_estimate\":7279.903189461835,\"standard_error\":4.138627137709316},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":30.71480794239275,\"upper_bound\":62.068013255324665},\"point_estimate\":46.795121524617194,\"standard_error\":8.118570044231129}}"
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    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[136.0,272.0,408.0,544.0,680.0,816.0,952.0,1088.0,1224.0,1360.0,1496.0,1632.0,1768.0,1904.0,2040.0,2176.0,2312.0,2448.0,2584.0,2720.0,2856.0,2992.0,3128.0,3264.0,3400.0,3536.0,3672.0,3808.0,3944.0,4080.0,4216.0,4352.0,4488.0,4624.0,4760.0,4896.0,5032.0,5168.0,5304.0,5440.0,5576.0,5712.0,5848.0,5984.0,6120.0,6256.0,6392.0,6528.0,6664.0,6800.0,6936.0,7072.0,7208.0,7344.0,7480.0,7616.0,7752.0,7888.0,8024.0,8160.0,8296.0,8432.0,8568.0,8704.0,8840.0,8976.0,9112.0,9248.0,9384.0,9520.0,9656.0,9792.0,9928.0,10064.0,10200.0,10336.0,10472.0,10608.0,10744.0,10880.0,11016.0,11152.0,11288.0,11424.0,11560.0,11696.0,11832.0,11968.0,12104.0,12240.0,12376.0,12512.0,12648.0,12784.0,12920.0,13056.0,13192.0,13328.0,13464.0,13600.0],\"times\":[996124.0,1976165.0,3003291.0,4045123.0,5002668.0,6160250.0,6928499.0,7908584.0,8932623.0,9902083.0,10927251.0,11878583.0,12920709.0,13856790.0,15036290.0,15814670.0,16846834.0,17794502.0,18799166.0,19801876.0,20867878.0,21819790.0,22751501.0,23743874.0,25087415.0,26014582.0,26951001.0,27675834.0,28651460.0,29632668.0,30697460.0,31728751.0,32731293.0,33645000.0,34765376.0,35596916.0,36516833.0,37599833.0,38581917.0,39576874.0,40500418.0,41503459.0,42964707.0,43447335.0,44731375.0,45556168.0,46571584.0,47408833.0,48445543.0,49428539.0,50437794.0,52351126.0,53357582.0,53902957.0,54376709.0,55350585.0,56513208.0,57306291.0,58356335.0,59268959.0,60409792.0,61387043.0,62362168.0,62186167.0,64347583.0,65314834.0,66174791.0,67213457.0,68218416.0,69181082.0,70489292.0,71221666.0,72382708.0,73270042.0,74129416.0,75230997.0,76178668.0,77041333.0,78157875.0,79221210.0,80079333.0,81061251.0,82016915.0,83251915.0,84168084.0,85278083.0,87738042.0,87047337.0,88176206.0,88719708.0,90046418.0,90992542.0,91910209.0,93097209.0,93845460.0,95228084.0,95917333.0,96757835.0,97819710.0,99092209.0]}"
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  },
  {
    "path": "docs/criterion/Clone/FlexStr 0.9 (LocalStr)/20/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/FlexStr 0.9 (LocalStr)/20 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/FlexStr 0.9 (LocalStr)/20</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">7.2726 µs</td>\n                                <td>7.2799 µs</td>\n                                <td class=\"ci-bound\">7.2889 µs</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.9969529</td>\n                                <td>0.9970891</td>\n                                <td class=\"ci-bound\">0.9968810</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">7.2817 µs</td>\n                                <td>7.2903 µs</td>\n                                <td class=\"ci-bound\">7.3000 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">30.715 ns</td>\n                                <td>46.795 ns</td>\n                                <td class=\"ci-bound\">62.068 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">7.2735 µs</td>\n                                <td>7.2764 µs</td>\n                                <td class=\"ci-bound\">7.2806 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">10.155 ns</td>\n                                <td>14.188 ns</td>\n                                <td class=\"ci-bound\">19.062 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−0.5674%</td>\n                            <td>−0.2427%</td>\n                            <td class=\"ci-bound\">+0.0361%</td>\n                            <td>(p = 0.12 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
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    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":40317.946168510214,\"upper_bound\":40530.41430794591},\"point_estimate\":40406.92463246009,\"standard_error\":55.17801269369053},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":40230.796309260084,\"upper_bound\":40276.29101538462},\"point_estimate\":40242.10315578895,\"standard_error\":13.629702649397485},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":51.16889507394211,\"upper_bound\":103.69264910649206},\"point_estimate\":68.42430703249597,\"standard_error\":13.966714831833567},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":40270.70000425678,\"upper_bound\":40803.21205177729},\"point_estimate\":40490.29824796808,\"standard_error\":140.23693843741825},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":225.35512487543573,\"upper_bound\":867.5376888084876},\"point_estimate\":553.7410163011788,\"standard_error\":194.48794920995957}}"
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    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[25.0,50.0,75.0,100.0,125.0,150.0,175.0,200.0,225.0,250.0,275.0,300.0,325.0,350.0,375.0,400.0,425.0,450.0,475.0,500.0,525.0,550.0,575.0,600.0,625.0,650.0,675.0,700.0,725.0,750.0,775.0,800.0,825.0,850.0,875.0,900.0,925.0,950.0,975.0,1000.0,1025.0,1050.0,1075.0,1100.0,1125.0,1150.0,1175.0,1200.0,1225.0,1250.0,1275.0,1300.0,1325.0,1350.0,1375.0,1400.0,1425.0,1450.0,1475.0,1500.0,1525.0,1550.0,1575.0,1600.0,1625.0,1650.0,1675.0,1700.0,1725.0,1750.0,1775.0,1800.0,1825.0,1850.0,1875.0,1900.0,1925.0,1950.0,1975.0,2000.0,2025.0,2050.0,2075.0,2100.0,2125.0,2150.0,2175.0,2200.0,2225.0,2250.0,2275.0,2300.0,2325.0,2350.0,2375.0,2400.0,2425.0,2450.0,2475.0,2500.0],\"times\":[1012459.0,2005625.0,3013501.0,4121543.0,5049457.0,6154625.0,7143208.0,8046709.0,9059708.0,10139209.0,11122624.0,12107832.0,13088416.0,14074875.0,15309834.0,16162542.0,17185542.0,18332623.0,19250542.0,20156165.0,21137417.0,22176541.0,23157417.0,24160207.0,25175333.0,26209541.0,27576792.0,28151708.0,29311583.0,30173626.0,31898042.0,32757249.0,33254583.0,34238545.0,35204333.0,36187086.0,37248167.0,38199915.0,39234707.0,40308582.0,41298625.0,42247542.0,43260750.0,44229001.0,45373707.0,46387251.0,47266710.0,48364664.0,49246335.0,50274000.0,51365292.0,52493207.0,53294708.0,54295210.0,55269543.0,56264417.0,57250794.0,58278999.0,59294499.0,60468206.0,61348748.0,62452543.0,63356084.0,64318999.0,65360168.0,67262372.0,67395542.0,68698750.0,69462002.0,70349958.0,71353917.0,72465126.0,73313417.0,74430875.0,75540627.0,76416665.0,77414876.0,78354625.0,79487331.0,80320748.0,81422416.0,82492874.0,83416001.0,84374792.0,85402210.0,86399293.0,87646124.0,88483666.0,89504540.0,90449084.0,91537500.0,92430042.0,93561832.0,94491668.0,95509042.0,96451959.0,109171751.0,100962583.0,102955291.0,104453210.0]}"
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    "content": "[39840.56195184769,40025.3473449048,40518.10839305712,40702.89378611424]"
  },
  {
    "path": "docs/criterion/Clone/FlexStr 0.9 (LocalStr)/500/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/FlexStr 0.9 (LocalStr)/500 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/FlexStr 0.9 (LocalStr)/500</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">40.271 µs</td>\n                                <td>40.490 µs</td>\n                                <td class=\"ci-bound\">40.803 µs</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.9451805</td>\n                                <td>0.9483855</td>\n                                <td class=\"ci-bound\">0.9419005</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">40.318 µs</td>\n                                <td>40.407 µs</td>\n                                <td class=\"ci-bound\">40.530 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">225.36 ns</td>\n                                <td>553.74 ns</td>\n                                <td class=\"ci-bound\">867.54 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">40.231 µs</td>\n                                <td>40.242 µs</td>\n                                <td class=\"ci-bound\">40.276 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">51.169 ns</td>\n                                <td>68.424 ns</td>\n                                <td class=\"ci-bound\">103.69 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−0.0509%</td>\n                            <td>+0.1909%</td>\n                            <td class=\"ci-bound\">+0.5268%</td>\n                            <td>(p = 0.21 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Clone/FlexStr 0.9 (LocalStr)/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/FlexStr 0.9 (LocalStr) Summary - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/FlexStr 0.9 (LocalStr)</h2>\n        <h3>Violin Plot</h3>\n        <a href=\"violin.svg\">\n            <img src=\"violin.svg\" alt=\"Violin Plot\" />\n        </a>\n        <p>This chart shows the relationship between function/parameter and iteration time. The thickness of the shaded\n            region indicates the probability that a measurement of the given function/parameter would take a particular\n            length of time.</p>\n        <h3>Line Chart</h3>\n        <img src=\"lines.svg\" alt=\"Line Chart\" />\n        <p>This chart shows the mean measured time for each function as the input (or the size of the input) increases.</p>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/FlexStr 0.9 (LocalStr)/0/report/index.html\">\n                <h4>Clone/FlexStr 0.9 (LocalStr)/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.9 (LocalStr)/0/report/pdf.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.9 (LocalStr)/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.9 (LocalStr)/0/report/regression.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.9 (LocalStr)/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/FlexStr 0.9 (LocalStr)/10/report/index.html\">\n                <h4>Clone/FlexStr 0.9 (LocalStr)/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.9 (LocalStr)/10/report/pdf.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.9 (LocalStr)/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.9 (LocalStr)/10/report/regression.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.9 (LocalStr)/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/FlexStr 0.9 (LocalStr)/20/report/index.html\">\n                <h4>Clone/FlexStr 0.9 (LocalStr)/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.9 (LocalStr)/20/report/pdf.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.9 (LocalStr)/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.9 (LocalStr)/20/report/regression.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.9 (LocalStr)/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/FlexStr 0.9 (LocalStr)/100/report/index.html\">\n                <h4>Clone/FlexStr 0.9 (LocalStr)/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.9 (LocalStr)/100/report/pdf.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.9 (LocalStr)/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.9 (LocalStr)/100/report/regression.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.9 (LocalStr)/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/FlexStr 0.9 (LocalStr)/500/report/index.html\">\n                <h4>Clone/FlexStr 0.9 (LocalStr)/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.9 (LocalStr)/500/report/pdf.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.9 (LocalStr)/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.9 (LocalStr)/500/report/regression.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.9 (LocalStr)/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Clone/FlexStr 0.9 (SharedStr)/0/base/benchmark.json",
    "content": "{\"group_id\":\"Clone\",\"function_id\":\"FlexStr 0.9 (SharedStr)\",\"value_str\":\"0\",\"throughput\":null,\"full_id\":\"Clone/FlexStr 0.9 (SharedStr)/0\",\"directory_name\":\"Clone/FlexStr 0.9 (SharedStr)/0\",\"title\":\"Clone/FlexStr 0.9 (SharedStr)/0\"}"
  },
  {
    "path": "docs/criterion/Clone/FlexStr 0.9 (SharedStr)/0/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":9344.996820585247,\"upper_bound\":9369.586376692761},\"point_estimate\":9356.269424931172,\"standard_error\":6.325307705254591},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":9331.409871967655,\"upper_bound\":9340.141886792453},\"point_estimate\":9337.876712442228,\"standard_error\":2.3740942586732183},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":10.697062434601058,\"upper_bound\":19.472379962391305},\"point_estimate\":17.22457837044011,\"standard_error\":2.4259648008472534},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":9333.172775194053,\"upper_bound\":9341.640921028968},\"point_estimate\":9337.0234234395,\"standard_error\":2.166239108119337},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":37.347283780885576,\"upper_bound\":83.77546907591352},\"point_estimate\":63.416934374449994,\"standard_error\":11.853150747113652}}"
  },
  {
    "path": "docs/criterion/Clone/FlexStr 0.9 (SharedStr)/0/base/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[106.0,212.0,318.0,424.0,530.0,636.0,742.0,848.0,954.0,1060.0,1166.0,1272.0,1378.0,1484.0,1590.0,1696.0,1802.0,1908.0,2014.0,2120.0,2226.0,2332.0,2438.0,2544.0,2650.0,2756.0,2862.0,2968.0,3074.0,3180.0,3286.0,3392.0,3498.0,3604.0,3710.0,3816.0,3922.0,4028.0,4134.0,4240.0,4346.0,4452.0,4558.0,4664.0,4770.0,4876.0,4982.0,5088.0,5194.0,5300.0,5406.0,5512.0,5618.0,5724.0,5830.0,5936.0,6042.0,6148.0,6254.0,6360.0,6466.0,6572.0,6678.0,6784.0,6890.0,6996.0,7102.0,7208.0,7314.0,7420.0,7526.0,7632.0,7738.0,7844.0,7950.0,8056.0,8162.0,8268.0,8374.0,8480.0,8586.0,8692.0,8798.0,8904.0,9010.0,9116.0,9222.0,9328.0,9434.0,9540.0,9646.0,9752.0,9858.0,9964.0,10070.0,10176.0,10282.0,10388.0,10494.0,10600.0],\"times\":[999251.0,1980000.0,2963834.0,4080374.0,5058417.0,6093791.0,6965916.0,8162876.0,8925624.0,9946459.0,10968000.0,11866791.0,12885002.0,13846374.0,15040125.0,16001625.0,16856334.0,17905624.0,18809500.0,19827376.0,20790042.0,21814710.0,22740374.0,23823206.0,24751376.0,25840623.0,26717584.0,27684248.0,28674792.0,29653123.0,30662001.0,31675334.0,33776584.0,33654668.0,34654000.0,35694166.0,36569374.0,37573208.0,38573293.0,39513873.0,40547584.0,41513916.0,42498918.0,43476251.0,44710709.0,45536127.0,46483708.0,47576375.0,48521541.0,49483207.0,50448208.0,51412001.0,52473166.0,53434250.0,54482625.0,55391249.0,56429915.0,57684084.0,58321334.0,59343625.0,60305000.0,61444499.0,62421210.0,63365166.0,64428418.0,65843081.0,66315708.0,67361915.0,68198499.0,69209790.0,70297458.0,71206417.0,72346835.0,73175584.0,74187375.0,75229751.0,76042833.0,77307290.0,78091291.0,79122334.0,80193708.0,81034211.0,82004544.0,83037875.0,84027751.0,85254416.0,86038086.0,87356916.0,87996208.0,89120123.0,89993958.0,91190915.0,92044583.0,92878168.0,93884334.0,94853333.0,95991666.0,96856374.0,97866376.0,98922542.0]}"
  },
  {
    "path": "docs/criterion/Clone/FlexStr 0.9 (SharedStr)/0/base/tukey.json",
    "content": "[9257.296684792995,9292.434741893758,9386.13622749579,9421.274284596551]"
  },
  {
    "path": "docs/criterion/Clone/FlexStr 0.9 (SharedStr)/0/change/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.00320894047972709,\"upper_bound\":0.0009439420099736906},\"point_estimate\":-0.0011156708518441638,\"standard_error\":0.0010594783370335857},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.0010269386264858404,\"upper_bound\":0.0004970049603663096},\"point_estimate\":-0.0000935054715550665,\"standard_error\":0.0003863570895990185}}"
  },
  {
    "path": "docs/criterion/Clone/FlexStr 0.9 (SharedStr)/0/new/benchmark.json",
    "content": "{\"group_id\":\"Clone\",\"function_id\":\"FlexStr 0.9 (SharedStr)\",\"value_str\":\"0\",\"throughput\":null,\"full_id\":\"Clone/FlexStr 0.9 (SharedStr)/0\",\"directory_name\":\"Clone/FlexStr 0.9 (SharedStr)/0\",\"title\":\"Clone/FlexStr 0.9 (SharedStr)/0\"}"
  },
  {
    "path": "docs/criterion/Clone/FlexStr 0.9 (SharedStr)/0/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":9344.996820585247,\"upper_bound\":9369.586376692761},\"point_estimate\":9356.269424931172,\"standard_error\":6.325307705254591},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":9331.409871967655,\"upper_bound\":9340.141886792453},\"point_estimate\":9337.876712442228,\"standard_error\":2.3740942586732183},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":10.697062434601058,\"upper_bound\":19.472379962391305},\"point_estimate\":17.22457837044011,\"standard_error\":2.4259648008472534},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":9333.172775194053,\"upper_bound\":9341.640921028968},\"point_estimate\":9337.0234234395,\"standard_error\":2.166239108119337},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":37.347283780885576,\"upper_bound\":83.77546907591352},\"point_estimate\":63.416934374449994,\"standard_error\":11.853150747113652}}"
  },
  {
    "path": "docs/criterion/Clone/FlexStr 0.9 (SharedStr)/0/new/sample.json",
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    "path": "docs/criterion/Clone/FlexStr 0.9 (SharedStr)/0/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/FlexStr 0.9 (SharedStr)/0 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/FlexStr 0.9 (SharedStr)/0</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">9.3332 µs</td>\n                                <td>9.3370 µs</td>\n                                <td class=\"ci-bound\">9.3416 µs</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.9990193</td>\n                                <td>0.9990428</td>\n                                <td class=\"ci-bound\">0.9990090</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">9.3450 µs</td>\n                                <td>9.3563 µs</td>\n                                <td class=\"ci-bound\">9.3696 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">37.347 ns</td>\n                                <td>63.417 ns</td>\n                                <td class=\"ci-bound\">83.775 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">9.3314 µs</td>\n                                <td>9.3379 µs</td>\n                                <td class=\"ci-bound\">9.3401 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">10.697 ns</td>\n                                <td>17.225 ns</td>\n                                <td class=\"ci-bound\">19.472 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−0.3209%</td>\n                            <td>−0.1116%</td>\n                            <td class=\"ci-bound\">+0.0944%</td>\n                            <td>(p = 0.31 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
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    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/FlexStr 0.9 (SharedStr)/10 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/FlexStr 0.9 (SharedStr)/10</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">7.2904 µs</td>\n                                <td>7.3064 µs</td>\n                                <td class=\"ci-bound\">7.3248 µs</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.9867236</td>\n                                <td>0.9873749</td>\n                                <td class=\"ci-bound\">0.9865002</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">7.2923 µs</td>\n                                <td>7.3038 µs</td>\n                                <td class=\"ci-bound\">7.3164 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">44.430 ns</td>\n                                <td>61.831 ns</td>\n                                <td class=\"ci-bound\">76.288 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">7.2779 µs</td>\n                                <td>7.2815 µs</td>\n                                <td class=\"ci-bound\">7.2846 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">12.117 ns</td>\n                                <td>18.684 ns</td>\n                                <td class=\"ci-bound\">22.877 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">+0.0252%</td>\n                            <td>+0.2202%</td>\n                            <td class=\"ci-bound\">+0.4307%</td>\n                            <td>(p = 0.03 &lt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                Change within noise threshold.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
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    "path": "docs/criterion/Clone/FlexStr 0.9 (SharedStr)/100/base/benchmark.json",
    "content": "{\"group_id\":\"Clone\",\"function_id\":\"FlexStr 0.9 (SharedStr)\",\"value_str\":\"100\",\"throughput\":null,\"full_id\":\"Clone/FlexStr 0.9 (SharedStr)/100\",\"directory_name\":\"Clone/FlexStr 0.9 (SharedStr)/100\",\"title\":\"Clone/FlexStr 0.9 (SharedStr)/100\"}"
  },
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    "path": "docs/criterion/Clone/FlexStr 0.9 (SharedStr)/100/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":95055.86507112415,\"upper_bound\":95293.91401418211},\"point_estimate\":95166.04059505717,\"standard_error\":61.03271051608203},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":94919.62809917355,\"upper_bound\":94988.58386683739},\"point_estimate\":94950.93061045234,\"standard_error\":17.53945190098385},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":137.29427628131972,\"upper_bound\":249.0743270465606},\"point_estimate\":197.0592907598723,\"standard_error\":27.73398223643025},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":94930.40866760508,\"upper_bound\":95129.2989342039},\"point_estimate\":95018.22729556538,\"standard_error\":51.44811401014757},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":394.5848847339057,\"upper_bound\":801.6616998119332},\"point_estimate\":612.447474670894,\"standard_error\":104.19969301532802}}"
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    "path": "docs/criterion/Clone/FlexStr 0.9 (SharedStr)/100/base/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[11.0,22.0,33.0,44.0,55.0,66.0,77.0,88.0,99.0,110.0,121.0,132.0,143.0,154.0,165.0,176.0,187.0,198.0,209.0,220.0,231.0,242.0,253.0,264.0,275.0,286.0,297.0,308.0,319.0,330.0,341.0,352.0,363.0,374.0,385.0,396.0,407.0,418.0,429.0,440.0,451.0,462.0,473.0,484.0,495.0,506.0,517.0,528.0,539.0,550.0,561.0,572.0,583.0,594.0,605.0,616.0,627.0,638.0,649.0,660.0,671.0,682.0,693.0,704.0,715.0,726.0,737.0,748.0,759.0,770.0,781.0,792.0,803.0,814.0,825.0,836.0,847.0,858.0,869.0,880.0,891.0,902.0,913.0,924.0,935.0,946.0,957.0,968.0,979.0,990.0,1001.0,1012.0,1023.0,1034.0,1045.0,1056.0,1067.0,1078.0,1089.0,1100.0],\"times\":[1055209.0,2084042.0,3130460.0,4271207.0,5323668.0,6355541.0,7366790.0,8486876.0,9511333.0,10494502.0,11534167.0,12640041.0,14051792.0,15064876.0,15840208.0,16857500.0,17870664.0,18843043.0,19839168.0,20897831.0,21948582.0,22974417.0,24023125.0,25059540.0,26102209.0,27228501.0,28199793.0,29231790.0,30253417.0,31293582.0,32370876.0,33509252.0,34449706.0,35460291.0,36509957.0,37684374.0,38776042.0,39796500.0,40696749.0,41717125.0,42755792.0,43901709.0,44852415.0,45912249.0,47063417.0,47973667.0,49219002.0,50257750.0,51117250.0,52150250.0,53191876.0,54237042.0,55304500.0,56451625.0,57426375.0,58432583.0,59617960.0,60580209.0,61605126.0,62565167.0,63612751.0,64720709.0,65792082.0,66727501.0,67952583.0,68962293.0,69867041.0,70918794.0,72040417.0,73122416.0,74186084.0,75231707.0,76156623.0,77151957.0,78165709.0,79384042.0,80435332.0,81350458.0,82517416.0,83429416.0,84519081.0,85810084.0,86839041.0,87763416.0,88730000.0,89663835.0,91092209.0,91937627.0,92814250.0,93931457.0,94885377.0,95922332.0,97910751.0,98151292.0,99276710.0,101076582.0,101469625.0,102370208.0,105001834.0,104439418.0]}"
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    "path": "docs/criterion/Clone/FlexStr 0.9 (SharedStr)/100/base/tukey.json",
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    "path": "docs/criterion/Clone/FlexStr 0.9 (SharedStr)/100/new/benchmark.json",
    "content": "{\"group_id\":\"Clone\",\"function_id\":\"FlexStr 0.9 (SharedStr)\",\"value_str\":\"100\",\"throughput\":null,\"full_id\":\"Clone/FlexStr 0.9 (SharedStr)/100\",\"directory_name\":\"Clone/FlexStr 0.9 (SharedStr)/100\",\"title\":\"Clone/FlexStr 0.9 (SharedStr)/100\"}"
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    "path": "docs/criterion/Clone/FlexStr 0.9 (SharedStr)/100/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":95055.86507112415,\"upper_bound\":95293.91401418211},\"point_estimate\":95166.04059505717,\"standard_error\":61.03271051608203},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":94919.62809917355,\"upper_bound\":94988.58386683739},\"point_estimate\":94950.93061045234,\"standard_error\":17.53945190098385},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":137.29427628131972,\"upper_bound\":249.0743270465606},\"point_estimate\":197.0592907598723,\"standard_error\":27.73398223643025},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":94930.40866760508,\"upper_bound\":95129.2989342039},\"point_estimate\":95018.22729556538,\"standard_error\":51.44811401014757},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":394.5848847339057,\"upper_bound\":801.6616998119332},\"point_estimate\":612.447474670894,\"standard_error\":104.19969301532802}}"
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    "path": "docs/criterion/Clone/FlexStr 0.9 (SharedStr)/100/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[11.0,22.0,33.0,44.0,55.0,66.0,77.0,88.0,99.0,110.0,121.0,132.0,143.0,154.0,165.0,176.0,187.0,198.0,209.0,220.0,231.0,242.0,253.0,264.0,275.0,286.0,297.0,308.0,319.0,330.0,341.0,352.0,363.0,374.0,385.0,396.0,407.0,418.0,429.0,440.0,451.0,462.0,473.0,484.0,495.0,506.0,517.0,528.0,539.0,550.0,561.0,572.0,583.0,594.0,605.0,616.0,627.0,638.0,649.0,660.0,671.0,682.0,693.0,704.0,715.0,726.0,737.0,748.0,759.0,770.0,781.0,792.0,803.0,814.0,825.0,836.0,847.0,858.0,869.0,880.0,891.0,902.0,913.0,924.0,935.0,946.0,957.0,968.0,979.0,990.0,1001.0,1012.0,1023.0,1034.0,1045.0,1056.0,1067.0,1078.0,1089.0,1100.0],\"times\":[1055209.0,2084042.0,3130460.0,4271207.0,5323668.0,6355541.0,7366790.0,8486876.0,9511333.0,10494502.0,11534167.0,12640041.0,14051792.0,15064876.0,15840208.0,16857500.0,17870664.0,18843043.0,19839168.0,20897831.0,21948582.0,22974417.0,24023125.0,25059540.0,26102209.0,27228501.0,28199793.0,29231790.0,30253417.0,31293582.0,32370876.0,33509252.0,34449706.0,35460291.0,36509957.0,37684374.0,38776042.0,39796500.0,40696749.0,41717125.0,42755792.0,43901709.0,44852415.0,45912249.0,47063417.0,47973667.0,49219002.0,50257750.0,51117250.0,52150250.0,53191876.0,54237042.0,55304500.0,56451625.0,57426375.0,58432583.0,59617960.0,60580209.0,61605126.0,62565167.0,63612751.0,64720709.0,65792082.0,66727501.0,67952583.0,68962293.0,69867041.0,70918794.0,72040417.0,73122416.0,74186084.0,75231707.0,76156623.0,77151957.0,78165709.0,79384042.0,80435332.0,81350458.0,82517416.0,83429416.0,84519081.0,85810084.0,86839041.0,87763416.0,88730000.0,89663835.0,91092209.0,91937627.0,92814250.0,93931457.0,94885377.0,95922332.0,97910751.0,98151292.0,99276710.0,101076582.0,101469625.0,102370208.0,105001834.0,104439418.0]}"
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    "path": "docs/criterion/Clone/FlexStr 0.9 (SharedStr)/100/new/tukey.json",
    "content": "[93837.75386451602,94337.88842384524,95671.5805820565,96171.71514138572]"
  },
  {
    "path": "docs/criterion/Clone/FlexStr 0.9 (SharedStr)/100/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/FlexStr 0.9 (SharedStr)/100 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/FlexStr 0.9 (SharedStr)/100</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">94.930 µs</td>\n                                <td>95.018 µs</td>\n                                <td class=\"ci-bound\">95.129 µs</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.9981087</td>\n                                <td>0.9982266</td>\n                                <td class=\"ci-bound\">0.9980380</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">95.056 µs</td>\n                                <td>95.166 µs</td>\n                                <td class=\"ci-bound\">95.294 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">394.58 ns</td>\n                                <td>612.45 ns</td>\n                                <td class=\"ci-bound\">801.66 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">94.920 µs</td>\n                                <td>94.951 µs</td>\n                                <td class=\"ci-bound\">94.989 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">137.29 ns</td>\n                                <td>197.06 ns</td>\n                                <td class=\"ci-bound\">249.07 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−0.1070%</td>\n                            <td>+0.0727%</td>\n                            <td class=\"ci-bound\">+0.2500%</td>\n                            <td>(p = 0.45 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
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    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":7289.598233423135,\"upper_bound\":7314.523864795892},\"point_estimate\":7300.886684660979,\"standard_error\":6.368064647608124},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":7277.799687010955,\"upper_bound\":7288.690476190476},\"point_estimate\":7283.269801500847,\"standard_error\":3.063125923103102},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":14.89108111945497,\"upper_bound\":25.39314702046688},\"point_estimate\":19.833970093686986,\"standard_error\":2.7849173538311143},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":7280.678892785073,\"upper_bound\":7316.076110529161},\"point_estimate\":7294.280835733324,\"standard_error\":9.468519593433012},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":34.671489588419,\"upper_bound\":89.07466064005024},\"point_estimate\":64.02342380696989,\"standard_error\":13.936751607310669}}"
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    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[135.0,270.0,405.0,540.0,675.0,810.0,945.0,1080.0,1215.0,1350.0,1485.0,1620.0,1755.0,1890.0,2025.0,2160.0,2295.0,2430.0,2565.0,2700.0,2835.0,2970.0,3105.0,3240.0,3375.0,3510.0,3645.0,3780.0,3915.0,4050.0,4185.0,4320.0,4455.0,4590.0,4725.0,4860.0,4995.0,5130.0,5265.0,5400.0,5535.0,5670.0,5805.0,5940.0,6075.0,6210.0,6345.0,6480.0,6615.0,6750.0,6885.0,7020.0,7155.0,7290.0,7425.0,7560.0,7695.0,7830.0,7965.0,8100.0,8235.0,8370.0,8505.0,8640.0,8775.0,8910.0,9045.0,9180.0,9315.0,9450.0,9585.0,9720.0,9855.0,9990.0,10125.0,10260.0,10395.0,10530.0,10665.0,10800.0,10935.0,11070.0,11205.0,11340.0,11475.0,11610.0,11745.0,11880.0,12015.0,12150.0,12285.0,12420.0,12555.0,12690.0,12825.0,12960.0,13095.0,13230.0,13365.0,13500.0],\"times\":[985333.0,1964206.0,3066584.0,3924750.0,4913543.0,6049916.0,6908334.0,8021084.0,8800500.0,9907791.0,11189582.0,11832584.0,12819581.0,13777457.0,14973915.0,15743999.0,16722167.0,17726918.0,18709124.0,19686291.0,20663499.0,21679876.0,22797622.0,23764168.0,24521083.0,25553124.0,26520624.0,27551250.0,28550792.0,29449372.0,30461374.0,31453540.0,32368918.0,33431375.0,34429833.0,35395456.0,36352584.0,37384625.0,38276375.0,39433083.0,40749792.0,41271290.0,42206623.0,43153915.0,44789625.0,45200042.0,46165167.0,47106584.0,48245334.0,49196792.0,50214126.0,51034543.0,52024123.0,53408208.0,53993002.0,54880875.0,55980543.0,56955415.0,58007960.0,58929625.0,60508459.0,60762418.0,61820165.0,62714208.0,64061540.0,64764295.0,65973584.0,66890000.0,67890916.0,68676000.0,69757710.0,70814293.0,71915584.0,73314418.0,74122917.0,74525501.0,75564624.0,76508293.0,77503210.0,78554583.0,79834542.0,80630752.0,81721167.0,82582211.0,83402372.0,84331044.0,90295207.0,87638166.0,87425626.0,88256499.0,89336333.0,90546166.0,91345710.0,92229835.0,93742292.0,94184043.0,95658918.0,96530083.0,97162294.0,98062085.0]}"
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  },
  {
    "path": "docs/criterion/Clone/FlexStr 0.9 (SharedStr)/20/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/FlexStr 0.9 (SharedStr)/20 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/FlexStr 0.9 (SharedStr)/20</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">7.2807 µs</td>\n                                <td>7.2943 µs</td>\n                                <td class=\"ci-bound\">7.3161 µs</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.9885830</td>\n                                <td>0.9890605</td>\n                                <td class=\"ci-bound\">0.9878354</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">7.2896 µs</td>\n                                <td>7.3009 µs</td>\n                                <td class=\"ci-bound\">7.3145 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">34.671 ns</td>\n                                <td>64.023 ns</td>\n                                <td class=\"ci-bound\">89.075 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">7.2778 µs</td>\n                                <td>7.2833 µs</td>\n                                <td class=\"ci-bound\">7.2887 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">14.891 ns</td>\n                                <td>19.834 ns</td>\n                                <td class=\"ci-bound\">25.393 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−1.4777%</td>\n                            <td>−0.6778%</td>\n                            <td class=\"ci-bound\">−0.1528%</td>\n                            <td>(p = 0.03 &lt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                Change within noise threshold.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
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    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[11.0,22.0,33.0,44.0,55.0,66.0,77.0,88.0,99.0,110.0,121.0,132.0,143.0,154.0,165.0,176.0,187.0,198.0,209.0,220.0,231.0,242.0,253.0,264.0,275.0,286.0,297.0,308.0,319.0,330.0,341.0,352.0,363.0,374.0,385.0,396.0,407.0,418.0,429.0,440.0,451.0,462.0,473.0,484.0,495.0,506.0,517.0,528.0,539.0,550.0,561.0,572.0,583.0,594.0,605.0,616.0,627.0,638.0,649.0,660.0,671.0,682.0,693.0,704.0,715.0,726.0,737.0,748.0,759.0,770.0,781.0,792.0,803.0,814.0,825.0,836.0,847.0,858.0,869.0,880.0,891.0,902.0,913.0,924.0,935.0,946.0,957.0,968.0,979.0,990.0,1001.0,1012.0,1023.0,1034.0,1045.0,1056.0,1067.0,1078.0,1089.0,1100.0],\"times\":[1062084.0,2090167.0,3127875.0,4241832.0,5294999.0,6269958.0,7339955.0,8421582.0,9412375.0,10478751.0,11534875.0,12516166.0,13573209.0,14622791.0,15838251.0,16765669.0,17819668.0,18836625.0,19902164.0,20916625.0,21947460.0,23127748.0,24084082.0,25051583.0,26108500.0,27188374.0,28190458.0,29222625.0,30268045.0,31304123.0,32426792.0,33427125.0,34429083.0,35474709.0,36520499.0,37551417.0,38667335.0,40061125.0,40723876.0,41783625.0,42750543.0,43856583.0,44840667.0,46033752.0,47022750.0,48064874.0,49282419.0,50145625.0,51285249.0,52248041.0,53202541.0,54349874.0,56135377.0,56841790.0,57480169.0,58487250.0,59399460.0,60520252.0,61611455.0,62556415.0,63695791.0,64788707.0,65850252.0,66922247.0,67787082.0,69030708.0,69977124.0,71010416.0,71992418.0,73017915.0,74075125.0,75088165.0,76522957.0,77231834.0,78258541.0,79306708.0,80299708.0,81481333.0,82679084.0,83759041.0,84462581.0,85572709.0,86756377.0,87653504.0,89040707.0,89700249.0,90767167.0,91821582.0,93017834.0,93890336.0,95120709.0,95945290.0,96955752.0,98041502.0,99115958.0,100364332.0,101480292.0,102227586.0,103379002.0,104620542.0]}"
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    "content": "[94097.87588127544,94476.83565271842,95487.39504323305,95866.35481467603]"
  },
  {
    "path": "docs/criterion/Clone/FlexStr 0.9 (SharedStr)/500/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/FlexStr 0.9 (SharedStr)/500 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/FlexStr 0.9 (SharedStr)/500</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">94.922 µs</td>\n                                <td>94.963 µs</td>\n                                <td class=\"ci-bound\">95.010 µs</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.9993397</td>\n                                <td>0.9993655</td>\n                                <td class=\"ci-bound\">0.9993326</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">95.001 µs</td>\n                                <td>95.065 µs</td>\n                                <td class=\"ci-bound\">95.138 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">241.28 ns</td>\n                                <td>352.37 ns</td>\n                                <td class=\"ci-bound\">444.07 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">94.927 µs</td>\n                                <td>94.963 µs</td>\n                                <td class=\"ci-bound\">95.008 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">126.34 ns</td>\n                                <td>171.90 ns</td>\n                                <td class=\"ci-bound\">223.19 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−0.2460%</td>\n                            <td>−0.1017%</td>\n                            <td class=\"ci-bound\">+0.0336%</td>\n                            <td>(p = 0.17 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Clone/FlexStr 0.9 (SharedStr)/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/FlexStr 0.9 (SharedStr) Summary - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/FlexStr 0.9 (SharedStr)</h2>\n        <h3>Violin Plot</h3>\n        <a href=\"violin.svg\">\n            <img src=\"violin.svg\" alt=\"Violin Plot\" />\n        </a>\n        <p>This chart shows the relationship between function/parameter and iteration time. The thickness of the shaded\n            region indicates the probability that a measurement of the given function/parameter would take a particular\n            length of time.</p>\n        <h3>Line Chart</h3>\n        <img src=\"lines.svg\" alt=\"Line Chart\" />\n        <p>This chart shows the mean measured time for each function as the input (or the size of the input) increases.</p>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/FlexStr 0.9 (SharedStr)/0/report/index.html\">\n                <h4>Clone/FlexStr 0.9 (SharedStr)/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.9 (SharedStr)/0/report/pdf.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.9 (SharedStr)/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.9 (SharedStr)/0/report/regression.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.9 (SharedStr)/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/FlexStr 0.9 (SharedStr)/10/report/index.html\">\n                <h4>Clone/FlexStr 0.9 (SharedStr)/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.9 (SharedStr)/10/report/pdf.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.9 (SharedStr)/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.9 (SharedStr)/10/report/regression.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.9 (SharedStr)/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/FlexStr 0.9 (SharedStr)/20/report/index.html\">\n                <h4>Clone/FlexStr 0.9 (SharedStr)/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.9 (SharedStr)/20/report/pdf.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.9 (SharedStr)/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.9 (SharedStr)/20/report/regression.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.9 (SharedStr)/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/FlexStr 0.9 (SharedStr)/100/report/index.html\">\n                <h4>Clone/FlexStr 0.9 (SharedStr)/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.9 (SharedStr)/100/report/pdf.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.9 (SharedStr)/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.9 (SharedStr)/100/report/regression.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.9 (SharedStr)/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/FlexStr 0.9 (SharedStr)/500/report/index.html\">\n                <h4>Clone/FlexStr 0.9 (SharedStr)/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.9 (SharedStr)/500/report/pdf.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.9 (SharedStr)/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/FlexStr 0.9 (SharedStr)/500/report/regression.svg\">\n                                <img src=\"../../../Clone/FlexStr 0.9 (SharedStr)/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
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    "path": "docs/criterion/Clone/InlineFlexStr 0.1 (InlineStr)/0/base/benchmark.json",
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    "path": "docs/criterion/Clone/InlineFlexStr 0.1 (InlineStr)/0/new/sample.json",
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    "path": "docs/criterion/Clone/InlineFlexStr 0.1 (InlineStr)/0/new/tukey.json",
    "content": "[7319.007379305212,7354.612275329989,7449.558664729392,7485.163560754168]"
  },
  {
    "path": "docs/criterion/Clone/InlineFlexStr 0.1 (InlineStr)/0/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/InlineFlexStr 0.1 (InlineStr)/0 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/InlineFlexStr 0.1 (InlineStr)/0</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">7.3944 µs</td>\n                                <td>7.3974 µs</td>\n                                <td class=\"ci-bound\">7.4011 µs</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.9990786</td>\n                                <td>0.9991019</td>\n                                <td class=\"ci-bound\">0.9990680</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">7.4065 µs</td>\n                                <td>7.4181 µs</td>\n                                <td class=\"ci-bound\">7.4322 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">33.871 ns</td>\n                                <td>66.638 ns</td>\n                                <td class=\"ci-bound\">93.399 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">7.3935 µs</td>\n                                <td>7.3974 µs</td>\n                                <td class=\"ci-bound\">7.3996 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">8.6888 ns</td>\n                                <td>13.063 ns</td>\n                                <td class=\"ci-bound\">17.001 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−5.1405%</td>\n                            <td>−2.5059%</td>\n                            <td class=\"ci-bound\">−0.3853%</td>\n                            <td>(p = 0.03 &lt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                Change within noise threshold.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
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  },
  {
    "path": "docs/criterion/Clone/InlineFlexStr 0.1 (InlineStr)/10/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/InlineFlexStr 0.1 (InlineStr)/10 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/InlineFlexStr 0.1 (InlineStr)/10</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">7.4547 µs</td>\n                                <td>7.5466 µs</td>\n                                <td class=\"ci-bound\">7.6747 µs</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.1965403</td>\n                                <td>0.1974566</td>\n                                <td class=\"ci-bound\">0.1956801</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">7.6762 µs</td>\n                                <td>8.1592 µs</td>\n                                <td class=\"ci-bound\">8.7599 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">1.2831 µs</td>\n                                <td>2.8098 µs</td>\n                                <td class=\"ci-bound\">4.0073 µs</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">7.4058 µs</td>\n                                <td>7.4161 µs</td>\n                                <td class=\"ci-bound\">7.4339 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">26.200 ns</td>\n                                <td>40.272 ns</td>\n                                <td class=\"ci-bound\">65.374 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">+3.0581%</td>\n                            <td>+10.165%</td>\n                            <td class=\"ci-bound\">+17.974%</td>\n                            <td>(p = 0.00 &lt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                Performance has regressed.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
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  },
  {
    "path": "docs/criterion/Clone/InlineFlexStr 0.1 (InlineStr)/100/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/InlineFlexStr 0.1 (InlineStr)/100 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/InlineFlexStr 0.1 (InlineStr)/100</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">7.3902 µs</td>\n                                <td>7.3927 µs</td>\n                                <td class=\"ci-bound\">7.3956 µs</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.9992607</td>\n                                <td>0.9992764</td>\n                                <td class=\"ci-bound\">0.9992553</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">7.4023 µs</td>\n                                <td>7.4107 µs</td>\n                                <td class=\"ci-bound\">7.4203 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">28.938 ns</td>\n                                <td>46.204 ns</td>\n                                <td class=\"ci-bound\">60.477 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">7.3912 µs</td>\n                                <td>7.3945 µs</td>\n                                <td class=\"ci-bound\">7.3996 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">10.305 ns</td>\n                                <td>14.194 ns</td>\n                                <td class=\"ci-bound\">20.051 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−0.1798%</td>\n                            <td>−0.0132%</td>\n                            <td class=\"ci-bound\">+0.1575%</td>\n                            <td>(p = 0.89 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
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    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[133.0,266.0,399.0,532.0,665.0,798.0,931.0,1064.0,1197.0,1330.0,1463.0,1596.0,1729.0,1862.0,1995.0,2128.0,2261.0,2394.0,2527.0,2660.0,2793.0,2926.0,3059.0,3192.0,3325.0,3458.0,3591.0,3724.0,3857.0,3990.0,4123.0,4256.0,4389.0,4522.0,4655.0,4788.0,4921.0,5054.0,5187.0,5320.0,5453.0,5586.0,5719.0,5852.0,5985.0,6118.0,6251.0,6384.0,6517.0,6650.0,6783.0,6916.0,7049.0,7182.0,7315.0,7448.0,7581.0,7714.0,7847.0,7980.0,8113.0,8246.0,8379.0,8512.0,8645.0,8778.0,8911.0,9044.0,9177.0,9310.0,9443.0,9576.0,9709.0,9842.0,9975.0,10108.0,10241.0,10374.0,10507.0,10640.0,10773.0,10906.0,11039.0,11172.0,11305.0,11438.0,11571.0,11704.0,11837.0,11970.0,12103.0,12236.0,12369.0,12502.0,12635.0,12768.0,12901.0,13034.0,13167.0,13300.0],\"times\":[993835.0,1963292.0,2951418.0,4064459.0,4947750.0,5969124.0,6959748.0,7952876.0,8915083.0,10027207.0,11002083.0,11857502.0,12795081.0,13758749.0,14964960.0,15788584.0,18009377.0,17715541.0,18742207.0,20008125.0,20728623.0,21637544.0,22641332.0,23604252.0,24566292.0,25590169.0,26526416.0,27574040.0,28511416.0,29567914.0,30487918.0,31516708.0,32597248.0,33381956.0,34414958.0,35357207.0,36381958.0,37347333.0,38308875.0,39298541.0,40351710.0,41357499.0,42420458.0,43312416.0,44265502.0,45257878.0,46187083.0,47147959.0,48167753.0,49186875.0,50089458.0,51162708.0,52228917.0,53114210.0,54079457.0,55073456.0,56089125.0,57253459.0,58253210.0,58924626.0,60058417.0,61031625.0,61951083.0,62966709.0,63844417.0,64884918.0,65789375.0,66822542.0,67878165.0,68864500.0,69799584.0,70700666.0,71677793.0,72657626.0,84835249.0,79744959.0,123198125.0,140930999.0,121367292.0,87266292.0,82770794.0,83079668.0,81524543.0,82507873.0,83476208.0,84767792.0,85758751.0,86571207.0,87428709.0,88398666.0,89421000.0,90468209.0,91466626.0,92375249.0,93288415.0,94394834.0,95512998.0,96923709.0,97313460.0,98499751.0]}"
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  },
  {
    "path": "docs/criterion/Clone/InlineFlexStr 0.1 (InlineStr)/20/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/InlineFlexStr 0.1 (InlineStr)/20 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/InlineFlexStr 0.1 (InlineStr)/20</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">7.4521 µs</td>\n                                <td>7.7177 µs</td>\n                                <td class=\"ci-bound\">8.0559 µs</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.2093664</td>\n                                <td>0.2181150</td>\n                                <td class=\"ci-bound\">0.2042692</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">7.4440 µs</td>\n                                <td>7.5929 µs</td>\n                                <td class=\"ci-bound\">7.7839 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">158.64 ns</td>\n                                <td>875.63 ns</td>\n                                <td class=\"ci-bound\">1.2979 µs</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">7.3947 µs</td>\n                                <td>7.3972 µs</td>\n                                <td class=\"ci-bound\">7.4014 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">11.268 ns</td>\n                                <td>16.927 ns</td>\n                                <td class=\"ci-bound\">23.203 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">+0.3489%</td>\n                            <td>+2.2839%</td>\n                            <td class=\"ci-bound\">+4.5781%</td>\n                            <td>(p = 0.03 &lt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                Change within noise threshold.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
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    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":7409.188260904711,\"upper_bound\":7443.808237565852},\"point_estimate\":7424.812664645807,\"standard_error\":8.844235593585426},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":7391.642946341548,\"upper_bound\":7402.119757224386},\"point_estimate\":7395.081331299386,\"standard_error\":2.7961566204106023},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":10.345299562557432,\"upper_bound\":19.874668192429713},\"point_estimate\":15.060435091011664,\"standard_error\":2.4051326915173306},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":7393.642733188671,\"upper_bound\":7401.295628545062},\"point_estimate\":7397.063063007007,\"standard_error\":1.9574297157792104},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":49.94298628319375,\"upper_bound\":123.89205219097208},\"point_estimate\":88.81267372945672,\"standard_error\":19.187809821088095}}"
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    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[133.0,266.0,399.0,532.0,665.0,798.0,931.0,1064.0,1197.0,1330.0,1463.0,1596.0,1729.0,1862.0,1995.0,2128.0,2261.0,2394.0,2527.0,2660.0,2793.0,2926.0,3059.0,3192.0,3325.0,3458.0,3591.0,3724.0,3857.0,3990.0,4123.0,4256.0,4389.0,4522.0,4655.0,4788.0,4921.0,5054.0,5187.0,5320.0,5453.0,5586.0,5719.0,5852.0,5985.0,6118.0,6251.0,6384.0,6517.0,6650.0,6783.0,6916.0,7049.0,7182.0,7315.0,7448.0,7581.0,7714.0,7847.0,7980.0,8113.0,8246.0,8379.0,8512.0,8645.0,8778.0,8911.0,9044.0,9177.0,9310.0,9443.0,9576.0,9709.0,9842.0,9975.0,10108.0,10241.0,10374.0,10507.0,10640.0,10773.0,10906.0,11039.0,11172.0,11305.0,11438.0,11571.0,11704.0,11837.0,11970.0,12103.0,12236.0,12369.0,12502.0,12635.0,12768.0,12901.0,13034.0,13167.0,13300.0],\"times\":[1015707.0,1963459.0,2946083.0,4039042.0,5305293.0,6195583.0,6903625.0,8061417.0,8865459.0,9874290.0,11162294.0,11869168.0,12974709.0,14200540.0,15354165.0,15960250.0,16921751.0,17831125.0,18700960.0,19656624.0,20682917.0,21691207.0,22644083.0,23599708.0,24606752.0,25565667.0,26545586.0,27513583.0,28469334.0,29605541.0,30455628.0,31518168.0,32515127.0,33462583.0,34471251.0,35367418.0,36339834.0,37359249.0,38334667.0,39305293.0,40248539.0,41265248.0,42264749.0,43186959.0,44188542.0,45346749.0,46587459.0,47160166.0,48156667.0,49143833.0,50216041.0,51048336.0,52189123.0,53229249.0,54035124.0,55169375.0,56064417.0,57199666.0,57997209.0,59979750.0,60220084.0,60977333.0,61928166.0,62912459.0,63878000.0,64871586.0,65892291.0,66891332.0,67995208.0,68874249.0,69717498.0,70918250.0,71782458.0,72763292.0,73744624.0,74688542.0,75686710.0,76895541.0,77820001.0,78851919.0,79876292.0,80559958.0,81712000.0,82493457.0,83852416.0,84443789.0,85462751.0,86427915.0,87357292.0,88593582.0,89631166.0,90411127.0,91353290.0,92322458.0,93446710.0,94438792.0,95366335.0,96264040.0,97278875.0,98260875.0]}"
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  },
  {
    "path": "docs/criterion/Clone/InlineFlexStr 0.1 (InlineStr)/500/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/InlineFlexStr 0.1 (InlineStr)/500 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/InlineFlexStr 0.1 (InlineStr)/500</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">7.3936 µs</td>\n                                <td>7.3971 µs</td>\n                                <td class=\"ci-bound\">7.4013 µs</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.9987977</td>\n                                <td>0.9988273</td>\n                                <td class=\"ci-bound\">0.9987819</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">7.4092 µs</td>\n                                <td>7.4248 µs</td>\n                                <td class=\"ci-bound\">7.4438 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">49.943 ns</td>\n                                <td>88.813 ns</td>\n                                <td class=\"ci-bound\">123.89 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">7.3916 µs</td>\n                                <td>7.3951 µs</td>\n                                <td class=\"ci-bound\">7.4021 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">10.345 ns</td>\n                                <td>15.060 ns</td>\n                                <td class=\"ci-bound\">19.875 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−0.0173%</td>\n                            <td>+0.2239%</td>\n                            <td class=\"ci-bound\">+0.5087%</td>\n                            <td>(p = 0.09 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Clone/InlineFlexStr 0.1 (InlineStr)/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/InlineFlexStr 0.1 (InlineStr) Summary - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/InlineFlexStr 0.1 (InlineStr)</h2>\n        <h3>Violin Plot</h3>\n        <a href=\"violin.svg\">\n            <img src=\"violin.svg\" alt=\"Violin Plot\" />\n        </a>\n        <p>This chart shows the relationship between function/parameter and iteration time. The thickness of the shaded\n            region indicates the probability that a measurement of the given function/parameter would take a particular\n            length of time.</p>\n        <h3>Line Chart</h3>\n        <img src=\"lines.svg\" alt=\"Line Chart\" />\n        <p>This chart shows the mean measured time for each function as the input (or the size of the input) increases.</p>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/InlineFlexStr 0.1 (InlineStr)/0/report/index.html\">\n                <h4>Clone/InlineFlexStr 0.1 (InlineStr)/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/InlineFlexStr 0.1 (InlineStr)/0/report/pdf.svg\">\n                                <img src=\"../../../Clone/InlineFlexStr 0.1 (InlineStr)/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/InlineFlexStr 0.1 (InlineStr)/0/report/regression.svg\">\n                                <img src=\"../../../Clone/InlineFlexStr 0.1 (InlineStr)/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/InlineFlexStr 0.1 (InlineStr)/10/report/index.html\">\n                <h4>Clone/InlineFlexStr 0.1 (InlineStr)/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/InlineFlexStr 0.1 (InlineStr)/10/report/pdf.svg\">\n                                <img src=\"../../../Clone/InlineFlexStr 0.1 (InlineStr)/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/InlineFlexStr 0.1 (InlineStr)/10/report/regression.svg\">\n                                <img src=\"../../../Clone/InlineFlexStr 0.1 (InlineStr)/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/InlineFlexStr 0.1 (InlineStr)/20/report/index.html\">\n                <h4>Clone/InlineFlexStr 0.1 (InlineStr)/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/InlineFlexStr 0.1 (InlineStr)/20/report/pdf.svg\">\n                                <img src=\"../../../Clone/InlineFlexStr 0.1 (InlineStr)/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/InlineFlexStr 0.1 (InlineStr)/20/report/regression.svg\">\n                                <img src=\"../../../Clone/InlineFlexStr 0.1 (InlineStr)/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/InlineFlexStr 0.1 (InlineStr)/100/report/index.html\">\n                <h4>Clone/InlineFlexStr 0.1 (InlineStr)/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/InlineFlexStr 0.1 (InlineStr)/100/report/pdf.svg\">\n                                <img src=\"../../../Clone/InlineFlexStr 0.1 (InlineStr)/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/InlineFlexStr 0.1 (InlineStr)/100/report/regression.svg\">\n                                <img src=\"../../../Clone/InlineFlexStr 0.1 (InlineStr)/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/InlineFlexStr 0.1 (InlineStr)/500/report/index.html\">\n                <h4>Clone/InlineFlexStr 0.1 (InlineStr)/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/InlineFlexStr 0.1 (InlineStr)/500/report/pdf.svg\">\n                                <img src=\"../../../Clone/InlineFlexStr 0.1 (InlineStr)/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/InlineFlexStr 0.1 (InlineStr)/500/report/regression.svg\">\n                                <img src=\"../../../Clone/InlineFlexStr 0.1 (InlineStr)/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Clone/Rc_str_/0/base/benchmark.json",
    "content": "{\"group_id\":\"Clone\",\"function_id\":\"Rc<str>\",\"value_str\":\"0\",\"throughput\":null,\"full_id\":\"Clone/Rc<str>/0\",\"directory_name\":\"Clone/Rc_str_/0\",\"title\":\"Clone/Rc<str>/0\"}"
  },
  {
    "path": "docs/criterion/Clone/Rc_str_/0/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":40254.72547374264,\"upper_bound\":40468.3701533398},\"point_estimate\":40347.203269650134,\"standard_error\":54.911828317467},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":40180.00724637681,\"upper_bound\":40216.62028301887},\"point_estimate\":40200.07967466256,\"standard_error\":10.425928480394749},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":51.15579790405206,\"upper_bound\":91.43611378269509},\"point_estimate\":75.92037249268188,\"standard_error\":11.397476312900494},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":40174.64150058812,\"upper_bound\":40199.1011949012},\"point_estimate\":40185.767402714155,\"standard_error\":6.2199066103318605},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":239.7393142952519,\"upper_bound\":834.6326287083015},\"point_estimate\":549.6164136090489,\"standard_error\":165.51516357819}}"
  },
  {
    "path": "docs/criterion/Clone/Rc_str_/0/base/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[24.0,48.0,72.0,96.0,120.0,144.0,168.0,192.0,216.0,240.0,264.0,288.0,312.0,336.0,360.0,384.0,408.0,432.0,456.0,480.0,504.0,528.0,552.0,576.0,600.0,624.0,648.0,672.0,696.0,720.0,744.0,768.0,792.0,816.0,840.0,864.0,888.0,912.0,936.0,960.0,984.0,1008.0,1032.0,1056.0,1080.0,1104.0,1128.0,1152.0,1176.0,1200.0,1224.0,1248.0,1272.0,1296.0,1320.0,1344.0,1368.0,1392.0,1416.0,1440.0,1464.0,1488.0,1512.0,1536.0,1560.0,1584.0,1608.0,1632.0,1656.0,1680.0,1704.0,1728.0,1752.0,1776.0,1800.0,1824.0,1848.0,1872.0,1896.0,1920.0,1944.0,1968.0,1992.0,2016.0,2040.0,2064.0,2088.0,2112.0,2136.0,2160.0,2184.0,2208.0,2232.0,2256.0,2280.0,2304.0,2328.0,2352.0,2376.0,2400.0],\"times\":[1000376.0,1987873.0,2980584.0,3982250.0,5344208.0,5869583.0,7096249.0,7882543.0,8678085.0,9748919.0,10619251.0,11595374.0,12537543.0,13548000.0,14588667.0,15501958.0,16430750.0,17394917.0,18399249.0,19709209.0,20274751.0,21280335.0,22185459.0,23172873.0,24102501.0,25075207.0,26053874.0,26999084.0,27928834.0,29030043.0,29878250.0,30872167.0,31900582.0,32786875.0,33717000.0,34793292.0,35742833.0,36612249.0,37617832.0,38604667.0,39502583.0,40573957.0,41422544.0,42457000.0,43505711.0,44469582.0,45286750.0,46314584.0,47405876.0,48167501.0,49226044.0,50110417.0,51155541.0,52033082.0,53117959.0,54031582.0,55083208.0,55978124.0,57018459.0,57923876.0,58818125.0,59764208.0,60683918.0,61764125.0,62770167.0,63789168.0,64593711.0,65477583.0,66509000.0,67436585.0,68504251.0,69419042.0,70389041.0,71528919.0,72355956.0,73403958.0,74189166.0,75125457.0,76105210.0,77491541.0,78033248.0,79000751.0,79981750.0,80984876.0,82051624.0,82867043.0,83963374.0,84868584.0,85793668.0,86685417.0,87642249.0,88717456.0,89635710.0,90538919.0,91580914.0,92581166.0,93497833.0,94504043.0,95434709.0,96338625.0]}"
  },
  {
    "path": "docs/criterion/Clone/Rc_str_/0/base/tukey.json",
    "content": "[39842.39112233883,40001.978870600185,40427.54619929714,40587.1339475585]"
  },
  {
    "path": "docs/criterion/Clone/Rc_str_/0/change/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.0183819625445751,\"upper_bound\":0.0018423938099467272},\"point_estimate\":-0.0061627848130728635,\"standard_error\":0.0054116612842752786},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.0008942024541087612,\"upper_bound\":0.001421887085136353},\"point_estimate\":0.00038346268358369073,\"standard_error\":0.0005733865724321635}}"
  },
  {
    "path": "docs/criterion/Clone/Rc_str_/0/new/benchmark.json",
    "content": "{\"group_id\":\"Clone\",\"function_id\":\"Rc<str>\",\"value_str\":\"0\",\"throughput\":null,\"full_id\":\"Clone/Rc<str>/0\",\"directory_name\":\"Clone/Rc_str_/0\",\"title\":\"Clone/Rc<str>/0\"}"
  },
  {
    "path": "docs/criterion/Clone/Rc_str_/0/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":40254.72547374264,\"upper_bound\":40468.3701533398},\"point_estimate\":40347.203269650134,\"standard_error\":54.911828317467},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":40180.00724637681,\"upper_bound\":40216.62028301887},\"point_estimate\":40200.07967466256,\"standard_error\":10.425928480394749},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":51.15579790405206,\"upper_bound\":91.43611378269509},\"point_estimate\":75.92037249268188,\"standard_error\":11.397476312900494},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":40174.64150058812,\"upper_bound\":40199.1011949012},\"point_estimate\":40185.767402714155,\"standard_error\":6.2199066103318605},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":239.7393142952519,\"upper_bound\":834.6326287083015},\"point_estimate\":549.6164136090489,\"standard_error\":165.51516357819}}"
  },
  {
    "path": "docs/criterion/Clone/Rc_str_/0/new/sample.json",
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  {
    "path": "docs/criterion/Clone/Rc_str_/0/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/Rc&lt;str&gt;/0 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/Rc&lt;str&gt;/0</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">40.175 µs</td>\n                                <td>40.186 µs</td>\n                                <td class=\"ci-bound\">40.199 µs</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.9994888</td>\n                                <td>0.9994994</td>\n                                <td class=\"ci-bound\">0.9994842</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">40.255 µs</td>\n                                <td>40.347 µs</td>\n                                <td class=\"ci-bound\">40.468 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">239.74 ns</td>\n                                <td>549.62 ns</td>\n                                <td class=\"ci-bound\">834.63 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">40.180 µs</td>\n                                <td>40.200 µs</td>\n                                <td class=\"ci-bound\">40.217 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">51.156 ns</td>\n                                <td>75.920 ns</td>\n                                <td class=\"ci-bound\">91.436 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−1.8382%</td>\n                            <td>−0.6163%</td>\n                            <td class=\"ci-bound\">+0.1842%</td>\n                            <td>(p = 0.30 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
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    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/Rc&lt;str&gt;/10 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/Rc&lt;str&gt;/10</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">40.209 µs</td>\n                                <td>40.259 µs</td>\n                                <td class=\"ci-bound\">40.324 µs</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.9935795</td>\n                                <td>0.9937921</td>\n                                <td class=\"ci-bound\">0.9934327</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">40.284 µs</td>\n                                <td>40.351 µs</td>\n                                <td class=\"ci-bound\">40.426 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">254.45 ns</td>\n                                <td>364.33 ns</td>\n                                <td class=\"ci-bound\">452.58 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">40.178 µs</td>\n                                <td>40.199 µs</td>\n                                <td class=\"ci-bound\">40.223 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">48.931 ns</td>\n                                <td>78.419 ns</td>\n                                <td class=\"ci-bound\">122.84 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−3.7607%</td>\n                            <td>−1.8520%</td>\n                            <td class=\"ci-bound\">−0.3192%</td>\n                            <td>(p = 0.03 &lt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                Change within noise threshold.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
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    "path": "docs/criterion/Clone/Rc_str_/100/base/benchmark.json",
    "content": "{\"group_id\":\"Clone\",\"function_id\":\"Rc<str>\",\"value_str\":\"100\",\"throughput\":null,\"full_id\":\"Clone/Rc<str>/100\",\"directory_name\":\"Clone/Rc_str_/100\",\"title\":\"Clone/Rc<str>/100\"}"
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    "path": "docs/criterion/Clone/Rc_str_/100/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[25.0,50.0,75.0,100.0,125.0,150.0,175.0,200.0,225.0,250.0,275.0,300.0,325.0,350.0,375.0,400.0,425.0,450.0,475.0,500.0,525.0,550.0,575.0,600.0,625.0,650.0,675.0,700.0,725.0,750.0,775.0,800.0,825.0,850.0,875.0,900.0,925.0,950.0,975.0,1000.0,1025.0,1050.0,1075.0,1100.0,1125.0,1150.0,1175.0,1200.0,1225.0,1250.0,1275.0,1300.0,1325.0,1350.0,1375.0,1400.0,1425.0,1450.0,1475.0,1500.0,1525.0,1550.0,1575.0,1600.0,1625.0,1650.0,1675.0,1700.0,1725.0,1750.0,1775.0,1800.0,1825.0,1850.0,1875.0,1900.0,1925.0,1950.0,1975.0,2000.0,2025.0,2050.0,2075.0,2100.0,2125.0,2150.0,2175.0,2200.0,2225.0,2250.0,2275.0,2300.0,2325.0,2350.0,2375.0,2400.0,2425.0,2450.0,2475.0,2500.0],\"times\":[1023918.0,2017625.0,3028875.0,4131126.0,5235833.0,6119541.0,7077583.0,8160294.0,9083792.0,10087707.0,11274875.0,12183792.0,13116666.0,14102125.0,15255584.0,16116084.0,17146333.0,18067792.0,19103791.0,20232460.0,21135375.0,22082415.0,23193834.0,24116293.0,25149958.0,26274123.0,27098916.0,28624377.0,29162251.0,30664251.0,31159582.0,32208334.0,33151418.0,34214875.0,35144291.0,36196208.0,37207584.0,38244041.0,39240417.0,40224374.0,41162999.0,42099709.0,43152249.0,44135917.0,45178586.0,46321626.0,47258293.0,48171501.0,49446291.0,50153624.0,51184500.0,52181541.0,53183834.0,54188418.0,55165250.0,56265750.0,57265333.0,58203960.0,59182751.0,60264168.0,61176293.0,62184708.0,63203459.0,64207999.0,65309042.0,66329791.0,67666999.0,68301876.0,69437669.0,70478376.0,71161041.0,72294625.0,73181044.0,74165124.0,75181124.0,76152293.0,77151794.0,98386042.0,84528499.0,88285039.0,88252000.0,88122209.0,89684376.0,86327290.0,85753374.0,86467375.0,87360708.0,88351501.0,89623250.0,90574333.0,91714751.0,92464043.0,93367208.0,94262209.0,95377500.0,96514832.0,97427583.0,98283042.0,99424127.0,101085167.0]}"
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    "content": "[39515.151505795766,39832.08557613021,40677.243097022045,40994.17716735648]"
  },
  {
    "path": "docs/criterion/Clone/Rc_str_/100/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/Rc&lt;str&gt;/100 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/Rc&lt;str&gt;/100</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">40.339 µs</td>\n                                <td>40.706 µs</td>\n                                <td class=\"ci-bound\">41.192 µs</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.8084331</td>\n                                <td>0.8160064</td>\n                                <td class=\"ci-bound\">0.8028129</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">40.354 µs</td>\n                                <td>40.558 µs</td>\n                                <td class=\"ci-bound\">40.830 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">502.41 ns</td>\n                                <td>1.2387 µs</td>\n                                <td class=\"ci-bound\">1.9098 µs</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">40.186 µs</td>\n                                <td>40.218 µs</td>\n                                <td class=\"ci-bound\">40.255 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">87.030 ns</td>\n                                <td>117.28 ns</td>\n                                <td class=\"ci-bound\">169.13 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">+0.1101%</td>\n                            <td>+0.6580%</td>\n                            <td class=\"ci-bound\">+1.3318%</td>\n                            <td>(p = 0.03 &lt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                Change within noise threshold.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Clone/Rc_str_/20/base/benchmark.json",
    "content": "{\"group_id\":\"Clone\",\"function_id\":\"Rc<str>\",\"value_str\":\"20\",\"throughput\":null,\"full_id\":\"Clone/Rc<str>/20\",\"directory_name\":\"Clone/Rc_str_/20\",\"title\":\"Clone/Rc<str>/20\"}"
  },
  {
    "path": "docs/criterion/Clone/Rc_str_/20/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":40279.528945736536,\"upper_bound\":40395.871261643086},\"point_estimate\":40334.008349540265,\"standard_error\":29.74109421243841},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":40201.58571428571,\"upper_bound\":40242.97160539216},\"point_estimate\":40224.22282728765,\"standard_error\":13.21161804588045},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":74.7415377811722,\"upper_bound\":146.6928580372101},\"point_estimate\":117.31377344209464,\"standard_error\":20.264735853015704},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":40198.69143360895,\"upper_bound\":40237.45476488641},\"point_estimate\":40216.52577283877,\"standard_error\":9.88096611440063},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":195.380158192079,\"upper_bound\":386.6912329650827},\"point_estimate\":298.9427509536341,\"standard_error\":48.86116965660166}}"
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    "path": "docs/criterion/Clone/Rc_str_/20/base/sample.json",
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  },
  {
    "path": "docs/criterion/Clone/Rc_str_/20/base/tukey.json",
    "content": "[39577.2751214575,39871.199902834014,40654.99931983806,40948.92410121458]"
  },
  {
    "path": "docs/criterion/Clone/Rc_str_/20/change/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.0005710623085924099,\"upper_bound\":0.0032423350093530308},\"point_estimate\":0.0013883214852854486,\"standard_error\":0.0009731434010874342},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.00012248417559101998,\"upper_bound\":0.0013677268331606651},\"point_estimate\":0.0006656441833126081,\"standard_error\":0.0004009818286672115}}"
  },
  {
    "path": "docs/criterion/Clone/Rc_str_/20/new/benchmark.json",
    "content": "{\"group_id\":\"Clone\",\"function_id\":\"Rc<str>\",\"value_str\":\"20\",\"throughput\":null,\"full_id\":\"Clone/Rc<str>/20\",\"directory_name\":\"Clone/Rc_str_/20\",\"title\":\"Clone/Rc<str>/20\"}"
  },
  {
    "path": "docs/criterion/Clone/Rc_str_/20/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":40279.528945736536,\"upper_bound\":40395.871261643086},\"point_estimate\":40334.008349540265,\"standard_error\":29.74109421243841},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":40201.58571428571,\"upper_bound\":40242.97160539216},\"point_estimate\":40224.22282728765,\"standard_error\":13.21161804588045},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":74.7415377811722,\"upper_bound\":146.6928580372101},\"point_estimate\":117.31377344209464,\"standard_error\":20.264735853015704},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":40198.69143360895,\"upper_bound\":40237.45476488641},\"point_estimate\":40216.52577283877,\"standard_error\":9.88096611440063},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":195.380158192079,\"upper_bound\":386.6912329650827},\"point_estimate\":298.9427509536341,\"standard_error\":48.86116965660166}}"
  },
  {
    "path": "docs/criterion/Clone/Rc_str_/20/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[25.0,50.0,75.0,100.0,125.0,150.0,175.0,200.0,225.0,250.0,275.0,300.0,325.0,350.0,375.0,400.0,425.0,450.0,475.0,500.0,525.0,550.0,575.0,600.0,625.0,650.0,675.0,700.0,725.0,750.0,775.0,800.0,825.0,850.0,875.0,900.0,925.0,950.0,975.0,1000.0,1025.0,1050.0,1075.0,1100.0,1125.0,1150.0,1175.0,1200.0,1225.0,1250.0,1275.0,1300.0,1325.0,1350.0,1375.0,1400.0,1425.0,1450.0,1475.0,1500.0,1525.0,1550.0,1575.0,1600.0,1625.0,1650.0,1675.0,1700.0,1725.0,1750.0,1775.0,1800.0,1825.0,1850.0,1875.0,1900.0,1925.0,1950.0,1975.0,2000.0,2025.0,2050.0,2075.0,2100.0,2125.0,2150.0,2175.0,2200.0,2225.0,2250.0,2275.0,2300.0,2325.0,2350.0,2375.0,2400.0,2425.0,2450.0,2475.0,2500.0],\"times\":[1016209.0,2007958.0,3006458.0,4181041.0,5168249.0,6076792.0,7099709.0,8107334.0,9282749.0,10083957.0,11143707.0,12172957.0,13078249.0,14082957.0,15259292.0,16152291.0,17100416.0,18145749.0,19195125.0,20354958.0,21493084.0,22782708.0,23737999.0,24125833.0,25213708.0,26294667.0,27443584.0,28388249.0,29101085.0,30211583.0,31105334.0,32189666.0,33174916.0,34197873.0,35140833.0,36167750.0,37147499.0,38154750.0,39138584.0,40200041.0,41462543.0,42211665.0,43165959.0,44488458.0,45327958.0,46240542.0,47220584.0,48233624.0,49172250.0,50207335.0,51312250.0,52464458.0,53289791.0,54301082.0,55513751.0,56583501.0,57374038.0,58650709.0,59493833.0,60558708.0,61490250.0,62535748.0,63267752.0,64385666.0,65566709.0,66396959.0,67366166.0,68582668.0,69293960.0,70282583.0,71264041.0,72302539.0,73228417.0,74442834.0,75600291.0,76342710.0,77430209.0,78363250.0,79308248.0,80279542.0,81385456.0,82316915.0,83705958.0,84284417.0,85302333.0,86302207.0,87489289.0,88368043.0,89450333.0,90321167.0,91356249.0,92281708.0,93467751.0,94395084.0,95344251.0,96348585.0,97317461.0,98592125.0,99529541.0,100470793.0]}"
  },
  {
    "path": "docs/criterion/Clone/Rc_str_/20/new/tukey.json",
    "content": "[39577.2751214575,39871.199902834014,40654.99931983806,40948.92410121458]"
  },
  {
    "path": "docs/criterion/Clone/Rc_str_/20/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/Rc&lt;str&gt;/20 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/Rc&lt;str&gt;/20</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">40.199 µs</td>\n                                <td>40.217 µs</td>\n                                <td class=\"ci-bound\">40.237 µs</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.9989115</td>\n                                <td>0.9989387</td>\n                                <td class=\"ci-bound\">0.9989012</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">40.280 µs</td>\n                                <td>40.334 µs</td>\n                                <td class=\"ci-bound\">40.396 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">195.38 ns</td>\n                                <td>298.94 ns</td>\n                                <td class=\"ci-bound\">386.69 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">40.202 µs</td>\n                                <td>40.224 µs</td>\n                                <td class=\"ci-bound\">40.243 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">74.742 ns</td>\n                                <td>117.31 ns</td>\n                                <td class=\"ci-bound\">146.69 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−0.0571%</td>\n                            <td>+0.1388%</td>\n                            <td class=\"ci-bound\">+0.3242%</td>\n                            <td>(p = 0.16 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Clone/Rc_str_/500/base/benchmark.json",
    "content": "{\"group_id\":\"Clone\",\"function_id\":\"Rc<str>\",\"value_str\":\"500\",\"throughput\":null,\"full_id\":\"Clone/Rc<str>/500\",\"directory_name\":\"Clone/Rc_str_/500\",\"title\":\"Clone/Rc<str>/500\"}"
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    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":40256.17892332161,\"upper_bound\":40371.82200755127},\"point_estimate\":40309.74291910164,\"standard_error\":29.620590537010543},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":40183.51482394366,\"upper_bound\":40219.94275862069},\"point_estimate\":40194.520081632654,\"standard_error\":9.683175797014961},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":42.353000829432986,\"upper_bound\":90.98259322286917},\"point_estimate\":60.4964473923512,\"standard_error\":12.417275561667736},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":40185.642111165536,\"upper_bound\":40212.87528863189},\"point_estimate\":40198.35233621989,\"standard_error\":6.982383167621202},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":186.8237070282473,\"upper_bound\":388.9726008661178},\"point_estimate\":297.045322375589,\"standard_error\":51.8796429238427}}"
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    "path": "docs/criterion/Clone/Rc_str_/500/base/tukey.json",
    "content": "[39787.66491605575,39977.11219119844,40482.30492491227,40671.75220005496]"
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  {
    "path": "docs/criterion/Clone/Rc_str_/500/change/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.0006153824739983909,\"upper_bound\":0.003142809493609089},\"point_estimate\":0.0011591583206607137,\"standard_error\":0.0009658843762979514},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.0006508558242417362,\"upper_bound\":0.0008461257080745738},\"point_estimate\":0.00003146361766526162,\"standard_error\":0.00036851677869698395}}"
  },
  {
    "path": "docs/criterion/Clone/Rc_str_/500/new/benchmark.json",
    "content": "{\"group_id\":\"Clone\",\"function_id\":\"Rc<str>\",\"value_str\":\"500\",\"throughput\":null,\"full_id\":\"Clone/Rc<str>/500\",\"directory_name\":\"Clone/Rc_str_/500\",\"title\":\"Clone/Rc<str>/500\"}"
  },
  {
    "path": "docs/criterion/Clone/Rc_str_/500/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":40256.17892332161,\"upper_bound\":40371.82200755127},\"point_estimate\":40309.74291910164,\"standard_error\":29.620590537010543},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":40183.51482394366,\"upper_bound\":40219.94275862069},\"point_estimate\":40194.520081632654,\"standard_error\":9.683175797014961},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":42.353000829432986,\"upper_bound\":90.98259322286917},\"point_estimate\":60.4964473923512,\"standard_error\":12.417275561667736},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":40185.642111165536,\"upper_bound\":40212.87528863189},\"point_estimate\":40198.35233621989,\"standard_error\":6.982383167621202},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":186.8237070282473,\"upper_bound\":388.9726008661178},\"point_estimate\":297.045322375589,\"standard_error\":51.8796429238427}}"
  },
  {
    "path": "docs/criterion/Clone/Rc_str_/500/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[25.0,50.0,75.0,100.0,125.0,150.0,175.0,200.0,225.0,250.0,275.0,300.0,325.0,350.0,375.0,400.0,425.0,450.0,475.0,500.0,525.0,550.0,575.0,600.0,625.0,650.0,675.0,700.0,725.0,750.0,775.0,800.0,825.0,850.0,875.0,900.0,925.0,950.0,975.0,1000.0,1025.0,1050.0,1075.0,1100.0,1125.0,1150.0,1175.0,1200.0,1225.0,1250.0,1275.0,1300.0,1325.0,1350.0,1375.0,1400.0,1425.0,1450.0,1475.0,1500.0,1525.0,1550.0,1575.0,1600.0,1625.0,1650.0,1675.0,1700.0,1725.0,1750.0,1775.0,1800.0,1825.0,1850.0,1875.0,1900.0,1925.0,1950.0,1975.0,2000.0,2025.0,2050.0,2075.0,2100.0,2125.0,2150.0,2175.0,2200.0,2225.0,2250.0,2275.0,2300.0,2325.0,2350.0,2375.0,2400.0,2425.0,2450.0,2475.0,2500.0],\"times\":[1010752.0,2022084.0,3011668.0,4120333.0,5228876.0,6184377.0,7122125.0,8127582.0,9131084.0,10099125.0,11353334.0,12064917.0,13146709.0,14055874.0,15166250.0,16172334.0,17207541.0,18391957.0,19703084.0,20443667.0,21152541.0,22103833.0,23115583.0,24115414.0,25167083.0,26102081.0,27429083.0,28310166.0,29108417.0,30114124.0,31135501.0,32240875.0,33194002.0,34181917.0,35314874.0,36166459.0,37229625.0,38193250.0,39235959.0,40243584.0,41325418.0,42283042.0,43140374.0,44199958.0,45360459.0,46275125.0,47231792.0,48221250.0,49239375.0,50242040.0,51317416.0,52255668.0,53212042.0,54317918.0,55258001.0,56218708.0,57245375.0,58318917.0,59227710.0,60331751.0,61250917.0,62250916.0,63285041.0,64267669.0,65284002.0,66258459.0,67282416.0,68214793.0,69232543.0,70233375.0,71324212.0,72495084.0,73690251.0,74265249.0,75353209.0,76296999.0,77506333.0,78352917.0,79376959.0,80311333.0,81309957.0,82280332.0,83291623.0,84335335.0,85453543.0,86323834.0,87399459.0,88384084.0,89356707.0,90401249.0,91394209.0,92342041.0,93696960.0,94393000.0,95468833.0,96416960.0,97434832.0,98692750.0,99457167.0,100616082.0]}"
  },
  {
    "path": "docs/criterion/Clone/Rc_str_/500/new/tukey.json",
    "content": "[39787.66491605575,39977.11219119844,40482.30492491227,40671.75220005496]"
  },
  {
    "path": "docs/criterion/Clone/Rc_str_/500/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/Rc&lt;str&gt;/500 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/Rc&lt;str&gt;/500</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">40.186 µs</td>\n                                <td>40.198 µs</td>\n                                <td class=\"ci-bound\">40.213 µs</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.9993929</td>\n                                <td>0.9994066</td>\n                                <td class=\"ci-bound\">0.9993887</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">40.256 µs</td>\n                                <td>40.310 µs</td>\n                                <td class=\"ci-bound\">40.372 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">186.82 ns</td>\n                                <td>297.05 ns</td>\n                                <td class=\"ci-bound\">388.97 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">40.184 µs</td>\n                                <td>40.195 µs</td>\n                                <td class=\"ci-bound\">40.220 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">42.353 ns</td>\n                                <td>60.496 ns</td>\n                                <td class=\"ci-bound\">90.983 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−0.0615%</td>\n                            <td>+0.1159%</td>\n                            <td class=\"ci-bound\">+0.3143%</td>\n                            <td>(p = 0.19 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Clone/Rc_str_/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/Rc&lt;str&gt; Summary - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/Rc&lt;str&gt;</h2>\n        <h3>Violin Plot</h3>\n        <a href=\"violin.svg\">\n            <img src=\"violin.svg\" alt=\"Violin Plot\" />\n        </a>\n        <p>This chart shows the relationship between function/parameter and iteration time. The thickness of the shaded\n            region indicates the probability that a measurement of the given function/parameter would take a particular\n            length of time.</p>\n        <h3>Line Chart</h3>\n        <img src=\"lines.svg\" alt=\"Line Chart\" />\n        <p>This chart shows the mean measured time for each function as the input (or the size of the input) increases.</p>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/Rc_str_/0/report/index.html\">\n                <h4>Clone/Rc&lt;str&gt;/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/Rc_str_/0/report/pdf.svg\">\n                                <img src=\"../../../Clone/Rc_str_/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/Rc_str_/0/report/regression.svg\">\n                                <img src=\"../../../Clone/Rc_str_/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/Rc_str_/10/report/index.html\">\n                <h4>Clone/Rc&lt;str&gt;/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/Rc_str_/10/report/pdf.svg\">\n                                <img src=\"../../../Clone/Rc_str_/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/Rc_str_/10/report/regression.svg\">\n                                <img src=\"../../../Clone/Rc_str_/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/Rc_str_/20/report/index.html\">\n                <h4>Clone/Rc&lt;str&gt;/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/Rc_str_/20/report/pdf.svg\">\n                                <img src=\"../../../Clone/Rc_str_/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/Rc_str_/20/report/regression.svg\">\n                                <img src=\"../../../Clone/Rc_str_/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/Rc_str_/100/report/index.html\">\n                <h4>Clone/Rc&lt;str&gt;/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/Rc_str_/100/report/pdf.svg\">\n                                <img src=\"../../../Clone/Rc_str_/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/Rc_str_/100/report/regression.svg\">\n                                <img src=\"../../../Clone/Rc_str_/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/Rc_str_/500/report/index.html\">\n                <h4>Clone/Rc&lt;str&gt;/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/Rc_str_/500/report/pdf.svg\">\n                                <img src=\"../../../Clone/Rc_str_/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/Rc_str_/500/report/regression.svg\">\n                                <img src=\"../../../Clone/Rc_str_/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Clone/String/0/base/benchmark.json",
    "content": "{\"group_id\":\"Clone\",\"function_id\":\"String\",\"value_str\":\"0\",\"throughput\":null,\"full_id\":\"Clone/String/0\",\"directory_name\":\"Clone/String/0\",\"title\":\"Clone/String/0\"}"
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    "path": "docs/criterion/Clone/String/0/base/tukey.json",
    "content": "[30621.18593811322,30862.483710569562,31505.944437119804,31747.242209576143]"
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  {
    "path": "docs/criterion/Clone/String/0/new/benchmark.json",
    "content": "{\"group_id\":\"Clone\",\"function_id\":\"String\",\"value_str\":\"0\",\"throughput\":null,\"full_id\":\"Clone/String/0\",\"directory_name\":\"Clone/String/0\",\"title\":\"Clone/String/0\"}"
  },
  {
    "path": "docs/criterion/Clone/String/0/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":31226.361690504626,\"upper_bound\":31355.94216655644},\"point_estimate\":31286.886954971043,\"standard_error\":33.16325417261468},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":31126.42731938353,\"upper_bound\":31179.6875},\"point_estimate\":31148.610189900104,\"standard_error\":13.106344616747142},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":64.96518140171722,\"upper_bound\":127.95011515030961},\"point_estimate\":87.1541989531453,\"standard_error\":16.887861117267846},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":31198.47985165775,\"upper_bound\":31357.66655619764},\"point_estimate\":31273.263887985813,\"standard_error\":40.67805156985313},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":238.41599642970024,\"upper_bound\":418.9364415105593},\"point_estimate\":332.58416765223916,\"standard_error\":46.34735727306902}}"
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    "path": "docs/criterion/Clone/String/0/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[32.0,64.0,96.0,128.0,160.0,192.0,224.0,256.0,288.0,320.0,352.0,384.0,416.0,448.0,480.0,512.0,544.0,576.0,608.0,640.0,672.0,704.0,736.0,768.0,800.0,832.0,864.0,896.0,928.0,960.0,992.0,1024.0,1056.0,1088.0,1120.0,1152.0,1184.0,1216.0,1248.0,1280.0,1312.0,1344.0,1376.0,1408.0,1440.0,1472.0,1504.0,1536.0,1568.0,1600.0,1632.0,1664.0,1696.0,1728.0,1760.0,1792.0,1824.0,1856.0,1888.0,1920.0,1952.0,1984.0,2016.0,2048.0,2080.0,2112.0,2144.0,2176.0,2208.0,2240.0,2272.0,2304.0,2336.0,2368.0,2400.0,2432.0,2464.0,2496.0,2528.0,2560.0,2592.0,2624.0,2656.0,2688.0,2720.0,2752.0,2784.0,2816.0,2848.0,2880.0,2912.0,2944.0,2976.0,3008.0,3040.0,3072.0,3104.0,3136.0,3168.0,3200.0],\"times\":[998458.0,1986626.0,2994957.0,4201290.0,5213333.0,6080083.0,7039540.0,8102290.0,9072626.0,10082751.0,10953458.0,12256790.0,13011375.0,13972750.0,15098000.0,15992333.0,16951084.0,17973791.0,18957250.0,19888044.0,20944918.0,21934083.0,22871628.0,23939707.0,24861832.0,25877250.0,26895043.0,27889584.0,28865623.0,29991290.0,30838499.0,31906625.0,32999250.0,33796584.0,35741000.0,35919250.0,36840251.0,37813209.0,38899460.0,39867500.0,40769208.0,41782872.0,42744542.0,43870456.0,45685210.0,45761586.0,46922043.0,47826416.0,48771418.0,49917708.0,50713959.0,52038125.0,52717750.0,53917874.0,54692999.0,55762000.0,56796333.0,57691582.0,58725542.0,59749587.0,60789375.0,61688666.0,62839710.0,63889376.0,64736042.0,65757793.0,66624418.0,67662918.0,68582792.0,69998418.0,70758082.0,72637500.0,75052916.0,75869625.0,75901082.0,75694377.0,77622751.0,79381086.0,80797168.0,80286212.0,82705000.0,81729208.0,82822624.0,84227957.0,86783461.0,85672251.0,86600207.0,87552832.0,91137917.0,90034248.0,90601584.0,91450542.0,92516791.0,93700459.0,94477083.0,95553958.0,96457460.0,97561792.0,98562418.0,99571250.0]}"
  },
  {
    "path": "docs/criterion/Clone/String/0/new/tukey.json",
    "content": "[30621.18593811322,30862.483710569562,31505.944437119804,31747.242209576143]"
  },
  {
    "path": "docs/criterion/Clone/String/0/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/String/0 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/String/0</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">31.198 µs</td>\n                                <td>31.273 µs</td>\n                                <td class=\"ci-bound\">31.358 µs</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.9864623</td>\n                                <td>0.9872468</td>\n                                <td class=\"ci-bound\">0.9862477</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">31.226 µs</td>\n                                <td>31.287 µs</td>\n                                <td class=\"ci-bound\">31.356 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">238.42 ns</td>\n                                <td>332.58 ns</td>\n                                <td class=\"ci-bound\">418.94 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">31.126 µs</td>\n                                <td>31.149 µs</td>\n                                <td class=\"ci-bound\">31.180 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">64.965 ns</td>\n                                <td>87.154 ns</td>\n                                <td class=\"ci-bound\">127.95 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−2.3872%</td>\n                            <td>−0.7947%</td>\n                            <td class=\"ci-bound\">+0.1628%</td>\n                            <td>(p = 0.33 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Clone/String/10/base/benchmark.json",
    "content": "{\"group_id\":\"Clone\",\"function_id\":\"String\",\"value_str\":\"10\",\"throughput\":null,\"full_id\":\"Clone/String/10\",\"directory_name\":\"Clone/String/10\",\"title\":\"Clone/String/10\"}"
  },
  {
    "path": "docs/criterion/Clone/String/10/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":224599.0251581536,\"upper_bound\":225562.2241984213},\"point_estimate\":225044.92739067905,\"standard_error\":245.78850947590908},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":223904.95952380952,\"upper_bound\":224389.8698245614},\"point_estimate\":224041.31748768472,\"standard_error\":128.0563675459019},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":454.20420572308115,\"upper_bound\":1036.1075786054153},\"point_estimate\":679.33939974698,\"standard_error\":143.27658915691995},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":224630.34274401466,\"upper_bound\":226564.32117693944},\"point_estimate\":225525.1927755283,\"standard_error\":499.03652105923425},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":1567.3478172181035,\"upper_bound\":3228.7843176363604},\"point_estimate\":2471.2470097074665,\"standard_error\":424.39108953205124}}"
  },
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  {
    "path": "docs/criterion/Clone/String/10/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/String/10 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/String/10</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">224.63 µs</td>\n                                <td>225.53 µs</td>\n                                <td class=\"ci-bound\">226.56 µs</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.9682703</td>\n                                <td>0.9703713</td>\n                                <td class=\"ci-bound\">0.9675403</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">224.60 µs</td>\n                                <td>225.04 µs</td>\n                                <td class=\"ci-bound\">225.56 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">1.5673 µs</td>\n                                <td>2.4712 µs</td>\n                                <td class=\"ci-bound\">3.2288 µs</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">223.90 µs</td>\n                                <td>224.04 µs</td>\n                                <td class=\"ci-bound\">224.39 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">454.20 ns</td>\n                                <td>679.34 ns</td>\n                                <td class=\"ci-bound\">1.0361 µs</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−0.0718%</td>\n                            <td>+0.2338%</td>\n                            <td class=\"ci-bound\">+0.5405%</td>\n                            <td>(p = 0.14 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
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    "path": "docs/criterion/Clone/String/100/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/String/100 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/String/100</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">222.56 µs</td>\n                                <td>222.80 µs</td>\n                                <td class=\"ci-bound\">223.06 µs</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.9973349</td>\n                                <td>0.9974904</td>\n                                <td class=\"ci-bound\">0.9973060</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">222.67 µs</td>\n                                <td>222.91 µs</td>\n                                <td class=\"ci-bound\">223.16 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">923.62 ns</td>\n                                <td>1.2548 µs</td>\n                                <td class=\"ci-bound\">1.5963 µs</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">222.42 µs</td>\n                                <td>222.55 µs</td>\n                                <td class=\"ci-bound\">222.68 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">484.12 ns</td>\n                                <td>692.76 ns</td>\n                                <td class=\"ci-bound\">951.34 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−1.4168%</td>\n                            <td>−0.9869%</td>\n                            <td class=\"ci-bound\">−0.6102%</td>\n                            <td>(p = 0.00 &lt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                Change within noise threshold.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
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    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/String/20 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/String/20</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">245.84 µs</td>\n                                <td>246.10 µs</td>\n                                <td class=\"ci-bound\">246.42 µs</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.9970368</td>\n                                <td>0.9971949</td>\n                                <td class=\"ci-bound\">0.9969638</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">246.17 µs</td>\n                                <td>246.45 µs</td>\n                                <td class=\"ci-bound\">246.75 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">1.1650 µs</td>\n                                <td>1.5186 µs</td>\n                                <td class=\"ci-bound\">1.8247 µs</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">245.76 µs</td>\n                                <td>245.85 µs</td>\n                                <td class=\"ci-bound\">246.01 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">468.10 ns</td>\n                                <td>616.83 ns</td>\n                                <td class=\"ci-bound\">804.59 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−1.4973%</td>\n                            <td>−0.6068%</td>\n                            <td class=\"ci-bound\">−0.0612%</td>\n                            <td>(p = 0.09 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
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    "path": "docs/criterion/Clone/String/500/base/benchmark.json",
    "content": "{\"group_id\":\"Clone\",\"function_id\":\"String\",\"value_str\":\"500\",\"throughput\":null,\"full_id\":\"Clone/String/500\",\"directory_name\":\"Clone/String/500\",\"title\":\"Clone/String/500\"}"
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    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":492029.19478467095,\"upper_bound\":493935.8803314969},\"point_estimate\":492982.53776051715,\"standard_error\":485.2024297346945},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":492331.9871794872,\"upper_bound\":493967.6282932417},\"point_estimate\":493009.89145819616,\"standard_error\":439.070350969204},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2574.6178092913715,\"upper_bound\":4133.828078644789},\"point_estimate\":3554.5233141004783,\"standard_error\":397.5925692347991},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":492285.1508775134,\"upper_bound\":493424.7467390829},\"point_estimate\":492852.98927589774,\"standard_error\":290.7127701511807},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3686.6243521684496,\"upper_bound\":6013.955134236364},\"point_estimate\":4881.314319009194,\"standard_error\":595.0644536782141}}"
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    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[2.0,4.0,6.0,8.0,10.0,12.0,14.0,16.0,18.0,20.0,22.0,24.0,26.0,28.0,30.0,32.0,34.0,36.0,38.0,40.0,42.0,44.0,46.0,48.0,50.0,52.0,54.0,56.0,58.0,60.0,62.0,64.0,66.0,68.0,70.0,72.0,74.0,76.0,78.0,80.0,82.0,84.0,86.0,88.0,90.0,92.0,94.0,96.0,98.0,100.0,102.0,104.0,106.0,108.0,110.0,112.0,114.0,116.0,118.0,120.0,122.0,124.0,126.0,128.0,130.0,132.0,134.0,136.0,138.0,140.0,142.0,144.0,146.0,148.0,150.0,152.0,154.0,156.0,158.0,160.0,162.0,164.0,166.0,168.0,170.0,172.0,174.0,176.0,178.0,180.0,182.0,184.0,186.0,188.0,190.0,192.0,194.0,196.0,198.0,200.0],\"times\":[980208.0,1936915.0,2906044.0,4110416.0,5001206.0,5764624.0,6794999.0,7648332.0,8623125.0,9589540.0,10989583.0,11944791.0,12838293.0,13845085.0,15049543.0,15956208.0,16927916.0,17845166.0,18919792.0,19841457.0,20826457.0,21922043.0,22655375.0,23538082.0,24799626.0,25690999.0,26487584.0,27491500.0,28947710.0,29707000.0,30477916.0,31461625.0,32684583.0,33706584.0,34591918.0,35756083.0,36390292.0,37224581.0,38273959.0,39809250.0,40318832.0,41709000.0,43430209.0,43474290.0,44314917.0,44727876.0,46274625.0,47644377.0,47951668.0,48907669.0,50015583.0,51490249.0,52368292.0,52949960.0,53976792.0,54952958.0,56548500.0,57628458.0,58123749.0,59302668.0,59690374.0,61134374.0,62232541.0,63082041.0,63501127.0,65094709.0,66396999.0,67380710.0,68536211.0,69087833.0,70185083.0,71044583.0,72116707.0,72929334.0,73709083.0,75334168.0,75766916.0,76803790.0,77504999.0,78078333.0,79684541.0,80738625.0,81586124.0,82906333.0,84486169.0,84413210.0,85599583.0,86674252.0,87398624.0,89087917.0,89199667.0,90487583.0,91870042.0,91820625.0,93744001.0,94625332.0,95841083.0,96628125.0,98179209.0,98538499.0]}"
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    "content": "[476113.81099529384,483434.59791308036,502956.696360511,510277.48327829747]"
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    "path": "docs/criterion/Clone/String/500/change/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.0045183289330360385,\"upper_bound\":0.00010957853215820312},\"point_estimate\":-0.0020682768773140348,\"standard_error\":0.0011820415552581522},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.0037611968216539893,\"upper_bound\":0.0009416123956522693},\"point_estimate\":-0.001574804970585597,\"standard_error\":0.0011946792798350168}}"
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    "content": "{\"group_id\":\"Clone\",\"function_id\":\"String\",\"value_str\":\"500\",\"throughput\":null,\"full_id\":\"Clone/String/500\",\"directory_name\":\"Clone/String/500\",\"title\":\"Clone/String/500\"}"
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    "path": "docs/criterion/Clone/String/500/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":492029.19478467095,\"upper_bound\":493935.8803314969},\"point_estimate\":492982.53776051715,\"standard_error\":485.2024297346945},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":492331.9871794872,\"upper_bound\":493967.6282932417},\"point_estimate\":493009.89145819616,\"standard_error\":439.070350969204},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2574.6178092913715,\"upper_bound\":4133.828078644789},\"point_estimate\":3554.5233141004783,\"standard_error\":397.5925692347991},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":492285.1508775134,\"upper_bound\":493424.7467390829},\"point_estimate\":492852.98927589774,\"standard_error\":290.7127701511807},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3686.6243521684496,\"upper_bound\":6013.955134236364},\"point_estimate\":4881.314319009194,\"standard_error\":595.0644536782141}}"
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    "path": "docs/criterion/Clone/String/500/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[2.0,4.0,6.0,8.0,10.0,12.0,14.0,16.0,18.0,20.0,22.0,24.0,26.0,28.0,30.0,32.0,34.0,36.0,38.0,40.0,42.0,44.0,46.0,48.0,50.0,52.0,54.0,56.0,58.0,60.0,62.0,64.0,66.0,68.0,70.0,72.0,74.0,76.0,78.0,80.0,82.0,84.0,86.0,88.0,90.0,92.0,94.0,96.0,98.0,100.0,102.0,104.0,106.0,108.0,110.0,112.0,114.0,116.0,118.0,120.0,122.0,124.0,126.0,128.0,130.0,132.0,134.0,136.0,138.0,140.0,142.0,144.0,146.0,148.0,150.0,152.0,154.0,156.0,158.0,160.0,162.0,164.0,166.0,168.0,170.0,172.0,174.0,176.0,178.0,180.0,182.0,184.0,186.0,188.0,190.0,192.0,194.0,196.0,198.0,200.0],\"times\":[980208.0,1936915.0,2906044.0,4110416.0,5001206.0,5764624.0,6794999.0,7648332.0,8623125.0,9589540.0,10989583.0,11944791.0,12838293.0,13845085.0,15049543.0,15956208.0,16927916.0,17845166.0,18919792.0,19841457.0,20826457.0,21922043.0,22655375.0,23538082.0,24799626.0,25690999.0,26487584.0,27491500.0,28947710.0,29707000.0,30477916.0,31461625.0,32684583.0,33706584.0,34591918.0,35756083.0,36390292.0,37224581.0,38273959.0,39809250.0,40318832.0,41709000.0,43430209.0,43474290.0,44314917.0,44727876.0,46274625.0,47644377.0,47951668.0,48907669.0,50015583.0,51490249.0,52368292.0,52949960.0,53976792.0,54952958.0,56548500.0,57628458.0,58123749.0,59302668.0,59690374.0,61134374.0,62232541.0,63082041.0,63501127.0,65094709.0,66396999.0,67380710.0,68536211.0,69087833.0,70185083.0,71044583.0,72116707.0,72929334.0,73709083.0,75334168.0,75766916.0,76803790.0,77504999.0,78078333.0,79684541.0,80738625.0,81586124.0,82906333.0,84486169.0,84413210.0,85599583.0,86674252.0,87398624.0,89087917.0,89199667.0,90487583.0,91870042.0,91820625.0,93744001.0,94625332.0,95841083.0,96628125.0,98179209.0,98538499.0]}"
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    "content": "[476113.81099529384,483434.59791308036,502956.696360511,510277.48327829747]"
  },
  {
    "path": "docs/criterion/Clone/String/500/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/String/500 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/String/500</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">492.29 µs</td>\n                                <td>492.85 µs</td>\n                                <td class=\"ci-bound\">493.42 µs</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.9962949</td>\n                                <td>0.9964772</td>\n                                <td class=\"ci-bound\">0.9962924</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">492.03 µs</td>\n                                <td>492.98 µs</td>\n                                <td class=\"ci-bound\">493.94 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">3.6866 µs</td>\n                                <td>4.8813 µs</td>\n                                <td class=\"ci-bound\">6.0140 µs</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">492.33 µs</td>\n                                <td>493.01 µs</td>\n                                <td class=\"ci-bound\">493.97 µs</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">2.5746 µs</td>\n                                <td>3.5545 µs</td>\n                                <td class=\"ci-bound\">4.1338 µs</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−0.4518%</td>\n                            <td>−0.2068%</td>\n                            <td class=\"ci-bound\">+0.0110%</td>\n                            <td>(p = 0.09 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Clone/String/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone/String Summary - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone/String</h2>\n        <h3>Violin Plot</h3>\n        <a href=\"violin.svg\">\n            <img src=\"violin.svg\" alt=\"Violin Plot\" />\n        </a>\n        <p>This chart shows the relationship between function/parameter and iteration time. The thickness of the shaded\n            region indicates the probability that a measurement of the given function/parameter would take a particular\n            length of time.</p>\n        <h3>Line Chart</h3>\n        <img src=\"lines.svg\" alt=\"Line Chart\" />\n        <p>This chart shows the mean measured time for each function as the input (or the size of the input) increases.</p>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/String/0/report/index.html\">\n                <h4>Clone/String/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/String/0/report/pdf.svg\">\n                                <img src=\"../../../Clone/String/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/String/0/report/regression.svg\">\n                                <img src=\"../../../Clone/String/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/String/10/report/index.html\">\n                <h4>Clone/String/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/String/10/report/pdf.svg\">\n                                <img src=\"../../../Clone/String/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/String/10/report/regression.svg\">\n                                <img src=\"../../../Clone/String/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/String/20/report/index.html\">\n                <h4>Clone/String/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/String/20/report/pdf.svg\">\n                                <img src=\"../../../Clone/String/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/String/20/report/regression.svg\">\n                                <img src=\"../../../Clone/String/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/String/100/report/index.html\">\n                <h4>Clone/String/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/String/100/report/pdf.svg\">\n                                <img src=\"../../../Clone/String/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/String/100/report/regression.svg\">\n                                <img src=\"../../../Clone/String/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Clone/String/500/report/index.html\">\n                <h4>Clone/String/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Clone/String/500/report/pdf.svg\">\n                                <img src=\"../../../Clone/String/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Clone/String/500/report/regression.svg\">\n                                <img src=\"../../../Clone/String/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Clone/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Clone Summary - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Clone</h2>\n        <h3>Violin Plot</h3>\n        <a href=\"violin.svg\">\n            <img src=\"violin.svg\" alt=\"Violin Plot\" />\n        </a>\n        <p>This chart shows the relationship between function/parameter and iteration time. The thickness of the shaded\n            region indicates the probability that a measurement of the given function/parameter would take a particular\n            length of time.</p>\n        <h3>Line Chart</h3>\n        <img src=\"lines.svg\" alt=\"Line Chart\" />\n        <p>This chart shows the mean measured time for each function as the input (or the size of the input) increases.</p>\n        <section class=\"plots\">\n            <a href=\"../../Clone/Arc_str_/0/report/index.html\">\n                <h4>Clone/Arc&lt;str&gt;/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Clone/Arc_str_/0/report/pdf.svg\">\n                                <img src=\"../../Clone/Arc_str_/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Clone/Arc_str_/0/report/regression.svg\">\n                                <img src=\"../../Clone/Arc_str_/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Clone/Arc_str_/10/report/index.html\">\n                <h4>Clone/Arc&lt;str&gt;/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Clone/Arc_str_/10/report/pdf.svg\">\n                                <img src=\"../../Clone/Arc_str_/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Clone/Arc_str_/10/report/regression.svg\">\n                                <img src=\"../../Clone/Arc_str_/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Clone/Arc_str_/20/report/index.html\">\n                <h4>Clone/Arc&lt;str&gt;/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Clone/Arc_str_/20/report/pdf.svg\">\n                                <img src=\"../../Clone/Arc_str_/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Clone/Arc_str_/20/report/regression.svg\">\n                                <img src=\"../../Clone/Arc_str_/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Clone/Arc_str_/100/report/index.html\">\n                <h4>Clone/Arc&lt;str&gt;/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Clone/Arc_str_/100/report/pdf.svg\">\n                                <img src=\"../../Clone/Arc_str_/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Clone/Arc_str_/100/report/regression.svg\">\n                                <img src=\"../../Clone/Arc_str_/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Clone/Arc_str_/500/report/index.html\">\n                <h4>Clone/Arc&lt;str&gt;/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Clone/Arc_str_/500/report/pdf.svg\">\n                                <img src=\"../../Clone/Arc_str_/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Clone/Arc_str_/500/report/regression.svg\">\n                                <img src=\"../../Clone/Arc_str_/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Clone/FlexStr 0.10 (LocalStr - Boxed)/0/report/index.html\">\n                <h4>Clone/FlexStr 0.10 (LocalStr - Boxed)/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Clone/FlexStr 0.10 (LocalStr - Boxed)/0/report/pdf.svg\">\n                                <img src=\"../../Clone/FlexStr 0.10 (LocalStr - Boxed)/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Clone/FlexStr 0.10 (LocalStr - Boxed)/0/report/regression.svg\">\n                                <img src=\"../../Clone/FlexStr 0.10 (LocalStr - Boxed)/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Clone/FlexStr 0.10 (LocalStr - Boxed)/10/report/index.html\">\n                <h4>Clone/FlexStr 0.10 (LocalStr - Boxed)/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Clone/FlexStr 0.10 (LocalStr - Boxed)/10/report/pdf.svg\">\n                                <img src=\"../../Clone/FlexStr 0.10 (LocalStr - Boxed)/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Clone/FlexStr 0.10 (LocalStr - Boxed)/10/report/regression.svg\">\n                                <img src=\"../../Clone/FlexStr 0.10 (LocalStr - Boxed)/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Clone/FlexStr 0.10 (LocalStr - Boxed)/20/report/index.html\">\n                <h4>Clone/FlexStr 0.10 (LocalStr - Boxed)/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Clone/FlexStr 0.10 (LocalStr - Boxed)/20/report/pdf.svg\">\n                                <img src=\"../../Clone/FlexStr 0.10 (LocalStr - Boxed)/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Clone/FlexStr 0.10 (LocalStr - Boxed)/20/report/regression.svg\">\n                                <img src=\"../../Clone/FlexStr 0.10 (LocalStr - Boxed)/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Clone/FlexStr 0.10 (LocalStr - Boxed)/100/report/index.html\">\n                <h4>Clone/FlexStr 0.10 (LocalStr - Boxed)/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Clone/FlexStr 0.10 (LocalStr - Boxed)/100/report/pdf.svg\">\n                                <img src=\"../../Clone/FlexStr 0.10 (LocalStr - Boxed)/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Clone/FlexStr 0.10 (LocalStr - Boxed)/100/report/regression.svg\">\n                                <img src=\"../../Clone/FlexStr 0.10 (LocalStr - Boxed)/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Clone/FlexStr 0.10 (LocalStr - Boxed)/500/report/index.html\">\n                <h4>Clone/FlexStr 0.10 (LocalStr - Boxed)/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Clone/FlexStr 0.10 (LocalStr - Boxed)/500/report/pdf.svg\">\n                                <img src=\"../../Clone/FlexStr 0.10 (LocalStr - Boxed)/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Clone/FlexStr 0.10 (LocalStr - Boxed)/500/report/regression.svg\">\n                                <img src=\"../../Clone/FlexStr 0.10 (LocalStr - Boxed)/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Clone/FlexStr 0.10 (LocalStr - Optimized)/0/report/index.html\">\n                <h4>Clone/FlexStr 0.10 (LocalStr - Optimized)/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Clone/FlexStr 0.10 (LocalStr - Optimized)/0/report/pdf.svg\">\n                                <img src=\"../../Clone/FlexStr 0.10 (LocalStr - Optimized)/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Clone/FlexStr 0.10 (LocalStr - Optimized)/0/report/regression.svg\">\n                                <img src=\"../../Clone/FlexStr 0.10 (LocalStr - Optimized)/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Clone/FlexStr 0.10 (LocalStr - Optimized)/10/report/index.html\">\n                <h4>Clone/FlexStr 0.10 (LocalStr - Optimized)/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Clone/FlexStr 0.10 (LocalStr - Optimized)/10/report/pdf.svg\">\n                                <img src=\"../../Clone/FlexStr 0.10 (LocalStr - Optimized)/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Clone/FlexStr 0.10 (LocalStr - Optimized)/10/report/regression.svg\">\n                                <img src=\"../../Clone/FlexStr 0.10 (LocalStr - Optimized)/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Clone/FlexStr 0.10 (LocalStr - Optimized)/20/report/index.html\">\n                <h4>Clone/FlexStr 0.10 (LocalStr - Optimized)/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Clone/FlexStr 0.10 (LocalStr - Optimized)/20/report/pdf.svg\">\n                                <img src=\"../../Clone/FlexStr 0.10 (LocalStr - Optimized)/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Clone/FlexStr 0.10 (LocalStr - Optimized)/20/report/regression.svg\">\n                                <img src=\"../../Clone/FlexStr 0.10 (LocalStr - Optimized)/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Clone/FlexStr 0.10 (LocalStr - Optimized)/100/report/index.html\">\n                <h4>Clone/FlexStr 0.10 (LocalStr - Optimized)/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Clone/FlexStr 0.10 (LocalStr - Optimized)/100/report/pdf.svg\">\n                                <img src=\"../../Clone/FlexStr 0.10 (LocalStr - Optimized)/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Clone/FlexStr 0.10 (LocalStr - Optimized)/100/report/regression.svg\">\n                                <img src=\"../../Clone/FlexStr 0.10 (LocalStr - Optimized)/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Clone/FlexStr 0.10 (LocalStr - Optimized)/500/report/index.html\">\n                <h4>Clone/FlexStr 0.10 (LocalStr - Optimized)/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Clone/FlexStr 0.10 (LocalStr - Optimized)/500/report/pdf.svg\">\n                                <img src=\"../../Clone/FlexStr 0.10 (LocalStr - Optimized)/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Clone/FlexStr 0.10 (LocalStr - Optimized)/500/report/regression.svg\">\n                                <img src=\"../../Clone/FlexStr 0.10 (LocalStr - Optimized)/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Clone/FlexStr 0.10 (SharedStr - Boxed)/0/report/index.html\">\n                <h4>Clone/FlexStr 0.10 (SharedStr - Boxed)/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Clone/FlexStr 0.10 (SharedStr - Boxed)/0/report/pdf.svg\">\n                                <img src=\"../../Clone/FlexStr 0.10 (SharedStr - Boxed)/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Clone/FlexStr 0.10 (SharedStr - Boxed)/0/report/regression.svg\">\n                                <img src=\"../../Clone/FlexStr 0.10 (SharedStr - Boxed)/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Clone/FlexStr 0.10 (SharedStr - Boxed)/10/report/index.html\">\n                <h4>Clone/FlexStr 0.10 (SharedStr - Boxed)/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Clone/FlexStr 0.10 (SharedStr - Boxed)/10/report/pdf.svg\">\n                                <img src=\"../../Clone/FlexStr 0.10 (SharedStr - Boxed)/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Clone/FlexStr 0.10 (SharedStr - Boxed)/10/report/regression.svg\">\n                                <img src=\"../../Clone/FlexStr 0.10 (SharedStr - Boxed)/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Clone/FlexStr 0.10 (SharedStr - Boxed)/20/report/index.html\">\n                <h4>Clone/FlexStr 0.10 (SharedStr - Boxed)/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Clone/FlexStr 0.10 (SharedStr - Boxed)/20/report/pdf.svg\">\n                                <img src=\"../../Clone/FlexStr 0.10 (SharedStr - Boxed)/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Clone/FlexStr 0.10 (SharedStr - Boxed)/20/report/regression.svg\">\n                                <img src=\"../../Clone/FlexStr 0.10 (SharedStr - Boxed)/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Clone/FlexStr 0.10 (SharedStr - Boxed)/100/report/index.html\">\n                <h4>Clone/FlexStr 0.10 (SharedStr - Boxed)/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Clone/FlexStr 0.10 (SharedStr - Boxed)/100/report/pdf.svg\">\n                                <img src=\"../../Clone/FlexStr 0.10 (SharedStr - Boxed)/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Clone/FlexStr 0.10 (SharedStr - Boxed)/100/report/regression.svg\">\n                                <img src=\"../../Clone/FlexStr 0.10 (SharedStr - Boxed)/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Clone/FlexStr 0.10 (SharedStr - Boxed)/500/report/index.html\">\n                <h4>Clone/FlexStr 0.10 (SharedStr - Boxed)/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Clone/FlexStr 0.10 (SharedStr - Boxed)/500/report/pdf.svg\">\n                                <img src=\"../../Clone/FlexStr 0.10 (SharedStr - Boxed)/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Clone/FlexStr 0.10 (SharedStr - Boxed)/500/report/regression.svg\">\n                                <img src=\"../../Clone/FlexStr 0.10 (SharedStr - Boxed)/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Clone/FlexStr 0.10 (SharedStr - Optimized)/0/report/index.html\">\n                <h4>Clone/FlexStr 0.10 (SharedStr - Optimized)/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Clone/FlexStr 0.10 (SharedStr - Optimized)/0/report/pdf.svg\">\n                                <img src=\"../../Clone/FlexStr 0.10 (SharedStr - Optimized)/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Clone/FlexStr 0.10 (SharedStr - Optimized)/0/report/regression.svg\">\n                                <img src=\"../../Clone/FlexStr 0.10 (SharedStr - Optimized)/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Clone/FlexStr 0.10 (SharedStr - Optimized)/10/report/index.html\">\n                <h4>Clone/FlexStr 0.10 (SharedStr - Optimized)/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Clone/FlexStr 0.10 (SharedStr - Optimized)/10/report/pdf.svg\">\n                                <img src=\"../../Clone/FlexStr 0.10 (SharedStr - Optimized)/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Clone/FlexStr 0.10 (SharedStr - Optimized)/10/report/regression.svg\">\n                                <img src=\"../../Clone/FlexStr 0.10 (SharedStr - Optimized)/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Clone/FlexStr 0.10 (SharedStr - Optimized)/20/report/index.html\">\n                <h4>Clone/FlexStr 0.10 (SharedStr - Optimized)/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Clone/FlexStr 0.10 (SharedStr - Optimized)/20/report/pdf.svg\">\n                                <img src=\"../../Clone/FlexStr 0.10 (SharedStr - Optimized)/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Clone/FlexStr 0.10 (SharedStr - Optimized)/20/report/regression.svg\">\n                                <img src=\"../../Clone/FlexStr 0.10 (SharedStr - Optimized)/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Clone/FlexStr 0.10 (SharedStr - Optimized)/100/report/index.html\">\n                <h4>Clone/FlexStr 0.10 (SharedStr - Optimized)/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Clone/FlexStr 0.10 (SharedStr - Optimized)/100/report/pdf.svg\">\n                                <img src=\"../../Clone/FlexStr 0.10 (SharedStr - Optimized)/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Clone/FlexStr 0.10 (SharedStr - Optimized)/100/report/regression.svg\">\n                                <img src=\"../../Clone/FlexStr 0.10 (SharedStr - Optimized)/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Clone/FlexStr 0.10 (SharedStr - Optimized)/500/report/index.html\">\n                <h4>Clone/FlexStr 0.10 (SharedStr - Optimized)/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Clone/FlexStr 0.10 (SharedStr - Optimized)/500/report/pdf.svg\">\n                                <img src=\"../../Clone/FlexStr 0.10 (SharedStr - Optimized)/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Clone/FlexStr 0.10 (SharedStr - Optimized)/500/report/regression.svg\">\n                                <img src=\"../../Clone/FlexStr 0.10 (SharedStr - Optimized)/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Clone/FlexStr 0.9 (LocalStr)/0/report/index.html\">\n                <h4>Clone/FlexStr 0.9 (LocalStr)/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Clone/FlexStr 0.9 (LocalStr)/0/report/pdf.svg\">\n                                <img src=\"../../Clone/FlexStr 0.9 (LocalStr)/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Clone/FlexStr 0.9 (LocalStr)/0/report/regression.svg\">\n                                <img src=\"../../Clone/FlexStr 0.9 (LocalStr)/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Clone/FlexStr 0.9 (LocalStr)/10/report/index.html\">\n                <h4>Clone/FlexStr 0.9 (LocalStr)/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Clone/FlexStr 0.9 (LocalStr)/10/report/pdf.svg\">\n                                <img src=\"../../Clone/FlexStr 0.9 (LocalStr)/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Clone/FlexStr 0.9 (LocalStr)/10/report/regression.svg\">\n                                <img src=\"../../Clone/FlexStr 0.9 (LocalStr)/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Clone/FlexStr 0.9 (LocalStr)/20/report/index.html\">\n                <h4>Clone/FlexStr 0.9 (LocalStr)/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Clone/FlexStr 0.9 (LocalStr)/20/report/pdf.svg\">\n                                <img src=\"../../Clone/FlexStr 0.9 (LocalStr)/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Clone/FlexStr 0.9 (LocalStr)/20/report/regression.svg\">\n                                <img src=\"../../Clone/FlexStr 0.9 (LocalStr)/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Clone/FlexStr 0.9 (LocalStr)/100/report/index.html\">\n                <h4>Clone/FlexStr 0.9 (LocalStr)/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Clone/FlexStr 0.9 (LocalStr)/100/report/pdf.svg\">\n                                <img src=\"../../Clone/FlexStr 0.9 (LocalStr)/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Clone/FlexStr 0.9 (LocalStr)/100/report/regression.svg\">\n                                <img src=\"../../Clone/FlexStr 0.9 (LocalStr)/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Clone/FlexStr 0.9 (LocalStr)/500/report/index.html\">\n                <h4>Clone/FlexStr 0.9 (LocalStr)/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Clone/FlexStr 0.9 (LocalStr)/500/report/pdf.svg\">\n                                <img src=\"../../Clone/FlexStr 0.9 (LocalStr)/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Clone/FlexStr 0.9 (LocalStr)/500/report/regression.svg\">\n                                <img src=\"../../Clone/FlexStr 0.9 (LocalStr)/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Clone/FlexStr 0.9 (SharedStr)/0/report/index.html\">\n                <h4>Clone/FlexStr 0.9 (SharedStr)/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Clone/FlexStr 0.9 (SharedStr)/0/report/pdf.svg\">\n                                <img src=\"../../Clone/FlexStr 0.9 (SharedStr)/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Clone/FlexStr 0.9 (SharedStr)/0/report/regression.svg\">\n                                <img src=\"../../Clone/FlexStr 0.9 (SharedStr)/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Clone/FlexStr 0.9 (SharedStr)/10/report/index.html\">\n                <h4>Clone/FlexStr 0.9 (SharedStr)/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Clone/FlexStr 0.9 (SharedStr)/10/report/pdf.svg\">\n                                <img src=\"../../Clone/FlexStr 0.9 (SharedStr)/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Clone/FlexStr 0.9 (SharedStr)/10/report/regression.svg\">\n                                <img src=\"../../Clone/FlexStr 0.9 (SharedStr)/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Clone/FlexStr 0.9 (SharedStr)/20/report/index.html\">\n                <h4>Clone/FlexStr 0.9 (SharedStr)/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Clone/FlexStr 0.9 (SharedStr)/20/report/pdf.svg\">\n                                <img src=\"../../Clone/FlexStr 0.9 (SharedStr)/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Clone/FlexStr 0.9 (SharedStr)/20/report/regression.svg\">\n                                <img src=\"../../Clone/FlexStr 0.9 (SharedStr)/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Clone/FlexStr 0.9 (SharedStr)/100/report/index.html\">\n                <h4>Clone/FlexStr 0.9 (SharedStr)/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Clone/FlexStr 0.9 (SharedStr)/100/report/pdf.svg\">\n                                <img src=\"../../Clone/FlexStr 0.9 (SharedStr)/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Clone/FlexStr 0.9 (SharedStr)/100/report/regression.svg\">\n                                <img src=\"../../Clone/FlexStr 0.9 (SharedStr)/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Clone/FlexStr 0.9 (SharedStr)/500/report/index.html\">\n                <h4>Clone/FlexStr 0.9 (SharedStr)/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Clone/FlexStr 0.9 (SharedStr)/500/report/pdf.svg\">\n                                <img src=\"../../Clone/FlexStr 0.9 (SharedStr)/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Clone/FlexStr 0.9 (SharedStr)/500/report/regression.svg\">\n                                <img src=\"../../Clone/FlexStr 0.9 (SharedStr)/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Clone/InlineFlexStr 0.1 (InlineStr)/0/report/index.html\">\n                <h4>Clone/InlineFlexStr 0.1 (InlineStr)/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Clone/InlineFlexStr 0.1 (InlineStr)/0/report/pdf.svg\">\n                                <img src=\"../../Clone/InlineFlexStr 0.1 (InlineStr)/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Clone/InlineFlexStr 0.1 (InlineStr)/0/report/regression.svg\">\n                                <img src=\"../../Clone/InlineFlexStr 0.1 (InlineStr)/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Clone/InlineFlexStr 0.1 (InlineStr)/10/report/index.html\">\n                <h4>Clone/InlineFlexStr 0.1 (InlineStr)/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Clone/InlineFlexStr 0.1 (InlineStr)/10/report/pdf.svg\">\n                                <img src=\"../../Clone/InlineFlexStr 0.1 (InlineStr)/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Clone/InlineFlexStr 0.1 (InlineStr)/10/report/regression.svg\">\n                                <img src=\"../../Clone/InlineFlexStr 0.1 (InlineStr)/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Clone/InlineFlexStr 0.1 (InlineStr)/20/report/index.html\">\n                <h4>Clone/InlineFlexStr 0.1 (InlineStr)/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Clone/InlineFlexStr 0.1 (InlineStr)/20/report/pdf.svg\">\n                                <img src=\"../../Clone/InlineFlexStr 0.1 (InlineStr)/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Clone/InlineFlexStr 0.1 (InlineStr)/20/report/regression.svg\">\n                                <img src=\"../../Clone/InlineFlexStr 0.1 (InlineStr)/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Clone/InlineFlexStr 0.1 (InlineStr)/100/report/index.html\">\n                <h4>Clone/InlineFlexStr 0.1 (InlineStr)/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Clone/InlineFlexStr 0.1 (InlineStr)/100/report/pdf.svg\">\n                                <img src=\"../../Clone/InlineFlexStr 0.1 (InlineStr)/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Clone/InlineFlexStr 0.1 (InlineStr)/100/report/regression.svg\">\n                                <img src=\"../../Clone/InlineFlexStr 0.1 (InlineStr)/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Clone/InlineFlexStr 0.1 (InlineStr)/500/report/index.html\">\n                <h4>Clone/InlineFlexStr 0.1 (InlineStr)/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Clone/InlineFlexStr 0.1 (InlineStr)/500/report/pdf.svg\">\n                                <img src=\"../../Clone/InlineFlexStr 0.1 (InlineStr)/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Clone/InlineFlexStr 0.1 (InlineStr)/500/report/regression.svg\">\n                                <img src=\"../../Clone/InlineFlexStr 0.1 (InlineStr)/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Clone/Rc_str_/0/report/index.html\">\n                <h4>Clone/Rc&lt;str&gt;/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Clone/Rc_str_/0/report/pdf.svg\">\n                                <img src=\"../../Clone/Rc_str_/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Clone/Rc_str_/0/report/regression.svg\">\n                                <img src=\"../../Clone/Rc_str_/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Clone/Rc_str_/10/report/index.html\">\n                <h4>Clone/Rc&lt;str&gt;/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Clone/Rc_str_/10/report/pdf.svg\">\n                                <img src=\"../../Clone/Rc_str_/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Clone/Rc_str_/10/report/regression.svg\">\n                                <img src=\"../../Clone/Rc_str_/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Clone/Rc_str_/20/report/index.html\">\n                <h4>Clone/Rc&lt;str&gt;/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Clone/Rc_str_/20/report/pdf.svg\">\n                                <img src=\"../../Clone/Rc_str_/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Clone/Rc_str_/20/report/regression.svg\">\n                                <img src=\"../../Clone/Rc_str_/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Clone/Rc_str_/100/report/index.html\">\n                <h4>Clone/Rc&lt;str&gt;/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Clone/Rc_str_/100/report/pdf.svg\">\n                                <img src=\"../../Clone/Rc_str_/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Clone/Rc_str_/100/report/regression.svg\">\n                                <img src=\"../../Clone/Rc_str_/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Clone/Rc_str_/500/report/index.html\">\n                <h4>Clone/Rc&lt;str&gt;/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Clone/Rc_str_/500/report/pdf.svg\">\n                                <img src=\"../../Clone/Rc_str_/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Clone/Rc_str_/500/report/regression.svg\">\n                                <img src=\"../../Clone/Rc_str_/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Clone/String/0/report/index.html\">\n                <h4>Clone/String/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Clone/String/0/report/pdf.svg\">\n                                <img src=\"../../Clone/String/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Clone/String/0/report/regression.svg\">\n                                <img src=\"../../Clone/String/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Clone/String/10/report/index.html\">\n                <h4>Clone/String/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Clone/String/10/report/pdf.svg\">\n                                <img src=\"../../Clone/String/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Clone/String/10/report/regression.svg\">\n                                <img src=\"../../Clone/String/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Clone/String/20/report/index.html\">\n                <h4>Clone/String/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Clone/String/20/report/pdf.svg\">\n                                <img src=\"../../Clone/String/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Clone/String/20/report/regression.svg\">\n                                <img src=\"../../Clone/String/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Clone/String/100/report/index.html\">\n                <h4>Clone/String/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Clone/String/100/report/pdf.svg\">\n                                <img src=\"../../Clone/String/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Clone/String/100/report/regression.svg\">\n                                <img src=\"../../Clone/String/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Clone/String/500/report/index.html\">\n                <h4>Clone/String/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Clone/String/500/report/pdf.svg\">\n                                <img src=\"../../Clone/String/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Clone/String/500/report/regression.svg\">\n                                <img src=\"../../Clone/String/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/0/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as borrowed, own and destroy/0 Summary - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as borrowed, own and destroy/0</h2>\n        <h3>Violin Plot</h3>\n        <a href=\"violin.svg\">\n            <img src=\"violin.svg\" alt=\"Violin Plot\" />\n        </a>\n        <p>This chart shows the relationship between function/parameter and iteration time. The thickness of the shaded\n            region indicates the probability that a measurement of the given function/parameter would take a particular\n            length of time.</p>\n        <section class=\"plots\">\n            <a href=\"../../../Import as borrowed, own and destroy/Cow_&#39;_, str_/0/report/index.html\">\n                <h4>Import as borrowed, own and destroy/Cow&lt;&#39;_, str&gt;/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as borrowed, own and destroy/Cow_&#39;_, str_/0/report/pdf.svg\">\n                                <img src=\"../../../Import as borrowed, own and destroy/Cow_&#39;_, str_/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as borrowed, own and destroy/Cow_&#39;_, str_/0/report/regression.svg\">\n                                <img src=\"../../../Import as borrowed, own and destroy/Cow_&#39;_, str_/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/0/report/index.html\">\n                <h4>Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/0/report/pdf.svg\">\n                                <img src=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/0/report/regression.svg\">\n                                <img src=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/0/report/index.html\">\n                <h4>Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/0/report/pdf.svg\">\n                                <img src=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/0/report/regression.svg\">\n                                <img src=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/10/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as borrowed, own and destroy/10 Summary - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as borrowed, own and destroy/10</h2>\n        <h3>Violin Plot</h3>\n        <a href=\"violin.svg\">\n            <img src=\"violin.svg\" alt=\"Violin Plot\" />\n        </a>\n        <p>This chart shows the relationship between function/parameter and iteration time. The thickness of the shaded\n            region indicates the probability that a measurement of the given function/parameter would take a particular\n            length of time.</p>\n        <section class=\"plots\">\n            <a href=\"../../../Import as borrowed, own and destroy/Cow_&#39;_, str_/10/report/index.html\">\n                <h4>Import as borrowed, own and destroy/Cow&lt;&#39;_, str&gt;/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as borrowed, own and destroy/Cow_&#39;_, str_/10/report/pdf.svg\">\n                                <img src=\"../../../Import as borrowed, own and destroy/Cow_&#39;_, str_/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as borrowed, own and destroy/Cow_&#39;_, str_/10/report/regression.svg\">\n                                <img src=\"../../../Import as borrowed, own and destroy/Cow_&#39;_, str_/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/10/report/index.html\">\n                <h4>Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/10/report/pdf.svg\">\n                                <img src=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/10/report/regression.svg\">\n                                <img src=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/10/report/index.html\">\n                <h4>Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/10/report/pdf.svg\">\n                                <img src=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/10/report/regression.svg\">\n                                <img src=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/100/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as borrowed, own and destroy/100 Summary - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as borrowed, own and destroy/100</h2>\n        <h3>Violin Plot</h3>\n        <a href=\"violin.svg\">\n            <img src=\"violin.svg\" alt=\"Violin Plot\" />\n        </a>\n        <p>This chart shows the relationship between function/parameter and iteration time. The thickness of the shaded\n            region indicates the probability that a measurement of the given function/parameter would take a particular\n            length of time.</p>\n        <section class=\"plots\">\n            <a href=\"../../../Import as borrowed, own and destroy/Cow_&#39;_, str_/100/report/index.html\">\n                <h4>Import as borrowed, own and destroy/Cow&lt;&#39;_, str&gt;/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as borrowed, own and destroy/Cow_&#39;_, str_/100/report/pdf.svg\">\n                                <img src=\"../../../Import as borrowed, own and destroy/Cow_&#39;_, str_/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as borrowed, own and destroy/Cow_&#39;_, str_/100/report/regression.svg\">\n                                <img src=\"../../../Import as borrowed, own and destroy/Cow_&#39;_, str_/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/100/report/index.html\">\n                <h4>Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/100/report/pdf.svg\">\n                                <img src=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/100/report/regression.svg\">\n                                <img src=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/100/report/index.html\">\n                <h4>Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/100/report/pdf.svg\">\n                                <img src=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/100/report/regression.svg\">\n                                <img src=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/20/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as borrowed, own and destroy/20 Summary - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as borrowed, own and destroy/20</h2>\n        <h3>Violin Plot</h3>\n        <a href=\"violin.svg\">\n            <img src=\"violin.svg\" alt=\"Violin Plot\" />\n        </a>\n        <p>This chart shows the relationship between function/parameter and iteration time. The thickness of the shaded\n            region indicates the probability that a measurement of the given function/parameter would take a particular\n            length of time.</p>\n        <section class=\"plots\">\n            <a href=\"../../../Import as borrowed, own and destroy/Cow_&#39;_, str_/20/report/index.html\">\n                <h4>Import as borrowed, own and destroy/Cow&lt;&#39;_, str&gt;/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as borrowed, own and destroy/Cow_&#39;_, str_/20/report/pdf.svg\">\n                                <img src=\"../../../Import as borrowed, own and destroy/Cow_&#39;_, str_/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as borrowed, own and destroy/Cow_&#39;_, str_/20/report/regression.svg\">\n                                <img src=\"../../../Import as borrowed, own and destroy/Cow_&#39;_, str_/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/20/report/index.html\">\n                <h4>Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/20/report/pdf.svg\">\n                                <img src=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/20/report/regression.svg\">\n                                <img src=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/20/report/index.html\">\n                <h4>Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/20/report/pdf.svg\">\n                                <img src=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/20/report/regression.svg\">\n                                <img src=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/500/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as borrowed, own and destroy/500 Summary - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as borrowed, own and destroy/500</h2>\n        <h3>Violin Plot</h3>\n        <a href=\"violin.svg\">\n            <img src=\"violin.svg\" alt=\"Violin Plot\" />\n        </a>\n        <p>This chart shows the relationship between function/parameter and iteration time. The thickness of the shaded\n            region indicates the probability that a measurement of the given function/parameter would take a particular\n            length of time.</p>\n        <section class=\"plots\">\n            <a href=\"../../../Import as borrowed, own and destroy/Cow_&#39;_, str_/500/report/index.html\">\n                <h4>Import as borrowed, own and destroy/Cow&lt;&#39;_, str&gt;/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as borrowed, own and destroy/Cow_&#39;_, str_/500/report/pdf.svg\">\n                                <img src=\"../../../Import as borrowed, own and destroy/Cow_&#39;_, str_/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as borrowed, own and destroy/Cow_&#39;_, str_/500/report/regression.svg\">\n                                <img src=\"../../../Import as borrowed, own and destroy/Cow_&#39;_, str_/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/500/report/index.html\">\n                <h4>Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/500/report/pdf.svg\">\n                                <img src=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/500/report/regression.svg\">\n                                <img src=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/500/report/index.html\">\n                <h4>Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/500/report/pdf.svg\">\n                                <img src=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/500/report/regression.svg\">\n                                <img src=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/Cow_'_, str_/0/base/benchmark.json",
    "content": "{\"group_id\":\"Import as borrowed, own and destroy\",\"function_id\":\"Cow<'_, str>\",\"value_str\":\"0\",\"throughput\":null,\"full_id\":\"Import as borrowed, own and destroy/Cow<'_, str>/0\",\"directory_name\":\"Import as borrowed, own and destroy/Cow_'_, str_/0\",\"title\":\"Import as borrowed, own and destroy/Cow<'_, str>/0\"}"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/Cow_'_, str_/0/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.9608889033808117,\"upper_bound\":4.055740414203935},\"point_estimate\":4.003340648796448,\"standard_error\":0.02434823545683492},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.8567387959294415,\"upper_bound\":4.041026656228535},\"point_estimate\":3.970242857054903,\"standard_error\":0.050088958289434514},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.06846601351554109,\"upper_bound\":0.22997794365279445},\"point_estimate\":0.2058848749169522,\"standard_error\":0.04568885117147452},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.972690036583421,\"upper_bound\":4.045627082717556},\"point_estimate\":4.011858233516293,\"standard_error\":0.018608209704169057},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.13892675030833918,\"upper_bound\":0.35860710173163934},\"point_estimate\":0.2444974609728573,\"standard_error\":0.06353571928959084}}"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/Cow_'_, str_/0/base/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[111131.0,222262.0,333393.0,444524.0,555655.0,666786.0,777917.0,889048.0,1000179.0,1111310.0,1222441.0,1333572.0,1444703.0,1555834.0,1666965.0,1778096.0,1889227.0,2000358.0,2111489.0,2222620.0,2333751.0,2444882.0,2556013.0,2667144.0,2778275.0,2889406.0,3000537.0,3111668.0,3222799.0,3333930.0,3445061.0,3556192.0,3667323.0,3778454.0,3889585.0,4000716.0,4111847.0,4222978.0,4334109.0,4445240.0,4556371.0,4667502.0,4778633.0,4889764.0,5000895.0,5112026.0,5223157.0,5334288.0,5445419.0,5556550.0,5667681.0,5778812.0,5889943.0,6001074.0,6112205.0,6223336.0,6334467.0,6445598.0,6556729.0,6667860.0,6778991.0,6890122.0,7001253.0,7112384.0,7223515.0,7334646.0,7445777.0,7556908.0,7668039.0,7779170.0,7890301.0,8001432.0,8112563.0,8223694.0,8334825.0,8445956.0,8557087.0,8668218.0,8779349.0,8890480.0,9001611.0,9112742.0,9223873.0,9335004.0,9446135.0,9557266.0,9668397.0,9779528.0,9890659.0,10001790.0,10112921.0,10224052.0,10335183.0,10446314.0,10557445.0,10668576.0,10779707.0,10890838.0,11001969.0,11113100.0],\"times\":[640206.0,850877.0,1293250.0,2158919.0,2138293.0,2864667.0,3119331.0,3744041.0,4167374.0,4445959.0,5025417.0,5498748.0,6122207.0,6442293.0,6671916.0,7309958.0,7704666.0,8083500.0,8380789.0,8868499.0,9292542.0,9650375.0,10299458.0,11168792.0,11033499.0,11590791.0,11863416.0,12686250.0,12930333.0,13489750.0,14222416.0,13694958.0,14109458.0,14541000.0,15005582.0,15396043.0,15754000.0,16404665.0,16939374.0,17111168.0,17536997.0,17959083.0,18357291.0,18913916.0,19223414.0,19715749.0,20036294.0,20469585.0,20892623.0,21327583.0,21725169.0,22662042.0,22566625.0,22947916.0,23397249.0,23745082.0,24319500.0,24700209.0,25286917.0,25456793.0,26045290.0,26336041.0,26903166.0,27249085.0,27502999.0,27944332.0,28381291.0,28929083.0,29320917.0,29582705.0,30287500.0,30362624.0,30920125.0,31419125.0,32055958.0,36188167.0,35565500.0,35971210.0,36672041.0,37130292.0,37319000.0,37703165.0,38379290.0,38470292.0,38943333.0,39524459.0,39854374.0,40309666.0,40830457.0,41242751.0,41671833.0,42152667.0,42702334.0,42978206.0,43298876.0,43844749.0,44231082.0,45025418.0,45188374.0,45588666.0]}"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/Cow_'_, str_/0/base/tukey.json",
    "content": "[2.989480686483657,3.414274711749243,4.547058779124139,4.971852804389725]"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/Cow_'_, str_/0/change/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.022084374967590574,\"upper_bound\":0.013390504903912455},\"point_estimate\":-0.005063116059655037,\"standard_error\":0.009074915875593356},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.03565371500746972,\"upper_bound\":0.03335271682389959},\"point_estimate\":0.002503567210385249,\"standard_error\":0.017198995727582638}}"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/Cow_'_, str_/0/new/benchmark.json",
    "content": "{\"group_id\":\"Import as borrowed, own and destroy\",\"function_id\":\"Cow<'_, str>\",\"value_str\":\"0\",\"throughput\":null,\"full_id\":\"Import as borrowed, own and destroy/Cow<'_, str>/0\",\"directory_name\":\"Import as borrowed, own and destroy/Cow_'_, str_/0\",\"title\":\"Import as borrowed, own and destroy/Cow<'_, str>/0\"}"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/Cow_'_, str_/0/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.9608889033808117,\"upper_bound\":4.055740414203935},\"point_estimate\":4.003340648796448,\"standard_error\":0.02434823545683492},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.8567387959294415,\"upper_bound\":4.041026656228535},\"point_estimate\":3.970242857054903,\"standard_error\":0.050088958289434514},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.06846601351554109,\"upper_bound\":0.22997794365279445},\"point_estimate\":0.2058848749169522,\"standard_error\":0.04568885117147452},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.972690036583421,\"upper_bound\":4.045627082717556},\"point_estimate\":4.011858233516293,\"standard_error\":0.018608209704169057},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.13892675030833918,\"upper_bound\":0.35860710173163934},\"point_estimate\":0.2444974609728573,\"standard_error\":0.06353571928959084}}"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/Cow_'_, str_/0/new/sample.json",
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    "path": "docs/criterion/Import as borrowed, own and destroy/Cow_'_, str_/0/new/tukey.json",
    "content": "[2.989480686483657,3.414274711749243,4.547058779124139,4.971852804389725]"
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  {
    "path": "docs/criterion/Import as borrowed, own and destroy/Cow_'_, str_/0/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as borrowed, own and destroy/Cow&lt;&#39;_, str&gt;/0 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as borrowed, own and destroy/Cow&lt;&#39;_, str&gt;/0</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">3.9727 ns</td>\n                                <td>4.0119 ns</td>\n                                <td class=\"ci-bound\">4.0456 ns</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.8453017</td>\n                                <td>0.8538921</td>\n                                <td class=\"ci-bound\">0.8474903</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">3.9609 ns</td>\n                                <td>4.0033 ns</td>\n                                <td class=\"ci-bound\">4.0557 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">138.93 ps</td>\n                                <td>244.50 ps</td>\n                                <td class=\"ci-bound\">358.61 ps</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">3.8567 ns</td>\n                                <td>3.9702 ns</td>\n                                <td class=\"ci-bound\">4.0410 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">68.466 ps</td>\n                                <td>205.88 ps</td>\n                                <td class=\"ci-bound\">229.98 ps</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−2.2084%</td>\n                            <td>−0.5063%</td>\n                            <td class=\"ci-bound\">+1.3391%</td>\n                            <td>(p = 0.57 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/Cow_'_, str_/10/base/benchmark.json",
    "content": "{\"group_id\":\"Import as borrowed, own and destroy\",\"function_id\":\"Cow<'_, str>\",\"value_str\":\"10\",\"throughput\":null,\"full_id\":\"Import as borrowed, own and destroy/Cow<'_, str>/10\",\"directory_name\":\"Import as borrowed, own and destroy/Cow_'_, str_/10\",\"title\":\"Import as borrowed, own and destroy/Cow<'_, str>/10\"}"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/Cow_'_, str_/10/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":50.32315099280947,\"upper_bound\":51.758707269900846},\"point_estimate\":51.0180367321016,\"standard_error\":0.3657739646569019},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":48.34268672149625,\"upper_bound\":51.42609282052198},\"point_estimate\":49.76957857768291,\"standard_error\":0.860617965138204},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":1.0469640834587486,\"upper_bound\":4.865954310788295},\"point_estimate\":3.0044625990398,\"standard_error\":1.133604468348822},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":52.01215808478354,\"upper_bound\":53.20949800447599},\"point_estimate\":52.65727727040909,\"standard_error\":0.30560453277389},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.0011606548019936,\"upper_bound\":4.36681436444187},\"point_estimate\":3.6731617004354082,\"standard_error\":0.3540790792392544}}"
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    "path": "docs/criterion/Import as borrowed, own and destroy/Cow_'_, str_/10/change/estimates.json",
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    "content": "{\"group_id\":\"Import as borrowed, own and destroy\",\"function_id\":\"Cow<'_, str>\",\"value_str\":\"10\",\"throughput\":null,\"full_id\":\"Import as borrowed, own and destroy/Cow<'_, str>/10\",\"directory_name\":\"Import as borrowed, own and destroy/Cow_'_, str_/10\",\"title\":\"Import as borrowed, own and destroy/Cow<'_, str>/10\"}"
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    "path": "docs/criterion/Import as borrowed, own and destroy/Cow_'_, str_/10/new/estimates.json",
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    "path": "docs/criterion/Import as borrowed, own and destroy/Cow_'_, str_/10/new/sample.json",
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    "content": "[28.81129806547083,38.33981342328953,63.749187710806055,73.27770306862476]"
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  {
    "path": "docs/criterion/Import as borrowed, own and destroy/Cow_'_, str_/10/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as borrowed, own and destroy/Cow&lt;&#39;_, str&gt;/10 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as borrowed, own and destroy/Cow&lt;&#39;_, str&gt;/10</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">52.012 ns</td>\n                                <td>52.657 ns</td>\n                                <td class=\"ci-bound\">53.209 ns</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.7380709</td>\n                                <td>0.7484733</td>\n                                <td class=\"ci-bound\">0.7408227</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">50.323 ns</td>\n                                <td>51.018 ns</td>\n                                <td class=\"ci-bound\">51.759 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">3.0012 ns</td>\n                                <td>3.6732 ns</td>\n                                <td class=\"ci-bound\">4.3668 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">48.343 ns</td>\n                                <td>49.770 ns</td>\n                                <td class=\"ci-bound\">51.426 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">1.0470 ns</td>\n                                <td>3.0045 ns</td>\n                                <td class=\"ci-bound\">4.8660 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−11.254%</td>\n                            <td>−5.3486%</td>\n                            <td class=\"ci-bound\">−0.4837%</td>\n                            <td>(p = 0.06 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
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    "path": "docs/criterion/Import as borrowed, own and destroy/Cow_'_, str_/100/base/benchmark.json",
    "content": "{\"group_id\":\"Import as borrowed, own and destroy\",\"function_id\":\"Cow<'_, str>\",\"value_str\":\"100\",\"throughput\":null,\"full_id\":\"Import as borrowed, own and destroy/Cow<'_, str>/100\",\"directory_name\":\"Import as borrowed, own and destroy/Cow_'_, str_/100\",\"title\":\"Import as borrowed, own and destroy/Cow<'_, str>/100\"}"
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    "path": "docs/criterion/Import as borrowed, own and destroy/Cow_'_, str_/100/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":58.379127767914085,\"upper_bound\":60.02092634355676},\"point_estimate\":59.19670982577489,\"standard_error\":0.42008176435586475},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":58.422500971871145,\"upper_bound\":60.35292757255374},\"point_estimate\":59.34796902743176,\"standard_error\":0.5164649530402777},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.027498900431335,\"upper_bound\":5.262711133592181},\"point_estimate\":4.249006583173159,\"standard_error\":0.5638262283044545},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":59.461610321259684,\"upper_bound\":61.08893772618308},\"point_estimate\":60.28454884035322,\"standard_error\":0.4151480440948287},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.5353233044534678,\"upper_bound\":4.939810162967223},\"point_estimate\":4.222963650281504,\"standard_error\":0.3606187325082189}}"
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  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/Cow_'_, str_/100/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as borrowed, own and destroy/Cow&lt;&#39;_, str&gt;/100 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as borrowed, own and destroy/Cow&lt;&#39;_, str&gt;/100</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">59.462 ns</td>\n                                <td>60.285 ns</td>\n                                <td class=\"ci-bound\">61.089 ns</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.7177725</td>\n                                <td>0.7297167</td>\n                                <td class=\"ci-bound\">0.7182965</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">58.379 ns</td>\n                                <td>59.197 ns</td>\n                                <td class=\"ci-bound\">60.021 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">3.5353 ns</td>\n                                <td>4.2230 ns</td>\n                                <td class=\"ci-bound\">4.9398 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">58.423 ns</td>\n                                <td>59.348 ns</td>\n                                <td class=\"ci-bound\">60.353 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">3.0275 ns</td>\n                                <td>4.2490 ns</td>\n                                <td class=\"ci-bound\">5.2627 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−2.1252%</td>\n                            <td>−0.0758%</td>\n                            <td class=\"ci-bound\">+1.8199%</td>\n                            <td>(p = 0.94 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/Cow_'_, str_/20/base/benchmark.json",
    "content": "{\"group_id\":\"Import as borrowed, own and destroy\",\"function_id\":\"Cow<'_, str>\",\"value_str\":\"20\",\"throughput\":null,\"full_id\":\"Import as borrowed, own and destroy/Cow<'_, str>/20\",\"directory_name\":\"Import as borrowed, own and destroy/Cow_'_, str_/20\",\"title\":\"Import as borrowed, own and destroy/Cow<'_, str>/20\"}"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/Cow_'_, str_/20/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":55.21317380829794,\"upper_bound\":56.534590464546596},\"point_estimate\":55.87052751218874,\"standard_error\":0.33796583033730426},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":55.345814209656695,\"upper_bound\":56.85187081896038},\"point_estimate\":56.33416065907208,\"standard_error\":0.39751034665410256},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.314657880513485,\"upper_bound\":4.877939227429333},\"point_estimate\":3.2258908215278823,\"standard_error\":0.6954930824035179},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":56.59658373051964,\"upper_bound\":57.78163307295939},\"point_estimate\":57.2024620518657,\"standard_error\":0.3026126002553018},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.955368309431354,\"upper_bound\":3.83689669410951},\"point_estimate\":3.3937952655322565,\"standard_error\":0.22487501249219938}}"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/Cow_'_, str_/20/base/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[10894.0,21788.0,32682.0,43576.0,54470.0,65364.0,76258.0,87152.0,98046.0,108940.0,119834.0,130728.0,141622.0,152516.0,163410.0,174304.0,185198.0,196092.0,206986.0,217880.0,228774.0,239668.0,250562.0,261456.0,272350.0,283244.0,294138.0,305032.0,315926.0,326820.0,337714.0,348608.0,359502.0,370396.0,381290.0,392184.0,403078.0,413972.0,424866.0,435760.0,446654.0,457548.0,468442.0,479336.0,490230.0,501124.0,512018.0,522912.0,533806.0,544700.0,555594.0,566488.0,577382.0,588276.0,599170.0,610064.0,620958.0,631852.0,642746.0,653640.0,664534.0,675428.0,686322.0,697216.0,708110.0,719004.0,729898.0,740792.0,751686.0,762580.0,773474.0,784368.0,795262.0,806156.0,817050.0,827944.0,838838.0,849732.0,860626.0,871520.0,882414.0,893308.0,904202.0,915096.0,925990.0,936884.0,947778.0,958672.0,969566.0,980460.0,991354.0,1002248.0,1013142.0,1024036.0,1034930.0,1045824.0,1056718.0,1067612.0,1078506.0,1089400.0],\"times\":[563875.0,1462958.0,1659539.0,2677582.0,2907290.0,3794125.0,4276000.0,4511541.0,5020835.0,6029373.0,6515623.0,6726331.0,7232833.0,7776331.0,8344417.0,8952126.0,10225585.0,10010042.0,10490125.0,11056124.0,11642706.0,12261249.0,12722916.0,13301459.0,13877416.0,14813251.0,14976376.0,15729916.0,16096875.0,19957333.0,20439584.0,20995875.0,20835999.0,21025877.0,21703418.0,21897586.0,22232252.0,22599625.0,22850209.0,23184250.0,23616208.0,25140335.0,24722792.0,24531291.0,28509334.0,29090374.0,29751375.0,30268793.0,30828669.0,31381209.0,32199000.0,32487210.0,32576918.0,33768292.0,34000792.0,34654250.0,35302624.0,35798959.0,36554792.0,38866209.0,39867044.0,40579667.0,39850792.0,40380041.0,41436999.0,41463708.0,41039669.0,40997666.0,40942292.0,41432207.0,41336874.0,40861167.0,41487834.0,44784666.0,45439081.0,46852628.0,46620083.0,47827585.0,48239583.0,48158835.0,49175752.0,53103084.0,54758581.0,55707417.0,55942083.0,56170294.0,56380290.0,56307043.0,59768543.0,59849873.0,58779583.0,59673000.0,59271082.0,59389792.0,59810790.0,59137373.0,59580749.0,58473166.0,60860751.0,62594500.0]}"
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    "path": "docs/criterion/Import as borrowed, own and destroy/Cow_'_, str_/20/base/tukey.json",
    "content": "[37.25605099945194,45.052707327738936,65.84379086983759,73.64044719812458]"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/Cow_'_, str_/20/change/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.01809438984694779,\"upper_bound\":0.015530964343304397},\"point_estimate\":-0.0009820060370570038,\"standard_error\":0.008555716179541832},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.019737366720248617,\"upper_bound\":0.017400452450896386},\"point_estimate\":0.000017448768562911,\"standard_error\":0.009307874077646886}}"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/Cow_'_, str_/20/new/benchmark.json",
    "content": "{\"group_id\":\"Import as borrowed, own and destroy\",\"function_id\":\"Cow<'_, str>\",\"value_str\":\"20\",\"throughput\":null,\"full_id\":\"Import as borrowed, own and destroy/Cow<'_, str>/20\",\"directory_name\":\"Import as borrowed, own and destroy/Cow_'_, str_/20\",\"title\":\"Import as borrowed, own and destroy/Cow<'_, str>/20\"}"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/Cow_'_, str_/20/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":55.21317380829794,\"upper_bound\":56.534590464546596},\"point_estimate\":55.87052751218874,\"standard_error\":0.33796583033730426},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":55.345814209656695,\"upper_bound\":56.85187081896038},\"point_estimate\":56.33416065907208,\"standard_error\":0.39751034665410256},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.314657880513485,\"upper_bound\":4.877939227429333},\"point_estimate\":3.2258908215278823,\"standard_error\":0.6954930824035179},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":56.59658373051964,\"upper_bound\":57.78163307295939},\"point_estimate\":57.2024620518657,\"standard_error\":0.3026126002553018},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.955368309431354,\"upper_bound\":3.83689669410951},\"point_estimate\":3.3937952655322565,\"standard_error\":0.22487501249219938}}"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/Cow_'_, str_/20/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[10894.0,21788.0,32682.0,43576.0,54470.0,65364.0,76258.0,87152.0,98046.0,108940.0,119834.0,130728.0,141622.0,152516.0,163410.0,174304.0,185198.0,196092.0,206986.0,217880.0,228774.0,239668.0,250562.0,261456.0,272350.0,283244.0,294138.0,305032.0,315926.0,326820.0,337714.0,348608.0,359502.0,370396.0,381290.0,392184.0,403078.0,413972.0,424866.0,435760.0,446654.0,457548.0,468442.0,479336.0,490230.0,501124.0,512018.0,522912.0,533806.0,544700.0,555594.0,566488.0,577382.0,588276.0,599170.0,610064.0,620958.0,631852.0,642746.0,653640.0,664534.0,675428.0,686322.0,697216.0,708110.0,719004.0,729898.0,740792.0,751686.0,762580.0,773474.0,784368.0,795262.0,806156.0,817050.0,827944.0,838838.0,849732.0,860626.0,871520.0,882414.0,893308.0,904202.0,915096.0,925990.0,936884.0,947778.0,958672.0,969566.0,980460.0,991354.0,1002248.0,1013142.0,1024036.0,1034930.0,1045824.0,1056718.0,1067612.0,1078506.0,1089400.0],\"times\":[563875.0,1462958.0,1659539.0,2677582.0,2907290.0,3794125.0,4276000.0,4511541.0,5020835.0,6029373.0,6515623.0,6726331.0,7232833.0,7776331.0,8344417.0,8952126.0,10225585.0,10010042.0,10490125.0,11056124.0,11642706.0,12261249.0,12722916.0,13301459.0,13877416.0,14813251.0,14976376.0,15729916.0,16096875.0,19957333.0,20439584.0,20995875.0,20835999.0,21025877.0,21703418.0,21897586.0,22232252.0,22599625.0,22850209.0,23184250.0,23616208.0,25140335.0,24722792.0,24531291.0,28509334.0,29090374.0,29751375.0,30268793.0,30828669.0,31381209.0,32199000.0,32487210.0,32576918.0,33768292.0,34000792.0,34654250.0,35302624.0,35798959.0,36554792.0,38866209.0,39867044.0,40579667.0,39850792.0,40380041.0,41436999.0,41463708.0,41039669.0,40997666.0,40942292.0,41432207.0,41336874.0,40861167.0,41487834.0,44784666.0,45439081.0,46852628.0,46620083.0,47827585.0,48239583.0,48158835.0,49175752.0,53103084.0,54758581.0,55707417.0,55942083.0,56170294.0,56380290.0,56307043.0,59768543.0,59849873.0,58779583.0,59673000.0,59271082.0,59389792.0,59810790.0,59137373.0,59580749.0,58473166.0,60860751.0,62594500.0]}"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/Cow_'_, str_/20/new/tukey.json",
    "content": "[37.25605099945194,45.052707327738936,65.84379086983759,73.64044719812458]"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/Cow_'_, str_/20/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as borrowed, own and destroy/Cow&lt;&#39;_, str&gt;/20 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as borrowed, own and destroy/Cow&lt;&#39;_, str&gt;/20</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">56.597 ns</td>\n                                <td>57.202 ns</td>\n                                <td class=\"ci-bound\">57.782 ns</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.7937288</td>\n                                <td>0.8032749</td>\n                                <td class=\"ci-bound\">0.7945429</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">55.213 ns</td>\n                                <td>55.871 ns</td>\n                                <td class=\"ci-bound\">56.535 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">2.9554 ns</td>\n                                <td>3.3938 ns</td>\n                                <td class=\"ci-bound\">3.8369 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">55.346 ns</td>\n                                <td>56.334 ns</td>\n                                <td class=\"ci-bound\">56.852 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">2.3147 ns</td>\n                                <td>3.2259 ns</td>\n                                <td class=\"ci-bound\">4.8779 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−1.8094%</td>\n                            <td>−0.0982%</td>\n                            <td class=\"ci-bound\">+1.5531%</td>\n                            <td>(p = 0.91 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/Cow_'_, str_/500/base/benchmark.json",
    "content": "{\"group_id\":\"Import as borrowed, own and destroy\",\"function_id\":\"Cow<'_, str>\",\"value_str\":\"500\",\"throughput\":null,\"full_id\":\"Import as borrowed, own and destroy/Cow<'_, str>/500\",\"directory_name\":\"Import as borrowed, own and destroy/Cow_'_, str_/500\",\"title\":\"Import as borrowed, own and destroy/Cow<'_, str>/500\"}"
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    "path": "docs/criterion/Import as borrowed, own and destroy/Cow_'_, str_/500/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":97.90302072140136,\"upper_bound\":100.51956187548244},\"point_estimate\":99.2270257085067,\"standard_error\":0.6672987496253787},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":97.73780438687204,\"upper_bound\":100.51434850051706},\"point_estimate\":99.4444973818552,\"standard_error\":0.7283706785854308},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":4.18723766747942,\"upper_bound\":6.645844513632839},\"point_estimate\":5.336755686865007,\"standard_error\":0.639176383470732},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":98.07688504614691,\"upper_bound\":100.20532545710502},\"point_estimate\":99.10235278113004,\"standard_error\":0.5439111675645801},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":5.208617178927317,\"upper_bound\":8.080337935200731},\"point_estimate\":6.705007984631004,\"standard_error\":0.736041293966924}}"
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    "path": "docs/criterion/Import as borrowed, own and destroy/Cow_'_, str_/500/base/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[4835.0,9670.0,14505.0,19340.0,24175.0,29010.0,33845.0,38680.0,43515.0,48350.0,53185.0,58020.0,62855.0,67690.0,72525.0,77360.0,82195.0,87030.0,91865.0,96700.0,101535.0,106370.0,111205.0,116040.0,120875.0,125710.0,130545.0,135380.0,140215.0,145050.0,149885.0,154720.0,159555.0,164390.0,169225.0,174060.0,178895.0,183730.0,188565.0,193400.0,198235.0,203070.0,207905.0,212740.0,217575.0,222410.0,227245.0,232080.0,236915.0,241750.0,246585.0,251420.0,256255.0,261090.0,265925.0,270760.0,275595.0,280430.0,285265.0,290100.0,294935.0,299770.0,304605.0,309440.0,314275.0,319110.0,323945.0,328780.0,333615.0,338450.0,343285.0,348120.0,352955.0,357790.0,362625.0,367460.0,372295.0,377130.0,381965.0,386800.0,391635.0,396470.0,401305.0,406140.0,410975.0,415810.0,420645.0,425480.0,430315.0,435150.0,439985.0,444820.0,449655.0,454490.0,459325.0,464160.0,468995.0,473830.0,478665.0,483500.0],\"times\":[383206.0,730209.0,1308706.0,1470334.0,2322709.0,2718082.0,3195998.0,3232210.0,4177457.0,4634041.0,4908876.0,5418834.0,5887582.0,6682669.0,7348792.0,8040040.0,8273000.0,9381541.0,9589126.0,10620708.0,11138626.0,11832374.0,12853168.0,13714166.0,12162916.0,12250459.0,12613378.0,13438125.0,14087335.0,14262249.0,14964876.0,15593667.0,16032502.0,16967668.0,17683627.0,17300833.0,19818376.0,19854251.0,19267459.0,19445750.0,19864457.0,20204083.0,20202833.0,21921335.0,23247541.0,23547874.0,24424625.0,23843626.0,23774210.0,22805918.0,23358041.0,25189251.0,26091043.0,26744417.0,26656332.0,27111039.0,26728250.0,26138500.0,26699624.0,28682751.0,29920460.0,30594210.0,31002250.0,30006710.0,31062289.0,30379957.0,31473459.0,33697334.0,35467543.0,33435458.0,32794251.0,33188000.0,33355455.0,38597373.0,39140417.0,34942373.0,35113541.0,36701707.0,39002582.0,40834708.0,39483873.0,41005499.0,38574584.0,41852417.0,42036959.0,40270500.0,39571832.0,42029959.0,45083041.0,42935709.0,42317415.0,42216209.0,42807082.0,42340960.0,44893417.0,43790792.0,44138542.0,45097374.0,48963417.0,48583000.0]}"
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    "path": "docs/criterion/Import as borrowed, own and destroy/Cow_'_, str_/500/base/tukey.json",
    "content": "[73.86209549721933,84.58191931327389,113.16811615608606,123.88793997214063]"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/Cow_'_, str_/500/change/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.00481639493718635,\"upper_bound\":0.02858606168959015},\"point_estimate\":0.012210476248189162,\"standard_error\":0.008456273710799182},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.011559210251373297,\"upper_bound\":0.021186609606643758},\"point_estimate\":0.007041005006878764,\"standard_error\":0.008311328601963574}}"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/Cow_'_, str_/500/new/benchmark.json",
    "content": "{\"group_id\":\"Import as borrowed, own and destroy\",\"function_id\":\"Cow<'_, str>\",\"value_str\":\"500\",\"throughput\":null,\"full_id\":\"Import as borrowed, own and destroy/Cow<'_, str>/500\",\"directory_name\":\"Import as borrowed, own and destroy/Cow_'_, str_/500\",\"title\":\"Import as borrowed, own and destroy/Cow<'_, str>/500\"}"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/Cow_'_, str_/500/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":97.90302072140136,\"upper_bound\":100.51956187548244},\"point_estimate\":99.2270257085067,\"standard_error\":0.6672987496253787},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":97.73780438687204,\"upper_bound\":100.51434850051706},\"point_estimate\":99.4444973818552,\"standard_error\":0.7283706785854308},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":4.18723766747942,\"upper_bound\":6.645844513632839},\"point_estimate\":5.336755686865007,\"standard_error\":0.639176383470732},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":98.07688504614691,\"upper_bound\":100.20532545710502},\"point_estimate\":99.10235278113004,\"standard_error\":0.5439111675645801},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":5.208617178927317,\"upper_bound\":8.080337935200731},\"point_estimate\":6.705007984631004,\"standard_error\":0.736041293966924}}"
  },
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    "path": "docs/criterion/Import as borrowed, own and destroy/Cow_'_, str_/500/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[4835.0,9670.0,14505.0,19340.0,24175.0,29010.0,33845.0,38680.0,43515.0,48350.0,53185.0,58020.0,62855.0,67690.0,72525.0,77360.0,82195.0,87030.0,91865.0,96700.0,101535.0,106370.0,111205.0,116040.0,120875.0,125710.0,130545.0,135380.0,140215.0,145050.0,149885.0,154720.0,159555.0,164390.0,169225.0,174060.0,178895.0,183730.0,188565.0,193400.0,198235.0,203070.0,207905.0,212740.0,217575.0,222410.0,227245.0,232080.0,236915.0,241750.0,246585.0,251420.0,256255.0,261090.0,265925.0,270760.0,275595.0,280430.0,285265.0,290100.0,294935.0,299770.0,304605.0,309440.0,314275.0,319110.0,323945.0,328780.0,333615.0,338450.0,343285.0,348120.0,352955.0,357790.0,362625.0,367460.0,372295.0,377130.0,381965.0,386800.0,391635.0,396470.0,401305.0,406140.0,410975.0,415810.0,420645.0,425480.0,430315.0,435150.0,439985.0,444820.0,449655.0,454490.0,459325.0,464160.0,468995.0,473830.0,478665.0,483500.0],\"times\":[383206.0,730209.0,1308706.0,1470334.0,2322709.0,2718082.0,3195998.0,3232210.0,4177457.0,4634041.0,4908876.0,5418834.0,5887582.0,6682669.0,7348792.0,8040040.0,8273000.0,9381541.0,9589126.0,10620708.0,11138626.0,11832374.0,12853168.0,13714166.0,12162916.0,12250459.0,12613378.0,13438125.0,14087335.0,14262249.0,14964876.0,15593667.0,16032502.0,16967668.0,17683627.0,17300833.0,19818376.0,19854251.0,19267459.0,19445750.0,19864457.0,20204083.0,20202833.0,21921335.0,23247541.0,23547874.0,24424625.0,23843626.0,23774210.0,22805918.0,23358041.0,25189251.0,26091043.0,26744417.0,26656332.0,27111039.0,26728250.0,26138500.0,26699624.0,28682751.0,29920460.0,30594210.0,31002250.0,30006710.0,31062289.0,30379957.0,31473459.0,33697334.0,35467543.0,33435458.0,32794251.0,33188000.0,33355455.0,38597373.0,39140417.0,34942373.0,35113541.0,36701707.0,39002582.0,40834708.0,39483873.0,41005499.0,38574584.0,41852417.0,42036959.0,40270500.0,39571832.0,42029959.0,45083041.0,42935709.0,42317415.0,42216209.0,42807082.0,42340960.0,44893417.0,43790792.0,44138542.0,45097374.0,48963417.0,48583000.0]}"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/Cow_'_, str_/500/new/tukey.json",
    "content": "[73.86209549721933,84.58191931327389,113.16811615608606,123.88793997214063]"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/Cow_'_, str_/500/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as borrowed, own and destroy/Cow&lt;&#39;_, str&gt;/500 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as borrowed, own and destroy/Cow&lt;&#39;_, str&gt;/500</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">98.077 ns</td>\n                                <td>99.102 ns</td>\n                                <td class=\"ci-bound\">100.21 ns</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.7912877</td>\n                                <td>0.8002311</td>\n                                <td class=\"ci-bound\">0.7899029</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">97.903 ns</td>\n                                <td>99.227 ns</td>\n                                <td class=\"ci-bound\">100.52 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">5.2086 ns</td>\n                                <td>6.7050 ns</td>\n                                <td class=\"ci-bound\">8.0803 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">97.738 ns</td>\n                                <td>99.444 ns</td>\n                                <td class=\"ci-bound\">100.51 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">4.1872 ns</td>\n                                <td>5.3368 ns</td>\n                                <td class=\"ci-bound\">6.6458 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−0.4816%</td>\n                            <td>+1.2210%</td>\n                            <td class=\"ci-bound\">+2.8586%</td>\n                            <td>(p = 0.15 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/Cow_'_, str_/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as borrowed, own and destroy/Cow&lt;&#39;_, str&gt; Summary - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as borrowed, own and destroy/Cow&lt;&#39;_, str&gt;</h2>\n        <h3>Violin Plot</h3>\n        <a href=\"violin.svg\">\n            <img src=\"violin.svg\" alt=\"Violin Plot\" />\n        </a>\n        <p>This chart shows the relationship between function/parameter and iteration time. The thickness of the shaded\n            region indicates the probability that a measurement of the given function/parameter would take a particular\n            length of time.</p>\n        <h3>Line Chart</h3>\n        <img src=\"lines.svg\" alt=\"Line Chart\" />\n        <p>This chart shows the mean measured time for each function as the input (or the size of the input) increases.</p>\n        <section class=\"plots\">\n            <a href=\"../../../Import as borrowed, own and destroy/Cow_&#39;_, str_/0/report/index.html\">\n                <h4>Import as borrowed, own and destroy/Cow&lt;&#39;_, str&gt;/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as borrowed, own and destroy/Cow_&#39;_, str_/0/report/pdf.svg\">\n                                <img src=\"../../../Import as borrowed, own and destroy/Cow_&#39;_, str_/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as borrowed, own and destroy/Cow_&#39;_, str_/0/report/regression.svg\">\n                                <img src=\"../../../Import as borrowed, own and destroy/Cow_&#39;_, str_/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as borrowed, own and destroy/Cow_&#39;_, str_/10/report/index.html\">\n                <h4>Import as borrowed, own and destroy/Cow&lt;&#39;_, str&gt;/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as borrowed, own and destroy/Cow_&#39;_, str_/10/report/pdf.svg\">\n                                <img src=\"../../../Import as borrowed, own and destroy/Cow_&#39;_, str_/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as borrowed, own and destroy/Cow_&#39;_, str_/10/report/regression.svg\">\n                                <img src=\"../../../Import as borrowed, own and destroy/Cow_&#39;_, str_/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as borrowed, own and destroy/Cow_&#39;_, str_/20/report/index.html\">\n                <h4>Import as borrowed, own and destroy/Cow&lt;&#39;_, str&gt;/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as borrowed, own and destroy/Cow_&#39;_, str_/20/report/pdf.svg\">\n                                <img src=\"../../../Import as borrowed, own and destroy/Cow_&#39;_, str_/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as borrowed, own and destroy/Cow_&#39;_, str_/20/report/regression.svg\">\n                                <img src=\"../../../Import as borrowed, own and destroy/Cow_&#39;_, str_/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as borrowed, own and destroy/Cow_&#39;_, str_/100/report/index.html\">\n                <h4>Import as borrowed, own and destroy/Cow&lt;&#39;_, str&gt;/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as borrowed, own and destroy/Cow_&#39;_, str_/100/report/pdf.svg\">\n                                <img src=\"../../../Import as borrowed, own and destroy/Cow_&#39;_, str_/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as borrowed, own and destroy/Cow_&#39;_, str_/100/report/regression.svg\">\n                                <img src=\"../../../Import as borrowed, own and destroy/Cow_&#39;_, str_/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as borrowed, own and destroy/Cow_&#39;_, str_/500/report/index.html\">\n                <h4>Import as borrowed, own and destroy/Cow&lt;&#39;_, str&gt;/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as borrowed, own and destroy/Cow_&#39;_, str_/500/report/pdf.svg\">\n                                <img src=\"../../../Import as borrowed, own and destroy/Cow_&#39;_, str_/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as borrowed, own and destroy/Cow_&#39;_, str_/500/report/regression.svg\">\n                                <img src=\"../../../Import as borrowed, own and destroy/Cow_&#39;_, str_/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/0/base/benchmark.json",
    "content": "{\"group_id\":\"Import as borrowed, own and destroy\",\"function_id\":\"FlexStr 0.10 (LocalStr)\",\"value_str\":\"0\",\"throughput\":null,\"full_id\":\"Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/0\",\"directory_name\":\"Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/0\",\"title\":\"Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/0\"}"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/0/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":8.979334700146817,\"upper_bound\":9.233589390882118},\"point_estimate\":9.093588750824175,\"standard_error\":0.06536799202239152},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":8.865646169940334,\"upper_bound\":9.009412590962615},\"point_estimate\":8.927920087694346,\"standard_error\":0.03170658344975978},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.1792190205772536,\"upper_bound\":0.35034557706287045},\"point_estimate\":0.22565815671170064,\"standard_error\":0.04477801321100676},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":8.859647698172571,\"upper_bound\":8.985849211839712},\"point_estimate\":8.915721417067246,\"standard_error\":0.032084577827271504},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.3577515215057851,\"upper_bound\":0.9582850398996491},\"point_estimate\":0.6571783662516163,\"standard_error\":0.16653196330898123}}"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/0/base/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[75756.0,151512.0,227268.0,303024.0,378780.0,454536.0,530292.0,606048.0,681804.0,757560.0,833316.0,909072.0,984828.0,1060584.0,1136340.0,1212096.0,1287852.0,1363608.0,1439364.0,1515120.0,1590876.0,1666632.0,1742388.0,1818144.0,1893900.0,1969656.0,2045412.0,2121168.0,2196924.0,2272680.0,2348436.0,2424192.0,2499948.0,2575704.0,2651460.0,2727216.0,2802972.0,2878728.0,2954484.0,3030240.0,3105996.0,3181752.0,3257508.0,3333264.0,3409020.0,3484776.0,3560532.0,3636288.0,3712044.0,3787800.0,3863556.0,3939312.0,4015068.0,4090824.0,4166580.0,4242336.0,4318092.0,4393848.0,4469604.0,4545360.0,4621116.0,4696872.0,4772628.0,4848384.0,4924140.0,4999896.0,5075652.0,5151408.0,5227164.0,5302920.0,5378676.0,5454432.0,5530188.0,5605944.0,5681700.0,5757456.0,5833212.0,5908968.0,5984724.0,6060480.0,6136236.0,6211992.0,6287748.0,6363504.0,6439260.0,6515016.0,6590772.0,6666528.0,6742284.0,6818040.0,6893796.0,6969552.0,7045308.0,7121064.0,7196820.0,7272576.0,7348332.0,7424088.0,7499844.0,7575600.0],\"times\":[1039831.0,1268959.0,1911040.0,2588543.0,3629877.0,4298293.0,4508249.0,5470210.0,5981999.0,7417627.0,7208210.0,7971377.0,8790666.0,9125041.0,10606376.0,10659916.0,11309083.0,11738042.0,12789374.0,13108918.0,14584415.0,15480209.0,15964540.0,16405623.0,16971876.0,17503040.0,18099291.0,18867626.0,19636083.0,22028207.0,22794583.0,27706458.0,25022917.0,25413791.0,25230750.0,27013124.0,26494834.0,27646457.0,31296625.0,28423873.0,30216499.0,30181667.0,30478835.0,32461293.0,31270960.0,30608499.0,30894125.0,31695000.0,31880335.0,34107832.0,34878166.0,35042043.0,36250291.0,36860207.0,37574417.0,38410501.0,39014164.0,39685874.0,40476625.0,41133166.0,41769416.0,43393499.0,48542168.0,44161377.0,44672208.0,44639583.0,45407544.0,46129918.0,46666750.0,47590166.0,48045043.0,48841916.0,49366626.0,49701876.0,50358999.0,50660000.0,51958334.0,52112750.0,52942917.0,53743877.0,54356916.0,54987042.0,56648916.0,56275001.0,56392334.0,57344583.0,58341877.0,57868167.0,59027125.0,60171583.0,60266292.0,61221793.0,61841251.0,62804917.0,62888669.0,63277876.0,63612710.0,63606292.0,64490333.0,65318125.0]}"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/0/base/tukey.json",
    "content": "[7.640664639708323,8.211810607039876,9.734866519924015,10.306012487255567]"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/0/change/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.00562153378985655,\"upper_bound\":0.0425383209854737},\"point_estimate\":0.02363857730284713,\"standard_error\":0.009210485788718728},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.0014466115380040723,\"upper_bound\":0.02269714318657856},\"point_estimate\":0.01095316930407031,\"standard_error\":0.005435796308502907}}"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/0/new/benchmark.json",
    "content": "{\"group_id\":\"Import as borrowed, own and destroy\",\"function_id\":\"FlexStr 0.10 (LocalStr)\",\"value_str\":\"0\",\"throughput\":null,\"full_id\":\"Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/0\",\"directory_name\":\"Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/0\",\"title\":\"Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/0\"}"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/0/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":8.979334700146817,\"upper_bound\":9.233589390882118},\"point_estimate\":9.093588750824175,\"standard_error\":0.06536799202239152},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":8.865646169940334,\"upper_bound\":9.009412590962615},\"point_estimate\":8.927920087694346,\"standard_error\":0.03170658344975978},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.1792190205772536,\"upper_bound\":0.35034557706287045},\"point_estimate\":0.22565815671170064,\"standard_error\":0.04477801321100676},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":8.859647698172571,\"upper_bound\":8.985849211839712},\"point_estimate\":8.915721417067246,\"standard_error\":0.032084577827271504},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.3577515215057851,\"upper_bound\":0.9582850398996491},\"point_estimate\":0.6571783662516163,\"standard_error\":0.16653196330898123}}"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/0/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[75756.0,151512.0,227268.0,303024.0,378780.0,454536.0,530292.0,606048.0,681804.0,757560.0,833316.0,909072.0,984828.0,1060584.0,1136340.0,1212096.0,1287852.0,1363608.0,1439364.0,1515120.0,1590876.0,1666632.0,1742388.0,1818144.0,1893900.0,1969656.0,2045412.0,2121168.0,2196924.0,2272680.0,2348436.0,2424192.0,2499948.0,2575704.0,2651460.0,2727216.0,2802972.0,2878728.0,2954484.0,3030240.0,3105996.0,3181752.0,3257508.0,3333264.0,3409020.0,3484776.0,3560532.0,3636288.0,3712044.0,3787800.0,3863556.0,3939312.0,4015068.0,4090824.0,4166580.0,4242336.0,4318092.0,4393848.0,4469604.0,4545360.0,4621116.0,4696872.0,4772628.0,4848384.0,4924140.0,4999896.0,5075652.0,5151408.0,5227164.0,5302920.0,5378676.0,5454432.0,5530188.0,5605944.0,5681700.0,5757456.0,5833212.0,5908968.0,5984724.0,6060480.0,6136236.0,6211992.0,6287748.0,6363504.0,6439260.0,6515016.0,6590772.0,6666528.0,6742284.0,6818040.0,6893796.0,6969552.0,7045308.0,7121064.0,7196820.0,7272576.0,7348332.0,7424088.0,7499844.0,7575600.0],\"times\":[1039831.0,1268959.0,1911040.0,2588543.0,3629877.0,4298293.0,4508249.0,5470210.0,5981999.0,7417627.0,7208210.0,7971377.0,8790666.0,9125041.0,10606376.0,10659916.0,11309083.0,11738042.0,12789374.0,13108918.0,14584415.0,15480209.0,15964540.0,16405623.0,16971876.0,17503040.0,18099291.0,18867626.0,19636083.0,22028207.0,22794583.0,27706458.0,25022917.0,25413791.0,25230750.0,27013124.0,26494834.0,27646457.0,31296625.0,28423873.0,30216499.0,30181667.0,30478835.0,32461293.0,31270960.0,30608499.0,30894125.0,31695000.0,31880335.0,34107832.0,34878166.0,35042043.0,36250291.0,36860207.0,37574417.0,38410501.0,39014164.0,39685874.0,40476625.0,41133166.0,41769416.0,43393499.0,48542168.0,44161377.0,44672208.0,44639583.0,45407544.0,46129918.0,46666750.0,47590166.0,48045043.0,48841916.0,49366626.0,49701876.0,50358999.0,50660000.0,51958334.0,52112750.0,52942917.0,53743877.0,54356916.0,54987042.0,56648916.0,56275001.0,56392334.0,57344583.0,58341877.0,57868167.0,59027125.0,60171583.0,60266292.0,61221793.0,61841251.0,62804917.0,62888669.0,63277876.0,63612710.0,63606292.0,64490333.0,65318125.0]}"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/0/new/tukey.json",
    "content": "[7.640664639708323,8.211810607039876,9.734866519924015,10.306012487255567]"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/0/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/0 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/0</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">8.8596 ns</td>\n                                <td>8.9157 ns</td>\n                                <td class=\"ci-bound\">8.9858 ns</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.8198100</td>\n                                <td>0.8241212</td>\n                                <td class=\"ci-bound\">0.8173979</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">8.9793 ns</td>\n                                <td>9.0936 ns</td>\n                                <td class=\"ci-bound\">9.2336 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">357.75 ps</td>\n                                <td>657.18 ps</td>\n                                <td class=\"ci-bound\">958.29 ps</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">8.8656 ns</td>\n                                <td>8.9279 ns</td>\n                                <td class=\"ci-bound\">9.0094 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">179.22 ps</td>\n                                <td>225.66 ps</td>\n                                <td class=\"ci-bound\">350.35 ps</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">+0.5622%</td>\n                            <td>+2.3639%</td>\n                            <td class=\"ci-bound\">+4.2538%</td>\n                            <td>(p = 0.01 &lt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                Change within noise threshold.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/10/base/benchmark.json",
    "content": "{\"group_id\":\"Import as borrowed, own and destroy\",\"function_id\":\"FlexStr 0.10 (LocalStr)\",\"value_str\":\"10\",\"throughput\":null,\"full_id\":\"Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/10\",\"directory_name\":\"Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/10\",\"title\":\"Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/10\"}"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/10/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":36.96532161122457,\"upper_bound\":38.44623909034577},\"point_estimate\":37.693408832735685,\"standard_error\":0.37746492273982185},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":35.45367381981849,\"upper_bound\":39.702822300281994},\"point_estimate\":37.37861529565417,\"standard_error\":1.2894991541608052},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.0247862835297123,\"upper_bound\":5.498327211736226},\"point_estimate\":4.770148198349551,\"standard_error\":0.6312379360653394},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":39.11670621587491,\"upper_bound\":40.3207643739608},\"point_estimate\":39.74821246383323,\"standard_error\":0.30741017862485825},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.3073753737159124,\"upper_bound\":4.344770450701192},\"point_estimate\":3.796983054568984,\"standard_error\":0.2696360740330035}}"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/10/base/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[14329.0,28658.0,42987.0,57316.0,71645.0,85974.0,100303.0,114632.0,128961.0,143290.0,157619.0,171948.0,186277.0,200606.0,214935.0,229264.0,243593.0,257922.0,272251.0,286580.0,300909.0,315238.0,329567.0,343896.0,358225.0,372554.0,386883.0,401212.0,415541.0,429870.0,444199.0,458528.0,472857.0,487186.0,501515.0,515844.0,530173.0,544502.0,558831.0,573160.0,587489.0,601818.0,616147.0,630476.0,644805.0,659134.0,673463.0,687792.0,702121.0,716450.0,730779.0,745108.0,759437.0,773766.0,788095.0,802424.0,816753.0,831082.0,845411.0,859740.0,874069.0,888398.0,902727.0,917056.0,931385.0,945714.0,960043.0,974372.0,988701.0,1003030.0,1017359.0,1031688.0,1046017.0,1060346.0,1074675.0,1089004.0,1103333.0,1117662.0,1131991.0,1146320.0,1160649.0,1174978.0,1189307.0,1203636.0,1217965.0,1232294.0,1246623.0,1260952.0,1275281.0,1289610.0,1303939.0,1318268.0,1332597.0,1346926.0,1361255.0,1375584.0,1389913.0,1404242.0,1418571.0,1432900.0],\"times\":[739333.0,930294.0,1439292.0,2381209.0,2553334.0,3020040.0,3793250.0,3903916.0,4413706.0,4997375.0,5472456.0,6182167.0,6270458.0,7169791.0,7258208.0,7666252.0,8385624.0,8618290.0,9297330.0,9793167.0,10247919.0,10650459.0,11044081.0,11267793.0,11952582.0,12851001.0,13438918.0,13718794.0,14267169.0,14648752.0,14671041.0,15399125.0,16317333.0,16568501.0,18163415.0,18346041.0,18047542.0,18330834.0,18074375.0,19051917.0,19875710.0,20165624.0,20815500.0,20807040.0,21381335.0,29240124.0,28650167.0,29604293.0,30110085.0,29904792.0,29316919.0,30719250.0,32658083.0,30455042.0,31327918.0,30897417.0,31433209.0,31950707.0,31103792.0,31758210.0,31874252.0,31525957.0,34229541.0,32528333.0,32856125.0,33191583.0,33930082.0,40200626.0,41079540.0,40686125.0,41642208.0,42629876.0,43854375.0,43213083.0,43779583.0,43837583.0,44017541.0,45140540.0,46399083.0,46066375.0,46081041.0,47166752.0,46967791.0,48249167.0,48644831.0,49607666.0,49854251.0,49400208.0,50708584.0,58553834.0,56177916.0,58142751.0,56763334.0,57338999.0,56514166.0,56813543.0,56053292.0,56978124.0,56997711.0,55953292.0]}"
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  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/10/base/tukey.json",
    "content": "[14.82768036970787,24.479678755388726,50.21834111720434,59.870339502885194]"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/10/change/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.03481831569268849,\"upper_bound\":0.02147334886211855},\"point_estimate\":-0.00677152375082668,\"standard_error\":0.014461411496641352},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.08863317024331407,\"upper_bound\":0.06693295151217193},\"point_estimate\":-0.02561912219029061,\"standard_error\":0.04203762102205791}}"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/10/new/benchmark.json",
    "content": "{\"group_id\":\"Import as borrowed, own and destroy\",\"function_id\":\"FlexStr 0.10 (LocalStr)\",\"value_str\":\"10\",\"throughput\":null,\"full_id\":\"Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/10\",\"directory_name\":\"Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/10\",\"title\":\"Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/10\"}"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/10/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":36.96532161122457,\"upper_bound\":38.44623909034577},\"point_estimate\":37.693408832735685,\"standard_error\":0.37746492273982185},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":35.45367381981849,\"upper_bound\":39.702822300281994},\"point_estimate\":37.37861529565417,\"standard_error\":1.2894991541608052},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.0247862835297123,\"upper_bound\":5.498327211736226},\"point_estimate\":4.770148198349551,\"standard_error\":0.6312379360653394},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":39.11670621587491,\"upper_bound\":40.3207643739608},\"point_estimate\":39.74821246383323,\"standard_error\":0.30741017862485825},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.3073753737159124,\"upper_bound\":4.344770450701192},\"point_estimate\":3.796983054568984,\"standard_error\":0.2696360740330035}}"
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    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/10/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[14329.0,28658.0,42987.0,57316.0,71645.0,85974.0,100303.0,114632.0,128961.0,143290.0,157619.0,171948.0,186277.0,200606.0,214935.0,229264.0,243593.0,257922.0,272251.0,286580.0,300909.0,315238.0,329567.0,343896.0,358225.0,372554.0,386883.0,401212.0,415541.0,429870.0,444199.0,458528.0,472857.0,487186.0,501515.0,515844.0,530173.0,544502.0,558831.0,573160.0,587489.0,601818.0,616147.0,630476.0,644805.0,659134.0,673463.0,687792.0,702121.0,716450.0,730779.0,745108.0,759437.0,773766.0,788095.0,802424.0,816753.0,831082.0,845411.0,859740.0,874069.0,888398.0,902727.0,917056.0,931385.0,945714.0,960043.0,974372.0,988701.0,1003030.0,1017359.0,1031688.0,1046017.0,1060346.0,1074675.0,1089004.0,1103333.0,1117662.0,1131991.0,1146320.0,1160649.0,1174978.0,1189307.0,1203636.0,1217965.0,1232294.0,1246623.0,1260952.0,1275281.0,1289610.0,1303939.0,1318268.0,1332597.0,1346926.0,1361255.0,1375584.0,1389913.0,1404242.0,1418571.0,1432900.0],\"times\":[739333.0,930294.0,1439292.0,2381209.0,2553334.0,3020040.0,3793250.0,3903916.0,4413706.0,4997375.0,5472456.0,6182167.0,6270458.0,7169791.0,7258208.0,7666252.0,8385624.0,8618290.0,9297330.0,9793167.0,10247919.0,10650459.0,11044081.0,11267793.0,11952582.0,12851001.0,13438918.0,13718794.0,14267169.0,14648752.0,14671041.0,15399125.0,16317333.0,16568501.0,18163415.0,18346041.0,18047542.0,18330834.0,18074375.0,19051917.0,19875710.0,20165624.0,20815500.0,20807040.0,21381335.0,29240124.0,28650167.0,29604293.0,30110085.0,29904792.0,29316919.0,30719250.0,32658083.0,30455042.0,31327918.0,30897417.0,31433209.0,31950707.0,31103792.0,31758210.0,31874252.0,31525957.0,34229541.0,32528333.0,32856125.0,33191583.0,33930082.0,40200626.0,41079540.0,40686125.0,41642208.0,42629876.0,43854375.0,43213083.0,43779583.0,43837583.0,44017541.0,45140540.0,46399083.0,46066375.0,46081041.0,47166752.0,46967791.0,48249167.0,48644831.0,49607666.0,49854251.0,49400208.0,50708584.0,58553834.0,56177916.0,58142751.0,56763334.0,57338999.0,56514166.0,56813543.0,56053292.0,56978124.0,56997711.0,55953292.0]}"
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    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/10/new/tukey.json",
    "content": "[14.82768036970787,24.479678755388726,50.21834111720434,59.870339502885194]"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/10/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/10 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/10</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">39.117 ns</td>\n                                <td>39.748 ns</td>\n                                <td class=\"ci-bound\">40.321 ns</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.5752261</td>\n                                <td>0.5873716</td>\n                                <td class=\"ci-bound\">0.5773510</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">36.965 ns</td>\n                                <td>37.693 ns</td>\n                                <td class=\"ci-bound\">38.446 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">3.3074 ns</td>\n                                <td>3.7970 ns</td>\n                                <td class=\"ci-bound\">4.3448 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">35.454 ns</td>\n                                <td>37.379 ns</td>\n                                <td class=\"ci-bound\">39.703 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">3.0248 ns</td>\n                                <td>4.7701 ns</td>\n                                <td class=\"ci-bound\">5.4983 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−3.4818%</td>\n                            <td>−0.6772%</td>\n                            <td class=\"ci-bound\">+2.1473%</td>\n                            <td>(p = 0.64 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/100/base/benchmark.json",
    "content": "{\"group_id\":\"Import as borrowed, own and destroy\",\"function_id\":\"FlexStr 0.10 (LocalStr)\",\"value_str\":\"100\",\"throughput\":null,\"full_id\":\"Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/100\",\"directory_name\":\"Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/100\",\"title\":\"Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/100\"}"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/100/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":63.09561139243806,\"upper_bound\":69.1657528604034},\"point_estimate\":65.6750645134077,\"standard_error\":1.5791187816154098},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":61.8818127747206,\"upper_bound\":65.0587870899962},\"point_estimate\":62.92521950052867,\"standard_error\":0.7644842518704085},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.8886558729826004,\"upper_bound\":5.944478372431085},\"point_estimate\":4.8022623138117275,\"standard_error\":0.512434382828348},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":64.51765946076037,\"upper_bound\":78.55213770139527},\"point_estimate\":70.4982058543917,\"standard_error\":3.6816657227795377},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":4.424413612979983,\"upper_bound\":24.235667804260803},\"point_estimate\":15.870185141305173,\"standard_error\":5.356864086424078}}"
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    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/100/base/sample.json",
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    "content": "[40.3313260685338,50.186068084343724,76.46538012650353,86.32012214231345]"
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    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/100/change/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.004196768976358198,\"upper_bound\":0.09610178198494383},\"point_estimate\":0.041894080490997965,\"standard_error\":0.026237619214905247},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.026455105091964245,\"upper_bound\":0.03541140155459299},\"point_estimate\":-0.00205124972107662,\"standard_error\":0.015517666147296666}}"
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    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/100/new/benchmark.json",
    "content": "{\"group_id\":\"Import as borrowed, own and destroy\",\"function_id\":\"FlexStr 0.10 (LocalStr)\",\"value_str\":\"100\",\"throughput\":null,\"full_id\":\"Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/100\",\"directory_name\":\"Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/100\",\"title\":\"Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/100\"}"
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    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/100/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":63.09561139243806,\"upper_bound\":69.1657528604034},\"point_estimate\":65.6750645134077,\"standard_error\":1.5791187816154098},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":61.8818127747206,\"upper_bound\":65.0587870899962},\"point_estimate\":62.92521950052867,\"standard_error\":0.7644842518704085},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.8886558729826004,\"upper_bound\":5.944478372431085},\"point_estimate\":4.8022623138117275,\"standard_error\":0.512434382828348},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":64.51765946076037,\"upper_bound\":78.55213770139527},\"point_estimate\":70.4982058543917,\"standard_error\":3.6816657227795377},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":4.424413612979983,\"upper_bound\":24.235667804260803},\"point_estimate\":15.870185141305173,\"standard_error\":5.356864086424078}}"
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    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/100/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[8339.0,16678.0,25017.0,33356.0,41695.0,50034.0,58373.0,66712.0,75051.0,83390.0,91729.0,100068.0,108407.0,116746.0,125085.0,133424.0,141763.0,150102.0,158441.0,166780.0,175119.0,183458.0,191797.0,200136.0,208475.0,216814.0,225153.0,233492.0,241831.0,250170.0,258509.0,266848.0,275187.0,283526.0,291865.0,300204.0,308543.0,316882.0,325221.0,333560.0,341899.0,350238.0,358577.0,366916.0,375255.0,383594.0,391933.0,400272.0,408611.0,416950.0,425289.0,433628.0,441967.0,450306.0,458645.0,466984.0,475323.0,483662.0,492001.0,500340.0,508679.0,517018.0,525357.0,533696.0,542035.0,550374.0,558713.0,567052.0,575391.0,583730.0,592069.0,600408.0,608747.0,617086.0,625425.0,633764.0,642103.0,650442.0,658781.0,667120.0,675459.0,683798.0,692137.0,700476.0,708815.0,717154.0,725493.0,733832.0,742171.0,750510.0,758849.0,767188.0,775527.0,783866.0,792205.0,800544.0,808883.0,817222.0,825561.0,833900.0],\"times\":[467916.0,1344831.0,1371211.0,2328166.0,2732707.0,2736290.0,3240794.0,4085124.0,4177957.0,4618752.0,5456040.0,6622750.0,6766917.0,7272750.0,7400374.0,7536708.0,9248707.0,9459751.0,10042084.0,10968083.0,10935498.0,11357333.0,13113958.0,13039167.0,13005792.0,12820001.0,13391374.0,14139417.0,14661292.0,15185038.0,17164583.0,17417585.0,17960501.0,18677539.0,18689249.0,18413795.0,18820290.0,18932794.0,19828625.0,19905124.0,20473958.0,23951584.0,23997456.0,24088415.0,24818335.0,24920584.0,24021498.0,23803749.0,23569417.0,24822876.0,25707916.0,25886500.0,31231583.0,30679667.0,30502708.0,30927750.0,29970417.0,30360917.0,29179833.0,29022044.0,29598666.0,30136335.0,30644209.0,37109667.0,37671041.0,37277250.0,36775208.0,35933709.0,35101083.0,34919583.0,34185125.0,37060374.0,37156084.0,37082792.0,44068792.0,43322374.0,43735167.0,42265875.0,41390082.0,41753167.0,41904334.0,41305417.0,44135041.0,44829334.0,43384291.0,50037874.0,49504459.0,49371834.0,50327123.0,52393665.0,62155666.0,127795459.0,135763209.0,55641501.0,50927874.0,49840960.0,59554164.0,55792041.0,54064084.0,56143375.0]}"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/100/new/tukey.json",
    "content": "[40.3313260685338,50.186068084343724,76.46538012650353,86.32012214231345]"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/100/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/100 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/100</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">64.518 ns</td>\n                                <td>70.498 ns</td>\n                                <td class=\"ci-bound\">78.552 ns</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.0506620</td>\n                                <td>0.0537241</td>\n                                <td class=\"ci-bound\">0.0484169</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">63.096 ns</td>\n                                <td>65.675 ns</td>\n                                <td class=\"ci-bound\">69.166 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">4.4244 ns</td>\n                                <td>15.870 ns</td>\n                                <td class=\"ci-bound\">24.236 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">61.882 ns</td>\n                                <td>62.925 ns</td>\n                                <td class=\"ci-bound\">65.059 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">3.8887 ns</td>\n                                <td>4.8023 ns</td>\n                                <td class=\"ci-bound\">5.9445 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−0.4197%</td>\n                            <td>+4.1894%</td>\n                            <td class=\"ci-bound\">+9.6102%</td>\n                            <td>(p = 0.10 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/20/base/benchmark.json",
    "content": "{\"group_id\":\"Import as borrowed, own and destroy\",\"function_id\":\"FlexStr 0.10 (LocalStr)\",\"value_str\":\"20\",\"throughput\":null,\"full_id\":\"Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/20\",\"directory_name\":\"Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/20\",\"title\":\"Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/20\"}"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/20/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":37.795331996381336,\"upper_bound\":39.18099784967492},\"point_estimate\":38.49395682818282,\"standard_error\":0.3544120090205367},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":38.42500521602052,\"upper_bound\":39.81468867292351},\"point_estimate\":39.152679160792005,\"standard_error\":0.37374612909121524},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.7854260841561933,\"upper_bound\":5.262949147288018},\"point_estimate\":4.082798194501101,\"standard_error\":0.6516667732660264},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":39.38900551981099,\"upper_bound\":40.748741111902866},\"point_estimate\":40.09521248681141,\"standard_error\":0.34668175315348326},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.1859149954359065,\"upper_bound\":3.891975142776926},\"point_estimate\":3.5654471401307646,\"standard_error\":0.17952214527003427}}"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/20/base/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[13622.0,27244.0,40866.0,54488.0,68110.0,81732.0,95354.0,108976.0,122598.0,136220.0,149842.0,163464.0,177086.0,190708.0,204330.0,217952.0,231574.0,245196.0,258818.0,272440.0,286062.0,299684.0,313306.0,326928.0,340550.0,354172.0,367794.0,381416.0,395038.0,408660.0,422282.0,435904.0,449526.0,463148.0,476770.0,490392.0,504014.0,517636.0,531258.0,544880.0,558502.0,572124.0,585746.0,599368.0,612990.0,626612.0,640234.0,653856.0,667478.0,681100.0,694722.0,708344.0,721966.0,735588.0,749210.0,762832.0,776454.0,790076.0,803698.0,817320.0,830942.0,844564.0,858186.0,871808.0,885430.0,899052.0,912674.0,926296.0,939918.0,953540.0,967162.0,980784.0,994406.0,1008028.0,1021650.0,1035272.0,1048894.0,1062516.0,1076138.0,1089760.0,1103382.0,1117004.0,1130626.0,1144248.0,1157870.0,1171492.0,1185114.0,1198736.0,1212358.0,1225980.0,1239602.0,1253224.0,1266846.0,1280468.0,1294090.0,1307712.0,1321334.0,1334956.0,1348578.0,1362200.0],\"times\":[467625.0,1265667.0,1320001.0,2351791.0,2294000.0,2721542.0,3163959.0,4068251.0,4038460.0,4877042.0,5314375.0,5371250.0,5793125.0,6362543.0,6746461.0,7232250.0,7518586.0,8025374.0,8892958.0,9360794.0,9486001.0,10062249.0,10410042.0,14266543.0,14116248.0,14271458.0,14753834.0,14953998.0,15139000.0,15132664.0,15590750.0,15300585.0,15906876.0,15515127.0,15913751.0,19739333.0,20332375.0,19890166.0,21078335.0,21903958.0,22426123.0,21964165.0,22688543.0,23352293.0,23752918.0,24129209.0,25046041.0,28849917.0,28538917.0,28530000.0,28058625.0,28092418.0,27789666.0,27143418.0,27046082.0,27080414.0,27674501.0,27113207.0,31493085.0,31786790.0,32947668.0,33965833.0,34489753.0,34361083.0,38166377.0,38574417.0,38669334.0,38598999.0,39366915.0,39205666.0,42699498.0,41985000.0,41680999.0,40919084.0,40586001.0,41362335.0,39599043.0,39737833.0,39179876.0,39032540.0,38396001.0,38257666.0,44185083.0,46580000.0,45622250.0,47118668.0,46647501.0,47953041.0,53896583.0,52639124.0,52253583.0,53893208.0,54346167.0,54211168.0,57230210.0,56834000.0,54589752.0,54292085.0,53366709.0,52908584.0]}"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/20/base/tukey.json",
    "content": "[19.355620825364632,27.40099299833921,48.85531879293808,56.90069096591266]"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/20/change/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.024646971418838363,\"upper_bound\":0.027873710936417873},\"point_estimate\":0.0018553307930682106,\"standard_error\":0.01337991156441059},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.02389320052855859,\"upper_bound\":0.029375067612670978},\"point_estimate\":-0.0002154810614773961,\"standard_error\":0.014283210909449864}}"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/20/new/benchmark.json",
    "content": "{\"group_id\":\"Import as borrowed, own and destroy\",\"function_id\":\"FlexStr 0.10 (LocalStr)\",\"value_str\":\"20\",\"throughput\":null,\"full_id\":\"Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/20\",\"directory_name\":\"Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/20\",\"title\":\"Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/20\"}"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/20/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":37.795331996381336,\"upper_bound\":39.18099784967492},\"point_estimate\":38.49395682818282,\"standard_error\":0.3544120090205367},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":38.42500521602052,\"upper_bound\":39.81468867292351},\"point_estimate\":39.152679160792005,\"standard_error\":0.37374612909121524},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.7854260841561933,\"upper_bound\":5.262949147288018},\"point_estimate\":4.082798194501101,\"standard_error\":0.6516667732660264},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":39.38900551981099,\"upper_bound\":40.748741111902866},\"point_estimate\":40.09521248681141,\"standard_error\":0.34668175315348326},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.1859149954359065,\"upper_bound\":3.891975142776926},\"point_estimate\":3.5654471401307646,\"standard_error\":0.17952214527003427}}"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/20/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[13622.0,27244.0,40866.0,54488.0,68110.0,81732.0,95354.0,108976.0,122598.0,136220.0,149842.0,163464.0,177086.0,190708.0,204330.0,217952.0,231574.0,245196.0,258818.0,272440.0,286062.0,299684.0,313306.0,326928.0,340550.0,354172.0,367794.0,381416.0,395038.0,408660.0,422282.0,435904.0,449526.0,463148.0,476770.0,490392.0,504014.0,517636.0,531258.0,544880.0,558502.0,572124.0,585746.0,599368.0,612990.0,626612.0,640234.0,653856.0,667478.0,681100.0,694722.0,708344.0,721966.0,735588.0,749210.0,762832.0,776454.0,790076.0,803698.0,817320.0,830942.0,844564.0,858186.0,871808.0,885430.0,899052.0,912674.0,926296.0,939918.0,953540.0,967162.0,980784.0,994406.0,1008028.0,1021650.0,1035272.0,1048894.0,1062516.0,1076138.0,1089760.0,1103382.0,1117004.0,1130626.0,1144248.0,1157870.0,1171492.0,1185114.0,1198736.0,1212358.0,1225980.0,1239602.0,1253224.0,1266846.0,1280468.0,1294090.0,1307712.0,1321334.0,1334956.0,1348578.0,1362200.0],\"times\":[467625.0,1265667.0,1320001.0,2351791.0,2294000.0,2721542.0,3163959.0,4068251.0,4038460.0,4877042.0,5314375.0,5371250.0,5793125.0,6362543.0,6746461.0,7232250.0,7518586.0,8025374.0,8892958.0,9360794.0,9486001.0,10062249.0,10410042.0,14266543.0,14116248.0,14271458.0,14753834.0,14953998.0,15139000.0,15132664.0,15590750.0,15300585.0,15906876.0,15515127.0,15913751.0,19739333.0,20332375.0,19890166.0,21078335.0,21903958.0,22426123.0,21964165.0,22688543.0,23352293.0,23752918.0,24129209.0,25046041.0,28849917.0,28538917.0,28530000.0,28058625.0,28092418.0,27789666.0,27143418.0,27046082.0,27080414.0,27674501.0,27113207.0,31493085.0,31786790.0,32947668.0,33965833.0,34489753.0,34361083.0,38166377.0,38574417.0,38669334.0,38598999.0,39366915.0,39205666.0,42699498.0,41985000.0,41680999.0,40919084.0,40586001.0,41362335.0,39599043.0,39737833.0,39179876.0,39032540.0,38396001.0,38257666.0,44185083.0,46580000.0,45622250.0,47118668.0,46647501.0,47953041.0,53896583.0,52639124.0,52253583.0,53893208.0,54346167.0,54211168.0,57230210.0,56834000.0,54589752.0,54292085.0,53366709.0,52908584.0]}"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/20/new/tukey.json",
    "content": "[19.355620825364632,27.40099299833921,48.85531879293808,56.90069096591266]"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/20/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/20 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/20</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">39.389 ns</td>\n                                <td>40.095 ns</td>\n                                <td class=\"ci-bound\">40.749 ns</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.5698729</td>\n                                <td>0.5857342</td>\n                                <td class=\"ci-bound\">0.5720979</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">37.795 ns</td>\n                                <td>38.494 ns</td>\n                                <td class=\"ci-bound\">39.181 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">3.1859 ns</td>\n                                <td>3.5654 ns</td>\n                                <td class=\"ci-bound\">3.8920 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">38.425 ns</td>\n                                <td>39.153 ns</td>\n                                <td class=\"ci-bound\">39.815 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">2.7854 ns</td>\n                                <td>4.0828 ns</td>\n                                <td class=\"ci-bound\">5.2629 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−2.4647%</td>\n                            <td>+0.1855%</td>\n                            <td class=\"ci-bound\">+2.7874%</td>\n                            <td>(p = 0.89 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/500/base/benchmark.json",
    "content": "{\"group_id\":\"Import as borrowed, own and destroy\",\"function_id\":\"FlexStr 0.10 (LocalStr)\",\"value_str\":\"500\",\"throughput\":null,\"full_id\":\"Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/500\",\"directory_name\":\"Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/500\",\"title\":\"Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/500\"}"
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    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":101.41125251183178,\"upper_bound\":103.43569504046535},\"point_estimate\":102.47813369457954,\"standard_error\":0.5173568169322026},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":102.08968866196793,\"upper_bound\":104.1947918611163},\"point_estimate\":103.02826595972908,\"standard_error\":0.5355305959141878},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.8917616287383305,\"upper_bound\":4.7363410946295},\"point_estimate\":3.5840359374538533,\"standard_error\":0.4895572983038598},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":103.43760835134167,\"upper_bound\":104.95985315107106},\"point_estimate\":104.18668036846285,\"standard_error\":0.3881691601168593},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.537153255224193,\"upper_bound\":6.640085901029809},\"point_estimate\":5.197795848722108,\"standard_error\":0.7845612213022684}}"
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    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/500/base/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[4870.0,9740.0,14610.0,19480.0,24350.0,29220.0,34090.0,38960.0,43830.0,48700.0,53570.0,58440.0,63310.0,68180.0,73050.0,77920.0,82790.0,87660.0,92530.0,97400.0,102270.0,107140.0,112010.0,116880.0,121750.0,126620.0,131490.0,136360.0,141230.0,146100.0,150970.0,155840.0,160710.0,165580.0,170450.0,175320.0,180190.0,185060.0,189930.0,194800.0,199670.0,204540.0,209410.0,214280.0,219150.0,224020.0,228890.0,233760.0,238630.0,243500.0,248370.0,253240.0,258110.0,262980.0,267850.0,272720.0,277590.0,282460.0,287330.0,292200.0,297070.0,301940.0,306810.0,311680.0,316550.0,321420.0,326290.0,331160.0,336030.0,340900.0,345770.0,350640.0,355510.0,360380.0,365250.0,370120.0,374990.0,379860.0,384730.0,389600.0,394470.0,399340.0,404210.0,409080.0,413950.0,418820.0,423690.0,428560.0,433430.0,438300.0,443170.0,448040.0,452910.0,457780.0,462650.0,467520.0,472390.0,477260.0,482130.0,487000.0],\"times\":[399333.0,774335.0,1408709.0,1574669.0,2344208.0,2768332.0,3553083.0,3604208.0,4192290.0,4819292.0,5312501.0,5655083.0,6130707.0,6633126.0,7310085.0,8280666.0,8437499.0,9064252.0,9223668.0,9893124.0,10435542.0,11429082.0,11806709.0,12408666.0,12809585.0,13929709.0,13364793.0,14551333.0,14374124.0,15038292.0,16280416.0,15942834.0,15800208.0,16708252.0,18082375.0,18711042.0,18395541.0,18395375.0,18813128.0,19382877.0,21354833.0,21596376.0,22035378.0,21744874.0,22364708.0,23838209.0,24547540.0,25146043.0,25963707.0,25756666.0,26129208.0,26122168.0,26678377.0,26470000.0,27050499.0,27633374.0,29641459.0,28737543.0,29439374.0,29916667.0,32215040.0,31213665.0,31920667.0,32595081.0,34568250.0,33490290.0,33648667.0,34234792.0,35649625.0,35253917.0,36425125.0,36856249.0,37527126.0,36281458.0,36777955.0,37448542.0,37853084.0,38584834.0,38580498.0,39919249.0,41238042.0,40960250.0,39999834.0,41828209.0,41922084.0,42833582.0,43824832.0,45732333.0,44341708.0,47166207.0,46747210.0,47594792.0,48242414.0,49016543.0,48269418.0,47678001.0,50324083.0,50196459.0,54004581.0,52034458.0]}"
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    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/500/base/tukey.json",
    "content": "[86.17766379966207,93.55635389649603,113.23286082138662,120.6115509182206]"
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  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/500/change/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.043012825512955585,\"upper_bound\":-0.011336125264364361},\"point_estimate\":-0.02684250511934272,\"standard_error\":0.008055076718631272},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.03390718137304349,\"upper_bound\":-0.010523938793494003},\"point_estimate\":-0.023813488231509194,\"standard_error\":0.006266460725942023}}"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/500/new/benchmark.json",
    "content": "{\"group_id\":\"Import as borrowed, own and destroy\",\"function_id\":\"FlexStr 0.10 (LocalStr)\",\"value_str\":\"500\",\"throughput\":null,\"full_id\":\"Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/500\",\"directory_name\":\"Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/500\",\"title\":\"Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/500\"}"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/500/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":101.41125251183178,\"upper_bound\":103.43569504046535},\"point_estimate\":102.47813369457954,\"standard_error\":0.5173568169322026},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":102.08968866196793,\"upper_bound\":104.1947918611163},\"point_estimate\":103.02826595972908,\"standard_error\":0.5355305959141878},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.8917616287383305,\"upper_bound\":4.7363410946295},\"point_estimate\":3.5840359374538533,\"standard_error\":0.4895572983038598},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":103.43760835134167,\"upper_bound\":104.95985315107106},\"point_estimate\":104.18668036846285,\"standard_error\":0.3881691601168593},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.537153255224193,\"upper_bound\":6.640085901029809},\"point_estimate\":5.197795848722108,\"standard_error\":0.7845612213022684}}"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/500/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[4870.0,9740.0,14610.0,19480.0,24350.0,29220.0,34090.0,38960.0,43830.0,48700.0,53570.0,58440.0,63310.0,68180.0,73050.0,77920.0,82790.0,87660.0,92530.0,97400.0,102270.0,107140.0,112010.0,116880.0,121750.0,126620.0,131490.0,136360.0,141230.0,146100.0,150970.0,155840.0,160710.0,165580.0,170450.0,175320.0,180190.0,185060.0,189930.0,194800.0,199670.0,204540.0,209410.0,214280.0,219150.0,224020.0,228890.0,233760.0,238630.0,243500.0,248370.0,253240.0,258110.0,262980.0,267850.0,272720.0,277590.0,282460.0,287330.0,292200.0,297070.0,301940.0,306810.0,311680.0,316550.0,321420.0,326290.0,331160.0,336030.0,340900.0,345770.0,350640.0,355510.0,360380.0,365250.0,370120.0,374990.0,379860.0,384730.0,389600.0,394470.0,399340.0,404210.0,409080.0,413950.0,418820.0,423690.0,428560.0,433430.0,438300.0,443170.0,448040.0,452910.0,457780.0,462650.0,467520.0,472390.0,477260.0,482130.0,487000.0],\"times\":[399333.0,774335.0,1408709.0,1574669.0,2344208.0,2768332.0,3553083.0,3604208.0,4192290.0,4819292.0,5312501.0,5655083.0,6130707.0,6633126.0,7310085.0,8280666.0,8437499.0,9064252.0,9223668.0,9893124.0,10435542.0,11429082.0,11806709.0,12408666.0,12809585.0,13929709.0,13364793.0,14551333.0,14374124.0,15038292.0,16280416.0,15942834.0,15800208.0,16708252.0,18082375.0,18711042.0,18395541.0,18395375.0,18813128.0,19382877.0,21354833.0,21596376.0,22035378.0,21744874.0,22364708.0,23838209.0,24547540.0,25146043.0,25963707.0,25756666.0,26129208.0,26122168.0,26678377.0,26470000.0,27050499.0,27633374.0,29641459.0,28737543.0,29439374.0,29916667.0,32215040.0,31213665.0,31920667.0,32595081.0,34568250.0,33490290.0,33648667.0,34234792.0,35649625.0,35253917.0,36425125.0,36856249.0,37527126.0,36281458.0,36777955.0,37448542.0,37853084.0,38584834.0,38580498.0,39919249.0,41238042.0,40960250.0,39999834.0,41828209.0,41922084.0,42833582.0,43824832.0,45732333.0,44341708.0,47166207.0,46747210.0,47594792.0,48242414.0,49016543.0,48269418.0,47678001.0,50324083.0,50196459.0,54004581.0,52034458.0]}"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/500/new/tukey.json",
    "content": "[86.17766379966207,93.55635389649603,113.23286082138662,120.6115509182206]"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/500/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/500 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/500</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">103.44 ns</td>\n                                <td>104.19 ns</td>\n                                <td class=\"ci-bound\">104.96 ns</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.9103754</td>\n                                <td>0.9157277</td>\n                                <td class=\"ci-bound\">0.9100276</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">101.41 ns</td>\n                                <td>102.48 ns</td>\n                                <td class=\"ci-bound\">103.44 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">3.5372 ns</td>\n                                <td>5.1978 ns</td>\n                                <td class=\"ci-bound\">6.6401 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">102.09 ns</td>\n                                <td>103.03 ns</td>\n                                <td class=\"ci-bound\">104.19 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">2.8918 ns</td>\n                                <td>3.5840 ns</td>\n                                <td class=\"ci-bound\">4.7363 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−4.3013%</td>\n                            <td>−2.6843%</td>\n                            <td class=\"ci-bound\">−1.1336%</td>\n                            <td>(p = 0.00 &lt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                Performance has improved.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr) Summary - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)</h2>\n        <h3>Violin Plot</h3>\n        <a href=\"violin.svg\">\n            <img src=\"violin.svg\" alt=\"Violin Plot\" />\n        </a>\n        <p>This chart shows the relationship between function/parameter and iteration time. The thickness of the shaded\n            region indicates the probability that a measurement of the given function/parameter would take a particular\n            length of time.</p>\n        <h3>Line Chart</h3>\n        <img src=\"lines.svg\" alt=\"Line Chart\" />\n        <p>This chart shows the mean measured time for each function as the input (or the size of the input) increases.</p>\n        <section class=\"plots\">\n            <a href=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/0/report/index.html\">\n                <h4>Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/0/report/pdf.svg\">\n                                <img src=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/0/report/regression.svg\">\n                                <img src=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/10/report/index.html\">\n                <h4>Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/10/report/pdf.svg\">\n                                <img src=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/10/report/regression.svg\">\n                                <img src=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/20/report/index.html\">\n                <h4>Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/20/report/pdf.svg\">\n                                <img src=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/20/report/regression.svg\">\n                                <img src=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/100/report/index.html\">\n                <h4>Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/100/report/pdf.svg\">\n                                <img src=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/100/report/regression.svg\">\n                                <img src=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/500/report/index.html\">\n                <h4>Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/500/report/pdf.svg\">\n                                <img src=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/500/report/regression.svg\">\n                                <img src=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/0/base/benchmark.json",
    "content": "{\"group_id\":\"Import as borrowed, own and destroy\",\"function_id\":\"FlexStr 0.10 (SharedStr)\",\"value_str\":\"0\",\"throughput\":null,\"full_id\":\"Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/0\",\"directory_name\":\"Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/0\",\"title\":\"Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/0\"}"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/0/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":9.659428425668018,\"upper_bound\":9.86774218348159},\"point_estimate\":9.742384252164781,\"standard_error\":0.05458524941852085},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":9.64407897930771,\"upper_bound\":9.73637758603121},\"point_estimate\":9.696138680212002,\"standard_error\":0.024337153509998967},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.09797791129892536,\"upper_bound\":0.1862310849654595},\"point_estimate\":0.1368267365618609,\"standard_error\":0.02279367026383861},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":9.61458898821303,\"upper_bound\":9.685198515804275},\"point_estimate\":9.648604318895451,\"standard_error\":0.01807709047155808},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.15871389078130899,\"upper_bound\":0.8897514531602044},\"point_estimate\":0.5460705139630668,\"standard_error\":0.22728250644988585}}"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/0/base/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[70170.0,140340.0,210510.0,280680.0,350850.0,421020.0,491190.0,561360.0,631530.0,701700.0,771870.0,842040.0,912210.0,982380.0,1052550.0,1122720.0,1192890.0,1263060.0,1333230.0,1403400.0,1473570.0,1543740.0,1613910.0,1684080.0,1754250.0,1824420.0,1894590.0,1964760.0,2034930.0,2105100.0,2175270.0,2245440.0,2315610.0,2385780.0,2455950.0,2526120.0,2596290.0,2666460.0,2736630.0,2806800.0,2876970.0,2947140.0,3017310.0,3087480.0,3157650.0,3227820.0,3297990.0,3368160.0,3438330.0,3508500.0,3578670.0,3648840.0,3719010.0,3789180.0,3859350.0,3929520.0,3999690.0,4069860.0,4140030.0,4210200.0,4280370.0,4350540.0,4420710.0,4490880.0,4561050.0,4631220.0,4701390.0,4771560.0,4841730.0,4911900.0,4982070.0,5052240.0,5122410.0,5192580.0,5262750.0,5332920.0,5403090.0,5473260.0,5543430.0,5613600.0,5683770.0,5753940.0,5824110.0,5894280.0,5964450.0,6034620.0,6104790.0,6174960.0,6245130.0,6315300.0,6385470.0,6455640.0,6525810.0,6595980.0,6666150.0,6736320.0,6806490.0,6876660.0,6946830.0,7017000.0],\"times\":[1024918.0,1311625.0,1960916.0,2918250.0,3271335.0,4735123.0,4616626.0,5258041.0,6040125.0,6885958.0,7685126.0,8414210.0,9063416.0,9313835.0,10993625.0,10726000.0,11345917.0,12515209.0,12891750.0,13378376.0,14027918.0,14867833.0,15594833.0,16127292.0,16662667.0,17584375.0,18133000.0,18959585.0,19694582.0,20451501.0,20987960.0,21733502.0,22676041.0,22941291.0,23807834.0,24025959.0,24893124.0,25395624.0,26634458.0,27309250.0,27727875.0,28439373.0,29297959.0,29952749.0,30600875.0,31568333.0,32354416.0,33602083.0,33949166.0,33702750.0,34446418.0,35393376.0,36815958.0,36632625.0,37567750.0,38310167.0,38964876.0,39658167.0,40271043.0,41069791.0,41818375.0,42452250.0,43217209.0,44007875.0,44602416.0,45272835.0,45915708.0,46633083.0,47268165.0,47974334.0,48671998.0,49389457.0,49920543.0,51069709.0,51473458.0,52108209.0,52783667.0,53492959.0,54001208.0,54960540.0,55427416.0,55990331.0,55909582.0,57164711.0,56865498.0,57344915.0,57889917.0,58649750.0,59497668.0,59902665.0,60287209.0,61385710.0,61837083.0,63302082.0,64036459.0,63670458.0,64001042.0,65844917.0,66355875.0,66913917.0]}"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/0/base/tukey.json",
    "content": "[8.898014097763701,9.225596694806683,10.0991502869213,10.426732883964283]"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/0/change/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.0530658948708273,\"upper_bound\":-0.002599609723650051},\"point_estimate\":-0.025986609528683924,\"standard_error\":0.01289387677260734},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.011825238562651497,\"upper_bound\":-0.0007707762091008208},\"point_estimate\":-0.006062192388290533,\"standard_error\":0.002856913973866556}}"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/0/new/benchmark.json",
    "content": "{\"group_id\":\"Import as borrowed, own and destroy\",\"function_id\":\"FlexStr 0.10 (SharedStr)\",\"value_str\":\"0\",\"throughput\":null,\"full_id\":\"Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/0\",\"directory_name\":\"Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/0\",\"title\":\"Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/0\"}"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/0/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":9.659428425668018,\"upper_bound\":9.86774218348159},\"point_estimate\":9.742384252164781,\"standard_error\":0.05458524941852085},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":9.64407897930771,\"upper_bound\":9.73637758603121},\"point_estimate\":9.696138680212002,\"standard_error\":0.024337153509998967},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.09797791129892536,\"upper_bound\":0.1862310849654595},\"point_estimate\":0.1368267365618609,\"standard_error\":0.02279367026383861},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":9.61458898821303,\"upper_bound\":9.685198515804275},\"point_estimate\":9.648604318895451,\"standard_error\":0.01807709047155808},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.15871389078130899,\"upper_bound\":0.8897514531602044},\"point_estimate\":0.5460705139630668,\"standard_error\":0.22728250644988585}}"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/0/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[70170.0,140340.0,210510.0,280680.0,350850.0,421020.0,491190.0,561360.0,631530.0,701700.0,771870.0,842040.0,912210.0,982380.0,1052550.0,1122720.0,1192890.0,1263060.0,1333230.0,1403400.0,1473570.0,1543740.0,1613910.0,1684080.0,1754250.0,1824420.0,1894590.0,1964760.0,2034930.0,2105100.0,2175270.0,2245440.0,2315610.0,2385780.0,2455950.0,2526120.0,2596290.0,2666460.0,2736630.0,2806800.0,2876970.0,2947140.0,3017310.0,3087480.0,3157650.0,3227820.0,3297990.0,3368160.0,3438330.0,3508500.0,3578670.0,3648840.0,3719010.0,3789180.0,3859350.0,3929520.0,3999690.0,4069860.0,4140030.0,4210200.0,4280370.0,4350540.0,4420710.0,4490880.0,4561050.0,4631220.0,4701390.0,4771560.0,4841730.0,4911900.0,4982070.0,5052240.0,5122410.0,5192580.0,5262750.0,5332920.0,5403090.0,5473260.0,5543430.0,5613600.0,5683770.0,5753940.0,5824110.0,5894280.0,5964450.0,6034620.0,6104790.0,6174960.0,6245130.0,6315300.0,6385470.0,6455640.0,6525810.0,6595980.0,6666150.0,6736320.0,6806490.0,6876660.0,6946830.0,7017000.0],\"times\":[1024918.0,1311625.0,1960916.0,2918250.0,3271335.0,4735123.0,4616626.0,5258041.0,6040125.0,6885958.0,7685126.0,8414210.0,9063416.0,9313835.0,10993625.0,10726000.0,11345917.0,12515209.0,12891750.0,13378376.0,14027918.0,14867833.0,15594833.0,16127292.0,16662667.0,17584375.0,18133000.0,18959585.0,19694582.0,20451501.0,20987960.0,21733502.0,22676041.0,22941291.0,23807834.0,24025959.0,24893124.0,25395624.0,26634458.0,27309250.0,27727875.0,28439373.0,29297959.0,29952749.0,30600875.0,31568333.0,32354416.0,33602083.0,33949166.0,33702750.0,34446418.0,35393376.0,36815958.0,36632625.0,37567750.0,38310167.0,38964876.0,39658167.0,40271043.0,41069791.0,41818375.0,42452250.0,43217209.0,44007875.0,44602416.0,45272835.0,45915708.0,46633083.0,47268165.0,47974334.0,48671998.0,49389457.0,49920543.0,51069709.0,51473458.0,52108209.0,52783667.0,53492959.0,54001208.0,54960540.0,55427416.0,55990331.0,55909582.0,57164711.0,56865498.0,57344915.0,57889917.0,58649750.0,59497668.0,59902665.0,60287209.0,61385710.0,61837083.0,63302082.0,64036459.0,63670458.0,64001042.0,65844917.0,66355875.0,66913917.0]}"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/0/new/tukey.json",
    "content": "[8.898014097763701,9.225596694806683,10.0991502869213,10.426732883964283]"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/0/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/0 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/0</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">9.6146 ns</td>\n                                <td>9.6486 ns</td>\n                                <td class=\"ci-bound\">9.6852 ns</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.9709256</td>\n                                <td>0.9726333</td>\n                                <td class=\"ci-bound\">0.9706574</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">9.6594 ns</td>\n                                <td>9.7424 ns</td>\n                                <td class=\"ci-bound\">9.8677 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">158.71 ps</td>\n                                <td>546.07 ps</td>\n                                <td class=\"ci-bound\">889.75 ps</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">9.6441 ns</td>\n                                <td>9.6961 ns</td>\n                                <td class=\"ci-bound\">9.7364 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">97.978 ps</td>\n                                <td>136.83 ps</td>\n                                <td class=\"ci-bound\">186.23 ps</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−5.3066%</td>\n                            <td>−2.5987%</td>\n                            <td class=\"ci-bound\">−0.2600%</td>\n                            <td>(p = 0.03 &lt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                Change within noise threshold.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/10/base/benchmark.json",
    "content": "{\"group_id\":\"Import as borrowed, own and destroy\",\"function_id\":\"FlexStr 0.10 (SharedStr)\",\"value_str\":\"10\",\"throughput\":null,\"full_id\":\"Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/10\",\"directory_name\":\"Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/10\",\"title\":\"Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/10\"}"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/10/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":37.250406249327796,\"upper_bound\":38.74280180744994},\"point_estimate\":37.97097286986987,\"standard_error\":0.38062970957633246},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":36.32037953109908,\"upper_bound\":39.44997309294207},\"point_estimate\":37.99267863847946,\"standard_error\":0.8933969342302217},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.997746934038688,\"upper_bound\":5.0790699071364775},\"point_estimate\":4.540411737865676,\"standard_error\":0.5108619196415463},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":38.88738539121213,\"upper_bound\":39.97772868973616},\"point_estimate\":39.44307909184501,\"standard_error\":0.2781635548145071},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.0369562058949664,\"upper_bound\":4.840835912721742},\"point_estimate\":3.8296230714241557,\"standard_error\":0.5108862950333486}}"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/10/base/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[15253.0,30506.0,45759.0,61012.0,76265.0,91518.0,106771.0,122024.0,137277.0,152530.0,167783.0,183036.0,198289.0,213542.0,228795.0,244048.0,259301.0,274554.0,289807.0,305060.0,320313.0,335566.0,350819.0,366072.0,381325.0,396578.0,411831.0,427084.0,442337.0,457590.0,472843.0,488096.0,503349.0,518602.0,533855.0,549108.0,564361.0,579614.0,594867.0,610120.0,625373.0,640626.0,655879.0,671132.0,686385.0,701638.0,716891.0,732144.0,747397.0,762650.0,777903.0,793156.0,808409.0,823662.0,838915.0,854168.0,869421.0,884674.0,899927.0,915180.0,930433.0,945686.0,960939.0,976192.0,991445.0,1006698.0,1021951.0,1037204.0,1052457.0,1067710.0,1082963.0,1098216.0,1113469.0,1128722.0,1143975.0,1159228.0,1174481.0,1189734.0,1204987.0,1220240.0,1235493.0,1250746.0,1265999.0,1281252.0,1296505.0,1311758.0,1327011.0,1342264.0,1357517.0,1372770.0,1388023.0,1403276.0,1418529.0,1433782.0,1449035.0,1464288.0,1479541.0,1494794.0,1510047.0,1525300.0],\"times\":[885960.0,1035583.0,1560417.0,2582834.0,2652624.0,3768083.0,3676124.0,4978334.0,4668042.0,5147541.0,5737625.0,6280707.0,6566789.0,7816333.0,7790789.0,8303416.0,8892249.0,9497417.0,10253791.0,10518125.0,10979543.0,11465623.0,11728917.0,12842958.0,12968124.0,13808165.0,14134124.0,14444877.0,14692542.0,15647334.0,15758291.0,17111959.0,17179292.0,17888624.0,18374708.0,18940542.0,18533751.0,19136417.0,21452499.0,21673750.0,21255958.0,21888458.0,28168419.0,29719958.0,29554752.0,29923291.0,30206749.0,29999918.0,30172290.0,30866123.0,30718125.0,30702711.0,31654624.0,30934458.0,31886251.0,31291459.0,31801749.0,32315081.0,32213959.0,33924210.0,32764334.0,33696917.0,35832375.0,40248041.0,40993708.0,41448749.0,41694252.0,42223293.0,42279668.0,42597876.0,43667542.0,44532000.0,44073794.0,44484708.0,46227708.0,45876876.0,47401624.0,48016459.0,47516460.0,48329373.0,48859791.0,50395377.0,49588542.0,50445207.0,57785833.0,56416582.0,57577501.0,57898169.0,56986334.0,56740459.0,57096125.0,57495709.0,56703541.0,57629875.0,56896290.0,56049958.0,56244419.0,56325623.0,57346209.0,56456252.0]}"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/10/base/tukey.json",
    "content": "[16.432851663841312,25.430034396043872,49.42252168191737,58.41970441411993]"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/10/change/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.027905529753529466,\"upper_bound\":0.024840446949341403},\"point_estimate\":-0.0010233990571711926,\"standard_error\":0.013486094423047129},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.0630299958307673,\"upper_bound\":0.05717514904050147},\"point_estimate\":-0.00291183184066357,\"standard_error\":0.03178099205679987}}"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/10/new/benchmark.json",
    "content": "{\"group_id\":\"Import as borrowed, own and destroy\",\"function_id\":\"FlexStr 0.10 (SharedStr)\",\"value_str\":\"10\",\"throughput\":null,\"full_id\":\"Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/10\",\"directory_name\":\"Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/10\",\"title\":\"Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/10\"}"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/10/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":37.250406249327796,\"upper_bound\":38.74280180744994},\"point_estimate\":37.97097286986987,\"standard_error\":0.38062970957633246},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":36.32037953109908,\"upper_bound\":39.44997309294207},\"point_estimate\":37.99267863847946,\"standard_error\":0.8933969342302217},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.997746934038688,\"upper_bound\":5.0790699071364775},\"point_estimate\":4.540411737865676,\"standard_error\":0.5108619196415463},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":38.88738539121213,\"upper_bound\":39.97772868973616},\"point_estimate\":39.44307909184501,\"standard_error\":0.2781635548145071},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.0369562058949664,\"upper_bound\":4.840835912721742},\"point_estimate\":3.8296230714241557,\"standard_error\":0.5108862950333486}}"
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  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/10/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[15253.0,30506.0,45759.0,61012.0,76265.0,91518.0,106771.0,122024.0,137277.0,152530.0,167783.0,183036.0,198289.0,213542.0,228795.0,244048.0,259301.0,274554.0,289807.0,305060.0,320313.0,335566.0,350819.0,366072.0,381325.0,396578.0,411831.0,427084.0,442337.0,457590.0,472843.0,488096.0,503349.0,518602.0,533855.0,549108.0,564361.0,579614.0,594867.0,610120.0,625373.0,640626.0,655879.0,671132.0,686385.0,701638.0,716891.0,732144.0,747397.0,762650.0,777903.0,793156.0,808409.0,823662.0,838915.0,854168.0,869421.0,884674.0,899927.0,915180.0,930433.0,945686.0,960939.0,976192.0,991445.0,1006698.0,1021951.0,1037204.0,1052457.0,1067710.0,1082963.0,1098216.0,1113469.0,1128722.0,1143975.0,1159228.0,1174481.0,1189734.0,1204987.0,1220240.0,1235493.0,1250746.0,1265999.0,1281252.0,1296505.0,1311758.0,1327011.0,1342264.0,1357517.0,1372770.0,1388023.0,1403276.0,1418529.0,1433782.0,1449035.0,1464288.0,1479541.0,1494794.0,1510047.0,1525300.0],\"times\":[885960.0,1035583.0,1560417.0,2582834.0,2652624.0,3768083.0,3676124.0,4978334.0,4668042.0,5147541.0,5737625.0,6280707.0,6566789.0,7816333.0,7790789.0,8303416.0,8892249.0,9497417.0,10253791.0,10518125.0,10979543.0,11465623.0,11728917.0,12842958.0,12968124.0,13808165.0,14134124.0,14444877.0,14692542.0,15647334.0,15758291.0,17111959.0,17179292.0,17888624.0,18374708.0,18940542.0,18533751.0,19136417.0,21452499.0,21673750.0,21255958.0,21888458.0,28168419.0,29719958.0,29554752.0,29923291.0,30206749.0,29999918.0,30172290.0,30866123.0,30718125.0,30702711.0,31654624.0,30934458.0,31886251.0,31291459.0,31801749.0,32315081.0,32213959.0,33924210.0,32764334.0,33696917.0,35832375.0,40248041.0,40993708.0,41448749.0,41694252.0,42223293.0,42279668.0,42597876.0,43667542.0,44532000.0,44073794.0,44484708.0,46227708.0,45876876.0,47401624.0,48016459.0,47516460.0,48329373.0,48859791.0,50395377.0,49588542.0,50445207.0,57785833.0,56416582.0,57577501.0,57898169.0,56986334.0,56740459.0,57096125.0,57495709.0,56703541.0,57629875.0,56896290.0,56049958.0,56244419.0,56325623.0,57346209.0,56456252.0]}"
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    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/10/new/tukey.json",
    "content": "[16.432851663841312,25.430034396043872,49.42252168191737,58.41970441411993]"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/10/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/10 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/10</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">38.887 ns</td>\n                                <td>39.443 ns</td>\n                                <td class=\"ci-bound\">39.978 ns</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.5873403</td>\n                                <td>0.5995270</td>\n                                <td class=\"ci-bound\">0.5882288</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">37.250 ns</td>\n                                <td>37.971 ns</td>\n                                <td class=\"ci-bound\">38.743 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">3.0370 ns</td>\n                                <td>3.8296 ns</td>\n                                <td class=\"ci-bound\">4.8408 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">36.320 ns</td>\n                                <td>37.993 ns</td>\n                                <td class=\"ci-bound\">39.450 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">2.9977 ns</td>\n                                <td>4.5404 ns</td>\n                                <td class=\"ci-bound\">5.0791 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−2.7906%</td>\n                            <td>−0.1023%</td>\n                            <td class=\"ci-bound\">+2.4840%</td>\n                            <td>(p = 0.94 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/100/base/benchmark.json",
    "content": "{\"group_id\":\"Import as borrowed, own and destroy\",\"function_id\":\"FlexStr 0.10 (SharedStr)\",\"value_str\":\"100\",\"throughput\":null,\"full_id\":\"Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/100\",\"directory_name\":\"Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/100\",\"title\":\"Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/100\"}"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/100/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":61.58104805055121,\"upper_bound\":63.22595789420465},\"point_estimate\":62.39194774608348,\"standard_error\":0.41997813883863633},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":61.15493950206419,\"upper_bound\":63.10598887202833},\"point_estimate\":62.02729167316088,\"standard_error\":0.45924836415716325},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.6815905624487923,\"upper_bound\":5.590731695726715},\"point_estimate\":4.741245908334975,\"standard_error\":0.498638123147318},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":62.144028894753326,\"upper_bound\":63.90921252826234},\"point_estimate\":63.03342531359788,\"standard_error\":0.44940809910953927},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.6261298290395403,\"upper_bound\":4.8406225658668705},\"point_estimate\":4.226052349393067,\"standard_error\":0.31243418121103983}}"
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    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/100/base/sample.json",
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    "content": "[39.99037679764976,49.64306771897218,75.38357684249866,85.03626776382107]"
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    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/100/change/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.024499483171914638,\"upper_bound\":0.016473290595864755},\"point_estimate\":-0.0037378860139687387,\"standard_error\":0.010468802818836139},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.025996705799392616,\"upper_bound\":0.01954501800241289},\"point_estimate\":-0.003872919276450948,\"standard_error\":0.01174672868838376}}"
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    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/100/new/benchmark.json",
    "content": "{\"group_id\":\"Import as borrowed, own and destroy\",\"function_id\":\"FlexStr 0.10 (SharedStr)\",\"value_str\":\"100\",\"throughput\":null,\"full_id\":\"Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/100\",\"directory_name\":\"Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/100\",\"title\":\"Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/100\"}"
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    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/100/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":61.58104805055121,\"upper_bound\":63.22595789420465},\"point_estimate\":62.39194774608348,\"standard_error\":0.41997813883863633},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":61.15493950206419,\"upper_bound\":63.10598887202833},\"point_estimate\":62.02729167316088,\"standard_error\":0.45924836415716325},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.6815905624487923,\"upper_bound\":5.590731695726715},\"point_estimate\":4.741245908334975,\"standard_error\":0.498638123147318},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":62.144028894753326,\"upper_bound\":63.90921252826234},\"point_estimate\":63.03342531359788,\"standard_error\":0.44940809910953927},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.6261298290395403,\"upper_bound\":4.8406225658668705},\"point_estimate\":4.226052349393067,\"standard_error\":0.31243418121103983}}"
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    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/100/new/sample.json",
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  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/100/new/tukey.json",
    "content": "[39.99037679764976,49.64306771897218,75.38357684249866,85.03626776382107]"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/100/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/100 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/100</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">62.144 ns</td>\n                                <td>63.033 ns</td>\n                                <td class=\"ci-bound\">63.909 ns</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.6611154</td>\n                                <td>0.6743074</td>\n                                <td class=\"ci-bound\">0.6615085</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">61.581 ns</td>\n                                <td>62.392 ns</td>\n                                <td class=\"ci-bound\">63.226 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">3.6261 ns</td>\n                                <td>4.2261 ns</td>\n                                <td class=\"ci-bound\">4.8406 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">61.155 ns</td>\n                                <td>62.027 ns</td>\n                                <td class=\"ci-bound\">63.106 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">3.6816 ns</td>\n                                <td>4.7412 ns</td>\n                                <td class=\"ci-bound\">5.5907 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−2.4499%</td>\n                            <td>−0.3738%</td>\n                            <td class=\"ci-bound\">+1.6473%</td>\n                            <td>(p = 0.72 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/20/base/benchmark.json",
    "content": "{\"group_id\":\"Import as borrowed, own and destroy\",\"function_id\":\"FlexStr 0.10 (SharedStr)\",\"value_str\":\"20\",\"throughput\":null,\"full_id\":\"Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/20\",\"directory_name\":\"Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/20\",\"title\":\"Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/20\"}"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/20/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":39.07139938479099,\"upper_bound\":40.79905984195087},\"point_estimate\":39.91948104422559,\"standard_error\":0.43971046347748705},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":39.792352468007316,\"upper_bound\":41.324861709028724},\"point_estimate\":40.65419052230468,\"standard_error\":0.3575350096430883},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.6318009079986,\"upper_bound\":5.497417396230711},\"point_estimate\":3.9408591468547782,\"standard_error\":0.7586552090383926},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":40.79726648394168,\"upper_bound\":42.305077490781706},\"point_estimate\":41.58030627610225,\"standard_error\":0.38435795412018814},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.5471530576721073,\"upper_bound\":5.45886415465909},\"point_estimate\":4.405059660979711,\"standard_error\":0.5151439107022624}}"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/20/base/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[13675.0,27350.0,41025.0,54700.0,68375.0,82050.0,95725.0,109400.0,123075.0,136750.0,150425.0,164100.0,177775.0,191450.0,205125.0,218800.0,232475.0,246150.0,259825.0,273500.0,287175.0,300850.0,314525.0,328200.0,341875.0,355550.0,369225.0,382900.0,396575.0,410250.0,423925.0,437600.0,451275.0,464950.0,478625.0,492300.0,505975.0,519650.0,533325.0,547000.0,560675.0,574350.0,588025.0,601700.0,615375.0,629050.0,642725.0,656400.0,670075.0,683750.0,697425.0,711100.0,724775.0,738450.0,752125.0,765800.0,779475.0,793150.0,806825.0,820500.0,834175.0,847850.0,861525.0,875200.0,888875.0,902550.0,916225.0,929900.0,943575.0,957250.0,970925.0,984600.0,998275.0,1011950.0,1025625.0,1039300.0,1052975.0,1066650.0,1080325.0,1094000.0,1107675.0,1121350.0,1135025.0,1148700.0,1162375.0,1176050.0,1189725.0,1203400.0,1217075.0,1230750.0,1244425.0,1258100.0,1271775.0,1285450.0,1299125.0,1312800.0,1326475.0,1340150.0,1353825.0,1367500.0],\"times\":[837333.0,902082.0,1358085.0,2262042.0,2382835.0,3214624.0,3709625.0,3756960.0,4076293.0,4593291.0,5007208.0,5542999.0,6309794.0,6442916.0,6826751.0,7260294.0,8274251.0,8648043.0,9067331.0,9050750.0,9480958.0,10082834.0,10527334.0,14807875.0,15049458.0,15166915.0,15525000.0,15314206.0,15743542.0,15555666.0,16362498.0,15780501.0,15842625.0,16022415.0,16428459.0,20194628.0,20966042.0,21574083.0,22156834.0,22130208.0,23038169.0,23150583.0,23807041.0,24379041.0,24828249.0,25977623.0,26137958.0,29423417.0,29240081.0,29280289.0,28923378.0,29318835.0,28504793.0,28483878.0,28975998.0,30955959.0,28472126.0,28992542.0,33066167.0,34442041.0,34155752.0,35012917.0,35848916.0,36400290.0,39887499.0,41370499.0,38959668.0,40455375.0,41613418.0,41173122.0,43132583.0,43531999.0,43613708.0,42753377.0,42684001.0,41818002.0,40970541.0,42018626.0,39989251.0,39762248.0,38716584.0,39324875.0,44708959.0,46815416.0,47290582.0,49706167.0,48351585.0,52813208.0,55996250.0,57109543.0,56335998.0,57489956.0,55712582.0,55518709.0,58525207.0,56757168.0,57619669.0,56046666.0,56506750.0,54416042.0]}"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/20/base/tukey.json",
    "content": "[17.431132218425518,26.852905745867236,51.97763515237848,61.399408679820205]"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/20/change/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.05596129360898528,\"upper_bound\":0.01876693439980723},\"point_estimate\":-0.017337726285738264,\"standard_error\":0.019031294438906107},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.027105993959548047,\"upper_bound\":0.0251079481935772},\"point_estimate\":-0.0017561171151802002,\"standard_error\":0.01316248604741439}}"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/20/new/benchmark.json",
    "content": "{\"group_id\":\"Import as borrowed, own and destroy\",\"function_id\":\"FlexStr 0.10 (SharedStr)\",\"value_str\":\"20\",\"throughput\":null,\"full_id\":\"Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/20\",\"directory_name\":\"Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/20\",\"title\":\"Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/20\"}"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/20/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":39.07139938479099,\"upper_bound\":40.79905984195087},\"point_estimate\":39.91948104422559,\"standard_error\":0.43971046347748705},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":39.792352468007316,\"upper_bound\":41.324861709028724},\"point_estimate\":40.65419052230468,\"standard_error\":0.3575350096430883},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.6318009079986,\"upper_bound\":5.497417396230711},\"point_estimate\":3.9408591468547782,\"standard_error\":0.7586552090383926},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":40.79726648394168,\"upper_bound\":42.305077490781706},\"point_estimate\":41.58030627610225,\"standard_error\":0.38435795412018814},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.5471530576721073,\"upper_bound\":5.45886415465909},\"point_estimate\":4.405059660979711,\"standard_error\":0.5151439107022624}}"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/20/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[13675.0,27350.0,41025.0,54700.0,68375.0,82050.0,95725.0,109400.0,123075.0,136750.0,150425.0,164100.0,177775.0,191450.0,205125.0,218800.0,232475.0,246150.0,259825.0,273500.0,287175.0,300850.0,314525.0,328200.0,341875.0,355550.0,369225.0,382900.0,396575.0,410250.0,423925.0,437600.0,451275.0,464950.0,478625.0,492300.0,505975.0,519650.0,533325.0,547000.0,560675.0,574350.0,588025.0,601700.0,615375.0,629050.0,642725.0,656400.0,670075.0,683750.0,697425.0,711100.0,724775.0,738450.0,752125.0,765800.0,779475.0,793150.0,806825.0,820500.0,834175.0,847850.0,861525.0,875200.0,888875.0,902550.0,916225.0,929900.0,943575.0,957250.0,970925.0,984600.0,998275.0,1011950.0,1025625.0,1039300.0,1052975.0,1066650.0,1080325.0,1094000.0,1107675.0,1121350.0,1135025.0,1148700.0,1162375.0,1176050.0,1189725.0,1203400.0,1217075.0,1230750.0,1244425.0,1258100.0,1271775.0,1285450.0,1299125.0,1312800.0,1326475.0,1340150.0,1353825.0,1367500.0],\"times\":[837333.0,902082.0,1358085.0,2262042.0,2382835.0,3214624.0,3709625.0,3756960.0,4076293.0,4593291.0,5007208.0,5542999.0,6309794.0,6442916.0,6826751.0,7260294.0,8274251.0,8648043.0,9067331.0,9050750.0,9480958.0,10082834.0,10527334.0,14807875.0,15049458.0,15166915.0,15525000.0,15314206.0,15743542.0,15555666.0,16362498.0,15780501.0,15842625.0,16022415.0,16428459.0,20194628.0,20966042.0,21574083.0,22156834.0,22130208.0,23038169.0,23150583.0,23807041.0,24379041.0,24828249.0,25977623.0,26137958.0,29423417.0,29240081.0,29280289.0,28923378.0,29318835.0,28504793.0,28483878.0,28975998.0,30955959.0,28472126.0,28992542.0,33066167.0,34442041.0,34155752.0,35012917.0,35848916.0,36400290.0,39887499.0,41370499.0,38959668.0,40455375.0,41613418.0,41173122.0,43132583.0,43531999.0,43613708.0,42753377.0,42684001.0,41818002.0,40970541.0,42018626.0,39989251.0,39762248.0,38716584.0,39324875.0,44708959.0,46815416.0,47290582.0,49706167.0,48351585.0,52813208.0,55996250.0,57109543.0,56335998.0,57489956.0,55712582.0,55518709.0,58525207.0,56757168.0,57619669.0,56046666.0,56506750.0,54416042.0]}"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/20/new/tukey.json",
    "content": "[17.431132218425518,26.852905745867236,51.97763515237848,61.399408679820205]"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/20/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/20 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/20</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">40.797 ns</td>\n                                <td>41.580 ns</td>\n                                <td class=\"ci-bound\">42.305 ns</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.5311909</td>\n                                <td>0.5478005</td>\n                                <td class=\"ci-bound\">0.5335087</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">39.071 ns</td>\n                                <td>39.919 ns</td>\n                                <td class=\"ci-bound\">40.799 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">3.5472 ns</td>\n                                <td>4.4051 ns</td>\n                                <td class=\"ci-bound\">5.4589 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">39.792 ns</td>\n                                <td>40.654 ns</td>\n                                <td class=\"ci-bound\">41.325 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">2.6318 ns</td>\n                                <td>3.9409 ns</td>\n                                <td class=\"ci-bound\">5.4974 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−5.5961%</td>\n                            <td>−1.7338%</td>\n                            <td class=\"ci-bound\">+1.8767%</td>\n                            <td>(p = 0.38 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
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    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/500/base/benchmark.json",
    "content": "{\"group_id\":\"Import as borrowed, own and destroy\",\"function_id\":\"FlexStr 0.10 (SharedStr)\",\"value_str\":\"500\",\"throughput\":null,\"full_id\":\"Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/500\",\"directory_name\":\"Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/500\",\"title\":\"Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/500\"}"
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    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":100.34076999009623,\"upper_bound\":102.62135839784904},\"point_estimate\":101.54104776709625,\"standard_error\":0.5824977598106748},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":100.87207700745394,\"upper_bound\":103.57875481357003},\"point_estimate\":102.00655469726594,\"standard_error\":0.7194076489955507},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.0845483708128882,\"upper_bound\":5.159185642138225},\"point_estimate\":4.132181553183208,\"standard_error\":0.5256649864594751},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":103.57241697079786,\"upper_bound\":105.14144810551957},\"point_estimate\":104.3902770399939,\"standard_error\":0.39966897192214146},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":4.08934121888074,\"upper_bound\":7.438229016364029},\"point_estimate\":5.863161125504557,\"standard_error\":0.8522928397875672}}"
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    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[4457.0,8914.0,13371.0,17828.0,22285.0,26742.0,31199.0,35656.0,40113.0,44570.0,49027.0,53484.0,57941.0,62398.0,66855.0,71312.0,75769.0,80226.0,84683.0,89140.0,93597.0,98054.0,102511.0,106968.0,111425.0,115882.0,120339.0,124796.0,129253.0,133710.0,138167.0,142624.0,147081.0,151538.0,155995.0,160452.0,164909.0,169366.0,173823.0,178280.0,182737.0,187194.0,191651.0,196108.0,200565.0,205022.0,209479.0,213936.0,218393.0,222850.0,227307.0,231764.0,236221.0,240678.0,245135.0,249592.0,254049.0,258506.0,262963.0,267420.0,271877.0,276334.0,280791.0,285248.0,289705.0,294162.0,298619.0,303076.0,307533.0,311990.0,316447.0,320904.0,325361.0,329818.0,334275.0,338732.0,343189.0,347646.0,352103.0,356560.0,361017.0,365474.0,369931.0,374388.0,378845.0,383302.0,387759.0,392216.0,396673.0,401130.0,405587.0,410044.0,414501.0,418958.0,423415.0,427872.0,432329.0,436786.0,441243.0,445700.0],\"times\":[357208.0,683667.0,1016126.0,1611915.0,2019167.0,2770623.0,3186917.0,3246208.0,3888083.0,4147541.0,4757712.0,5362832.0,5585876.0,6235209.0,6366458.0,6805584.0,7565502.0,7599082.0,8573959.0,8776708.0,9160041.0,9792331.0,10381916.0,11030460.0,11854833.0,12433751.0,12505750.0,13085167.0,13517627.0,13865794.0,14551542.0,14400833.0,14867251.0,15402624.0,16259792.0,15831627.0,16433916.0,17001045.0,17348708.0,17981707.0,17987294.0,18427208.0,19330792.0,20885165.0,20061414.0,21630501.0,21317666.0,21637582.0,22620875.0,22294249.0,23316417.0,23230334.0,24926999.0,24263664.0,25180041.0,25524250.0,26388126.0,26245543.0,26048332.0,26739834.0,27794251.0,27354042.0,28602792.0,30346958.0,31350292.0,31775918.0,32880292.0,32433791.0,32735374.0,33066874.0,33143042.0,32370253.0,32731294.0,34046540.0,35320875.0,35971750.0,34365917.0,34712583.0,35282042.0,35934708.0,36369501.0,37760917.0,38176958.0,39457625.0,39499916.0,40614000.0,41448751.0,40742876.0,42410750.0,42010125.0,42527125.0,43178456.0,44847249.0,44580542.0,45721166.0,46659793.0,45970541.0,47868623.0,47855790.0,47030915.0]}"
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    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/500/base/tukey.json",
    "content": "[83.38574988373117,91.64862345070473,113.68295296263425,121.94582652960781]"
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    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.0351917004211445,\"upper_bound\":-0.004337524698445727},\"point_estimate\":-0.01968680352104102,\"standard_error\":0.007912026403471441},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.03548429555325816,\"upper_bound\":-0.0044421606932788515},\"point_estimate\":-0.02034493229326817,\"standard_error\":0.007964510446884692}}"
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    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/500/new/benchmark.json",
    "content": "{\"group_id\":\"Import as borrowed, own and destroy\",\"function_id\":\"FlexStr 0.10 (SharedStr)\",\"value_str\":\"500\",\"throughput\":null,\"full_id\":\"Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/500\",\"directory_name\":\"Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/500\",\"title\":\"Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/500\"}"
  },
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    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/500/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":100.34076999009623,\"upper_bound\":102.62135839784904},\"point_estimate\":101.54104776709625,\"standard_error\":0.5824977598106748},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":100.87207700745394,\"upper_bound\":103.57875481357003},\"point_estimate\":102.00655469726594,\"standard_error\":0.7194076489955507},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.0845483708128882,\"upper_bound\":5.159185642138225},\"point_estimate\":4.132181553183208,\"standard_error\":0.5256649864594751},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":103.57241697079786,\"upper_bound\":105.14144810551957},\"point_estimate\":104.3902770399939,\"standard_error\":0.39966897192214146},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":4.08934121888074,\"upper_bound\":7.438229016364029},\"point_estimate\":5.863161125504557,\"standard_error\":0.8522928397875672}}"
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    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/500/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[4457.0,8914.0,13371.0,17828.0,22285.0,26742.0,31199.0,35656.0,40113.0,44570.0,49027.0,53484.0,57941.0,62398.0,66855.0,71312.0,75769.0,80226.0,84683.0,89140.0,93597.0,98054.0,102511.0,106968.0,111425.0,115882.0,120339.0,124796.0,129253.0,133710.0,138167.0,142624.0,147081.0,151538.0,155995.0,160452.0,164909.0,169366.0,173823.0,178280.0,182737.0,187194.0,191651.0,196108.0,200565.0,205022.0,209479.0,213936.0,218393.0,222850.0,227307.0,231764.0,236221.0,240678.0,245135.0,249592.0,254049.0,258506.0,262963.0,267420.0,271877.0,276334.0,280791.0,285248.0,289705.0,294162.0,298619.0,303076.0,307533.0,311990.0,316447.0,320904.0,325361.0,329818.0,334275.0,338732.0,343189.0,347646.0,352103.0,356560.0,361017.0,365474.0,369931.0,374388.0,378845.0,383302.0,387759.0,392216.0,396673.0,401130.0,405587.0,410044.0,414501.0,418958.0,423415.0,427872.0,432329.0,436786.0,441243.0,445700.0],\"times\":[357208.0,683667.0,1016126.0,1611915.0,2019167.0,2770623.0,3186917.0,3246208.0,3888083.0,4147541.0,4757712.0,5362832.0,5585876.0,6235209.0,6366458.0,6805584.0,7565502.0,7599082.0,8573959.0,8776708.0,9160041.0,9792331.0,10381916.0,11030460.0,11854833.0,12433751.0,12505750.0,13085167.0,13517627.0,13865794.0,14551542.0,14400833.0,14867251.0,15402624.0,16259792.0,15831627.0,16433916.0,17001045.0,17348708.0,17981707.0,17987294.0,18427208.0,19330792.0,20885165.0,20061414.0,21630501.0,21317666.0,21637582.0,22620875.0,22294249.0,23316417.0,23230334.0,24926999.0,24263664.0,25180041.0,25524250.0,26388126.0,26245543.0,26048332.0,26739834.0,27794251.0,27354042.0,28602792.0,30346958.0,31350292.0,31775918.0,32880292.0,32433791.0,32735374.0,33066874.0,33143042.0,32370253.0,32731294.0,34046540.0,35320875.0,35971750.0,34365917.0,34712583.0,35282042.0,35934708.0,36369501.0,37760917.0,38176958.0,39457625.0,39499916.0,40614000.0,41448751.0,40742876.0,42410750.0,42010125.0,42527125.0,43178456.0,44847249.0,44580542.0,45721166.0,46659793.0,45970541.0,47868623.0,47855790.0,47030915.0]}"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/500/new/tukey.json",
    "content": "[83.38574988373117,91.64862345070473,113.68295296263425,121.94582652960781]"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/500/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/500 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/500</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">103.57 ns</td>\n                                <td>104.39 ns</td>\n                                <td class=\"ci-bound\">105.14 ns</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.8896281</td>\n                                <td>0.8960092</td>\n                                <td class=\"ci-bound\">0.8906203</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">100.34 ns</td>\n                                <td>101.54 ns</td>\n                                <td class=\"ci-bound\">102.62 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">4.0893 ns</td>\n                                <td>5.8632 ns</td>\n                                <td class=\"ci-bound\">7.4382 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">100.87 ns</td>\n                                <td>102.01 ns</td>\n                                <td class=\"ci-bound\">103.58 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">3.0845 ns</td>\n                                <td>4.1322 ns</td>\n                                <td class=\"ci-bound\">5.1592 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−3.5192%</td>\n                            <td>−1.9687%</td>\n                            <td class=\"ci-bound\">−0.4338%</td>\n                            <td>(p = 0.01 &lt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                Change within noise threshold.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr) Summary - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)</h2>\n        <h3>Violin Plot</h3>\n        <a href=\"violin.svg\">\n            <img src=\"violin.svg\" alt=\"Violin Plot\" />\n        </a>\n        <p>This chart shows the relationship between function/parameter and iteration time. The thickness of the shaded\n            region indicates the probability that a measurement of the given function/parameter would take a particular\n            length of time.</p>\n        <h3>Line Chart</h3>\n        <img src=\"lines.svg\" alt=\"Line Chart\" />\n        <p>This chart shows the mean measured time for each function as the input (or the size of the input) increases.</p>\n        <section class=\"plots\">\n            <a href=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/0/report/index.html\">\n                <h4>Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/0/report/pdf.svg\">\n                                <img src=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/0/report/regression.svg\">\n                                <img src=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/10/report/index.html\">\n                <h4>Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/10/report/pdf.svg\">\n                                <img src=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/10/report/regression.svg\">\n                                <img src=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/20/report/index.html\">\n                <h4>Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/20/report/pdf.svg\">\n                                <img src=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/20/report/regression.svg\">\n                                <img src=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/100/report/index.html\">\n                <h4>Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/100/report/pdf.svg\">\n                                <img src=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/100/report/regression.svg\">\n                                <img src=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/500/report/index.html\">\n                <h4>Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/500/report/pdf.svg\">\n                                <img src=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/500/report/regression.svg\">\n                                <img src=\"../../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as borrowed, own and destroy/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as borrowed, own and destroy Summary - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as borrowed, own and destroy</h2>\n        <h3>Violin Plot</h3>\n        <a href=\"violin.svg\">\n            <img src=\"violin.svg\" alt=\"Violin Plot\" />\n        </a>\n        <p>This chart shows the relationship between function/parameter and iteration time. The thickness of the shaded\n            region indicates the probability that a measurement of the given function/parameter would take a particular\n            length of time.</p>\n        <h3>Line Chart</h3>\n        <img src=\"lines.svg\" alt=\"Line Chart\" />\n        <p>This chart shows the mean measured time for each function as the input (or the size of the input) increases.</p>\n        <section class=\"plots\">\n            <a href=\"../../Import as borrowed, own and destroy/Cow_&#39;_, str_/0/report/index.html\">\n                <h4>Import as borrowed, own and destroy/Cow&lt;&#39;_, str&gt;/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as borrowed, own and destroy/Cow_&#39;_, str_/0/report/pdf.svg\">\n                                <img src=\"../../Import as borrowed, own and destroy/Cow_&#39;_, str_/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as borrowed, own and destroy/Cow_&#39;_, str_/0/report/regression.svg\">\n                                <img src=\"../../Import as borrowed, own and destroy/Cow_&#39;_, str_/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Import as borrowed, own and destroy/Cow_&#39;_, str_/10/report/index.html\">\n                <h4>Import as borrowed, own and destroy/Cow&lt;&#39;_, str&gt;/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as borrowed, own and destroy/Cow_&#39;_, str_/10/report/pdf.svg\">\n                                <img src=\"../../Import as borrowed, own and destroy/Cow_&#39;_, str_/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as borrowed, own and destroy/Cow_&#39;_, str_/10/report/regression.svg\">\n                                <img src=\"../../Import as borrowed, own and destroy/Cow_&#39;_, str_/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Import as borrowed, own and destroy/Cow_&#39;_, str_/20/report/index.html\">\n                <h4>Import as borrowed, own and destroy/Cow&lt;&#39;_, str&gt;/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as borrowed, own and destroy/Cow_&#39;_, str_/20/report/pdf.svg\">\n                                <img src=\"../../Import as borrowed, own and destroy/Cow_&#39;_, str_/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as borrowed, own and destroy/Cow_&#39;_, str_/20/report/regression.svg\">\n                                <img src=\"../../Import as borrowed, own and destroy/Cow_&#39;_, str_/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Import as borrowed, own and destroy/Cow_&#39;_, str_/100/report/index.html\">\n                <h4>Import as borrowed, own and destroy/Cow&lt;&#39;_, str&gt;/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as borrowed, own and destroy/Cow_&#39;_, str_/100/report/pdf.svg\">\n                                <img src=\"../../Import as borrowed, own and destroy/Cow_&#39;_, str_/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as borrowed, own and destroy/Cow_&#39;_, str_/100/report/regression.svg\">\n                                <img src=\"../../Import as borrowed, own and destroy/Cow_&#39;_, str_/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Import as borrowed, own and destroy/Cow_&#39;_, str_/500/report/index.html\">\n                <h4>Import as borrowed, own and destroy/Cow&lt;&#39;_, str&gt;/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as borrowed, own and destroy/Cow_&#39;_, str_/500/report/pdf.svg\">\n                                <img src=\"../../Import as borrowed, own and destroy/Cow_&#39;_, str_/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as borrowed, own and destroy/Cow_&#39;_, str_/500/report/regression.svg\">\n                                <img src=\"../../Import as borrowed, own and destroy/Cow_&#39;_, str_/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/0/report/index.html\">\n                <h4>Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/0/report/pdf.svg\">\n                                <img src=\"../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/0/report/regression.svg\">\n                                <img src=\"../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/10/report/index.html\">\n                <h4>Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/10/report/pdf.svg\">\n                                <img src=\"../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/10/report/regression.svg\">\n                                <img src=\"../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/20/report/index.html\">\n                <h4>Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/20/report/pdf.svg\">\n                                <img src=\"../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/20/report/regression.svg\">\n                                <img src=\"../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/100/report/index.html\">\n                <h4>Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/100/report/pdf.svg\">\n                                <img src=\"../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/100/report/regression.svg\">\n                                <img src=\"../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/500/report/index.html\">\n                <h4>Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/500/report/pdf.svg\">\n                                <img src=\"../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/500/report/regression.svg\">\n                                <img src=\"../../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/0/report/index.html\">\n                <h4>Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/0/report/pdf.svg\">\n                                <img src=\"../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/0/report/regression.svg\">\n                                <img src=\"../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/10/report/index.html\">\n                <h4>Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/10/report/pdf.svg\">\n                                <img src=\"../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/10/report/regression.svg\">\n                                <img src=\"../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/20/report/index.html\">\n                <h4>Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/20/report/pdf.svg\">\n                                <img src=\"../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/20/report/regression.svg\">\n                                <img src=\"../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/100/report/index.html\">\n                <h4>Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/100/report/pdf.svg\">\n                                <img src=\"../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/100/report/regression.svg\">\n                                <img src=\"../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/500/report/index.html\">\n                <h4>Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/500/report/pdf.svg\">\n                                <img src=\"../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/500/report/regression.svg\">\n                                <img src=\"../../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/0/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/0 Summary - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/0</h2>\n        <h3>Violin Plot</h3>\n        <a href=\"violin.svg\">\n            <img src=\"violin.svg\" alt=\"Violin Plot\" />\n        </a>\n        <p>This chart shows the relationship between function/parameter and iteration time. The thickness of the shaded\n            region indicates the probability that a measurement of the given function/parameter would take a particular\n            length of time.</p>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/Rc_str_/0/report/index.html\">\n                <h4>Import as owned and destroy/Rc&lt;str&gt;/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/Rc_str_/0/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/Rc_str_/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/Rc_str_/0/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/Rc_str_/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/Arc_str_/0/report/index.html\">\n                <h4>Import as owned and destroy/Arc&lt;str&gt;/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/Arc_str_/0/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/Arc_str_/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/Arc_str_/0/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/Arc_str_/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/Cow_&#39;_, str_/0/report/index.html\">\n                <h4>Import as owned and destroy/Cow&lt;&#39;_, str&gt;/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/Cow_&#39;_, str_/0/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/Cow_&#39;_, str_/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/Cow_&#39;_, str_/0/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/Cow_&#39;_, str_/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/0/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.9 (SharedStr)/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/0/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/0/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/0/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.9 (LocalStr)/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/0/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/0/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/0/report/index.html\">\n                <h4>Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/0/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/0/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/0/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/0/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/0/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/0/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/0/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/0/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/0/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/0/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/0/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/0/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/0/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/0/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/10/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/10 Summary - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/10</h2>\n        <h3>Violin Plot</h3>\n        <a href=\"violin.svg\">\n            <img src=\"violin.svg\" alt=\"Violin Plot\" />\n        </a>\n        <p>This chart shows the relationship between function/parameter and iteration time. The thickness of the shaded\n            region indicates the probability that a measurement of the given function/parameter would take a particular\n            length of time.</p>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/Rc_str_/10/report/index.html\">\n                <h4>Import as owned and destroy/Rc&lt;str&gt;/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/Rc_str_/10/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/Rc_str_/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/Rc_str_/10/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/Rc_str_/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/Arc_str_/10/report/index.html\">\n                <h4>Import as owned and destroy/Arc&lt;str&gt;/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/Arc_str_/10/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/Arc_str_/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/Arc_str_/10/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/Arc_str_/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/Cow_&#39;_, str_/10/report/index.html\">\n                <h4>Import as owned and destroy/Cow&lt;&#39;_, str&gt;/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/Cow_&#39;_, str_/10/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/Cow_&#39;_, str_/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/Cow_&#39;_, str_/10/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/Cow_&#39;_, str_/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/10/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.9 (SharedStr)/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/10/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/10/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/10/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.9 (LocalStr)/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/10/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/10/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/10/report/index.html\">\n                <h4>Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/10/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/10/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/10/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/10/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/10/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/10/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/10/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/10/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/10/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/10/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/10/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/10/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/10/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/10/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/100/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/100 Summary - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/100</h2>\n        <h3>Violin Plot</h3>\n        <a href=\"violin.svg\">\n            <img src=\"violin.svg\" alt=\"Violin Plot\" />\n        </a>\n        <p>This chart shows the relationship between function/parameter and iteration time. The thickness of the shaded\n            region indicates the probability that a measurement of the given function/parameter would take a particular\n            length of time.</p>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/Rc_str_/100/report/index.html\">\n                <h4>Import as owned and destroy/Rc&lt;str&gt;/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/Rc_str_/100/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/Rc_str_/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/Rc_str_/100/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/Rc_str_/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/Arc_str_/100/report/index.html\">\n                <h4>Import as owned and destroy/Arc&lt;str&gt;/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/Arc_str_/100/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/Arc_str_/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/Arc_str_/100/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/Arc_str_/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/Cow_&#39;_, str_/100/report/index.html\">\n                <h4>Import as owned and destroy/Cow&lt;&#39;_, str&gt;/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/Cow_&#39;_, str_/100/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/Cow_&#39;_, str_/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/Cow_&#39;_, str_/100/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/Cow_&#39;_, str_/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/100/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.9 (SharedStr)/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/100/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/100/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/100/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.9 (LocalStr)/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/100/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/100/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/100/report/index.html\">\n                <h4>Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/100/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/100/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/100/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/100/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/100/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/100/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/100/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/100/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/100/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/100/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/100/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/100/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/100/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/100/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/20/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/20 Summary - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/20</h2>\n        <h3>Violin Plot</h3>\n        <a href=\"violin.svg\">\n            <img src=\"violin.svg\" alt=\"Violin Plot\" />\n        </a>\n        <p>This chart shows the relationship between function/parameter and iteration time. The thickness of the shaded\n            region indicates the probability that a measurement of the given function/parameter would take a particular\n            length of time.</p>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/Rc_str_/20/report/index.html\">\n                <h4>Import as owned and destroy/Rc&lt;str&gt;/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/Rc_str_/20/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/Rc_str_/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/Rc_str_/20/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/Rc_str_/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/Arc_str_/20/report/index.html\">\n                <h4>Import as owned and destroy/Arc&lt;str&gt;/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/Arc_str_/20/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/Arc_str_/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/Arc_str_/20/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/Arc_str_/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/Cow_&#39;_, str_/20/report/index.html\">\n                <h4>Import as owned and destroy/Cow&lt;&#39;_, str&gt;/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/Cow_&#39;_, str_/20/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/Cow_&#39;_, str_/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/Cow_&#39;_, str_/20/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/Cow_&#39;_, str_/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/20/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.9 (SharedStr)/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/20/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/20/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/20/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.9 (LocalStr)/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/20/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/20/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/20/report/index.html\">\n                <h4>Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/20/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/20/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/20/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/20/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/20/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/20/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/20/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/20/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/20/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/20/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/20/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/20/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/20/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/20/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/500/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/500 Summary - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/500</h2>\n        <h3>Violin Plot</h3>\n        <a href=\"violin.svg\">\n            <img src=\"violin.svg\" alt=\"Violin Plot\" />\n        </a>\n        <p>This chart shows the relationship between function/parameter and iteration time. The thickness of the shaded\n            region indicates the probability that a measurement of the given function/parameter would take a particular\n            length of time.</p>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/Rc_str_/500/report/index.html\">\n                <h4>Import as owned and destroy/Rc&lt;str&gt;/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/Rc_str_/500/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/Rc_str_/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/Rc_str_/500/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/Rc_str_/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/Arc_str_/500/report/index.html\">\n                <h4>Import as owned and destroy/Arc&lt;str&gt;/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/Arc_str_/500/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/Arc_str_/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/Arc_str_/500/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/Arc_str_/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/Cow_&#39;_, str_/500/report/index.html\">\n                <h4>Import as owned and destroy/Cow&lt;&#39;_, str&gt;/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/Cow_&#39;_, str_/500/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/Cow_&#39;_, str_/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/Cow_&#39;_, str_/500/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/Cow_&#39;_, str_/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/500/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.9 (SharedStr)/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/500/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/500/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/500/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.9 (LocalStr)/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/500/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/500/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/500/report/index.html\">\n                <h4>Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/500/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/500/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/500/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/500/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/500/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/500/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/500/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/500/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/500/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/500/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/500/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/500/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/500/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/500/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Arc_str_/0/base/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"Arc<str>\",\"value_str\":\"0\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/Arc<str>/0\",\"directory_name\":\"Import as owned and destroy/Arc_str_/0\",\"title\":\"Import as owned and destroy/Arc<str>/0\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Arc_str_/0/base/estimates.json",
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    "path": "docs/criterion/Import as owned and destroy/Arc_str_/0/new/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"Arc<str>\",\"value_str\":\"0\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/Arc<str>/0\",\"directory_name\":\"Import as owned and destroy/Arc_str_/0\",\"title\":\"Import as owned and destroy/Arc<str>/0\"}"
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    "path": "docs/criterion/Import as owned and destroy/Arc_str_/0/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":23.397010840061018,\"upper_bound\":23.801539153088722},\"point_estimate\":23.5608399279269,\"standard_error\":0.10601007221345884},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":23.3228033417453,\"upper_bound\":23.40893607446129},\"point_estimate\":23.36534685384268,\"standard_error\":0.02373252233350628},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.15747972780429847,\"upper_bound\":0.29112922649655404},\"point_estimate\":0.22391094124423327,\"standard_error\":0.03479288659747457},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":23.327733989500402,\"upper_bound\":23.436149170324022},\"point_estimate\":23.380195603978116,\"standard_error\":0.02766552894619532},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.30876669476906893,\"upper_bound\":1.7197809585638912},\"point_estimate\":1.0649869750650733,\"standard_error\":0.42395686422916556}}"
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    "path": "docs/criterion/Import as owned and destroy/Arc_str_/0/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[35426.0,70852.0,106278.0,141704.0,177130.0,212556.0,247982.0,283408.0,318834.0,354260.0,389686.0,425112.0,460538.0,495964.0,531390.0,566816.0,602242.0,637668.0,673094.0,708520.0,743946.0,779372.0,814798.0,850224.0,885650.0,921076.0,956502.0,991928.0,1027354.0,1062780.0,1098206.0,1133632.0,1169058.0,1204484.0,1239910.0,1275336.0,1310762.0,1346188.0,1381614.0,1417040.0,1452466.0,1487892.0,1523318.0,1558744.0,1594170.0,1629596.0,1665022.0,1700448.0,1735874.0,1771300.0,1806726.0,1842152.0,1877578.0,1913004.0,1948430.0,1983856.0,2019282.0,2054708.0,2090134.0,2125560.0,2160986.0,2196412.0,2231838.0,2267264.0,2302690.0,2338116.0,2373542.0,2408968.0,2444394.0,2479820.0,2515246.0,2550672.0,2586098.0,2621524.0,2656950.0,2692376.0,2727802.0,2763228.0,2798654.0,2834080.0,2869506.0,2904932.0,2940358.0,2975784.0,3011210.0,3046636.0,3082062.0,3117488.0,3152914.0,3188340.0,3223766.0,3259192.0,3294618.0,3330044.0,3365470.0,3400896.0,3436322.0,3471748.0,3507174.0,3542600.0],\"times\":[1164001.0,1636085.0,2448791.0,3802960.0,4488875.0,4927458.0,5730960.0,6650207.0,7338625.0,8770042.0,9429126.0,10093625.0,10725668.0,11897625.0,12696335.0,13220791.0,13964042.0,14781417.0,15663752.0,16727834.0,17595167.0,18237750.0,18845044.0,19708211.0,20656706.0,21383208.0,22396084.0,23143457.0,24054666.0,24587334.0,25550501.0,26186083.0,27208209.0,28111459.0,28929164.0,29572917.0,32784499.0,32505082.0,32286168.0,33436168.0,33950998.0,34355917.0,35192792.0,36145915.0,36896751.0,38144916.0,39053750.0,39702125.0,41385708.0,40988128.0,41935709.0,43482165.0,43826665.0,44821038.0,45802459.0,46757040.0,47488499.0,47679085.0,48951000.0,49372750.0,50227708.0,51494291.0,52790541.0,53738498.0,54592083.0,54713833.0,55777000.0,55927418.0,57540666.0,59472709.0,58932583.0,59412126.0,60898458.0,61041748.0,61896460.0,63011501.0,63329377.0,65285790.0,65401209.0,66133710.0,66835375.0,67725417.0,68131791.0,69179291.0,71083750.0,71419249.0,72176375.0,72453667.0,73638749.0,74544500.0,75365124.0,76440165.0,77048750.0,78021791.0,77862249.0,79452585.0,81646582.0,80329667.0,80799749.0,81533166.0]}"
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    "content": "[22.294963210675107,22.75551455288456,23.9836514654431,24.44420280765255]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Arc_str_/0/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/Arc&lt;str&gt;/0 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/Arc&lt;str&gt;/0</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">23.328 ns</td>\n                                <td>23.380 ns</td>\n                                <td class=\"ci-bound\">23.436 ns</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.9852770</td>\n                                <td>0.9859986</td>\n                                <td class=\"ci-bound\">0.9851779</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">23.397 ns</td>\n                                <td>23.561 ns</td>\n                                <td class=\"ci-bound\">23.802 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">308.77 ps</td>\n                                <td>1.0650 ns</td>\n                                <td class=\"ci-bound\">1.7198 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">23.323 ns</td>\n                                <td>23.365 ns</td>\n                                <td class=\"ci-bound\">23.409 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">157.48 ps</td>\n                                <td>223.91 ps</td>\n                                <td class=\"ci-bound\">291.13 ps</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−1.2068%</td>\n                            <td>+0.1639%</td>\n                            <td class=\"ci-bound\">+1.5084%</td>\n                            <td>(p = 0.82 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Arc_str_/10/base/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"Arc<str>\",\"value_str\":\"10\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/Arc<str>/10\",\"directory_name\":\"Import as owned and destroy/Arc_str_/10\",\"title\":\"Import as owned and destroy/Arc<str>/10\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Arc_str_/10/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":52.22060620492381,\"upper_bound\":53.72913320499839},\"point_estimate\":52.94457511301484,\"standard_error\":0.385532002875295},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":50.35864895597567,\"upper_bound\":52.15295130091536},\"point_estimate\":50.99963642193066,\"standard_error\":0.5083004265895688},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":1.149586047401809,\"upper_bound\":3.726769538011217},\"point_estimate\":2.0421384500838204,\"standard_error\":0.694137226358955},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":53.72984915547746,\"upper_bound\":55.156733874906},\"point_estimate\":54.487170131964234,\"standard_error\":0.36434147356588004},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.090804293375686,\"upper_bound\":4.696282737801023},\"point_estimate\":3.863612133725707,\"standard_error\":0.4182344063220074}}"
  },
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    "path": "docs/criterion/Import as owned and destroy/Arc_str_/10/change/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.05385751070060856,\"upper_bound\":0.011096012690110313},\"point_estimate\":-0.017407430220112374,\"standard_error\":0.01675263510722102},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.042027733686001545,\"upper_bound\":0.01377139875711575},\"point_estimate\":-0.0162993300256441,\"standard_error\":0.014199185778030208}}"
  },
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    "path": "docs/criterion/Import as owned and destroy/Arc_str_/10/new/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"Arc<str>\",\"value_str\":\"10\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/Arc<str>/10\",\"directory_name\":\"Import as owned and destroy/Arc_str_/10\",\"title\":\"Import as owned and destroy/Arc<str>/10\"}"
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    "path": "docs/criterion/Import as owned and destroy/Arc_str_/10/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":52.22060620492381,\"upper_bound\":53.72913320499839},\"point_estimate\":52.94457511301484,\"standard_error\":0.385532002875295},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":50.35864895597567,\"upper_bound\":52.15295130091536},\"point_estimate\":50.99963642193066,\"standard_error\":0.5083004265895688},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":1.149586047401809,\"upper_bound\":3.726769538011217},\"point_estimate\":2.0421384500838204,\"standard_error\":0.694137226358955},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":53.72984915547746,\"upper_bound\":55.156733874906},\"point_estimate\":54.487170131964234,\"standard_error\":0.36434147356588004},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.090804293375686,\"upper_bound\":4.696282737801023},\"point_estimate\":3.863612133725707,\"standard_error\":0.4182344063220074}}"
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    "path": "docs/criterion/Import as owned and destroy/Arc_str_/10/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[11166.0,22332.0,33498.0,44664.0,55830.0,66996.0,78162.0,89328.0,100494.0,111660.0,122826.0,133992.0,145158.0,156324.0,167490.0,178656.0,189822.0,200988.0,212154.0,223320.0,234486.0,245652.0,256818.0,267984.0,279150.0,290316.0,301482.0,312648.0,323814.0,334980.0,346146.0,357312.0,368478.0,379644.0,390810.0,401976.0,413142.0,424308.0,435474.0,446640.0,457806.0,468972.0,480138.0,491304.0,502470.0,513636.0,524802.0,535968.0,547134.0,558300.0,569466.0,580632.0,591798.0,602964.0,614130.0,625296.0,636462.0,647628.0,658794.0,669960.0,681126.0,692292.0,703458.0,714624.0,725790.0,736956.0,748122.0,759288.0,770454.0,781620.0,792786.0,803952.0,815118.0,826284.0,837450.0,848616.0,859782.0,870948.0,882114.0,893280.0,904446.0,915612.0,926778.0,937944.0,949110.0,960276.0,971442.0,982608.0,993774.0,1004940.0,1016106.0,1027272.0,1038438.0,1049604.0,1060770.0,1071936.0,1083102.0,1094268.0,1105434.0,1116600.0],\"times\":[574875.0,1569418.0,1669999.0,2237749.0,3574126.0,3348708.0,4433832.0,4453708.0,4946667.0,5606791.0,6067585.0,6924625.0,7603043.0,7757250.0,8642168.0,9389917.0,9544207.0,10128333.0,10639374.0,11182666.0,11724583.0,12216914.0,12717542.0,13499832.0,13827540.0,14661753.0,14947750.0,15726874.0,16049374.0,17043000.0,17366750.0,17791416.0,18543498.0,19073836.0,19408874.0,20458916.0,20432085.0,20998374.0,21615751.0,22309375.0,22899792.0,23553708.0,24054124.0,24397167.0,25060165.0,25834416.0,26393499.0,26587790.0,27601834.0,28369375.0,28754500.0,29065961.0,29448833.0,30457667.0,30650167.0,31410415.0,31413792.0,39790540.0,39246168.0,39817502.0,39633709.0,41003793.0,40126000.0,41319084.0,42073250.0,41410792.0,42204832.0,42269666.0,42720834.0,43436331.0,43893875.0,46250000.0,43897084.0,44661334.0,44890126.0,45840044.0,45803292.0,46291457.0,45998165.0,46332500.0,46966250.0,47067416.0,47832625.0,48028542.0,48459752.0,48917587.0,56227167.0,56762416.0,56401584.0,57272582.0,58797875.0,57653166.0,59493042.0,59015957.0,60304999.0,61120750.0,60981459.0,61869708.0,62449293.0,62768416.0]}"
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    "path": "docs/criterion/Import as owned and destroy/Arc_str_/10/new/tukey.json",
    "content": "[31.54688520860752,40.7982262956406,65.46846919439548,74.71981028142855]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Arc_str_/10/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/Arc&lt;str&gt;/10 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/Arc&lt;str&gt;/10</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">53.730 ns</td>\n                                <td>54.487 ns</td>\n                                <td class=\"ci-bound\">55.157 ns</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.7134381</td>\n                                <td>0.7253439</td>\n                                <td class=\"ci-bound\">0.7160040</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">52.221 ns</td>\n                                <td>52.945 ns</td>\n                                <td class=\"ci-bound\">53.729 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">3.0908 ns</td>\n                                <td>3.8636 ns</td>\n                                <td class=\"ci-bound\">4.6963 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">50.359 ns</td>\n                                <td>51.000 ns</td>\n                                <td class=\"ci-bound\">52.153 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">1.1496 ns</td>\n                                <td>2.0421 ns</td>\n                                <td class=\"ci-bound\">3.7268 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−5.3858%</td>\n                            <td>−1.7407%</td>\n                            <td class=\"ci-bound\">+1.1096%</td>\n                            <td>(p = 0.35 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Arc_str_/100/base/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"Arc<str>\",\"value_str\":\"100\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/Arc<str>/100\",\"directory_name\":\"Import as owned and destroy/Arc_str_/100\",\"title\":\"Import as owned and destroy/Arc<str>/100\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Arc_str_/100/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":60.688667524340275,\"upper_bound\":62.43857270669618},\"point_estimate\":61.54586075570924,\"standard_error\":0.4453469596282505},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":60.48625306962235,\"upper_bound\":62.27601786627492},\"point_estimate\":61.39359696307673,\"standard_error\":0.46919222180469267},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.4457049089994034,\"upper_bound\":5.646776497389735},\"point_estimate\":4.738720231680037,\"standard_error\":0.5780157399755508},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":61.256792007138046,\"upper_bound\":62.88196750292118},\"point_estimate\":62.07229937205682,\"standard_error\":0.41567403859168817},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.623661619260953,\"upper_bound\":5.449152510698892},\"point_estimate\":4.475968449082917,\"standard_error\":0.47817646143335235}}"
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    "path": "docs/criterion/Import as owned and destroy/Arc_str_/100/base/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[7904.0,15808.0,23712.0,31616.0,39520.0,47424.0,55328.0,63232.0,71136.0,79040.0,86944.0,94848.0,102752.0,110656.0,118560.0,126464.0,134368.0,142272.0,150176.0,158080.0,165984.0,173888.0,181792.0,189696.0,197600.0,205504.0,213408.0,221312.0,229216.0,237120.0,245024.0,252928.0,260832.0,268736.0,276640.0,284544.0,292448.0,300352.0,308256.0,316160.0,324064.0,331968.0,339872.0,347776.0,355680.0,363584.0,371488.0,379392.0,387296.0,395200.0,403104.0,411008.0,418912.0,426816.0,434720.0,442624.0,450528.0,458432.0,466336.0,474240.0,482144.0,490048.0,497952.0,505856.0,513760.0,521664.0,529568.0,537472.0,545376.0,553280.0,561184.0,569088.0,576992.0,584896.0,592800.0,600704.0,608608.0,616512.0,624416.0,632320.0,640224.0,648128.0,656032.0,663936.0,671840.0,679744.0,687648.0,695552.0,703456.0,711360.0,719264.0,727168.0,735072.0,742976.0,750880.0,758784.0,766688.0,774592.0,782496.0,790400.0],\"times\":[438250.0,1292543.0,1283999.0,1718085.0,2611666.0,3114793.0,3190542.0,3344126.0,3780666.0,4197457.0,4586622.0,6436460.0,6536333.0,7260626.0,6916499.0,7127749.0,7676626.0,8941710.0,9320539.0,9925169.0,10204876.0,10871249.0,11074999.0,12258583.0,12205210.0,12738499.0,12267875.0,12486290.0,13362294.0,14457125.0,14916708.0,16498292.0,16925917.0,17148666.0,18609419.0,18369417.0,18168332.0,18160833.0,18349875.0,18253999.0,18983625.0,19707999.0,20926999.0,23629374.0,23508623.0,23498790.0,24626750.0,23936749.0,23796042.0,23461334.0,23177833.0,23141751.0,24066499.0,24506542.0,25103836.0,29854082.0,30079168.0,30009416.0,30467125.0,29938250.0,29163084.0,28624417.0,28050458.0,28935044.0,29474499.0,29879625.0,37024168.0,36701083.0,35648249.0,35371625.0,35640374.0,34702042.0,34205582.0,33471543.0,33667625.0,35729086.0,36452127.0,36095418.0,43183459.0,42529750.0,42271124.0,40347791.0,40115958.0,40067833.0,41214500.0,40320751.0,42021750.0,42313544.0,42976082.0,42444125.0,48472748.0,48408333.0,47348417.0,48332876.0,47182708.0,47679959.0,47779084.0,46163667.0,48697250.0,48964540.0]}"
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    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.005249040700065012,\"upper_bound\":0.03511780443124523},\"point_estimate\":0.014581877902558604,\"standard_error\":0.010358470956016748},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.01136880507726612,\"upper_bound\":0.03755182941389301},\"point_estimate\":0.011639821076777856,\"standard_error\":0.012204930274222972}}"
  },
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    "path": "docs/criterion/Import as owned and destroy/Arc_str_/100/new/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"Arc<str>\",\"value_str\":\"100\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/Arc<str>/100\",\"directory_name\":\"Import as owned and destroy/Arc_str_/100\",\"title\":\"Import as owned and destroy/Arc<str>/100\"}"
  },
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    "path": "docs/criterion/Import as owned and destroy/Arc_str_/100/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":60.688667524340275,\"upper_bound\":62.43857270669618},\"point_estimate\":61.54586075570924,\"standard_error\":0.4453469596282505},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":60.48625306962235,\"upper_bound\":62.27601786627492},\"point_estimate\":61.39359696307673,\"standard_error\":0.46919222180469267},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.4457049089994034,\"upper_bound\":5.646776497389735},\"point_estimate\":4.738720231680037,\"standard_error\":0.5780157399755508},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":61.256792007138046,\"upper_bound\":62.88196750292118},\"point_estimate\":62.07229937205682,\"standard_error\":0.41567403859168817},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.623661619260953,\"upper_bound\":5.449152510698892},\"point_estimate\":4.475968449082917,\"standard_error\":0.47817646143335235}}"
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    "path": "docs/criterion/Import as owned and destroy/Arc_str_/100/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[7904.0,15808.0,23712.0,31616.0,39520.0,47424.0,55328.0,63232.0,71136.0,79040.0,86944.0,94848.0,102752.0,110656.0,118560.0,126464.0,134368.0,142272.0,150176.0,158080.0,165984.0,173888.0,181792.0,189696.0,197600.0,205504.0,213408.0,221312.0,229216.0,237120.0,245024.0,252928.0,260832.0,268736.0,276640.0,284544.0,292448.0,300352.0,308256.0,316160.0,324064.0,331968.0,339872.0,347776.0,355680.0,363584.0,371488.0,379392.0,387296.0,395200.0,403104.0,411008.0,418912.0,426816.0,434720.0,442624.0,450528.0,458432.0,466336.0,474240.0,482144.0,490048.0,497952.0,505856.0,513760.0,521664.0,529568.0,537472.0,545376.0,553280.0,561184.0,569088.0,576992.0,584896.0,592800.0,600704.0,608608.0,616512.0,624416.0,632320.0,640224.0,648128.0,656032.0,663936.0,671840.0,679744.0,687648.0,695552.0,703456.0,711360.0,719264.0,727168.0,735072.0,742976.0,750880.0,758784.0,766688.0,774592.0,782496.0,790400.0],\"times\":[438250.0,1292543.0,1283999.0,1718085.0,2611666.0,3114793.0,3190542.0,3344126.0,3780666.0,4197457.0,4586622.0,6436460.0,6536333.0,7260626.0,6916499.0,7127749.0,7676626.0,8941710.0,9320539.0,9925169.0,10204876.0,10871249.0,11074999.0,12258583.0,12205210.0,12738499.0,12267875.0,12486290.0,13362294.0,14457125.0,14916708.0,16498292.0,16925917.0,17148666.0,18609419.0,18369417.0,18168332.0,18160833.0,18349875.0,18253999.0,18983625.0,19707999.0,20926999.0,23629374.0,23508623.0,23498790.0,24626750.0,23936749.0,23796042.0,23461334.0,23177833.0,23141751.0,24066499.0,24506542.0,25103836.0,29854082.0,30079168.0,30009416.0,30467125.0,29938250.0,29163084.0,28624417.0,28050458.0,28935044.0,29474499.0,29879625.0,37024168.0,36701083.0,35648249.0,35371625.0,35640374.0,34702042.0,34205582.0,33471543.0,33667625.0,35729086.0,36452127.0,36095418.0,43183459.0,42529750.0,42271124.0,40347791.0,40115958.0,40067833.0,41214500.0,40320751.0,42021750.0,42313544.0,42976082.0,42444125.0,48472748.0,48408333.0,47348417.0,48332876.0,47182708.0,47679959.0,47779084.0,46163667.0,48697250.0,48964540.0]}"
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  {
    "path": "docs/criterion/Import as owned and destroy/Arc_str_/100/new/tukey.json",
    "content": "[39.43496415973124,48.881015711898286,74.07048651767708,83.51653806984413]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Arc_str_/100/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/Arc&lt;str&gt;/100 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/Arc&lt;str&gt;/100</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">61.257 ns</td>\n                                <td>62.072 ns</td>\n                                <td class=\"ci-bound\">62.882 ns</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.6982051</td>\n                                <td>0.7100532</td>\n                                <td class=\"ci-bound\">0.6983714</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">60.689 ns</td>\n                                <td>61.546 ns</td>\n                                <td class=\"ci-bound\">62.439 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">3.6237 ns</td>\n                                <td>4.4760 ns</td>\n                                <td class=\"ci-bound\">5.4492 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">60.486 ns</td>\n                                <td>61.394 ns</td>\n                                <td class=\"ci-bound\">62.276 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">3.4457 ns</td>\n                                <td>4.7387 ns</td>\n                                <td class=\"ci-bound\">5.6468 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−0.5249%</td>\n                            <td>+1.4582%</td>\n                            <td class=\"ci-bound\">+3.5118%</td>\n                            <td>(p = 0.15 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Arc_str_/20/base/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"Arc<str>\",\"value_str\":\"20\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/Arc<str>/20\",\"directory_name\":\"Import as owned and destroy/Arc_str_/20\",\"title\":\"Import as owned and destroy/Arc<str>/20\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Arc_str_/20/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":56.99882054303447,\"upper_bound\":58.39455439160427},\"point_estimate\":57.68579190255569,\"standard_error\":0.35590834276001104},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":56.79322381930185,\"upper_bound\":58.752749828884326},\"point_estimate\":58.05280180459985,\"standard_error\":0.5492003091837233},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.8506463691106387,\"upper_bound\":5.2499245212653385},\"point_estimate\":4.090593766870941,\"standard_error\":0.5967144899204374},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":58.5586585879374,\"upper_bound\":59.875893380948455},\"point_estimate\":59.238566628605,\"standard_error\":0.33589586134984284},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.033497218115003,\"upper_bound\":4.207103682230954},\"point_estimate\":3.5791759691835177,\"standard_error\":0.30706214713460106}}"
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    "path": "docs/criterion/Import as owned and destroy/Arc_str_/20/base/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[9740.0,19480.0,29220.0,38960.0,48700.0,58440.0,68180.0,77920.0,87660.0,97400.0,107140.0,116880.0,126620.0,136360.0,146100.0,155840.0,165580.0,175320.0,185060.0,194800.0,204540.0,214280.0,224020.0,233760.0,243500.0,253240.0,262980.0,272720.0,282460.0,292200.0,301940.0,311680.0,321420.0,331160.0,340900.0,350640.0,360380.0,370120.0,379860.0,389600.0,399340.0,409080.0,418820.0,428560.0,438300.0,448040.0,457780.0,467520.0,477260.0,487000.0,496740.0,506480.0,516220.0,525960.0,535700.0,545440.0,555180.0,564920.0,574660.0,584400.0,594140.0,603880.0,613620.0,623360.0,633100.0,642840.0,652580.0,662320.0,672060.0,681800.0,691540.0,701280.0,711020.0,720760.0,730500.0,740240.0,749980.0,759720.0,769460.0,779200.0,788940.0,798680.0,808420.0,818160.0,827900.0,837640.0,847380.0,857120.0,866860.0,876600.0,886340.0,896080.0,905820.0,915560.0,925300.0,935040.0,944780.0,954520.0,964260.0,974000.0],\"times\":[553166.0,1407333.0,1543543.0,2156749.0,2650084.0,3245127.0,3586874.0,4985539.0,5000041.0,5212459.0,5607418.0,6259331.0,6746501.0,7318293.0,7701876.0,8216458.0,8982957.0,9277417.0,9764751.0,10712584.0,10760834.0,11689083.0,12124335.0,12690791.0,13148583.0,13430623.0,14129169.0,14605667.0,15120877.0,16168998.0,15982375.0,16633790.0,17169334.0,20715542.0,20882957.0,21727710.0,22505749.0,22067792.0,22690376.0,22636457.0,23310419.0,23397083.0,23772458.0,23989209.0,24237580.0,24460208.0,25609750.0,24933707.0,25966002.0,28671752.0,29815458.0,30358332.0,31037668.0,31257625.0,31807873.0,32795375.0,33493209.0,33932833.0,33964875.0,34300582.0,34884876.0,35966789.0,36042625.0,37390958.0,37452127.0,38530501.0,41000331.0,41283167.0,41672250.0,41465167.0,41094333.0,41924916.0,42057417.0,42212083.0,42962040.0,42077248.0,42722251.0,43474789.0,43376669.0,42896000.0,43933457.0,43963082.0,47064207.0,47460000.0,47892293.0,48376499.0,49196583.0,49754374.0,50422291.0,51198545.0,56394709.0,55814917.0,56381042.0,57015249.0,57866625.0,58259248.0,58229210.0,58688042.0,57597377.0,61658665.0]}"
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    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.023182980187090252,\"upper_bound\":0.011271694652966988},\"point_estimate\":-0.006072608355940146,\"standard_error\":0.008760055582803121},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.04075206772035045,\"upper_bound\":0.014487752842098356},\"point_estimate\":-0.01025962276954473,\"standard_error\":0.013846433651807094}}"
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  {
    "path": "docs/criterion/Import as owned and destroy/Arc_str_/20/new/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"Arc<str>\",\"value_str\":\"20\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/Arc<str>/20\",\"directory_name\":\"Import as owned and destroy/Arc_str_/20\",\"title\":\"Import as owned and destroy/Arc<str>/20\"}"
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    "path": "docs/criterion/Import as owned and destroy/Arc_str_/20/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":56.99882054303447,\"upper_bound\":58.39455439160427},\"point_estimate\":57.68579190255569,\"standard_error\":0.35590834276001104},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":56.79322381930185,\"upper_bound\":58.752749828884326},\"point_estimate\":58.05280180459985,\"standard_error\":0.5492003091837233},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.8506463691106387,\"upper_bound\":5.2499245212653385},\"point_estimate\":4.090593766870941,\"standard_error\":0.5967144899204374},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":58.5586585879374,\"upper_bound\":59.875893380948455},\"point_estimate\":59.238566628605,\"standard_error\":0.33589586134984284},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.033497218115003,\"upper_bound\":4.207103682230954},\"point_estimate\":3.5791759691835177,\"standard_error\":0.30706214713460106}}"
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    "path": "docs/criterion/Import as owned and destroy/Arc_str_/20/new/sample.json",
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    "content": "[37.804090967540276,46.10903737498248,68.25556112816167,76.56050753560388]"
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  {
    "path": "docs/criterion/Import as owned and destroy/Arc_str_/20/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/Arc&lt;str&gt;/20 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/Arc&lt;str&gt;/20</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">58.559 ns</td>\n                                <td>59.239 ns</td>\n                                <td class=\"ci-bound\">59.876 ns</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.8227470</td>\n                                <td>0.8321945</td>\n                                <td class=\"ci-bound\">0.8238819</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">56.999 ns</td>\n                                <td>57.686 ns</td>\n                                <td class=\"ci-bound\">58.395 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">3.0335 ns</td>\n                                <td>3.5792 ns</td>\n                                <td class=\"ci-bound\">4.2071 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">56.793 ns</td>\n                                <td>58.053 ns</td>\n                                <td class=\"ci-bound\">58.753 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">2.8506 ns</td>\n                                <td>4.0906 ns</td>\n                                <td class=\"ci-bound\">5.2499 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−2.3183%</td>\n                            <td>−0.6073%</td>\n                            <td class=\"ci-bound\">+1.1272%</td>\n                            <td>(p = 0.49 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
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    "path": "docs/criterion/Import as owned and destroy/Arc_str_/500/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":100.35863267481878,\"upper_bound\":102.78806647282667},\"point_estimate\":101.63020679588699,\"standard_error\":0.6207803657736525},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":101.19863152037263,\"upper_bound\":103.7391823471624},\"point_estimate\":102.66324122307326,\"standard_error\":0.7371833072300654},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.3011100732700913,\"upper_bound\":5.163160244301159},\"point_estimate\":4.1065360090050245,\"standard_error\":0.4677870455751196},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":104.21994120182241,\"upper_bound\":105.89517312348197},\"point_estimate\":105.09220976603187,\"standard_error\":0.428088024024974},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":4.4306442793803695,\"upper_bound\":7.806554463670714},\"point_estimate\":6.234695995922934,\"standard_error\":0.8639777548208202}}"
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  {
    "path": "docs/criterion/Import as owned and destroy/Arc_str_/500/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/Arc&lt;str&gt;/500 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/Arc&lt;str&gt;/500</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">104.22 ns</td>\n                                <td>105.09 ns</td>\n                                <td class=\"ci-bound\">105.90 ns</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.8869550</td>\n                                <td>0.8935113</td>\n                                <td class=\"ci-bound\">0.8879492</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">100.36 ns</td>\n                                <td>101.63 ns</td>\n                                <td class=\"ci-bound\">102.79 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">4.4306 ns</td>\n                                <td>6.2347 ns</td>\n                                <td class=\"ci-bound\">7.8066 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">101.20 ns</td>\n                                <td>102.66 ns</td>\n                                <td class=\"ci-bound\">103.74 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">3.3011 ns</td>\n                                <td>4.1065 ns</td>\n                                <td class=\"ci-bound\">5.1632 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−2.3062%</td>\n                            <td>−0.3076%</td>\n                            <td class=\"ci-bound\">+1.6894%</td>\n                            <td>(p = 0.77 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Arc_str_/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/Arc&lt;str&gt; Summary - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/Arc&lt;str&gt;</h2>\n        <h3>Violin Plot</h3>\n        <a href=\"violin.svg\">\n            <img src=\"violin.svg\" alt=\"Violin Plot\" />\n        </a>\n        <p>This chart shows the relationship between function/parameter and iteration time. The thickness of the shaded\n            region indicates the probability that a measurement of the given function/parameter would take a particular\n            length of time.</p>\n        <h3>Line Chart</h3>\n        <img src=\"lines.svg\" alt=\"Line Chart\" />\n        <p>This chart shows the mean measured time for each function as the input (or the size of the input) increases.</p>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/Arc_str_/0/report/index.html\">\n                <h4>Import as owned and destroy/Arc&lt;str&gt;/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/Arc_str_/0/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/Arc_str_/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/Arc_str_/0/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/Arc_str_/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/Arc_str_/10/report/index.html\">\n                <h4>Import as owned and destroy/Arc&lt;str&gt;/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/Arc_str_/10/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/Arc_str_/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/Arc_str_/10/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/Arc_str_/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/Arc_str_/20/report/index.html\">\n                <h4>Import as owned and destroy/Arc&lt;str&gt;/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/Arc_str_/20/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/Arc_str_/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/Arc_str_/20/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/Arc_str_/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/Arc_str_/100/report/index.html\">\n                <h4>Import as owned and destroy/Arc&lt;str&gt;/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/Arc_str_/100/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/Arc_str_/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/Arc_str_/100/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/Arc_str_/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/Arc_str_/500/report/index.html\">\n                <h4>Import as owned and destroy/Arc&lt;str&gt;/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/Arc_str_/500/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/Arc_str_/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/Arc_str_/500/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/Arc_str_/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Cow_'_, str_/0/base/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"Cow<'_, str>\",\"value_str\":\"0\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/Cow<'_, str>/0\",\"directory_name\":\"Import as owned and destroy/Cow_'_, str_/0\",\"title\":\"Import as owned and destroy/Cow<'_, str>/0\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Cow_'_, str_/0/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.6935933963363371,\"upper_bound\":0.7900657972970381},\"point_estimate\":0.7362291789647888,\"standard_error\":0.024736339694861696},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.7108373848277234,\"upper_bound\":0.7858723594944226},\"point_estimate\":0.7763804924422777,\"standard_error\":0.019737612911152076},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.08837278563673415,\"upper_bound\":0.21813027320615516},\"point_estimate\":0.12299613500674549,\"standard_error\":0.031625641147527014},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.7480466480973897,\"upper_bound\":0.779612106761877},\"point_estimate\":0.7653565395514442,\"standard_error\":0.008029786722160738},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.13204942996988572,\"upper_bound\":0.3778128229935145},\"point_estimate\":0.2506053382897813,\"standard_error\":0.07514801263740692}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Cow_'_, str_/0/base/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[160846.0,321692.0,482538.0,643384.0,804230.0,965076.0,1125922.0,1286768.0,1447614.0,1608460.0,1769306.0,1930152.0,2090998.0,2251844.0,2412690.0,2573536.0,2734382.0,2895228.0,3056074.0,3216920.0,3377766.0,3538612.0,3699458.0,3860304.0,4021150.0,4181996.0,4342842.0,4503688.0,4664534.0,4825380.0,4986226.0,5147072.0,5307918.0,5468764.0,5629610.0,5790456.0,5951302.0,6112148.0,6272994.0,6433840.0,6594686.0,6755532.0,6916378.0,7077224.0,7238070.0,7398916.0,7559762.0,7720608.0,7881454.0,8042300.0,8203146.0,8363992.0,8524838.0,8685684.0,8846530.0,9007376.0,9168222.0,9329068.0,9489914.0,9650760.0,9811606.0,9972452.0,10133298.0,10294144.0,10454990.0,10615836.0,10776682.0,10937528.0,11098374.0,11259220.0,11420066.0,11580912.0,11741758.0,11902604.0,12063450.0,12224296.0,12385142.0,12545988.0,12706834.0,12867680.0,13028526.0,13189372.0,13350218.0,13511064.0,13671910.0,13832756.0,13993602.0,14154448.0,14315294.0,14476140.0,14636986.0,14797832.0,14958678.0,15119524.0,15280370.0,15441216.0,15602062.0,15762908.0,15923754.0,16084600.0],\"times\":[433123.0,165832.0,244874.0,338250.0,960374.0,1314455.0,708835.0,1022167.0,989916.0,1387626.0,1086709.0,1623335.0,1388291.0,1630542.0,2209916.0,1785667.0,1973750.0,2137127.0,2152250.0,2286707.0,2626292.0,1898413.0,1985082.0,2080834.0,2176336.0,2253624.0,2397959.0,2473749.0,2591878.0,2674416.0,2776334.0,2863707.0,3047080.0,3037708.0,3104835.0,3203585.0,3229834.0,3372666.0,3393585.0,3489417.0,3553458.0,3606958.0,3733500.0,3740750.0,3793623.0,3829498.0,3924168.0,4070584.0,4088375.0,4236125.0,4303709.0,4399833.0,7951417.0,7660251.0,7723167.0,7839293.0,8029874.0,8143291.0,8159209.0,8240790.0,8279418.0,8484038.0,8464960.0,8667707.0,8889083.0,8754457.0,8850959.0,9289793.0,9029499.0,9094209.0,9443334.0,9429416.0,9337043.0,9576751.0,9691501.0,9719917.0,9861876.0,9858667.0,9984373.0,10240749.0,10240375.0,10379499.0,10403960.0,10519750.0,10683084.0,10878124.0,10981917.0,11240249.0,11272875.0,11189000.0,11394708.0,11471836.0,11682542.0,11712206.0,12065625.0,11954875.0,12044082.0,12069290.0,12478540.0,12871333.0]}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Cow_'_, str_/0/base/tukey.json",
    "content": "[-0.22063285554770384,0.16554734618674494,1.1953612174786084,1.5815414192130572]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Cow_'_, str_/0/change/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.028848479675405887,\"upper_bound\":0.13503057667723342},\"point_estimate\":0.04634813837566587,\"standard_error\":0.041838012864532044},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.04903072065955205,\"upper_bound\":0.0612031112235214},\"point_estimate\":0.03304956412491378,\"standard_error\":0.02847273703777581}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Cow_'_, str_/0/new/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"Cow<'_, str>\",\"value_str\":\"0\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/Cow<'_, str>/0\",\"directory_name\":\"Import as owned and destroy/Cow_'_, str_/0\",\"title\":\"Import as owned and destroy/Cow<'_, str>/0\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Cow_'_, str_/0/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.6935933963363371,\"upper_bound\":0.7900657972970381},\"point_estimate\":0.7362291789647888,\"standard_error\":0.024736339694861696},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.7108373848277234,\"upper_bound\":0.7858723594944226},\"point_estimate\":0.7763804924422777,\"standard_error\":0.019737612911152076},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.08837278563673415,\"upper_bound\":0.21813027320615516},\"point_estimate\":0.12299613500674549,\"standard_error\":0.031625641147527014},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.7480466480973897,\"upper_bound\":0.779612106761877},\"point_estimate\":0.7653565395514442,\"standard_error\":0.008029786722160738},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.13204942996988572,\"upper_bound\":0.3778128229935145},\"point_estimate\":0.2506053382897813,\"standard_error\":0.07514801263740692}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Cow_'_, str_/0/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[160846.0,321692.0,482538.0,643384.0,804230.0,965076.0,1125922.0,1286768.0,1447614.0,1608460.0,1769306.0,1930152.0,2090998.0,2251844.0,2412690.0,2573536.0,2734382.0,2895228.0,3056074.0,3216920.0,3377766.0,3538612.0,3699458.0,3860304.0,4021150.0,4181996.0,4342842.0,4503688.0,4664534.0,4825380.0,4986226.0,5147072.0,5307918.0,5468764.0,5629610.0,5790456.0,5951302.0,6112148.0,6272994.0,6433840.0,6594686.0,6755532.0,6916378.0,7077224.0,7238070.0,7398916.0,7559762.0,7720608.0,7881454.0,8042300.0,8203146.0,8363992.0,8524838.0,8685684.0,8846530.0,9007376.0,9168222.0,9329068.0,9489914.0,9650760.0,9811606.0,9972452.0,10133298.0,10294144.0,10454990.0,10615836.0,10776682.0,10937528.0,11098374.0,11259220.0,11420066.0,11580912.0,11741758.0,11902604.0,12063450.0,12224296.0,12385142.0,12545988.0,12706834.0,12867680.0,13028526.0,13189372.0,13350218.0,13511064.0,13671910.0,13832756.0,13993602.0,14154448.0,14315294.0,14476140.0,14636986.0,14797832.0,14958678.0,15119524.0,15280370.0,15441216.0,15602062.0,15762908.0,15923754.0,16084600.0],\"times\":[433123.0,165832.0,244874.0,338250.0,960374.0,1314455.0,708835.0,1022167.0,989916.0,1387626.0,1086709.0,1623335.0,1388291.0,1630542.0,2209916.0,1785667.0,1973750.0,2137127.0,2152250.0,2286707.0,2626292.0,1898413.0,1985082.0,2080834.0,2176336.0,2253624.0,2397959.0,2473749.0,2591878.0,2674416.0,2776334.0,2863707.0,3047080.0,3037708.0,3104835.0,3203585.0,3229834.0,3372666.0,3393585.0,3489417.0,3553458.0,3606958.0,3733500.0,3740750.0,3793623.0,3829498.0,3924168.0,4070584.0,4088375.0,4236125.0,4303709.0,4399833.0,7951417.0,7660251.0,7723167.0,7839293.0,8029874.0,8143291.0,8159209.0,8240790.0,8279418.0,8484038.0,8464960.0,8667707.0,8889083.0,8754457.0,8850959.0,9289793.0,9029499.0,9094209.0,9443334.0,9429416.0,9337043.0,9576751.0,9691501.0,9719917.0,9861876.0,9858667.0,9984373.0,10240749.0,10240375.0,10379499.0,10403960.0,10519750.0,10683084.0,10878124.0,10981917.0,11240249.0,11272875.0,11189000.0,11394708.0,11471836.0,11682542.0,11712206.0,12065625.0,11954875.0,12044082.0,12069290.0,12478540.0,12871333.0]}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Cow_'_, str_/0/new/tukey.json",
    "content": "[-0.22063285554770384,0.16554734618674494,1.1953612174786084,1.5815414192130572]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Cow_'_, str_/0/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/Cow&lt;&#39;_, str&gt;/0 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/Cow&lt;&#39;_, str&gt;/0</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">748.05 ps</td>\n                                <td>765.36 ps</td>\n                                <td class=\"ci-bound\">779.61 ps</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.3626275</td>\n                                <td>0.3701726</td>\n                                <td class=\"ci-bound\">0.3650214</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">693.59 ps</td>\n                                <td>736.23 ps</td>\n                                <td class=\"ci-bound\">790.07 ps</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">132.05 ps</td>\n                                <td>250.61 ps</td>\n                                <td class=\"ci-bound\">377.81 ps</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">710.84 ps</td>\n                                <td>776.38 ps</td>\n                                <td class=\"ci-bound\">785.87 ps</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">88.373 ps</td>\n                                <td>123.00 ps</td>\n                                <td class=\"ci-bound\">218.13 ps</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−2.8848%</td>\n                            <td>+4.6348%</td>\n                            <td class=\"ci-bound\">+13.503%</td>\n                            <td>(p = 0.27 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Cow_'_, str_/10/base/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"Cow<'_, str>\",\"value_str\":\"10\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/Cow<'_, str>/10\",\"directory_name\":\"Import as owned and destroy/Cow_'_, str_/10\",\"title\":\"Import as owned and destroy/Cow<'_, str>/10\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Cow_'_, str_/10/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":28.662145985069923,\"upper_bound\":30.10583454273917},\"point_estimate\":29.35680402199484,\"standard_error\":0.3687207857301947},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":27.819615899770202,\"upper_bound\":31.28186631896521},\"point_estimate\":29.112171493307095,\"standard_error\":0.8444021755127579},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.0794244603500034,\"upper_bound\":5.076053438576063},\"point_estimate\":4.653071892149554,\"standard_error\":0.5067843327099436},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":30.131683195749815,\"upper_bound\":31.243050738071624},\"point_estimate\":30.708034895437,\"standard_error\":0.28443244972216347},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.970456578566502,\"upper_bound\":4.673830489997651},\"point_estimate\":3.7156660537808692,\"standard_error\":0.48308939668862677}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Cow_'_, str_/10/base/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[17348.0,34696.0,52044.0,69392.0,86740.0,104088.0,121436.0,138784.0,156132.0,173480.0,190828.0,208176.0,225524.0,242872.0,260220.0,277568.0,294916.0,312264.0,329612.0,346960.0,364308.0,381656.0,399004.0,416352.0,433700.0,451048.0,468396.0,485744.0,503092.0,520440.0,537788.0,555136.0,572484.0,589832.0,607180.0,624528.0,641876.0,659224.0,676572.0,693920.0,711268.0,728616.0,745964.0,763312.0,780660.0,798008.0,815356.0,832704.0,850052.0,867400.0,884748.0,902096.0,919444.0,936792.0,954140.0,971488.0,988836.0,1006184.0,1023532.0,1040880.0,1058228.0,1075576.0,1092924.0,1110272.0,1127620.0,1144968.0,1162316.0,1179664.0,1197012.0,1214360.0,1231708.0,1249056.0,1266404.0,1283752.0,1301100.0,1318448.0,1335796.0,1353144.0,1370492.0,1387840.0,1405188.0,1422536.0,1439884.0,1457232.0,1474580.0,1491928.0,1509276.0,1526624.0,1543972.0,1561320.0,1578668.0,1596016.0,1613364.0,1630712.0,1648060.0,1665408.0,1682756.0,1700104.0,1717452.0,1734800.0],\"times\":[843543.0,868958.0,1303251.0,2241665.0,2244292.0,2674416.0,3419458.0,3906542.0,3905374.0,4388875.0,5350293.0,5272082.0,5719667.0,6337041.0,6524334.0,7561836.0,7433708.0,7916543.0,8283831.0,8737957.0,9191623.0,9498750.0,10115207.0,10893751.0,11225417.0,11496916.0,11965541.0,12171418.0,13094209.0,13485961.0,13490374.0,13913627.0,14536832.0,14973417.0,15281289.0,15832959.0,16164959.0,24052168.0,23567793.0,23773166.0,23513707.0,23784250.0,22812542.0,23480791.0,23151876.0,23564460.0,23853333.0,24197666.0,24656041.0,24111042.0,25259543.0,24452539.0,24676083.0,25321710.0,26650041.0,32076210.0,32093082.0,33167043.0,32068958.0,33254334.0,33314500.0,34473876.0,35658500.0,35912167.0,35783543.0,36211166.0,35663500.0,37484709.0,37615667.0,38181459.0,38530125.0,39291457.0,40037292.0,42255375.0,43877666.0,45342374.0,44527833.0,45207460.0,45665834.0,44679999.0,43993084.0,44651836.0,46003000.0,43792792.0,42581874.0,43512376.0,43418418.0,42428874.0,42952708.0,42089040.0,43725627.0,43127292.0,49152165.0,53166584.0,52753957.0,54803875.0,52853249.0,55600332.0,55866625.0,55404709.0]}"
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  {
    "path": "docs/criterion/Import as owned and destroy/Cow_'_, str_/10/base/tukey.json",
    "content": "[7.422372319392991,16.625579749735692,41.167466230649566,50.37067366099227]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Cow_'_, str_/10/change/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.028522905992567987,\"upper_bound\":0.039228647803726674},\"point_estimate\":0.003286008156166531,\"standard_error\":0.017253130833573996},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.08027561607082566,\"upper_bound\":0.07384476055620579},\"point_estimate\":-0.01151077490093988,\"standard_error\":0.039130238793931266}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Cow_'_, str_/10/new/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"Cow<'_, str>\",\"value_str\":\"10\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/Cow<'_, str>/10\",\"directory_name\":\"Import as owned and destroy/Cow_'_, str_/10\",\"title\":\"Import as owned and destroy/Cow<'_, str>/10\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Cow_'_, str_/10/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":28.662145985069923,\"upper_bound\":30.10583454273917},\"point_estimate\":29.35680402199484,\"standard_error\":0.3687207857301947},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":27.819615899770202,\"upper_bound\":31.28186631896521},\"point_estimate\":29.112171493307095,\"standard_error\":0.8444021755127579},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.0794244603500034,\"upper_bound\":5.076053438576063},\"point_estimate\":4.653071892149554,\"standard_error\":0.5067843327099436},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":30.131683195749815,\"upper_bound\":31.243050738071624},\"point_estimate\":30.708034895437,\"standard_error\":0.28443244972216347},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.970456578566502,\"upper_bound\":4.673830489997651},\"point_estimate\":3.7156660537808692,\"standard_error\":0.48308939668862677}}"
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    "path": "docs/criterion/Import as owned and destroy/Cow_'_, str_/10/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[17348.0,34696.0,52044.0,69392.0,86740.0,104088.0,121436.0,138784.0,156132.0,173480.0,190828.0,208176.0,225524.0,242872.0,260220.0,277568.0,294916.0,312264.0,329612.0,346960.0,364308.0,381656.0,399004.0,416352.0,433700.0,451048.0,468396.0,485744.0,503092.0,520440.0,537788.0,555136.0,572484.0,589832.0,607180.0,624528.0,641876.0,659224.0,676572.0,693920.0,711268.0,728616.0,745964.0,763312.0,780660.0,798008.0,815356.0,832704.0,850052.0,867400.0,884748.0,902096.0,919444.0,936792.0,954140.0,971488.0,988836.0,1006184.0,1023532.0,1040880.0,1058228.0,1075576.0,1092924.0,1110272.0,1127620.0,1144968.0,1162316.0,1179664.0,1197012.0,1214360.0,1231708.0,1249056.0,1266404.0,1283752.0,1301100.0,1318448.0,1335796.0,1353144.0,1370492.0,1387840.0,1405188.0,1422536.0,1439884.0,1457232.0,1474580.0,1491928.0,1509276.0,1526624.0,1543972.0,1561320.0,1578668.0,1596016.0,1613364.0,1630712.0,1648060.0,1665408.0,1682756.0,1700104.0,1717452.0,1734800.0],\"times\":[843543.0,868958.0,1303251.0,2241665.0,2244292.0,2674416.0,3419458.0,3906542.0,3905374.0,4388875.0,5350293.0,5272082.0,5719667.0,6337041.0,6524334.0,7561836.0,7433708.0,7916543.0,8283831.0,8737957.0,9191623.0,9498750.0,10115207.0,10893751.0,11225417.0,11496916.0,11965541.0,12171418.0,13094209.0,13485961.0,13490374.0,13913627.0,14536832.0,14973417.0,15281289.0,15832959.0,16164959.0,24052168.0,23567793.0,23773166.0,23513707.0,23784250.0,22812542.0,23480791.0,23151876.0,23564460.0,23853333.0,24197666.0,24656041.0,24111042.0,25259543.0,24452539.0,24676083.0,25321710.0,26650041.0,32076210.0,32093082.0,33167043.0,32068958.0,33254334.0,33314500.0,34473876.0,35658500.0,35912167.0,35783543.0,36211166.0,35663500.0,37484709.0,37615667.0,38181459.0,38530125.0,39291457.0,40037292.0,42255375.0,43877666.0,45342374.0,44527833.0,45207460.0,45665834.0,44679999.0,43993084.0,44651836.0,46003000.0,43792792.0,42581874.0,43512376.0,43418418.0,42428874.0,42952708.0,42089040.0,43725627.0,43127292.0,49152165.0,53166584.0,52753957.0,54803875.0,52853249.0,55600332.0,55866625.0,55404709.0]}"
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    "path": "docs/criterion/Import as owned and destroy/Cow_'_, str_/10/new/tukey.json",
    "content": "[7.422372319392991,16.625579749735692,41.167466230649566,50.37067366099227]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Cow_'_, str_/10/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/Cow&lt;&#39;_, str&gt;/10 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/Cow&lt;&#39;_, str&gt;/10</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">30.132 ns</td>\n                                <td>30.708 ns</td>\n                                <td class=\"ci-bound\">31.243 ns</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.5775728</td>\n                                <td>0.5914156</td>\n                                <td class=\"ci-bound\">0.5794485</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">28.662 ns</td>\n                                <td>29.357 ns</td>\n                                <td class=\"ci-bound\">30.106 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">2.9705 ns</td>\n                                <td>3.7157 ns</td>\n                                <td class=\"ci-bound\">4.6738 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">27.820 ns</td>\n                                <td>29.112 ns</td>\n                                <td class=\"ci-bound\">31.282 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">3.0794 ns</td>\n                                <td>4.6531 ns</td>\n                                <td class=\"ci-bound\">5.0761 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−2.8523%</td>\n                            <td>+0.3286%</td>\n                            <td class=\"ci-bound\">+3.9229%</td>\n                            <td>(p = 0.85 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
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  {
    "path": "docs/criterion/Import as owned and destroy/Cow_'_, str_/100/base/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"Cow<'_, str>\",\"value_str\":\"100\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/Cow<'_, str>/100\",\"directory_name\":\"Import as owned and destroy/Cow_'_, str_/100\",\"title\":\"Import as owned and destroy/Cow<'_, str>/100\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Cow_'_, str_/100/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":35.23968342872073,\"upper_bound\":36.988686335654535},\"point_estimate\":36.1190631775806,\"standard_error\":0.44618299599089406},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":34.884724380656365,\"upper_bound\":36.97122364252051},\"point_estimate\":36.00761883356205,\"standard_error\":0.5774275371503896},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.286594806568675,\"upper_bound\":5.581754223871893},\"point_estimate\":4.197927363662005,\"standard_error\":0.5741512081408002},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":36.522812109207194,\"upper_bound\":38.28577042365714},\"point_estimate\":37.41619816505175,\"standard_error\":0.44830597839530045},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.888101557726696,\"upper_bound\":5.029863282291056},\"point_estimate\":4.493201891566497,\"standard_error\":0.29021020913590445}}"
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    "path": "docs/criterion/Import as owned and destroy/Cow_'_, str_/100/change/estimates.json",
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    "path": "docs/criterion/Import as owned and destroy/Cow_'_, str_/100/new/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"Cow<'_, str>\",\"value_str\":\"100\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/Cow<'_, str>/100\",\"directory_name\":\"Import as owned and destroy/Cow_'_, str_/100\",\"title\":\"Import as owned and destroy/Cow<'_, str>/100\"}"
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    "path": "docs/criterion/Import as owned and destroy/Cow_'_, str_/100/new/estimates.json",
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    "path": "docs/criterion/Import as owned and destroy/Cow_'_, str_/100/new/sample.json",
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  {
    "path": "docs/criterion/Import as owned and destroy/Cow_'_, str_/100/new/tukey.json",
    "content": "[16.202480718779285,24.857890348490038,47.93898269438538,56.594392324096134]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Cow_'_, str_/100/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/Cow&lt;&#39;_, str&gt;/100 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/Cow&lt;&#39;_, str&gt;/100</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">36.523 ns</td>\n                                <td>37.416 ns</td>\n                                <td class=\"ci-bound\">38.286 ns</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.5125500</td>\n                                <td>0.5271618</td>\n                                <td class=\"ci-bound\">0.5132983</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">35.240 ns</td>\n                                <td>36.119 ns</td>\n                                <td class=\"ci-bound\">36.989 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">3.8881 ns</td>\n                                <td>4.4932 ns</td>\n                                <td class=\"ci-bound\">5.0299 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">34.885 ns</td>\n                                <td>36.008 ns</td>\n                                <td class=\"ci-bound\">36.971 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">3.2866 ns</td>\n                                <td>4.1979 ns</td>\n                                <td class=\"ci-bound\">5.5818 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−3.0629%</td>\n                            <td>+0.1900%</td>\n                            <td class=\"ci-bound\">+3.5909%</td>\n                            <td>(p = 0.91 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Cow_'_, str_/20/base/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"Cow<'_, str>\",\"value_str\":\"20\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/Cow<'_, str>/20\",\"directory_name\":\"Import as owned and destroy/Cow_'_, str_/20\",\"title\":\"Import as owned and destroy/Cow<'_, str>/20\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Cow_'_, str_/20/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":31.181198179715572,\"upper_bound\":32.77308302499177},\"point_estimate\":31.967476499161375,\"standard_error\":0.40647127143739487},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":31.647561569359848,\"upper_bound\":32.87511138658067},\"point_estimate\":32.51112970054554,\"standard_error\":0.3471189036684075},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.7523995614224233,\"upper_bound\":5.11334209237872},\"point_estimate\":3.8493195291669684,\"standard_error\":0.5940085448597703},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":32.174359474007844,\"upper_bound\":33.573924316945075},\"point_estimate\":32.86962468399923,\"standard_error\":0.35732017073724254},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.3088234322549264,\"upper_bound\":4.998069286059623},\"point_estimate\":4.085629405100495,\"standard_error\":0.4487791355082807}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Cow_'_, str_/20/base/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[14876.0,29752.0,44628.0,59504.0,74380.0,89256.0,104132.0,119008.0,133884.0,148760.0,163636.0,178512.0,193388.0,208264.0,223140.0,238016.0,252892.0,267768.0,282644.0,297520.0,312396.0,327272.0,342148.0,357024.0,371900.0,386776.0,401652.0,416528.0,431404.0,446280.0,461156.0,476032.0,490908.0,505784.0,520660.0,535536.0,550412.0,565288.0,580164.0,595040.0,609916.0,624792.0,639668.0,654544.0,669420.0,684296.0,699172.0,714048.0,728924.0,743800.0,758676.0,773552.0,788428.0,803304.0,818180.0,833056.0,847932.0,862808.0,877684.0,892560.0,907436.0,922312.0,937188.0,952064.0,966940.0,981816.0,996692.0,1011568.0,1026444.0,1041320.0,1056196.0,1071072.0,1085948.0,1100824.0,1115700.0,1130576.0,1145452.0,1160328.0,1175204.0,1190080.0,1204956.0,1219832.0,1234708.0,1249584.0,1264460.0,1279336.0,1294212.0,1309088.0,1323964.0,1338840.0,1353716.0,1368592.0,1383468.0,1398344.0,1413220.0,1428096.0,1442972.0,1457848.0,1472724.0,1487600.0],\"times\":[756919.0,775959.0,1156167.0,2189292.0,1921417.0,2381542.0,2696583.0,3903166.0,3855292.0,3861250.0,4259208.0,4724460.0,5007081.0,5398542.0,5804583.0,6063875.0,6940334.0,7043916.0,7416294.0,7617666.0,8276126.0,13347708.0,12343376.0,12215004.0,12988166.0,12714750.0,12305876.0,12294831.0,12529833.0,12563876.0,12629458.0,15919333.0,16322040.0,16704790.0,17639833.0,17535750.0,18081000.0,18555833.0,18786915.0,19045998.0,19774167.0,19961042.0,24357499.0,23548916.0,23478708.0,22923502.0,23002958.0,22715626.0,22618584.0,22329542.0,22200625.0,22397291.0,21488458.0,26119165.0,27437249.0,27835834.0,28351374.0,29022711.0,30160790.0,32147748.0,32422417.0,32562000.0,32753960.0,32546083.0,35461375.0,36265416.0,35074749.0,33972290.0,33082290.0,33131125.0,31814206.0,32851709.0,31277292.0,30311460.0,31463957.0,36925959.0,37626083.0,38038292.0,38049624.0,39388042.0,44627542.0,45969961.0,45440999.0,45549625.0,46309376.0,46518333.0,47545043.0,46831916.0,46335459.0,45242543.0,44006043.0,43086916.0,43280667.0,42160584.0,41175959.0,42672292.0,46976875.0,46203373.0,44496793.0,46426874.0]}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Cow_'_, str_/20/base/tukey.json",
    "content": "[13.333574712535892,21.177633310363802,42.09512290457157,49.93918150239948]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Cow_'_, str_/20/change/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.017910400646013395,\"upper_bound\":0.04946868138829234},\"point_estimate\":0.01599651892658982,\"standard_error\":0.017170400524176496},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.024029580053494537,\"upper_bound\":0.051238919261378246},\"point_estimate\":0.0053008407690862125,\"standard_error\":0.018667918435434656}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Cow_'_, str_/20/new/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"Cow<'_, str>\",\"value_str\":\"20\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/Cow<'_, str>/20\",\"directory_name\":\"Import as owned and destroy/Cow_'_, str_/20\",\"title\":\"Import as owned and destroy/Cow<'_, str>/20\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Cow_'_, str_/20/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":31.181198179715572,\"upper_bound\":32.77308302499177},\"point_estimate\":31.967476499161375,\"standard_error\":0.40647127143739487},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":31.647561569359848,\"upper_bound\":32.87511138658067},\"point_estimate\":32.51112970054554,\"standard_error\":0.3471189036684075},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.7523995614224233,\"upper_bound\":5.11334209237872},\"point_estimate\":3.8493195291669684,\"standard_error\":0.5940085448597703},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":32.174359474007844,\"upper_bound\":33.573924316945075},\"point_estimate\":32.86962468399923,\"standard_error\":0.35732017073724254},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.3088234322549264,\"upper_bound\":4.998069286059623},\"point_estimate\":4.085629405100495,\"standard_error\":0.4487791355082807}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Cow_'_, str_/20/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[14876.0,29752.0,44628.0,59504.0,74380.0,89256.0,104132.0,119008.0,133884.0,148760.0,163636.0,178512.0,193388.0,208264.0,223140.0,238016.0,252892.0,267768.0,282644.0,297520.0,312396.0,327272.0,342148.0,357024.0,371900.0,386776.0,401652.0,416528.0,431404.0,446280.0,461156.0,476032.0,490908.0,505784.0,520660.0,535536.0,550412.0,565288.0,580164.0,595040.0,609916.0,624792.0,639668.0,654544.0,669420.0,684296.0,699172.0,714048.0,728924.0,743800.0,758676.0,773552.0,788428.0,803304.0,818180.0,833056.0,847932.0,862808.0,877684.0,892560.0,907436.0,922312.0,937188.0,952064.0,966940.0,981816.0,996692.0,1011568.0,1026444.0,1041320.0,1056196.0,1071072.0,1085948.0,1100824.0,1115700.0,1130576.0,1145452.0,1160328.0,1175204.0,1190080.0,1204956.0,1219832.0,1234708.0,1249584.0,1264460.0,1279336.0,1294212.0,1309088.0,1323964.0,1338840.0,1353716.0,1368592.0,1383468.0,1398344.0,1413220.0,1428096.0,1442972.0,1457848.0,1472724.0,1487600.0],\"times\":[756919.0,775959.0,1156167.0,2189292.0,1921417.0,2381542.0,2696583.0,3903166.0,3855292.0,3861250.0,4259208.0,4724460.0,5007081.0,5398542.0,5804583.0,6063875.0,6940334.0,7043916.0,7416294.0,7617666.0,8276126.0,13347708.0,12343376.0,12215004.0,12988166.0,12714750.0,12305876.0,12294831.0,12529833.0,12563876.0,12629458.0,15919333.0,16322040.0,16704790.0,17639833.0,17535750.0,18081000.0,18555833.0,18786915.0,19045998.0,19774167.0,19961042.0,24357499.0,23548916.0,23478708.0,22923502.0,23002958.0,22715626.0,22618584.0,22329542.0,22200625.0,22397291.0,21488458.0,26119165.0,27437249.0,27835834.0,28351374.0,29022711.0,30160790.0,32147748.0,32422417.0,32562000.0,32753960.0,32546083.0,35461375.0,36265416.0,35074749.0,33972290.0,33082290.0,33131125.0,31814206.0,32851709.0,31277292.0,30311460.0,31463957.0,36925959.0,37626083.0,38038292.0,38049624.0,39388042.0,44627542.0,45969961.0,45440999.0,45549625.0,46309376.0,46518333.0,47545043.0,46831916.0,46335459.0,45242543.0,44006043.0,43086916.0,43280667.0,42160584.0,41175959.0,42672292.0,46976875.0,46203373.0,44496793.0,46426874.0]}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Cow_'_, str_/20/new/tukey.json",
    "content": "[13.333574712535892,21.177633310363802,42.09512290457157,49.93918150239948]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Cow_'_, str_/20/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/Cow&lt;&#39;_, str&gt;/20 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/Cow&lt;&#39;_, str&gt;/20</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">32.174 ns</td>\n                                <td>32.870 ns</td>\n                                <td class=\"ci-bound\">33.574 ns</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.4422576</td>\n                                <td>0.4575514</td>\n                                <td class=\"ci-bound\">0.4418713</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">31.181 ns</td>\n                                <td>31.967 ns</td>\n                                <td class=\"ci-bound\">32.773 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">3.3088 ns</td>\n                                <td>4.0856 ns</td>\n                                <td class=\"ci-bound\">4.9981 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">31.648 ns</td>\n                                <td>32.511 ns</td>\n                                <td class=\"ci-bound\">32.875 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">2.7524 ns</td>\n                                <td>3.8493 ns</td>\n                                <td class=\"ci-bound\">5.1133 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−1.7910%</td>\n                            <td>+1.5997%</td>\n                            <td class=\"ci-bound\">+4.9469%</td>\n                            <td>(p = 0.36 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
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    "path": "docs/criterion/Import as owned and destroy/Cow_'_, str_/500/base/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"Cow<'_, str>\",\"value_str\":\"500\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/Cow<'_, str>/500\",\"directory_name\":\"Import as owned and destroy/Cow_'_, str_/500\",\"title\":\"Import as owned and destroy/Cow<'_, str>/500\"}"
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    "path": "docs/criterion/Import as owned and destroy/Cow_'_, str_/500/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":45.47415276220672,\"upper_bound\":48.01731688946107},\"point_estimate\":46.74997358374575,\"standard_error\":0.6490047655443941},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":45.372724714623835,\"upper_bound\":48.27266488800245},\"point_estimate\":46.77702563797517,\"standard_error\":0.7964219214693793},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":4.308550204624646,\"upper_bound\":7.591567391880411},\"point_estimate\":6.032581164139882,\"standard_error\":0.8151024001258136},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":49.47134468792152,\"upper_bound\":52.182265145873245},\"point_estimate\":50.895169438358614,\"standard_error\":0.6896076133184161},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":5.5206202469404175,\"upper_bound\":7.419631454162414},\"point_estimate\":6.514947971376596,\"standard_error\":0.4830420202154658}}"
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    "path": "docs/criterion/Import as owned and destroy/Cow_'_, str_/500/change/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.06595521589841016,\"upper_bound\":0.016104728827064606},\"point_estimate\":-0.02730345154364333,\"standard_error\":0.020973822467476186},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.07452491746032341,\"upper_bound\":0.03108718983068015},\"point_estimate\":-0.019753141820476827,\"standard_error\":0.027535092254094676}}"
  },
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    "path": "docs/criterion/Import as owned and destroy/Cow_'_, str_/500/new/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"Cow<'_, str>\",\"value_str\":\"500\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/Cow<'_, str>/500\",\"directory_name\":\"Import as owned and destroy/Cow_'_, str_/500\",\"title\":\"Import as owned and destroy/Cow<'_, str>/500\"}"
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    "path": "docs/criterion/Import as owned and destroy/Cow_'_, str_/500/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":45.47415276220672,\"upper_bound\":48.01731688946107},\"point_estimate\":46.74997358374575,\"standard_error\":0.6490047655443941},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":45.372724714623835,\"upper_bound\":48.27266488800245},\"point_estimate\":46.77702563797517,\"standard_error\":0.7964219214693793},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":4.308550204624646,\"upper_bound\":7.591567391880411},\"point_estimate\":6.032581164139882,\"standard_error\":0.8151024001258136},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":49.47134468792152,\"upper_bound\":52.182265145873245},\"point_estimate\":50.895169438358614,\"standard_error\":0.6896076133184161},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":5.5206202469404175,\"upper_bound\":7.419631454162414},\"point_estimate\":6.514947971376596,\"standard_error\":0.4830420202154658}}"
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    "path": "docs/criterion/Import as owned and destroy/Cow_'_, str_/500/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[6361.0,12722.0,19083.0,25444.0,31805.0,38166.0,44527.0,50888.0,57249.0,63610.0,69971.0,76332.0,82693.0,89054.0,95415.0,101776.0,108137.0,114498.0,120859.0,127220.0,133581.0,139942.0,146303.0,152664.0,159025.0,165386.0,171747.0,178108.0,184469.0,190830.0,197191.0,203552.0,209913.0,216274.0,222635.0,228996.0,235357.0,241718.0,248079.0,254440.0,260801.0,267162.0,273523.0,279884.0,286245.0,292606.0,298967.0,305328.0,311689.0,318050.0,324411.0,330772.0,337133.0,343494.0,349855.0,356216.0,362577.0,368938.0,375299.0,381660.0,388021.0,394382.0,400743.0,407104.0,413465.0,419826.0,426187.0,432548.0,438909.0,445270.0,451631.0,457992.0,464353.0,470714.0,477075.0,483436.0,489797.0,496158.0,502519.0,508880.0,515241.0,521602.0,527963.0,534324.0,540685.0,547046.0,553407.0,559768.0,566129.0,572490.0,578851.0,585212.0,591573.0,597934.0,604295.0,610656.0,617017.0,623378.0,629739.0,636100.0],\"times\":[187918.0,364709.0,759292.0,946625.0,1310002.0,1758625.0,2276248.0,2169626.0,2590582.0,2819249.0,2544167.0,3938499.0,3868333.0,2849623.0,4181000.0,5437542.0,3817793.0,4096000.0,5628623.0,4833457.0,5382957.0,6934458.0,5954833.0,6308417.0,7640708.0,6744500.0,6810291.0,8603667.0,7950875.0,7011126.0,9936292.0,8940122.0,7758290.0,11210583.0,10397125.0,9051208.0,9617374.0,11472378.0,10396500.0,10285876.0,12756708.0,11831916.0,11991125.0,12941084.0,12683583.0,12848168.0,14421998.0,12859002.0,14063835.0,15635168.0,14726540.0,13451832.0,17204208.0,21250126.0,16759459.0,15520210.0,17488289.0,15839582.0,16077249.0,18585708.0,18064667.0,17773042.0,19422041.0,18520919.0,18859669.0,20259917.0,19282376.0,20481960.0,22270416.0,20469789.0,19864751.0,24148877.0,22446960.0,22017460.0,22385833.0,24593248.0,23626916.0,24135414.0,27237042.0,25626002.0,25077625.0,26507874.0,27430712.0,27383125.0,29768750.0,28196334.0,26883751.0,32385917.0,30208584.0,31033167.0,33634581.0,33498710.0,31400335.0,33299958.0,34459374.0,34401461.0,34513832.0,38422790.0,36626376.0,35293001.0]}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Cow_'_, str_/500/new/tukey.json",
    "content": "[18.90254949982217,30.905929479919003,62.91494276017722,74.91832274027405]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Cow_'_, str_/500/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/Cow&lt;&#39;_, str&gt;/500 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/Cow&lt;&#39;_, str&gt;/500</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">49.471 ns</td>\n                                <td>50.895 ns</td>\n                                <td class=\"ci-bound\">52.182 ns</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.4722623</td>\n                                <td>0.4892365</td>\n                                <td class=\"ci-bound\">0.4752773</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">45.474 ns</td>\n                                <td>46.750 ns</td>\n                                <td class=\"ci-bound\">48.017 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">5.5206 ns</td>\n                                <td>6.5149 ns</td>\n                                <td class=\"ci-bound\">7.4196 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">45.373 ns</td>\n                                <td>46.777 ns</td>\n                                <td class=\"ci-bound\">48.273 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">4.3086 ns</td>\n                                <td>6.0326 ns</td>\n                                <td class=\"ci-bound\">7.5916 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−6.5955%</td>\n                            <td>−2.7303%</td>\n                            <td class=\"ci-bound\">+1.6105%</td>\n                            <td>(p = 0.21 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Cow_'_, str_/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/Cow&lt;&#39;_, str&gt; Summary - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/Cow&lt;&#39;_, str&gt;</h2>\n        <h3>Violin Plot</h3>\n        <a href=\"violin.svg\">\n            <img src=\"violin.svg\" alt=\"Violin Plot\" />\n        </a>\n        <p>This chart shows the relationship between function/parameter and iteration time. The thickness of the shaded\n            region indicates the probability that a measurement of the given function/parameter would take a particular\n            length of time.</p>\n        <h3>Line Chart</h3>\n        <img src=\"lines.svg\" alt=\"Line Chart\" />\n        <p>This chart shows the mean measured time for each function as the input (or the size of the input) increases.</p>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/Cow_&#39;_, str_/0/report/index.html\">\n                <h4>Import as owned and destroy/Cow&lt;&#39;_, str&gt;/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/Cow_&#39;_, str_/0/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/Cow_&#39;_, str_/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/Cow_&#39;_, str_/0/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/Cow_&#39;_, str_/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/Cow_&#39;_, str_/10/report/index.html\">\n                <h4>Import as owned and destroy/Cow&lt;&#39;_, str&gt;/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/Cow_&#39;_, str_/10/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/Cow_&#39;_, str_/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/Cow_&#39;_, str_/10/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/Cow_&#39;_, str_/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/Cow_&#39;_, str_/20/report/index.html\">\n                <h4>Import as owned and destroy/Cow&lt;&#39;_, str&gt;/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/Cow_&#39;_, str_/20/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/Cow_&#39;_, str_/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/Cow_&#39;_, str_/20/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/Cow_&#39;_, str_/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/Cow_&#39;_, str_/100/report/index.html\">\n                <h4>Import as owned and destroy/Cow&lt;&#39;_, str&gt;/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/Cow_&#39;_, str_/100/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/Cow_&#39;_, str_/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/Cow_&#39;_, str_/100/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/Cow_&#39;_, str_/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/Cow_&#39;_, str_/500/report/index.html\">\n                <h4>Import as owned and destroy/Cow&lt;&#39;_, str&gt;/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/Cow_&#39;_, str_/500/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/Cow_&#39;_, str_/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/Cow_&#39;_, str_/500/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/Cow_&#39;_, str_/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/0/base/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"FlexStr 0.10 (LocalStr - As is)\",\"value_str\":\"0\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/0\",\"directory_name\":\"Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/0\",\"title\":\"Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/0\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/0/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.2174105632974404,\"upper_bound\":2.3209212155943755},\"point_estimate\":2.2593299330993077,\"standard_error\":0.027084428410779186},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.169831674139771,\"upper_bound\":2.3128125593032784},\"point_estimate\":2.256529756685847,\"standard_error\":0.038928222602210655},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.08538976432566761,\"upper_bound\":0.17864270396764162},\"point_estimate\":0.16305457674370233,\"standard_error\":0.029719083656677654},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.264623701546039,\"upper_bound\":2.305153993530497},\"point_estimate\":2.287032683640269,\"standard_error\":0.010333642414241015},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.11007712410494962,\"upper_bound\":0.4400373354452467},\"point_estimate\":0.2724259955195404,\"standard_error\":0.11176376067372233}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/0/base/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[136139.0,272278.0,408417.0,544556.0,680695.0,816834.0,952973.0,1089112.0,1225251.0,1361390.0,1497529.0,1633668.0,1769807.0,1905946.0,2042085.0,2178224.0,2314363.0,2450502.0,2586641.0,2722780.0,2858919.0,2995058.0,3131197.0,3267336.0,3403475.0,3539614.0,3675753.0,3811892.0,3948031.0,4084170.0,4220309.0,4356448.0,4492587.0,4628726.0,4764865.0,4901004.0,5037143.0,5173282.0,5309421.0,5445560.0,5581699.0,5717838.0,5853977.0,5990116.0,6126255.0,6262394.0,6398533.0,6534672.0,6670811.0,6806950.0,6943089.0,7079228.0,7215367.0,7351506.0,7487645.0,7623784.0,7759923.0,7896062.0,8032201.0,8168340.0,8304479.0,8440618.0,8576757.0,8712896.0,8849035.0,8985174.0,9121313.0,9257452.0,9393591.0,9529730.0,9665869.0,9802008.0,9938147.0,10074286.0,10210425.0,10346564.0,10482703.0,10618842.0,10754981.0,10891120.0,11027259.0,11163398.0,11299537.0,11435676.0,11571815.0,11707954.0,11844093.0,11980232.0,12116371.0,12252510.0,12388649.0,12524788.0,12660927.0,12797066.0,12933205.0,13069344.0,13205483.0,13341622.0,13477761.0,13613900.0],\"times\":[639167.0,564710.0,847418.0,1144707.0,1730791.0,1838127.0,2147334.0,2403669.0,2964959.0,2980999.0,3360542.0,3696085.0,4218791.0,4135582.0,4488331.0,5034456.0,5018753.0,5536125.0,6049625.0,6404250.0,6350040.0,6750500.0,7269001.0,7476708.0,7535879.0,7399459.0,7699375.0,7958168.0,8324500.0,8667499.0,8819624.0,9152708.0,9632789.0,9736753.0,9999626.0,10417373.0,10677918.0,11015251.0,11362415.0,11574418.0,11994792.0,12208794.0,12289666.0,12571167.0,13089917.0,13325793.0,13513376.0,13810041.0,13954833.0,14285499.0,14605248.0,14785502.0,15129918.0,15441127.0,15596958.0,16076293.0,16089794.0,16453623.0,16673290.0,17044458.0,17213083.0,20249208.0,20197667.0,20670707.0,21069249.0,21302164.0,21612418.0,21699874.0,21940540.0,22356083.0,22492709.0,23049206.0,23219832.0,23897875.0,24052082.0,24419168.0,24430750.0,24699663.0,24839665.0,25202709.0,25624251.0,25908540.0,26626417.0,26705749.0,27520665.0,27109541.0,27732209.0,27583833.0,27996333.0,28591751.0,28652623.0,29235417.0,29396668.0,30384959.0,30486542.0,30606334.0,30509708.0,31245790.0,31073374.0,31932918.0]}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/0/base/tukey.json",
    "content": "[1.4162582251455733,1.7624575069718826,2.685655591842041,3.03185487366835]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/0/change/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.021341160228903963,\"upper_bound\":0.02852232316040214},\"point_estimate\":0.00002145625909277804,\"standard_error\":0.012941310444593138},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.05283554680087754,\"upper_bound\":0.038126637616528125},\"point_estimate\":-0.01705277072163114,\"standard_error\":0.02438148081277484}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/0/new/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"FlexStr 0.10 (LocalStr - As is)\",\"value_str\":\"0\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/0\",\"directory_name\":\"Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/0\",\"title\":\"Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/0\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/0/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.2174105632974404,\"upper_bound\":2.3209212155943755},\"point_estimate\":2.2593299330993077,\"standard_error\":0.027084428410779186},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.169831674139771,\"upper_bound\":2.3128125593032784},\"point_estimate\":2.256529756685847,\"standard_error\":0.038928222602210655},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.08538976432566761,\"upper_bound\":0.17864270396764162},\"point_estimate\":0.16305457674370233,\"standard_error\":0.029719083656677654},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.264623701546039,\"upper_bound\":2.305153993530497},\"point_estimate\":2.287032683640269,\"standard_error\":0.010333642414241015},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.11007712410494962,\"upper_bound\":0.4400373354452467},\"point_estimate\":0.2724259955195404,\"standard_error\":0.11176376067372233}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/0/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[136139.0,272278.0,408417.0,544556.0,680695.0,816834.0,952973.0,1089112.0,1225251.0,1361390.0,1497529.0,1633668.0,1769807.0,1905946.0,2042085.0,2178224.0,2314363.0,2450502.0,2586641.0,2722780.0,2858919.0,2995058.0,3131197.0,3267336.0,3403475.0,3539614.0,3675753.0,3811892.0,3948031.0,4084170.0,4220309.0,4356448.0,4492587.0,4628726.0,4764865.0,4901004.0,5037143.0,5173282.0,5309421.0,5445560.0,5581699.0,5717838.0,5853977.0,5990116.0,6126255.0,6262394.0,6398533.0,6534672.0,6670811.0,6806950.0,6943089.0,7079228.0,7215367.0,7351506.0,7487645.0,7623784.0,7759923.0,7896062.0,8032201.0,8168340.0,8304479.0,8440618.0,8576757.0,8712896.0,8849035.0,8985174.0,9121313.0,9257452.0,9393591.0,9529730.0,9665869.0,9802008.0,9938147.0,10074286.0,10210425.0,10346564.0,10482703.0,10618842.0,10754981.0,10891120.0,11027259.0,11163398.0,11299537.0,11435676.0,11571815.0,11707954.0,11844093.0,11980232.0,12116371.0,12252510.0,12388649.0,12524788.0,12660927.0,12797066.0,12933205.0,13069344.0,13205483.0,13341622.0,13477761.0,13613900.0],\"times\":[639167.0,564710.0,847418.0,1144707.0,1730791.0,1838127.0,2147334.0,2403669.0,2964959.0,2980999.0,3360542.0,3696085.0,4218791.0,4135582.0,4488331.0,5034456.0,5018753.0,5536125.0,6049625.0,6404250.0,6350040.0,6750500.0,7269001.0,7476708.0,7535879.0,7399459.0,7699375.0,7958168.0,8324500.0,8667499.0,8819624.0,9152708.0,9632789.0,9736753.0,9999626.0,10417373.0,10677918.0,11015251.0,11362415.0,11574418.0,11994792.0,12208794.0,12289666.0,12571167.0,13089917.0,13325793.0,13513376.0,13810041.0,13954833.0,14285499.0,14605248.0,14785502.0,15129918.0,15441127.0,15596958.0,16076293.0,16089794.0,16453623.0,16673290.0,17044458.0,17213083.0,20249208.0,20197667.0,20670707.0,21069249.0,21302164.0,21612418.0,21699874.0,21940540.0,22356083.0,22492709.0,23049206.0,23219832.0,23897875.0,24052082.0,24419168.0,24430750.0,24699663.0,24839665.0,25202709.0,25624251.0,25908540.0,26626417.0,26705749.0,27520665.0,27109541.0,27732209.0,27583833.0,27996333.0,28591751.0,28652623.0,29235417.0,29396668.0,30384959.0,30486542.0,30606334.0,30509708.0,31245790.0,31073374.0,31932918.0]}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/0/new/tukey.json",
    "content": "[1.4162582251455733,1.7624575069718826,2.685655591842041,3.03185487366835]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/0/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/0 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/0</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">2.2646 ns</td>\n                                <td>2.2870 ns</td>\n                                <td class=\"ci-bound\">2.3052 ns</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.8038610</td>\n                                <td>0.8115195</td>\n                                <td class=\"ci-bound\">0.8064949</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">2.2174 ns</td>\n                                <td>2.2593 ns</td>\n                                <td class=\"ci-bound\">2.3209 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">110.08 ps</td>\n                                <td>272.43 ps</td>\n                                <td class=\"ci-bound\">440.04 ps</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">2.1698 ns</td>\n                                <td>2.2565 ns</td>\n                                <td class=\"ci-bound\">2.3128 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">85.390 ps</td>\n                                <td>163.05 ps</td>\n                                <td class=\"ci-bound\">178.64 ps</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−2.1341%</td>\n                            <td>+0.0021%</td>\n                            <td class=\"ci-bound\">+2.8522%</td>\n                            <td>(p = 1.00 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/10/base/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"FlexStr 0.10 (LocalStr - As is)\",\"value_str\":\"10\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/10\",\"directory_name\":\"Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/10\",\"title\":\"Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/10\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/10/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":29.945327770641544,\"upper_bound\":31.381296238872526},\"point_estimate\":30.642381678906762,\"standard_error\":0.36685661169024814},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":28.83919102450546,\"upper_bound\":32.21860394318145},\"point_estimate\":30.632846598769014,\"standard_error\":0.9140302183887603},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.1154430777320554,\"upper_bound\":5.0937843939971374},\"point_estimate\":4.563248897285517,\"standard_error\":0.4978920763149826},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":31.336249898427024,\"upper_bound\":32.50976514383824},\"point_estimate\":31.94131704944221,\"standard_error\":0.2992593516500935},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.0167940300243425,\"upper_bound\":4.56783533703572},\"point_estimate\":3.692702707296108,\"standard_error\":0.43301215780670715}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/10/base/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[16935.0,33870.0,50805.0,67740.0,84675.0,101610.0,118545.0,135480.0,152415.0,169350.0,186285.0,203220.0,220155.0,237090.0,254025.0,270960.0,287895.0,304830.0,321765.0,338700.0,355635.0,372570.0,389505.0,406440.0,423375.0,440310.0,457245.0,474180.0,491115.0,508050.0,524985.0,541920.0,558855.0,575790.0,592725.0,609660.0,626595.0,643530.0,660465.0,677400.0,694335.0,711270.0,728205.0,745140.0,762075.0,779010.0,795945.0,812880.0,829815.0,846750.0,863685.0,880620.0,897555.0,914490.0,931425.0,948360.0,965295.0,982230.0,999165.0,1016100.0,1033035.0,1049970.0,1066905.0,1083840.0,1100775.0,1117710.0,1134645.0,1151580.0,1168515.0,1185450.0,1202385.0,1219320.0,1236255.0,1253190.0,1270125.0,1287060.0,1303995.0,1320930.0,1337865.0,1354800.0,1371735.0,1388670.0,1405605.0,1422540.0,1439475.0,1456410.0,1473345.0,1490280.0,1507215.0,1524150.0,1541085.0,1558020.0,1574955.0,1591890.0,1608825.0,1625760.0,1642695.0,1659630.0,1676565.0,1693500.0],\"times\":[826250.0,896167.0,1339876.0,2314458.0,2289625.0,2718169.0,3121459.0,4000040.0,4011250.0,4883917.0,5430499.0,5469123.0,5807499.0,6657750.0,6773044.0,7276207.0,7989374.0,8048001.0,8561042.0,9605041.0,9847915.0,9880791.0,10476624.0,10929793.0,11311333.0,11818959.0,12182250.0,12658501.0,13191250.0,13496875.0,14084209.0,14398417.0,14809960.0,15216542.0,15942709.0,16174793.0,17067040.0,17003042.0,24552917.0,24414751.0,24418000.0,24784915.0,24730628.0,24942083.0,24407959.0,25012669.0,25157749.0,25619709.0,25274288.0,25798584.0,25269877.0,26107000.0,25697376.0,25831167.0,25983208.0,26125583.0,32909291.0,33596377.0,33079624.0,34246542.0,35762584.0,34706000.0,35559749.0,36183372.0,37084375.0,37004710.0,38238916.0,37823626.0,38045584.0,38905584.0,39039752.0,42185333.0,40618042.0,42003707.0,41163377.0,44097332.0,47266668.0,48088664.0,46981374.0,44598541.0,46390043.0,47205791.0,44664123.0,46832418.0,44714711.0,45750000.0,45717127.0,45630708.0,46191333.0,45043251.0,44741291.0,44206541.0,45200334.0,43904210.0,51209084.0,55410000.0,53315374.0,56318667.0,55350418.0,57278333.0]}"
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  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/10/base/tukey.json",
    "content": "[7.369500541458976,17.133401773460978,43.170471725466314,52.93437295746832]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/10/change/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.04472214077928836,\"upper_bound\":0.030367434312242706},\"point_estimate\":-0.006814081528786375,\"standard_error\":0.019247511168490487},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.08631407810437497,\"upper_bound\":0.07929590815106846},\"point_estimate\":-0.009842692514336893,\"standard_error\":0.0418898999734983}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/10/new/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"FlexStr 0.10 (LocalStr - As is)\",\"value_str\":\"10\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/10\",\"directory_name\":\"Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/10\",\"title\":\"Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/10\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/10/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":29.945327770641544,\"upper_bound\":31.381296238872526},\"point_estimate\":30.642381678906762,\"standard_error\":0.36685661169024814},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":28.83919102450546,\"upper_bound\":32.21860394318145},\"point_estimate\":30.632846598769014,\"standard_error\":0.9140302183887603},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.1154430777320554,\"upper_bound\":5.0937843939971374},\"point_estimate\":4.563248897285517,\"standard_error\":0.4978920763149826},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":31.336249898427024,\"upper_bound\":32.50976514383824},\"point_estimate\":31.94131704944221,\"standard_error\":0.2992593516500935},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.0167940300243425,\"upper_bound\":4.56783533703572},\"point_estimate\":3.692702707296108,\"standard_error\":0.43301215780670715}}"
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  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/10/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[16935.0,33870.0,50805.0,67740.0,84675.0,101610.0,118545.0,135480.0,152415.0,169350.0,186285.0,203220.0,220155.0,237090.0,254025.0,270960.0,287895.0,304830.0,321765.0,338700.0,355635.0,372570.0,389505.0,406440.0,423375.0,440310.0,457245.0,474180.0,491115.0,508050.0,524985.0,541920.0,558855.0,575790.0,592725.0,609660.0,626595.0,643530.0,660465.0,677400.0,694335.0,711270.0,728205.0,745140.0,762075.0,779010.0,795945.0,812880.0,829815.0,846750.0,863685.0,880620.0,897555.0,914490.0,931425.0,948360.0,965295.0,982230.0,999165.0,1016100.0,1033035.0,1049970.0,1066905.0,1083840.0,1100775.0,1117710.0,1134645.0,1151580.0,1168515.0,1185450.0,1202385.0,1219320.0,1236255.0,1253190.0,1270125.0,1287060.0,1303995.0,1320930.0,1337865.0,1354800.0,1371735.0,1388670.0,1405605.0,1422540.0,1439475.0,1456410.0,1473345.0,1490280.0,1507215.0,1524150.0,1541085.0,1558020.0,1574955.0,1591890.0,1608825.0,1625760.0,1642695.0,1659630.0,1676565.0,1693500.0],\"times\":[826250.0,896167.0,1339876.0,2314458.0,2289625.0,2718169.0,3121459.0,4000040.0,4011250.0,4883917.0,5430499.0,5469123.0,5807499.0,6657750.0,6773044.0,7276207.0,7989374.0,8048001.0,8561042.0,9605041.0,9847915.0,9880791.0,10476624.0,10929793.0,11311333.0,11818959.0,12182250.0,12658501.0,13191250.0,13496875.0,14084209.0,14398417.0,14809960.0,15216542.0,15942709.0,16174793.0,17067040.0,17003042.0,24552917.0,24414751.0,24418000.0,24784915.0,24730628.0,24942083.0,24407959.0,25012669.0,25157749.0,25619709.0,25274288.0,25798584.0,25269877.0,26107000.0,25697376.0,25831167.0,25983208.0,26125583.0,32909291.0,33596377.0,33079624.0,34246542.0,35762584.0,34706000.0,35559749.0,36183372.0,37084375.0,37004710.0,38238916.0,37823626.0,38045584.0,38905584.0,39039752.0,42185333.0,40618042.0,42003707.0,41163377.0,44097332.0,47266668.0,48088664.0,46981374.0,44598541.0,46390043.0,47205791.0,44664123.0,46832418.0,44714711.0,45750000.0,45717127.0,45630708.0,46191333.0,45043251.0,44741291.0,44206541.0,45200334.0,43904210.0,51209084.0,55410000.0,53315374.0,56318667.0,55350418.0,57278333.0]}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/10/new/tukey.json",
    "content": "[7.369500541458976,17.133401773460978,43.170471725466314,52.93437295746832]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/10/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/10 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/10</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">31.336 ns</td>\n                                <td>31.941 ns</td>\n                                <td class=\"ci-bound\">32.510 ns</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.5923640</td>\n                                <td>0.6062518</td>\n                                <td class=\"ci-bound\">0.5939611</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">29.945 ns</td>\n                                <td>30.642 ns</td>\n                                <td class=\"ci-bound\">31.381 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">3.0168 ns</td>\n                                <td>3.6927 ns</td>\n                                <td class=\"ci-bound\">4.5678 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">28.839 ns</td>\n                                <td>30.633 ns</td>\n                                <td class=\"ci-bound\">32.219 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">3.1154 ns</td>\n                                <td>4.5632 ns</td>\n                                <td class=\"ci-bound\">5.0938 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−4.4722%</td>\n                            <td>−0.6814%</td>\n                            <td class=\"ci-bound\">+3.0367%</td>\n                            <td>(p = 0.73 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/100/base/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"FlexStr 0.10 (LocalStr - As is)\",\"value_str\":\"100\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/100\",\"directory_name\":\"Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/100\",\"title\":\"Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/100\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/100/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":39.10725360630788,\"upper_bound\":40.629874625871196},\"point_estimate\":39.87494272000391,\"standard_error\":0.387373586526067},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":39.17786726034886,\"upper_bound\":40.53853811476669},\"point_estimate\":39.83022558084764,\"standard_error\":0.35591622183879074},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.8795819884648037,\"upper_bound\":4.933856995597923},\"point_estimate\":3.875451622564626,\"standard_error\":0.5069292929129212},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":40.11815703038945,\"upper_bound\":41.60122796428031},\"point_estimate\":40.85372321213239,\"standard_error\":0.37754181373461815},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.3867474592970517,\"upper_bound\":4.3316359781800715},\"point_estimate\":3.8921282750112898,\"standard_error\":0.24140487565527635}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/100/base/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[10851.0,21702.0,32553.0,43404.0,54255.0,65106.0,75957.0,86808.0,97659.0,108510.0,119361.0,130212.0,141063.0,151914.0,162765.0,173616.0,184467.0,195318.0,206169.0,217020.0,227871.0,238722.0,249573.0,260424.0,271275.0,282126.0,292977.0,303828.0,314679.0,325530.0,336381.0,347232.0,358083.0,368934.0,379785.0,390636.0,401487.0,412338.0,423189.0,434040.0,444891.0,455742.0,466593.0,477444.0,488295.0,499146.0,509997.0,520848.0,531699.0,542550.0,553401.0,564252.0,575103.0,585954.0,596805.0,607656.0,618507.0,629358.0,640209.0,651060.0,661911.0,672762.0,683613.0,694464.0,705315.0,716166.0,727017.0,737868.0,748719.0,759570.0,770421.0,781272.0,792123.0,802974.0,813825.0,824676.0,835527.0,846378.0,857229.0,868080.0,878931.0,889782.0,900633.0,911484.0,922335.0,933186.0,944037.0,954888.0,965739.0,976590.0,987441.0,998292.0,1009143.0,1019994.0,1030845.0,1041696.0,1052547.0,1063398.0,1074249.0,1085100.0],\"times\":[359373.0,702875.0,1015875.0,1325500.0,2004708.0,2131666.0,2748792.0,2783000.0,4451584.0,4272332.0,4442332.0,4763711.0,5943792.0,6125168.0,6722167.0,6864752.0,8157417.0,8290376.0,7965500.0,7897500.0,7489543.0,9597123.0,9932376.0,11373583.0,11305083.0,11969541.0,11742083.0,11153208.0,10715502.0,12694542.0,13870417.0,16025250.0,16420331.0,16694959.0,16092917.0,14961666.0,14172875.0,13240418.0,14722750.0,16518918.0,19795915.0,19918751.0,19835247.0,18773209.0,18278294.0,16839292.0,18153958.0,18985498.0,24412499.0,24421000.0,24028209.0,22907334.0,21351833.0,20447834.0,22629791.0,23190791.0,24238209.0,28745666.0,27711833.0,26605916.0,25400125.0,26665751.0,24580374.0,27108751.0,26921583.0,33644918.0,32796250.0,32445416.0,30917624.0,30589583.0,29191582.0,30786875.0,32148959.0,37155499.0,36991373.0,35505918.0,36602041.0,34263710.0,34157625.0,32630082.0,34993665.0,33537664.0,40450501.0,38679709.0,39575125.0,37583960.0,37302043.0,36364418.0,38587292.0,37450167.0,46181041.0,43323831.0,43422417.0,43001916.0,40826457.0,42228833.0,39751666.0,42376584.0,41326165.0,48426833.0]}"
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  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/100/base/tukey.json",
    "content": "[21.851083939149802,29.758641825775634,50.84546285677785,58.75302074340368]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/100/change/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.012983655101218865,\"upper_bound\":0.040823627919725186},\"point_estimate\":0.013863046956114067,\"standard_error\":0.013680135165924263},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.014323015151105678,\"upper_bound\":0.047368722897529025},\"point_estimate\":0.023682192018896764,\"standard_error\":0.015647456140019514}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/100/new/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"FlexStr 0.10 (LocalStr - As is)\",\"value_str\":\"100\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/100\",\"directory_name\":\"Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/100\",\"title\":\"Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/100\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/100/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":39.10725360630788,\"upper_bound\":40.629874625871196},\"point_estimate\":39.87494272000391,\"standard_error\":0.387373586526067},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":39.17786726034886,\"upper_bound\":40.53853811476669},\"point_estimate\":39.83022558084764,\"standard_error\":0.35591622183879074},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.8795819884648037,\"upper_bound\":4.933856995597923},\"point_estimate\":3.875451622564626,\"standard_error\":0.5069292929129212},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":40.11815703038945,\"upper_bound\":41.60122796428031},\"point_estimate\":40.85372321213239,\"standard_error\":0.37754181373461815},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.3867474592970517,\"upper_bound\":4.3316359781800715},\"point_estimate\":3.8921282750112898,\"standard_error\":0.24140487565527635}}"
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    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/100/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[10851.0,21702.0,32553.0,43404.0,54255.0,65106.0,75957.0,86808.0,97659.0,108510.0,119361.0,130212.0,141063.0,151914.0,162765.0,173616.0,184467.0,195318.0,206169.0,217020.0,227871.0,238722.0,249573.0,260424.0,271275.0,282126.0,292977.0,303828.0,314679.0,325530.0,336381.0,347232.0,358083.0,368934.0,379785.0,390636.0,401487.0,412338.0,423189.0,434040.0,444891.0,455742.0,466593.0,477444.0,488295.0,499146.0,509997.0,520848.0,531699.0,542550.0,553401.0,564252.0,575103.0,585954.0,596805.0,607656.0,618507.0,629358.0,640209.0,651060.0,661911.0,672762.0,683613.0,694464.0,705315.0,716166.0,727017.0,737868.0,748719.0,759570.0,770421.0,781272.0,792123.0,802974.0,813825.0,824676.0,835527.0,846378.0,857229.0,868080.0,878931.0,889782.0,900633.0,911484.0,922335.0,933186.0,944037.0,954888.0,965739.0,976590.0,987441.0,998292.0,1009143.0,1019994.0,1030845.0,1041696.0,1052547.0,1063398.0,1074249.0,1085100.0],\"times\":[359373.0,702875.0,1015875.0,1325500.0,2004708.0,2131666.0,2748792.0,2783000.0,4451584.0,4272332.0,4442332.0,4763711.0,5943792.0,6125168.0,6722167.0,6864752.0,8157417.0,8290376.0,7965500.0,7897500.0,7489543.0,9597123.0,9932376.0,11373583.0,11305083.0,11969541.0,11742083.0,11153208.0,10715502.0,12694542.0,13870417.0,16025250.0,16420331.0,16694959.0,16092917.0,14961666.0,14172875.0,13240418.0,14722750.0,16518918.0,19795915.0,19918751.0,19835247.0,18773209.0,18278294.0,16839292.0,18153958.0,18985498.0,24412499.0,24421000.0,24028209.0,22907334.0,21351833.0,20447834.0,22629791.0,23190791.0,24238209.0,28745666.0,27711833.0,26605916.0,25400125.0,26665751.0,24580374.0,27108751.0,26921583.0,33644918.0,32796250.0,32445416.0,30917624.0,30589583.0,29191582.0,30786875.0,32148959.0,37155499.0,36991373.0,35505918.0,36602041.0,34263710.0,34157625.0,32630082.0,34993665.0,33537664.0,40450501.0,38679709.0,39575125.0,37583960.0,37302043.0,36364418.0,38587292.0,37450167.0,46181041.0,43323831.0,43422417.0,43001916.0,40826457.0,42228833.0,39751666.0,42376584.0,41326165.0,48426833.0]}"
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    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/100/new/tukey.json",
    "content": "[21.851083939149802,29.758641825775634,50.84546285677785,58.75302074340368]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/100/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/100 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/100</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">40.118 ns</td>\n                                <td>40.854 ns</td>\n                                <td class=\"ci-bound\">41.601 ns</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.6340554</td>\n                                <td>0.6469776</td>\n                                <td class=\"ci-bound\">0.6336412</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">39.107 ns</td>\n                                <td>39.875 ns</td>\n                                <td class=\"ci-bound\">40.630 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">3.3867 ns</td>\n                                <td>3.8921 ns</td>\n                                <td class=\"ci-bound\">4.3316 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">39.178 ns</td>\n                                <td>39.830 ns</td>\n                                <td class=\"ci-bound\">40.539 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">2.8796 ns</td>\n                                <td>3.8755 ns</td>\n                                <td class=\"ci-bound\">4.9339 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−1.2984%</td>\n                            <td>+1.3863%</td>\n                            <td class=\"ci-bound\">+4.0824%</td>\n                            <td>(p = 0.31 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
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  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/20/base/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"FlexStr 0.10 (LocalStr - As is)\",\"value_str\":\"20\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/20\",\"directory_name\":\"Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/20\",\"title\":\"Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/20\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/20/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":32.162190279230416,\"upper_bound\":33.73576441665021},\"point_estimate\":32.932617555582404,\"standard_error\":0.3992068260428171},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":32.40946588691811,\"upper_bound\":34.03951957198316},\"point_estimate\":33.71243117723701,\"standard_error\":0.46660731813570117},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.8165833817198327,\"upper_bound\":4.875672095495967},\"point_estimate\":3.612449358628168,\"standard_error\":0.5321929025075175},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":33.21658002660252,\"upper_bound\":34.764268186111096},\"point_estimate\":33.99646992615506,\"standard_error\":0.39443579096886067},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.210951421611759,\"upper_bound\":4.974074743866796},\"point_estimate\":4.00295439089472,\"standard_error\":0.47678382091337584}}"
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    "content": "[13.440598352089658,21.657190997230984,43.56810471760785,51.78469736274918]"
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    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/20/change/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.023116750706297165,\"upper_bound\":0.04338542516871661},\"point_estimate\":0.009892514775224903,\"standard_error\":0.01703799567847585},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.03754129196418139,\"upper_bound\":0.059848016042034075},\"point_estimate\":0.008425334663055173,\"standard_error\":0.022961660537071847}}"
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    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/20/new/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"FlexStr 0.10 (LocalStr - As is)\",\"value_str\":\"20\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/20\",\"directory_name\":\"Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/20\",\"title\":\"Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/20\"}"
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    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/20/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":32.162190279230416,\"upper_bound\":33.73576441665021},\"point_estimate\":32.932617555582404,\"standard_error\":0.3992068260428171},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":32.40946588691811,\"upper_bound\":34.03951957198316},\"point_estimate\":33.71243117723701,\"standard_error\":0.46660731813570117},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.8165833817198327,\"upper_bound\":4.875672095495967},\"point_estimate\":3.612449358628168,\"standard_error\":0.5321929025075175},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":33.21658002660252,\"upper_bound\":34.764268186111096},\"point_estimate\":33.99646992615506,\"standard_error\":0.39443579096886067},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.210951421611759,\"upper_bound\":4.974074743866796},\"point_estimate\":4.00295439089472,\"standard_error\":0.47678382091337584}}"
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    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/20/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[14832.0,29664.0,44496.0,59328.0,74160.0,88992.0,103824.0,118656.0,133488.0,148320.0,163152.0,177984.0,192816.0,207648.0,222480.0,237312.0,252144.0,266976.0,281808.0,296640.0,311472.0,326304.0,341136.0,355968.0,370800.0,385632.0,400464.0,415296.0,430128.0,444960.0,459792.0,474624.0,489456.0,504288.0,519120.0,533952.0,548784.0,563616.0,578448.0,593280.0,608112.0,622944.0,637776.0,652608.0,667440.0,682272.0,697104.0,711936.0,726768.0,741600.0,756432.0,771264.0,786096.0,800928.0,815760.0,830592.0,845424.0,860256.0,875088.0,889920.0,904752.0,919584.0,934416.0,949248.0,964080.0,978912.0,993744.0,1008576.0,1023408.0,1038240.0,1053072.0,1067904.0,1082736.0,1097568.0,1112400.0,1127232.0,1142064.0,1156896.0,1171728.0,1186560.0,1201392.0,1216224.0,1231056.0,1245888.0,1260720.0,1275552.0,1290384.0,1305216.0,1320048.0,1334880.0,1349712.0,1364544.0,1379376.0,1394208.0,1409040.0,1423872.0,1438704.0,1453536.0,1468368.0,1483200.0],\"times\":[779169.0,794252.0,1190416.0,1689831.0,2262501.0,2456584.0,3728956.0,3222374.0,3689251.0,4031626.0,4452791.0,4852581.0,5622875.0,5705168.0,6272332.0,6390752.0,7374248.0,7311793.0,7568918.0,8063959.0,8525791.0,12653624.0,12187332.0,12478708.0,12962251.0,12286292.0,12643000.0,12633292.0,12860500.0,12933165.0,12915416.0,14498375.0,16560875.0,17338000.0,18156125.0,17712206.0,18687292.0,19122332.0,19620333.0,20133541.0,20352414.0,21132999.0,21729374.0,24335708.0,24305585.0,23631624.0,24011540.0,24146124.0,23458793.0,23289581.0,22959918.0,23639459.0,22301210.0,26062750.0,26745918.0,28549167.0,29353374.0,30222374.0,31504750.0,33505249.0,32815292.0,33676502.0,33898747.0,33801959.0,34563668.0,37186292.0,35802668.0,35619626.0,35497833.0,34998000.0,34162790.0,33675959.0,34041501.0,32857707.0,31615460.0,38641169.0,38505708.0,38628374.0,38384584.0,40388998.0,47284250.0,47149792.0,47968126.0,47948789.0,45966541.0,46890084.0,49298542.0,48456335.0,47385209.0,46544126.0,45926459.0,44738499.0,44273916.0,43114166.0,41985752.0,41266751.0,41827833.0,48783459.0,49695293.0,52588042.0]}"
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    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/20/new/tukey.json",
    "content": "[13.440598352089658,21.657190997230984,43.56810471760785,51.78469736274918]"
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  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/20/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/20 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/20</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">33.217 ns</td>\n                                <td>33.996 ns</td>\n                                <td class=\"ci-bound\">34.764 ns</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.5254171</td>\n                                <td>0.5427217</td>\n                                <td class=\"ci-bound\">0.5259331</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">32.162 ns</td>\n                                <td>32.933 ns</td>\n                                <td class=\"ci-bound\">33.736 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">3.2110 ns</td>\n                                <td>4.0030 ns</td>\n                                <td class=\"ci-bound\">4.9741 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">32.409 ns</td>\n                                <td>33.712 ns</td>\n                                <td class=\"ci-bound\">34.040 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">2.8166 ns</td>\n                                <td>3.6124 ns</td>\n                                <td class=\"ci-bound\">4.8757 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−2.3117%</td>\n                            <td>+0.9893%</td>\n                            <td class=\"ci-bound\">+4.3385%</td>\n                            <td>(p = 0.55 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
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    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/500/base/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"FlexStr 0.10 (LocalStr - As is)\",\"value_str\":\"500\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/500\",\"directory_name\":\"Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/500\",\"title\":\"Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/500\"}"
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    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/500/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":47.08994788302508,\"upper_bound\":49.585594548676305},\"point_estimate\":48.34424819013874,\"standard_error\":0.6365075737329349},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":46.9123790984206,\"upper_bound\":50.43560765555612},\"point_estimate\":48.88122709234578,\"standard_error\":0.9748691235316207},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":5.203084378930035,\"upper_bound\":8.189626588040618},\"point_estimate\":6.924253627803552,\"standard_error\":0.7556988592361082},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":51.12379863344037,\"upper_bound\":53.78804657613093},\"point_estimate\":52.52187667285391,\"standard_error\":0.6796666641478705},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":5.457165755020431,\"upper_bound\":7.250942173005163},\"point_estimate\":6.385455065257362,\"standard_error\":0.45806252327880814}}"
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  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/500/new/tukey.json",
    "content": "[15.49640521493081,29.533036243227173,66.96405231868414,81.00068334698051]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/500/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/500 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/500</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">51.124 ns</td>\n                                <td>52.522 ns</td>\n                                <td class=\"ci-bound\">53.788 ns</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.5648364</td>\n                                <td>0.5813226</td>\n                                <td class=\"ci-bound\">0.5677313</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">47.090 ns</td>\n                                <td>48.344 ns</td>\n                                <td class=\"ci-bound\">49.586 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">5.4572 ns</td>\n                                <td>6.3855 ns</td>\n                                <td class=\"ci-bound\">7.2509 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">46.912 ns</td>\n                                <td>48.881 ns</td>\n                                <td class=\"ci-bound\">50.436 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">5.2031 ns</td>\n                                <td>6.9243 ns</td>\n                                <td class=\"ci-bound\">8.1896 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−2.8981%</td>\n                            <td>+0.5215%</td>\n                            <td class=\"ci-bound\">+4.0537%</td>\n                            <td>(p = 0.77 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/FlexStr 0.10 (LocalStr - As is) Summary - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)</h2>\n        <h3>Violin Plot</h3>\n        <a href=\"violin.svg\">\n            <img src=\"violin.svg\" alt=\"Violin Plot\" />\n        </a>\n        <p>This chart shows the relationship between function/parameter and iteration time. The thickness of the shaded\n            region indicates the probability that a measurement of the given function/parameter would take a particular\n            length of time.</p>\n        <h3>Line Chart</h3>\n        <img src=\"lines.svg\" alt=\"Line Chart\" />\n        <p>This chart shows the mean measured time for each function as the input (or the size of the input) increases.</p>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/0/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/0/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/0/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/10/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/10/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/10/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/20/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/20/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/20/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/100/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/100/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/100/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/500/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/500/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/500/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/0/base/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"FlexStr 0.10 (LocalStr - Optimized)\",\"value_str\":\"0\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/0\",\"directory_name\":\"Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/0\",\"title\":\"Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/0\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/0/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":11.311003727539855,\"upper_bound\":11.559594601730529},\"point_estimate\":11.409783477656193,\"standard_error\":0.06533363794225039},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":11.262184854150114,\"upper_bound\":11.343607388359153},\"point_estimate\":11.302727797974221,\"standard_error\":0.02291783834540119},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.14426143708727593,\"upper_bound\":0.23019622526809003},\"point_estimate\":0.18950330149828645,\"standard_error\":0.022816730313649707},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":11.280001700601161,\"upper_bound\":11.376517793075402},\"point_estimate\":11.32535985388519,\"standard_error\":0.024674339374102856},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.2044901287464052,\"upper_bound\":1.0731580810066437},\"point_estimate\":0.6576687502567403,\"standard_error\":0.28089741235138854}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/0/base/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[63090.0,126180.0,189270.0,252360.0,315450.0,378540.0,441630.0,504720.0,567810.0,630900.0,693990.0,757080.0,820170.0,883260.0,946350.0,1009440.0,1072530.0,1135620.0,1198710.0,1261800.0,1324890.0,1387980.0,1451070.0,1514160.0,1577250.0,1640340.0,1703430.0,1766520.0,1829610.0,1892700.0,1955790.0,2018880.0,2081970.0,2145060.0,2208150.0,2271240.0,2334330.0,2397420.0,2460510.0,2523600.0,2586690.0,2649780.0,2712870.0,2775960.0,2839050.0,2902140.0,2965230.0,3028320.0,3091410.0,3154500.0,3217590.0,3280680.0,3343770.0,3406860.0,3469950.0,3533040.0,3596130.0,3659220.0,3722310.0,3785400.0,3848490.0,3911580.0,3974670.0,4037760.0,4100850.0,4163940.0,4227030.0,4290120.0,4353210.0,4416300.0,4479390.0,4542480.0,4605570.0,4668660.0,4731750.0,4794840.0,4857930.0,4921020.0,4984110.0,5047200.0,5110290.0,5173380.0,5236470.0,5299560.0,5362650.0,5425740.0,5488830.0,5551920.0,5615010.0,5678100.0,5741190.0,5804280.0,5867370.0,5930460.0,5993550.0,6056640.0,6119730.0,6182820.0,6245910.0,6309000.0],\"times\":[1095503.0,1430042.0,2131709.0,3175751.0,3458042.0,4737958.0,4866209.0,5543749.0,6262460.0,6890626.0,8210542.0,8958666.0,9492333.0,9905456.0,10821415.0,11501041.0,12042083.0,12681042.0,13571291.0,14481874.0,14942250.0,15443708.0,16621710.0,17287207.0,17542876.0,18697251.0,19278085.0,19776043.0,20284291.0,21345665.0,22101332.0,22717251.0,24143500.0,24156291.0,24507374.0,25450209.0,26000916.0,27156875.0,27987250.0,29045752.0,29648291.0,29992667.0,31372457.0,31875585.0,31927459.0,33114831.0,33271333.0,34764876.0,34333625.0,35324498.0,36643084.0,37505791.0,38373998.0,39058708.0,40300915.0,39386708.0,40544915.0,41603833.0,43861292.0,43039793.0,43765418.0,43055416.0,46698792.0,45543875.0,45868082.0,50027333.0,49399333.0,49957999.0,48735126.0,51005832.0,49513375.0,50665461.0,51387335.0,52583167.0,53955501.0,53521541.0,54203623.0,55712958.0,55712251.0,57334542.0,57771792.0,60100292.0,60079333.0,60008375.0,60722085.0,60888042.0,62146581.0,61592957.0,62703332.0,64056542.0,64553165.0,65126208.0,65577751.0,66800959.0,67069126.0,69132040.0,68861459.0,72693250.0,70523333.0,70319249.0]}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/0/base/tukey.json",
    "content": "[10.385981385141022,10.787449402350191,11.85803078157464,12.25949879878381]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/0/change/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.03432156752938607,\"upper_bound\":-0.0028331533879441405},\"point_estimate\":-0.018356337477656193,\"standard_error\":0.007875418974317407},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.025137830828085073,\"upper_bound\":-0.015737780960074943},\"point_estimate\":-0.0198567905382675,\"standard_error\":0.00247325764055382}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/0/new/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"FlexStr 0.10 (LocalStr - Optimized)\",\"value_str\":\"0\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/0\",\"directory_name\":\"Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/0\",\"title\":\"Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/0\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/0/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":11.311003727539855,\"upper_bound\":11.559594601730529},\"point_estimate\":11.409783477656193,\"standard_error\":0.06533363794225039},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":11.262184854150114,\"upper_bound\":11.343607388359153},\"point_estimate\":11.302727797974221,\"standard_error\":0.02291783834540119},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.14426143708727593,\"upper_bound\":0.23019622526809003},\"point_estimate\":0.18950330149828645,\"standard_error\":0.022816730313649707},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":11.280001700601161,\"upper_bound\":11.376517793075402},\"point_estimate\":11.32535985388519,\"standard_error\":0.024674339374102856},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.2044901287464052,\"upper_bound\":1.0731580810066437},\"point_estimate\":0.6576687502567403,\"standard_error\":0.28089741235138854}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/0/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[63090.0,126180.0,189270.0,252360.0,315450.0,378540.0,441630.0,504720.0,567810.0,630900.0,693990.0,757080.0,820170.0,883260.0,946350.0,1009440.0,1072530.0,1135620.0,1198710.0,1261800.0,1324890.0,1387980.0,1451070.0,1514160.0,1577250.0,1640340.0,1703430.0,1766520.0,1829610.0,1892700.0,1955790.0,2018880.0,2081970.0,2145060.0,2208150.0,2271240.0,2334330.0,2397420.0,2460510.0,2523600.0,2586690.0,2649780.0,2712870.0,2775960.0,2839050.0,2902140.0,2965230.0,3028320.0,3091410.0,3154500.0,3217590.0,3280680.0,3343770.0,3406860.0,3469950.0,3533040.0,3596130.0,3659220.0,3722310.0,3785400.0,3848490.0,3911580.0,3974670.0,4037760.0,4100850.0,4163940.0,4227030.0,4290120.0,4353210.0,4416300.0,4479390.0,4542480.0,4605570.0,4668660.0,4731750.0,4794840.0,4857930.0,4921020.0,4984110.0,5047200.0,5110290.0,5173380.0,5236470.0,5299560.0,5362650.0,5425740.0,5488830.0,5551920.0,5615010.0,5678100.0,5741190.0,5804280.0,5867370.0,5930460.0,5993550.0,6056640.0,6119730.0,6182820.0,6245910.0,6309000.0],\"times\":[1095503.0,1430042.0,2131709.0,3175751.0,3458042.0,4737958.0,4866209.0,5543749.0,6262460.0,6890626.0,8210542.0,8958666.0,9492333.0,9905456.0,10821415.0,11501041.0,12042083.0,12681042.0,13571291.0,14481874.0,14942250.0,15443708.0,16621710.0,17287207.0,17542876.0,18697251.0,19278085.0,19776043.0,20284291.0,21345665.0,22101332.0,22717251.0,24143500.0,24156291.0,24507374.0,25450209.0,26000916.0,27156875.0,27987250.0,29045752.0,29648291.0,29992667.0,31372457.0,31875585.0,31927459.0,33114831.0,33271333.0,34764876.0,34333625.0,35324498.0,36643084.0,37505791.0,38373998.0,39058708.0,40300915.0,39386708.0,40544915.0,41603833.0,43861292.0,43039793.0,43765418.0,43055416.0,46698792.0,45543875.0,45868082.0,50027333.0,49399333.0,49957999.0,48735126.0,51005832.0,49513375.0,50665461.0,51387335.0,52583167.0,53955501.0,53521541.0,54203623.0,55712958.0,55712251.0,57334542.0,57771792.0,60100292.0,60079333.0,60008375.0,60722085.0,60888042.0,62146581.0,61592957.0,62703332.0,64056542.0,64553165.0,65126208.0,65577751.0,66800959.0,67069126.0,69132040.0,68861459.0,72693250.0,70523333.0,70319249.0]}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/0/new/tukey.json",
    "content": "[10.385981385141022,10.787449402350191,11.85803078157464,12.25949879878381]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/0/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/0 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/0</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">11.280 ns</td>\n                                <td>11.325 ns</td>\n                                <td class=\"ci-bound\">11.377 ns</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.9572234</td>\n                                <td>0.9593978</td>\n                                <td class=\"ci-bound\">0.9566335</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">11.311 ns</td>\n                                <td>11.410 ns</td>\n                                <td class=\"ci-bound\">11.560 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">204.49 ps</td>\n                                <td>657.67 ps</td>\n                                <td class=\"ci-bound\">1.0732 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">11.262 ns</td>\n                                <td>11.303 ns</td>\n                                <td class=\"ci-bound\">11.344 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">144.26 ps</td>\n                                <td>189.50 ps</td>\n                                <td class=\"ci-bound\">230.20 ps</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−3.4322%</td>\n                            <td>−1.8356%</td>\n                            <td class=\"ci-bound\">−0.2833%</td>\n                            <td>(p = 0.01 &lt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                Change within noise threshold.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/10/base/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"FlexStr 0.10 (LocalStr - Optimized)\",\"value_str\":\"10\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/10\",\"directory_name\":\"Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/10\",\"title\":\"Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/10\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/10/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":41.36024248365138,\"upper_bound\":42.93481851084219},\"point_estimate\":42.11122271327216,\"standard_error\":0.4010355845642601},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":40.09951680098347,\"upper_bound\":43.465181498429175},\"point_estimate\":41.911204613751224,\"standard_error\":1.0428478915606207},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.4099591981777557,\"upper_bound\":5.006597734833452},\"point_estimate\":3.979393675672016,\"standard_error\":0.3987623231138364},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":43.11122032380541,\"upper_bound\":44.18940865369258},\"point_estimate\":43.66866937234694,\"standard_error\":0.2751985105463787},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.0773204654875608,\"upper_bound\":5.150850431482201},\"point_estimate\":4.0188958707761815,\"standard_error\":0.569998445746355}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/10/base/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[14642.0,29284.0,43926.0,58568.0,73210.0,87852.0,102494.0,117136.0,131778.0,146420.0,161062.0,175704.0,190346.0,204988.0,219630.0,234272.0,248914.0,263556.0,278198.0,292840.0,307482.0,322124.0,336766.0,351408.0,366050.0,380692.0,395334.0,409976.0,424618.0,439260.0,453902.0,468544.0,483186.0,497828.0,512470.0,527112.0,541754.0,556396.0,571038.0,585680.0,600322.0,614964.0,629606.0,644248.0,658890.0,673532.0,688174.0,702816.0,717458.0,732100.0,746742.0,761384.0,776026.0,790668.0,805310.0,819952.0,834594.0,849236.0,863878.0,878520.0,893162.0,907804.0,922446.0,937088.0,951730.0,966372.0,981014.0,995656.0,1010298.0,1024940.0,1039582.0,1054224.0,1068866.0,1083508.0,1098150.0,1112792.0,1127434.0,1142076.0,1156718.0,1171360.0,1186002.0,1200644.0,1215286.0,1229928.0,1244570.0,1259212.0,1273854.0,1288496.0,1303138.0,1317780.0,1332422.0,1347064.0,1361706.0,1376348.0,1390990.0,1405632.0,1420274.0,1434916.0,1449558.0,1464200.0],\"times\":[931332.0,1122584.0,1695624.0,2355042.0,2816166.0,4021625.0,3849210.0,5443878.0,4968293.0,5549667.0,6519290.0,7026165.0,7228624.0,7779791.0,8651917.0,8879124.0,9292375.0,9938586.0,10356336.0,11332459.0,11571001.0,11943419.0,12473546.0,13843377.0,13912167.0,14326248.0,14807332.0,21589125.0,16416752.0,17052128.0,17106958.0,17884455.0,18962249.0,19519875.0,20427790.0,20306081.0,21384624.0,22236418.0,22139290.0,23108289.0,23214333.0,24266457.0,25442790.0,26600541.0,31649252.0,32187084.0,32284375.0,32629667.0,32697375.0,33483292.0,32995040.0,33152665.0,33740291.0,33647582.0,34096375.0,34014043.0,34297917.0,34517791.0,34728166.0,35033499.0,36081460.0,35632458.0,36047209.0,38704583.0,36242166.0,43071458.0,44735625.0,44524834.0,45340125.0,46461250.0,45554416.0,46852709.0,47574831.0,46676084.0,48587459.0,49279918.0,49445958.0,49974917.0,49320248.0,50913375.0,52314542.0,52783417.0,52884708.0,53265832.0,54748127.0,54313418.0,56326583.0,60811665.0,63347208.0,62822167.0,61589332.0,62698667.0,62820209.0,61316043.0,62493501.0,62432207.0,62810167.0,62254582.0,62324499.0,62909707.0]}"
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  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/10/base/tukey.json",
    "content": "[21.74165783680332,30.246983624831003,52.927852392904825,61.43317818093251]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/10/change/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.0079442614052016,\"upper_bound\":0.04538482912039646},\"point_estimate\":0.017587549660055712,\"standard_error\":0.01349362529152557},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.05485009238945464,\"upper_bound\":0.10190552941432562},\"point_estimate\":0.00738826684250915,\"standard_error\":0.04213664959263864}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/10/new/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"FlexStr 0.10 (LocalStr - Optimized)\",\"value_str\":\"10\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/10\",\"directory_name\":\"Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/10\",\"title\":\"Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/10\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/10/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":41.36024248365138,\"upper_bound\":42.93481851084219},\"point_estimate\":42.11122271327216,\"standard_error\":0.4010355845642601},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":40.09951680098347,\"upper_bound\":43.465181498429175},\"point_estimate\":41.911204613751224,\"standard_error\":1.0428478915606207},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.4099591981777557,\"upper_bound\":5.006597734833452},\"point_estimate\":3.979393675672016,\"standard_error\":0.3987623231138364},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":43.11122032380541,\"upper_bound\":44.18940865369258},\"point_estimate\":43.66866937234694,\"standard_error\":0.2751985105463787},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.0773204654875608,\"upper_bound\":5.150850431482201},\"point_estimate\":4.0188958707761815,\"standard_error\":0.569998445746355}}"
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    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/10/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[14642.0,29284.0,43926.0,58568.0,73210.0,87852.0,102494.0,117136.0,131778.0,146420.0,161062.0,175704.0,190346.0,204988.0,219630.0,234272.0,248914.0,263556.0,278198.0,292840.0,307482.0,322124.0,336766.0,351408.0,366050.0,380692.0,395334.0,409976.0,424618.0,439260.0,453902.0,468544.0,483186.0,497828.0,512470.0,527112.0,541754.0,556396.0,571038.0,585680.0,600322.0,614964.0,629606.0,644248.0,658890.0,673532.0,688174.0,702816.0,717458.0,732100.0,746742.0,761384.0,776026.0,790668.0,805310.0,819952.0,834594.0,849236.0,863878.0,878520.0,893162.0,907804.0,922446.0,937088.0,951730.0,966372.0,981014.0,995656.0,1010298.0,1024940.0,1039582.0,1054224.0,1068866.0,1083508.0,1098150.0,1112792.0,1127434.0,1142076.0,1156718.0,1171360.0,1186002.0,1200644.0,1215286.0,1229928.0,1244570.0,1259212.0,1273854.0,1288496.0,1303138.0,1317780.0,1332422.0,1347064.0,1361706.0,1376348.0,1390990.0,1405632.0,1420274.0,1434916.0,1449558.0,1464200.0],\"times\":[931332.0,1122584.0,1695624.0,2355042.0,2816166.0,4021625.0,3849210.0,5443878.0,4968293.0,5549667.0,6519290.0,7026165.0,7228624.0,7779791.0,8651917.0,8879124.0,9292375.0,9938586.0,10356336.0,11332459.0,11571001.0,11943419.0,12473546.0,13843377.0,13912167.0,14326248.0,14807332.0,21589125.0,16416752.0,17052128.0,17106958.0,17884455.0,18962249.0,19519875.0,20427790.0,20306081.0,21384624.0,22236418.0,22139290.0,23108289.0,23214333.0,24266457.0,25442790.0,26600541.0,31649252.0,32187084.0,32284375.0,32629667.0,32697375.0,33483292.0,32995040.0,33152665.0,33740291.0,33647582.0,34096375.0,34014043.0,34297917.0,34517791.0,34728166.0,35033499.0,36081460.0,35632458.0,36047209.0,38704583.0,36242166.0,43071458.0,44735625.0,44524834.0,45340125.0,46461250.0,45554416.0,46852709.0,47574831.0,46676084.0,48587459.0,49279918.0,49445958.0,49974917.0,49320248.0,50913375.0,52314542.0,52783417.0,52884708.0,53265832.0,54748127.0,54313418.0,56326583.0,60811665.0,63347208.0,62822167.0,61589332.0,62698667.0,62820209.0,61316043.0,62493501.0,62432207.0,62810167.0,62254582.0,62324499.0,62909707.0]}"
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    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/10/new/tukey.json",
    "content": "[21.74165783680332,30.246983624831003,52.927852392904825,61.43317818093251]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/10/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/10 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/10</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">43.111 ns</td>\n                                <td>43.669 ns</td>\n                                <td class=\"ci-bound\">44.189 ns</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.6734975</td>\n                                <td>0.6842568</td>\n                                <td class=\"ci-bound\">0.6748490</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">41.360 ns</td>\n                                <td>42.111 ns</td>\n                                <td class=\"ci-bound\">42.935 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">3.0773 ns</td>\n                                <td>4.0189 ns</td>\n                                <td class=\"ci-bound\">5.1509 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">40.100 ns</td>\n                                <td>41.911 ns</td>\n                                <td class=\"ci-bound\">43.465 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">3.4100 ns</td>\n                                <td>3.9794 ns</td>\n                                <td class=\"ci-bound\">5.0066 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−0.7944%</td>\n                            <td>+1.7588%</td>\n                            <td class=\"ci-bound\">+4.5385%</td>\n                            <td>(p = 0.18 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/100/base/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"FlexStr 0.10 (LocalStr - Optimized)\",\"value_str\":\"100\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/100\",\"directory_name\":\"Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/100\",\"title\":\"Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/100\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/100/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":64.78741883396405,\"upper_bound\":66.48915285899305},\"point_estimate\":65.63233388926857,\"standard_error\":0.4346730912147659},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":64.05625065313839,\"upper_bound\":66.67965019878652},\"point_estimate\":65.15932940911003,\"standard_error\":0.6793130996184888},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.2655802212525944,\"upper_bound\":5.703545043765706},\"point_estimate\":4.24102350036093,\"standard_error\":0.6053630802301584},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":65.66146773882858,\"upper_bound\":67.63221988928564},\"point_estimate\":66.62769230089742,\"standard_error\":0.5053016740178953},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.80752374151733,\"upper_bound\":4.844329259145794},\"point_estimate\":4.356729308593566,\"standard_error\":0.26468868861541545}}"
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    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/100/base/sample.json",
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    "content": "[44.00041749526994,53.38471789760303,78.40951897049126,87.79381937282436]"
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    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/100/change/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.004338091985988312,\"upper_bound\":0.031195605901231382},\"point_estimate\":0.013721918129561583,\"standard_error\":0.009055936403589277},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.022608458566674372,\"upper_bound\":0.02973847662831197},\"point_estimate\":0.004420972885424979,\"standard_error\":0.013185457104741147}}"
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    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/100/new/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"FlexStr 0.10 (LocalStr - Optimized)\",\"value_str\":\"100\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/100\",\"directory_name\":\"Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/100\",\"title\":\"Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/100\"}"
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    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/100/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":64.78741883396405,\"upper_bound\":66.48915285899305},\"point_estimate\":65.63233388926857,\"standard_error\":0.4346730912147659},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":64.05625065313839,\"upper_bound\":66.67965019878652},\"point_estimate\":65.15932940911003,\"standard_error\":0.6793130996184888},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.2655802212525944,\"upper_bound\":5.703545043765706},\"point_estimate\":4.24102350036093,\"standard_error\":0.6053630802301584},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":65.66146773882858,\"upper_bound\":67.63221988928564},\"point_estimate\":66.62769230089742,\"standard_error\":0.5053016740178953},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.80752374151733,\"upper_bound\":4.844329259145794},\"point_estimate\":4.356729308593566,\"standard_error\":0.26468868861541545}}"
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    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/100/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[8097.0,16194.0,24291.0,32388.0,40485.0,48582.0,56679.0,64776.0,72873.0,80970.0,89067.0,97164.0,105261.0,113358.0,121455.0,129552.0,137649.0,145746.0,153843.0,161940.0,170037.0,178134.0,186231.0,194328.0,202425.0,210522.0,218619.0,226716.0,234813.0,242910.0,251007.0,259104.0,267201.0,275298.0,283395.0,291492.0,299589.0,307686.0,315783.0,323880.0,331977.0,340074.0,348171.0,356268.0,364365.0,372462.0,380559.0,388656.0,396753.0,404850.0,412947.0,421044.0,429141.0,437238.0,445335.0,453432.0,461529.0,469626.0,477723.0,485820.0,493917.0,502014.0,510111.0,518208.0,526305.0,534402.0,542499.0,550596.0,558693.0,566790.0,574887.0,582984.0,591081.0,599178.0,607275.0,615372.0,623469.0,631566.0,639663.0,647760.0,655857.0,663954.0,672051.0,680148.0,688245.0,696342.0,704439.0,712536.0,720633.0,728730.0,736827.0,744924.0,753021.0,761118.0,769215.0,777312.0,785409.0,793506.0,801603.0,809700.0],\"times\":[485623.0,1174542.0,1389000.0,1848750.0,2747211.0,2937748.0,3192292.0,3934541.0,4436626.0,4598999.0,5217334.0,6904582.0,7095961.0,7231000.0,7580292.0,7787416.0,9286833.0,9779790.0,10360750.0,10530667.0,11068875.0,11646832.0,13105834.0,13433000.0,13255750.0,13485250.0,13294208.0,13347456.0,14899167.0,15445001.0,16856625.0,17948210.0,18142835.0,19867375.0,19349709.0,19390418.0,19157083.0,19262625.0,18892627.0,20251209.0,20856041.0,21149458.0,24764623.0,25020792.0,25369000.0,26297167.0,25375541.0,24920625.0,25074001.0,25129124.0,25699332.0,25784583.0,27248956.0,33113126.0,32366336.0,32112918.0,32789917.0,32086667.0,31199125.0,31817792.0,31345208.0,29930374.0,31491249.0,32836124.0,32849917.0,38188292.0,38900208.0,39304958.0,37966002.0,37099333.0,36887126.0,35821542.0,35513418.0,38131585.0,39016291.0,39392124.0,45979208.0,45079666.0,44771459.0,43329541.0,42867334.0,42579708.0,44635291.0,43279083.0,43297250.0,46479209.0,45331958.0,54220457.0,52343583.0,51942667.0,51653876.0,51393667.0,50225749.0,52093500.0,50169585.0,49240165.0,50585042.0,50886126.0,50904333.0,57527501.0]}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/100/new/tukey.json",
    "content": "[44.00041749526994,53.38471789760303,78.40951897049126,87.79381937282436]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/100/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/100 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/100</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">65.661 ns</td>\n                                <td>66.628 ns</td>\n                                <td class=\"ci-bound\">67.632 ns</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.7200570</td>\n                                <td>0.7318784</td>\n                                <td class=\"ci-bound\">0.7191179</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">64.787 ns</td>\n                                <td>65.632 ns</td>\n                                <td class=\"ci-bound\">66.489 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">3.8075 ns</td>\n                                <td>4.3567 ns</td>\n                                <td class=\"ci-bound\">4.8443 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">64.056 ns</td>\n                                <td>65.159 ns</td>\n                                <td class=\"ci-bound\">66.680 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">3.2656 ns</td>\n                                <td>4.2410 ns</td>\n                                <td class=\"ci-bound\">5.7035 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−0.4338%</td>\n                            <td>+1.3722%</td>\n                            <td class=\"ci-bound\">+3.1196%</td>\n                            <td>(p = 0.14 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/20/base/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"FlexStr 0.10 (LocalStr - Optimized)\",\"value_str\":\"20\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/20\",\"directory_name\":\"Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/20\",\"title\":\"Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/20\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/20/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":39.91345311585895,\"upper_bound\":41.348672996155514},\"point_estimate\":40.63183852296937,\"standard_error\":0.3654708889594252},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":40.24486093735888,\"upper_bound\":41.86359889080417},\"point_estimate\":41.326098194193825,\"standard_error\":0.3588043769371176},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.7134590719643716,\"upper_bound\":5.239667956637386},\"point_estimate\":4.262247613854678,\"standard_error\":0.668826287449926},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":41.76387475265306,\"upper_bound\":43.20424389871522},\"point_estimate\":42.50878963527266,\"standard_error\":0.3671777786182416},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.2821304580527135,\"upper_bound\":4.021546075533754},\"point_estimate\":3.6820975400395555,\"standard_error\":0.18854921473916}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/20/base/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[13343.0,26686.0,40029.0,53372.0,66715.0,80058.0,93401.0,106744.0,120087.0,133430.0,146773.0,160116.0,173459.0,186802.0,200145.0,213488.0,226831.0,240174.0,253517.0,266860.0,280203.0,293546.0,306889.0,320232.0,333575.0,346918.0,360261.0,373604.0,386947.0,400290.0,413633.0,426976.0,440319.0,453662.0,467005.0,480348.0,493691.0,507034.0,520377.0,533720.0,547063.0,560406.0,573749.0,587092.0,600435.0,613778.0,627121.0,640464.0,653807.0,667150.0,680493.0,693836.0,707179.0,720522.0,733865.0,747208.0,760551.0,773894.0,787237.0,800580.0,813923.0,827266.0,840609.0,853952.0,867295.0,880638.0,893981.0,907324.0,920667.0,934010.0,947353.0,960696.0,974039.0,987382.0,1000725.0,1014068.0,1027411.0,1040754.0,1054097.0,1067440.0,1080783.0,1094126.0,1107469.0,1120812.0,1134155.0,1147498.0,1160841.0,1174184.0,1187527.0,1200870.0,1214213.0,1227556.0,1240899.0,1254242.0,1267585.0,1280928.0,1294271.0,1307614.0,1320957.0,1334300.0],\"times\":[466541.0,1275418.0,1380207.0,2247958.0,2371416.0,2847836.0,3219710.0,3729959.0,4606627.0,4655416.0,5955419.0,5660831.0,6061708.0,6458750.0,7478416.0,7506584.0,7868625.0,8384250.0,9184542.0,9428585.0,9733791.0,10285958.0,10778375.0,11266042.0,15607872.0,14435168.0,15458582.0,15999457.0,15517249.0,15851376.0,16180749.0,16036126.0,16472835.0,16762458.0,17116541.0,19881750.0,20985210.0,21425415.0,21501085.0,22268208.0,22626709.0,23177834.0,23938000.0,24271834.0,24883043.0,24986583.0,25717417.0,26285666.0,29889875.0,29815249.0,30078582.0,28678956.0,28983042.0,29371335.0,29123542.0,29554042.0,29162748.0,28989502.0,29503708.0,31083167.0,34572876.0,34632332.0,36123958.0,36459500.0,36885250.0,38814957.0,40894416.0,40494293.0,41009167.0,41599751.0,41979834.0,42678958.0,44393709.0,43643002.0,43291500.0,42959458.0,43289834.0,41885000.0,42176334.0,41528542.0,42115081.0,40948962.0,40753000.0,45714127.0,45421331.0,48267332.0,48755874.0,49804000.0,48830124.0,57378958.0,56734124.0,57403456.0,57320418.0,57185915.0,56744542.0,57919209.0,58157667.0,57512332.0,57173501.0,56999710.0]}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/20/base/tukey.json",
    "content": "[20.668382539383693,29.059689521264335,51.43650813961271,59.82781512149336]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/20/change/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.018021031905440417,\"upper_bound\":0.030919346503002435},\"point_estimate\":0.006545246929924531,\"standard_error\":0.012523187690005587},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.012288156926331117,\"upper_bound\":0.04652853173007809},\"point_estimate\":0.014610377173724709,\"standard_error\":0.01468087898979447}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/20/new/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"FlexStr 0.10 (LocalStr - Optimized)\",\"value_str\":\"20\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/20\",\"directory_name\":\"Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/20\",\"title\":\"Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/20\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/20/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":39.91345311585895,\"upper_bound\":41.348672996155514},\"point_estimate\":40.63183852296937,\"standard_error\":0.3654708889594252},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":40.24486093735888,\"upper_bound\":41.86359889080417},\"point_estimate\":41.326098194193825,\"standard_error\":0.3588043769371176},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.7134590719643716,\"upper_bound\":5.239667956637386},\"point_estimate\":4.262247613854678,\"standard_error\":0.668826287449926},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":41.76387475265306,\"upper_bound\":43.20424389871522},\"point_estimate\":42.50878963527266,\"standard_error\":0.3671777786182416},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.2821304580527135,\"upper_bound\":4.021546075533754},\"point_estimate\":3.6820975400395555,\"standard_error\":0.18854921473916}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/20/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[13343.0,26686.0,40029.0,53372.0,66715.0,80058.0,93401.0,106744.0,120087.0,133430.0,146773.0,160116.0,173459.0,186802.0,200145.0,213488.0,226831.0,240174.0,253517.0,266860.0,280203.0,293546.0,306889.0,320232.0,333575.0,346918.0,360261.0,373604.0,386947.0,400290.0,413633.0,426976.0,440319.0,453662.0,467005.0,480348.0,493691.0,507034.0,520377.0,533720.0,547063.0,560406.0,573749.0,587092.0,600435.0,613778.0,627121.0,640464.0,653807.0,667150.0,680493.0,693836.0,707179.0,720522.0,733865.0,747208.0,760551.0,773894.0,787237.0,800580.0,813923.0,827266.0,840609.0,853952.0,867295.0,880638.0,893981.0,907324.0,920667.0,934010.0,947353.0,960696.0,974039.0,987382.0,1000725.0,1014068.0,1027411.0,1040754.0,1054097.0,1067440.0,1080783.0,1094126.0,1107469.0,1120812.0,1134155.0,1147498.0,1160841.0,1174184.0,1187527.0,1200870.0,1214213.0,1227556.0,1240899.0,1254242.0,1267585.0,1280928.0,1294271.0,1307614.0,1320957.0,1334300.0],\"times\":[466541.0,1275418.0,1380207.0,2247958.0,2371416.0,2847836.0,3219710.0,3729959.0,4606627.0,4655416.0,5955419.0,5660831.0,6061708.0,6458750.0,7478416.0,7506584.0,7868625.0,8384250.0,9184542.0,9428585.0,9733791.0,10285958.0,10778375.0,11266042.0,15607872.0,14435168.0,15458582.0,15999457.0,15517249.0,15851376.0,16180749.0,16036126.0,16472835.0,16762458.0,17116541.0,19881750.0,20985210.0,21425415.0,21501085.0,22268208.0,22626709.0,23177834.0,23938000.0,24271834.0,24883043.0,24986583.0,25717417.0,26285666.0,29889875.0,29815249.0,30078582.0,28678956.0,28983042.0,29371335.0,29123542.0,29554042.0,29162748.0,28989502.0,29503708.0,31083167.0,34572876.0,34632332.0,36123958.0,36459500.0,36885250.0,38814957.0,40894416.0,40494293.0,41009167.0,41599751.0,41979834.0,42678958.0,44393709.0,43643002.0,43291500.0,42959458.0,43289834.0,41885000.0,42176334.0,41528542.0,42115081.0,40948962.0,40753000.0,45714127.0,45421331.0,48267332.0,48755874.0,49804000.0,48830124.0,57378958.0,56734124.0,57403456.0,57320418.0,57185915.0,56744542.0,57919209.0,58157667.0,57512332.0,57173501.0,56999710.0]}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/20/new/tukey.json",
    "content": "[20.668382539383693,29.059689521264335,51.43650813961271,59.82781512149336]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/20/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/20 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/20</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">41.764 ns</td>\n                                <td>42.509 ns</td>\n                                <td class=\"ci-bound\">43.204 ns</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.6155728</td>\n                                <td>0.6312874</td>\n                                <td class=\"ci-bound\">0.6175464</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">39.913 ns</td>\n                                <td>40.632 ns</td>\n                                <td class=\"ci-bound\">41.349 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">3.2821 ns</td>\n                                <td>3.6821 ns</td>\n                                <td class=\"ci-bound\">4.0215 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">40.245 ns</td>\n                                <td>41.326 ns</td>\n                                <td class=\"ci-bound\">41.864 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">2.7135 ns</td>\n                                <td>4.2622 ns</td>\n                                <td class=\"ci-bound\">5.2397 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−1.8021%</td>\n                            <td>+0.6545%</td>\n                            <td class=\"ci-bound\">+3.0919%</td>\n                            <td>(p = 0.61 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
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    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/500/base/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"FlexStr 0.10 (LocalStr - Optimized)\",\"value_str\":\"500\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/500\",\"directory_name\":\"Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/500\",\"title\":\"Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/500\"}"
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    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":104.20434708466355,\"upper_bound\":106.52247799108022},\"point_estimate\":105.43031120648318,\"standard_error\":0.5924001293053608},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":105.48418630239922,\"upper_bound\":107.68357467398509},\"point_estimate\":106.15053686564059,\"standard_error\":0.6212450729397957},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.26943161167313,\"upper_bound\":5.425277861876977},\"point_estimate\":4.505040848884352,\"standard_error\":0.5830906330407609},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":107.53030610120071,\"upper_bound\":108.92087162115028},\"point_estimate\":108.252859840638,\"standard_error\":0.3549331817908489},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.9876219772097463,\"upper_bound\":7.653132946941563},\"point_estimate\":5.9567911408965415,\"standard_error\":0.9263156928812493}}"
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    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[4808.0,9616.0,14424.0,19232.0,24040.0,28848.0,33656.0,38464.0,43272.0,48080.0,52888.0,57696.0,62504.0,67312.0,72120.0,76928.0,81736.0,86544.0,91352.0,96160.0,100968.0,105776.0,110584.0,115392.0,120200.0,125008.0,129816.0,134624.0,139432.0,144240.0,149048.0,153856.0,158664.0,163472.0,168280.0,173088.0,177896.0,182704.0,187512.0,192320.0,197128.0,201936.0,206744.0,211552.0,216360.0,221168.0,225976.0,230784.0,235592.0,240400.0,245208.0,250016.0,254824.0,259632.0,264440.0,269248.0,274056.0,278864.0,283672.0,288480.0,293288.0,298096.0,302904.0,307712.0,312520.0,317328.0,322136.0,326944.0,331752.0,336560.0,341368.0,346176.0,350984.0,355792.0,360600.0,365408.0,370216.0,375024.0,379832.0,384640.0,389448.0,394256.0,399064.0,403872.0,408680.0,413488.0,418296.0,423104.0,427912.0,432720.0,437528.0,442336.0,447144.0,451952.0,456760.0,461568.0,466376.0,471184.0,475992.0,480800.0],\"times\":[395999.0,753043.0,1373249.0,1535541.0,2487165.0,3026790.0,3565459.0,3701459.0,4506668.0,4711248.0,5247209.0,5764833.0,6341790.0,6616249.0,7361835.0,7961706.0,8135998.0,8898957.0,9339791.0,10033832.0,10678043.0,10787000.0,11336247.0,12821209.0,11965291.0,12701250.0,13089874.0,14991251.0,15045959.0,15503790.0,15722207.0,16172126.0,17155040.0,16757127.0,16730417.0,17590502.0,18603876.0,18930712.0,19990209.0,19313875.0,20622834.0,20659664.0,21235791.0,22219914.0,23503416.0,23447708.0,24438461.0,24813292.0,24958417.0,25500833.0,26285500.0,26650499.0,26890251.0,27113961.0,28462874.0,30134082.0,30631124.0,30885210.0,30410794.0,30626750.0,32932627.0,33529624.0,33503834.0,33524127.0,34301418.0,34840709.0,34643376.0,35426209.0,36551874.0,37469085.0,36227248.0,37369041.0,38126041.0,38703250.0,39554877.0,40163668.0,40943542.0,42066626.0,41339791.0,41164125.0,42287376.0,42520417.0,42148792.0,44301000.0,44865082.0,44765418.0,45614915.0,44618961.0,44364417.0,45637085.0,47382458.0,45548290.0,49064955.0,49250252.0,50051791.0,48988582.0,52509041.0,53198251.0,53149040.0,52968626.0]}"
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    "content": "[84.76755102563858,93.8515590529336,118.07558045905361,127.15958848634861]"
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    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/500/change/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.004745823383767586,\"upper_bound\":0.03351083515916308},\"point_estimate\":0.019031968081536066,\"standard_error\":0.007304958858435947},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.0064332917475930645,\"upper_bound\":0.03660254067832591},\"point_estimate\":0.017235790248363525,\"standard_error\":0.00783517465863276}}"
  },
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    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/500/new/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"FlexStr 0.10 (LocalStr - Optimized)\",\"value_str\":\"500\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/500\",\"directory_name\":\"Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/500\",\"title\":\"Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/500\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/500/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":104.20434708466355,\"upper_bound\":106.52247799108022},\"point_estimate\":105.43031120648318,\"standard_error\":0.5924001293053608},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":105.48418630239922,\"upper_bound\":107.68357467398509},\"point_estimate\":106.15053686564059,\"standard_error\":0.6212450729397957},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.26943161167313,\"upper_bound\":5.425277861876977},\"point_estimate\":4.505040848884352,\"standard_error\":0.5830906330407609},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":107.53030610120071,\"upper_bound\":108.92087162115028},\"point_estimate\":108.252859840638,\"standard_error\":0.3549331817908489},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.9876219772097463,\"upper_bound\":7.653132946941563},\"point_estimate\":5.9567911408965415,\"standard_error\":0.9263156928812493}}"
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    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/500/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[4808.0,9616.0,14424.0,19232.0,24040.0,28848.0,33656.0,38464.0,43272.0,48080.0,52888.0,57696.0,62504.0,67312.0,72120.0,76928.0,81736.0,86544.0,91352.0,96160.0,100968.0,105776.0,110584.0,115392.0,120200.0,125008.0,129816.0,134624.0,139432.0,144240.0,149048.0,153856.0,158664.0,163472.0,168280.0,173088.0,177896.0,182704.0,187512.0,192320.0,197128.0,201936.0,206744.0,211552.0,216360.0,221168.0,225976.0,230784.0,235592.0,240400.0,245208.0,250016.0,254824.0,259632.0,264440.0,269248.0,274056.0,278864.0,283672.0,288480.0,293288.0,298096.0,302904.0,307712.0,312520.0,317328.0,322136.0,326944.0,331752.0,336560.0,341368.0,346176.0,350984.0,355792.0,360600.0,365408.0,370216.0,375024.0,379832.0,384640.0,389448.0,394256.0,399064.0,403872.0,408680.0,413488.0,418296.0,423104.0,427912.0,432720.0,437528.0,442336.0,447144.0,451952.0,456760.0,461568.0,466376.0,471184.0,475992.0,480800.0],\"times\":[395999.0,753043.0,1373249.0,1535541.0,2487165.0,3026790.0,3565459.0,3701459.0,4506668.0,4711248.0,5247209.0,5764833.0,6341790.0,6616249.0,7361835.0,7961706.0,8135998.0,8898957.0,9339791.0,10033832.0,10678043.0,10787000.0,11336247.0,12821209.0,11965291.0,12701250.0,13089874.0,14991251.0,15045959.0,15503790.0,15722207.0,16172126.0,17155040.0,16757127.0,16730417.0,17590502.0,18603876.0,18930712.0,19990209.0,19313875.0,20622834.0,20659664.0,21235791.0,22219914.0,23503416.0,23447708.0,24438461.0,24813292.0,24958417.0,25500833.0,26285500.0,26650499.0,26890251.0,27113961.0,28462874.0,30134082.0,30631124.0,30885210.0,30410794.0,30626750.0,32932627.0,33529624.0,33503834.0,33524127.0,34301418.0,34840709.0,34643376.0,35426209.0,36551874.0,37469085.0,36227248.0,37369041.0,38126041.0,38703250.0,39554877.0,40163668.0,40943542.0,42066626.0,41339791.0,41164125.0,42287376.0,42520417.0,42148792.0,44301000.0,44865082.0,44765418.0,45614915.0,44618961.0,44364417.0,45637085.0,47382458.0,45548290.0,49064955.0,49250252.0,50051791.0,48988582.0,52509041.0,53198251.0,53149040.0,52968626.0]}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/500/new/tukey.json",
    "content": "[84.76755102563858,93.8515590529336,118.07558045905361,127.15958848634861]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/500/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/500 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/500</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">107.53 ns</td>\n                                <td>108.25 ns</td>\n                                <td class=\"ci-bound\">108.92 ns</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.9145302</td>\n                                <td>0.9192955</td>\n                                <td class=\"ci-bound\">0.9152194</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">104.20 ns</td>\n                                <td>105.43 ns</td>\n                                <td class=\"ci-bound\">106.52 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">3.9876 ns</td>\n                                <td>5.9568 ns</td>\n                                <td class=\"ci-bound\">7.6531 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">105.48 ns</td>\n                                <td>106.15 ns</td>\n                                <td class=\"ci-bound\">107.68 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">3.2694 ns</td>\n                                <td>4.5050 ns</td>\n                                <td class=\"ci-bound\">5.4253 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">+0.4746%</td>\n                            <td>+1.9032%</td>\n                            <td class=\"ci-bound\">+3.3511%</td>\n                            <td>(p = 0.01 &lt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                Change within noise threshold.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized) Summary - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)</h2>\n        <h3>Violin Plot</h3>\n        <a href=\"violin.svg\">\n            <img src=\"violin.svg\" alt=\"Violin Plot\" />\n        </a>\n        <p>This chart shows the relationship between function/parameter and iteration time. The thickness of the shaded\n            region indicates the probability that a measurement of the given function/parameter would take a particular\n            length of time.</p>\n        <h3>Line Chart</h3>\n        <img src=\"lines.svg\" alt=\"Line Chart\" />\n        <p>This chart shows the mean measured time for each function as the input (or the size of the input) increases.</p>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/0/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/0/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/0/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/10/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/10/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/10/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/20/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/20/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/20/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/100/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/100/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/100/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/500/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/500/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/500/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/0/base/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"FlexStr 0.10 (SharedStr - As is)\",\"value_str\":\"0\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/0\",\"directory_name\":\"Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/0\",\"title\":\"Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/0\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/0/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.5009382519803305,\"upper_bound\":2.607409637817401},\"point_estimate\":2.5493024613838258,\"standard_error\":0.027298499053334053},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.430472269447627,\"upper_bound\":2.5872788712418937},\"point_estimate\":2.5587837745208004,\"standard_error\":0.04647687764466679},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.14481102815007107,\"upper_bound\":0.257824247618586},\"point_estimate\":0.21967476207117392,\"standard_error\":0.027368686224253844},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.5477112743801715,\"upper_bound\":2.7511434394932226},\"point_estimate\":2.628951184459522,\"standard_error\":0.05533374200538615},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.1576867566960538,\"upper_bound\":0.3958322012826631},\"point_estimate\":0.2749619521770012,\"standard_error\":0.06523402806319799}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/0/base/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[134352.0,268704.0,403056.0,537408.0,671760.0,806112.0,940464.0,1074816.0,1209168.0,1343520.0,1477872.0,1612224.0,1746576.0,1880928.0,2015280.0,2149632.0,2283984.0,2418336.0,2552688.0,2687040.0,2821392.0,2955744.0,3090096.0,3224448.0,3358800.0,3493152.0,3627504.0,3761856.0,3896208.0,4030560.0,4164912.0,4299264.0,4433616.0,4567968.0,4702320.0,4836672.0,4971024.0,5105376.0,5239728.0,5374080.0,5508432.0,5642784.0,5777136.0,5911488.0,6045840.0,6180192.0,6314544.0,6448896.0,6583248.0,6717600.0,6851952.0,6986304.0,7120656.0,7255008.0,7389360.0,7523712.0,7658064.0,7792416.0,7926768.0,8061120.0,8195472.0,8329824.0,8464176.0,8598528.0,8732880.0,8867232.0,9001584.0,9135936.0,9270288.0,9404640.0,9538992.0,9673344.0,9807696.0,9942048.0,10076400.0,10210752.0,10345104.0,10479456.0,10613808.0,10748160.0,10882512.0,11016864.0,11151216.0,11285568.0,11419920.0,11554272.0,11688624.0,11822976.0,11957328.0,12091680.0,12226032.0,12360384.0,12494736.0,12629088.0,12763440.0,12897792.0,13032144.0,13166496.0,13300848.0,13435200.0],\"times\":[384544.0,871208.0,917626.0,1552040.0,1592623.0,2185376.0,3313250.0,2582834.0,3047750.0,3514584.0,3906583.0,4156582.0,4236915.0,5116083.0,5204834.0,5266708.0,5513333.0,6047375.0,7141416.0,6534666.0,7118335.0,7647334.0,7605585.0,7957123.0,8581001.0,8646083.0,8407000.0,8959168.0,9158957.0,9599250.0,9766168.0,10216418.0,10577040.0,10667126.0,10858332.0,11337291.0,11480458.0,12219460.0,12706290.0,12650415.0,12900208.0,12994625.0,13662040.0,13833875.0,14189291.0,14401832.0,15201127.0,15056416.0,15277291.0,15680874.0,16060292.0,16356916.0,16394000.0,17005125.0,17206000.0,17838083.0,17975336.0,18939251.0,18821792.0,18768292.0,19276169.0,19347876.0,23424874.0,23387459.0,23403626.0,23690919.0,24064625.0,24170043.0,24695376.0,25050708.0,25208957.0,25717002.0,25855042.0,26178916.0,26717960.0,26526248.0,27441626.0,27956917.0,27935335.0,28448085.0,28221874.0,28290166.0,28964835.0,29605665.0,29367876.0,29611124.0,30534293.0,30829292.0,30706623.0,31992042.0,31493625.0,32451206.0,32624418.0,32382375.0,33125543.0,37867582.0,33581419.0,36362083.0,36698541.0,59439585.0]}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/0/base/tukey.json",
    "content": "[1.4821420106854442,1.9178155788248838,3.0796117605300566,3.515285328669496]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/0/change/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.017523069981700348,\"upper_bound\":0.03918161396296982},\"point_estimate\":0.010472435994657303,\"standard_error\":0.01443164783062754},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.04315696332088881,\"upper_bound\":0.05847181727261387},\"point_estimate\":0.01959565681515274,\"standard_error\":0.02621540093333911}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/0/new/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"FlexStr 0.10 (SharedStr - As is)\",\"value_str\":\"0\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/0\",\"directory_name\":\"Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/0\",\"title\":\"Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/0\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/0/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.5009382519803305,\"upper_bound\":2.607409637817401},\"point_estimate\":2.5493024613838258,\"standard_error\":0.027298499053334053},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.430472269447627,\"upper_bound\":2.5872788712418937},\"point_estimate\":2.5587837745208004,\"standard_error\":0.04647687764466679},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.14481102815007107,\"upper_bound\":0.257824247618586},\"point_estimate\":0.21967476207117392,\"standard_error\":0.027368686224253844},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.5477112743801715,\"upper_bound\":2.7511434394932226},\"point_estimate\":2.628951184459522,\"standard_error\":0.05533374200538615},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.1576867566960538,\"upper_bound\":0.3958322012826631},\"point_estimate\":0.2749619521770012,\"standard_error\":0.06523402806319799}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/0/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[134352.0,268704.0,403056.0,537408.0,671760.0,806112.0,940464.0,1074816.0,1209168.0,1343520.0,1477872.0,1612224.0,1746576.0,1880928.0,2015280.0,2149632.0,2283984.0,2418336.0,2552688.0,2687040.0,2821392.0,2955744.0,3090096.0,3224448.0,3358800.0,3493152.0,3627504.0,3761856.0,3896208.0,4030560.0,4164912.0,4299264.0,4433616.0,4567968.0,4702320.0,4836672.0,4971024.0,5105376.0,5239728.0,5374080.0,5508432.0,5642784.0,5777136.0,5911488.0,6045840.0,6180192.0,6314544.0,6448896.0,6583248.0,6717600.0,6851952.0,6986304.0,7120656.0,7255008.0,7389360.0,7523712.0,7658064.0,7792416.0,7926768.0,8061120.0,8195472.0,8329824.0,8464176.0,8598528.0,8732880.0,8867232.0,9001584.0,9135936.0,9270288.0,9404640.0,9538992.0,9673344.0,9807696.0,9942048.0,10076400.0,10210752.0,10345104.0,10479456.0,10613808.0,10748160.0,10882512.0,11016864.0,11151216.0,11285568.0,11419920.0,11554272.0,11688624.0,11822976.0,11957328.0,12091680.0,12226032.0,12360384.0,12494736.0,12629088.0,12763440.0,12897792.0,13032144.0,13166496.0,13300848.0,13435200.0],\"times\":[384544.0,871208.0,917626.0,1552040.0,1592623.0,2185376.0,3313250.0,2582834.0,3047750.0,3514584.0,3906583.0,4156582.0,4236915.0,5116083.0,5204834.0,5266708.0,5513333.0,6047375.0,7141416.0,6534666.0,7118335.0,7647334.0,7605585.0,7957123.0,8581001.0,8646083.0,8407000.0,8959168.0,9158957.0,9599250.0,9766168.0,10216418.0,10577040.0,10667126.0,10858332.0,11337291.0,11480458.0,12219460.0,12706290.0,12650415.0,12900208.0,12994625.0,13662040.0,13833875.0,14189291.0,14401832.0,15201127.0,15056416.0,15277291.0,15680874.0,16060292.0,16356916.0,16394000.0,17005125.0,17206000.0,17838083.0,17975336.0,18939251.0,18821792.0,18768292.0,19276169.0,19347876.0,23424874.0,23387459.0,23403626.0,23690919.0,24064625.0,24170043.0,24695376.0,25050708.0,25208957.0,25717002.0,25855042.0,26178916.0,26717960.0,26526248.0,27441626.0,27956917.0,27935335.0,28448085.0,28221874.0,28290166.0,28964835.0,29605665.0,29367876.0,29611124.0,30534293.0,30829292.0,30706623.0,31992042.0,31493625.0,32451206.0,32624418.0,32382375.0,33125543.0,37867582.0,33581419.0,36362083.0,36698541.0,59439585.0]}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/0/new/tukey.json",
    "content": "[1.4821420106854442,1.9178155788248838,3.0796117605300566,3.515285328669496]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/0/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/0 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/0</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">2.5477 ns</td>\n                                <td>2.6290 ns</td>\n                                <td class=\"ci-bound\">2.7511 ns</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.6978344</td>\n                                <td>0.7091779</td>\n                                <td class=\"ci-bound\">0.6840235</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">2.5009 ns</td>\n                                <td>2.5493 ns</td>\n                                <td class=\"ci-bound\">2.6074 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">157.69 ps</td>\n                                <td>274.96 ps</td>\n                                <td class=\"ci-bound\">395.83 ps</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">2.4305 ns</td>\n                                <td>2.5588 ns</td>\n                                <td class=\"ci-bound\">2.5873 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">144.81 ps</td>\n                                <td>219.67 ps</td>\n                                <td class=\"ci-bound\">257.82 ps</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−1.7523%</td>\n                            <td>+1.0472%</td>\n                            <td class=\"ci-bound\">+3.9182%</td>\n                            <td>(p = 0.49 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/10/base/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"FlexStr 0.10 (SharedStr - As is)\",\"value_str\":\"10\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/10\",\"directory_name\":\"Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/10\",\"title\":\"Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/10\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/10/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":30.251116434182826,\"upper_bound\":31.71792575277108},\"point_estimate\":30.963239727671606,\"standard_error\":0.3740399932971555},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":29.16139435586962,\"upper_bound\":32.680944333392404},\"point_estimate\":31.52476123939308,\"standard_error\":0.9824098020087967},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.0145638026976105,\"upper_bound\":5.137889036734439},\"point_estimate\":4.279701214787598,\"standard_error\":0.5686373830765059},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":31.711670831575915,\"upper_bound\":32.831669201631875},\"point_estimate\":32.29166041290573,\"standard_error\":0.28628207972211805},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.0542784530237896,\"upper_bound\":4.6681898826870345},\"point_estimate\":3.754275152265011,\"standard_error\":0.4544132803144907}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/10/base/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[17123.0,34246.0,51369.0,68492.0,85615.0,102738.0,119861.0,136984.0,154107.0,171230.0,188353.0,205476.0,222599.0,239722.0,256845.0,273968.0,291091.0,308214.0,325337.0,342460.0,359583.0,376706.0,393829.0,410952.0,428075.0,445198.0,462321.0,479444.0,496567.0,513690.0,530813.0,547936.0,565059.0,582182.0,599305.0,616428.0,633551.0,650674.0,667797.0,684920.0,702043.0,719166.0,736289.0,753412.0,770535.0,787658.0,804781.0,821904.0,839027.0,856150.0,873273.0,890396.0,907519.0,924642.0,941765.0,958888.0,976011.0,993134.0,1010257.0,1027380.0,1044503.0,1061626.0,1078749.0,1095872.0,1112995.0,1130118.0,1147241.0,1164364.0,1181487.0,1198610.0,1215733.0,1232856.0,1249979.0,1267102.0,1284225.0,1301348.0,1318471.0,1335594.0,1352717.0,1369840.0,1386963.0,1404086.0,1421209.0,1438332.0,1455455.0,1472578.0,1489701.0,1506824.0,1523947.0,1541070.0,1558193.0,1575316.0,1592439.0,1609562.0,1626685.0,1643808.0,1660931.0,1678054.0,1695177.0,1712300.0],\"times\":[851084.0,913125.0,1381543.0,2186166.0,2279789.0,2773002.0,3683042.0,3686249.0,4553250.0,4563876.0,5063666.0,5502708.0,6332376.0,6465752.0,6791624.0,7368918.0,8185167.0,8275458.0,9182334.0,9120292.0,9997416.0,9995332.0,10514332.0,11091040.0,11514374.0,11905663.0,12425499.0,13271083.0,13285539.0,13892667.0,14251085.0,14676373.0,15173084.0,15799501.0,16113291.0,16517544.0,17075042.0,23924750.0,24903042.0,24066000.0,25068960.0,25679542.0,25308665.0,24881583.0,25922710.0,25438334.0,25332376.0,25949292.0,25299335.0,25613917.0,25579997.0,25947458.0,26296665.0,25939125.0,26664791.0,29350831.0,33916752.0,34206165.0,33200167.0,35228167.0,35396041.0,35830791.0,36215334.0,37059710.0,37447210.0,37885874.0,38512958.0,38761916.0,39261209.0,40159791.0,40623833.0,39874499.0,41154374.0,41357957.0,42895374.0,46855876.0,47787501.0,47410708.0,47818666.0,47350999.0,47751084.0,47715708.0,46523334.0,46438959.0,46444248.0,48045579.0,47226335.0,45559875.0,45918418.0,44939750.0,45176249.0,45141125.0,44279707.0,52708626.0,54078460.0,54670083.0,57055251.0,54297250.0,56267625.0,57142834.0]}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/10/base/tukey.json",
    "content": "[7.3555205752784545,17.17296897381182,43.3528313699008,53.17027976843417]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/10/change/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.028940131565599898,\"upper_bound\":0.033658808699233045},\"point_estimate\":0.0012567936171992145,\"standard_error\":0.016038436639874386},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.07886016369116466,\"upper_bound\":0.0835623704842603},\"point_estimate\":0.009364543503771028,\"standard_error\":0.04190245439648872}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/10/new/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"FlexStr 0.10 (SharedStr - As is)\",\"value_str\":\"10\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/10\",\"directory_name\":\"Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/10\",\"title\":\"Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/10\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/10/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":30.251116434182826,\"upper_bound\":31.71792575277108},\"point_estimate\":30.963239727671606,\"standard_error\":0.3740399932971555},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":29.16139435586962,\"upper_bound\":32.680944333392404},\"point_estimate\":31.52476123939308,\"standard_error\":0.9824098020087967},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.0145638026976105,\"upper_bound\":5.137889036734439},\"point_estimate\":4.279701214787598,\"standard_error\":0.5686373830765059},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":31.711670831575915,\"upper_bound\":32.831669201631875},\"point_estimate\":32.29166041290573,\"standard_error\":0.28628207972211805},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.0542784530237896,\"upper_bound\":4.6681898826870345},\"point_estimate\":3.754275152265011,\"standard_error\":0.4544132803144907}}"
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  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/10/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[17123.0,34246.0,51369.0,68492.0,85615.0,102738.0,119861.0,136984.0,154107.0,171230.0,188353.0,205476.0,222599.0,239722.0,256845.0,273968.0,291091.0,308214.0,325337.0,342460.0,359583.0,376706.0,393829.0,410952.0,428075.0,445198.0,462321.0,479444.0,496567.0,513690.0,530813.0,547936.0,565059.0,582182.0,599305.0,616428.0,633551.0,650674.0,667797.0,684920.0,702043.0,719166.0,736289.0,753412.0,770535.0,787658.0,804781.0,821904.0,839027.0,856150.0,873273.0,890396.0,907519.0,924642.0,941765.0,958888.0,976011.0,993134.0,1010257.0,1027380.0,1044503.0,1061626.0,1078749.0,1095872.0,1112995.0,1130118.0,1147241.0,1164364.0,1181487.0,1198610.0,1215733.0,1232856.0,1249979.0,1267102.0,1284225.0,1301348.0,1318471.0,1335594.0,1352717.0,1369840.0,1386963.0,1404086.0,1421209.0,1438332.0,1455455.0,1472578.0,1489701.0,1506824.0,1523947.0,1541070.0,1558193.0,1575316.0,1592439.0,1609562.0,1626685.0,1643808.0,1660931.0,1678054.0,1695177.0,1712300.0],\"times\":[851084.0,913125.0,1381543.0,2186166.0,2279789.0,2773002.0,3683042.0,3686249.0,4553250.0,4563876.0,5063666.0,5502708.0,6332376.0,6465752.0,6791624.0,7368918.0,8185167.0,8275458.0,9182334.0,9120292.0,9997416.0,9995332.0,10514332.0,11091040.0,11514374.0,11905663.0,12425499.0,13271083.0,13285539.0,13892667.0,14251085.0,14676373.0,15173084.0,15799501.0,16113291.0,16517544.0,17075042.0,23924750.0,24903042.0,24066000.0,25068960.0,25679542.0,25308665.0,24881583.0,25922710.0,25438334.0,25332376.0,25949292.0,25299335.0,25613917.0,25579997.0,25947458.0,26296665.0,25939125.0,26664791.0,29350831.0,33916752.0,34206165.0,33200167.0,35228167.0,35396041.0,35830791.0,36215334.0,37059710.0,37447210.0,37885874.0,38512958.0,38761916.0,39261209.0,40159791.0,40623833.0,39874499.0,41154374.0,41357957.0,42895374.0,46855876.0,47787501.0,47410708.0,47818666.0,47350999.0,47751084.0,47715708.0,46523334.0,46438959.0,46444248.0,48045579.0,47226335.0,45559875.0,45918418.0,44939750.0,45176249.0,45141125.0,44279707.0,52708626.0,54078460.0,54670083.0,57055251.0,54297250.0,56267625.0,57142834.0]}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/10/new/tukey.json",
    "content": "[7.3555205752784545,17.17296897381182,43.3528313699008,53.17027976843417]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/10/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/10 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/10</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">31.712 ns</td>\n                                <td>32.292 ns</td>\n                                <td class=\"ci-bound\">32.832 ns</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.5888364</td>\n                                <td>0.6023747</td>\n                                <td class=\"ci-bound\">0.5906033</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">30.251 ns</td>\n                                <td>30.963 ns</td>\n                                <td class=\"ci-bound\">31.718 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">3.0543 ns</td>\n                                <td>3.7543 ns</td>\n                                <td class=\"ci-bound\">4.6682 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">29.161 ns</td>\n                                <td>31.525 ns</td>\n                                <td class=\"ci-bound\">32.681 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">3.0146 ns</td>\n                                <td>4.2797 ns</td>\n                                <td class=\"ci-bound\">5.1379 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−2.8940%</td>\n                            <td>+0.1257%</td>\n                            <td class=\"ci-bound\">+3.3659%</td>\n                            <td>(p = 0.94 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/100/base/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"FlexStr 0.10 (SharedStr - As is)\",\"value_str\":\"100\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/100\",\"directory_name\":\"Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/100\",\"title\":\"Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/100\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/100/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":38.77519540044674,\"upper_bound\":40.29610894648774},\"point_estimate\":39.542562867245515,\"standard_error\":0.3896217098771971},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":38.758391996654055,\"upper_bound\":40.35936384893443},\"point_estimate\":39.547188999947124,\"standard_error\":0.47109989799064195},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.117561738956853,\"upper_bound\":5.274649297957817},\"point_estimate\":4.626255589300013,\"standard_error\":0.5257675737942579},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":39.97774735474569,\"upper_bound\":41.30453680804932},\"point_estimate\":40.647987059010596,\"standard_error\":0.33814248996104723},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.407808587208913,\"upper_bound\":4.356735022642185},\"point_estimate\":3.9117505386877744,\"standard_error\":0.24159636141849408}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/100/base/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[11001.0,22002.0,33003.0,44004.0,55005.0,66006.0,77007.0,88008.0,99009.0,110010.0,121011.0,132012.0,143013.0,154014.0,165015.0,176016.0,187017.0,198018.0,209019.0,220020.0,231021.0,242022.0,253023.0,264024.0,275025.0,286026.0,297027.0,308028.0,319029.0,330030.0,341031.0,352032.0,363033.0,374034.0,385035.0,396036.0,407037.0,418038.0,429039.0,440040.0,451041.0,462042.0,473043.0,484044.0,495045.0,506046.0,517047.0,528048.0,539049.0,550050.0,561051.0,572052.0,583053.0,594054.0,605055.0,616056.0,627057.0,638058.0,649059.0,660060.0,671061.0,682062.0,693063.0,704064.0,715065.0,726066.0,737067.0,748068.0,759069.0,770070.0,781071.0,792072.0,803073.0,814074.0,825075.0,836076.0,847077.0,858078.0,869079.0,880080.0,891081.0,902082.0,913083.0,924084.0,935085.0,946086.0,957087.0,968088.0,979089.0,990090.0,1001091.0,1012092.0,1023093.0,1034094.0,1045095.0,1056096.0,1067097.0,1078098.0,1089099.0,1100100.0],\"times\":[349042.0,768541.0,1011918.0,1355668.0,1999998.0,2054541.0,2585623.0,2884791.0,4318040.0,4292917.0,4227959.0,4173792.0,5668374.0,6021542.0,6366957.0,6736916.0,8056041.0,8029959.0,7593584.0,7393710.0,8939792.0,9959791.0,11122124.0,12608166.0,11377875.0,12021540.0,11380876.0,11155210.0,10837917.0,12876040.0,13699541.0,16633667.0,15803666.0,16140582.0,15471000.0,14802791.0,14166625.0,15135875.0,14809668.0,19959500.0,19684416.0,20377626.0,18998168.0,18360417.0,17198874.0,17816416.0,18637833.0,24523373.0,24226291.0,23733290.0,22714667.0,21230334.0,21004668.0,20571665.0,22130126.0,23517834.0,28560875.0,27863999.0,26355500.0,25491875.0,26101751.0,24961420.0,27186541.0,26416626.0,33199292.0,32099751.0,31774876.0,30322125.0,30392209.0,28970792.0,30278293.0,30310083.0,34721374.0,35250002.0,34499543.0,35780085.0,33799376.0,33554042.0,31524626.0,33506749.0,33704250.0,41182042.0,40922164.0,39545958.0,37377334.0,37123460.0,35077793.0,38747791.0,38633875.0,44259667.0,42918208.0,43029458.0,40847205.0,41735376.0,40530544.0,44406084.0,43387667.0,45928083.0,47294331.0,45175252.0]}"
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  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/100/base/tukey.json",
    "content": "[18.105834979572528,27.37150917863971,52.07997370948553,61.345647908552706]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/100/change/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.01803092274445305,\"upper_bound\":0.035219915187657234},\"point_estimate\":0.00836466384256429,\"standard_error\":0.01368243708386179},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.024093517524035768,\"upper_bound\":0.05012967504971244},\"point_estimate\":0.019794063478725032,\"standard_error\":0.019461477125510596}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/100/new/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"FlexStr 0.10 (SharedStr - As is)\",\"value_str\":\"100\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/100\",\"directory_name\":\"Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/100\",\"title\":\"Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/100\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/100/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":38.77519540044674,\"upper_bound\":40.29610894648774},\"point_estimate\":39.542562867245515,\"standard_error\":0.3896217098771971},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":38.758391996654055,\"upper_bound\":40.35936384893443},\"point_estimate\":39.547188999947124,\"standard_error\":0.47109989799064195},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.117561738956853,\"upper_bound\":5.274649297957817},\"point_estimate\":4.626255589300013,\"standard_error\":0.5257675737942579},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":39.97774735474569,\"upper_bound\":41.30453680804932},\"point_estimate\":40.647987059010596,\"standard_error\":0.33814248996104723},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.407808587208913,\"upper_bound\":4.356735022642185},\"point_estimate\":3.9117505386877744,\"standard_error\":0.24159636141849408}}"
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  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/100/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[11001.0,22002.0,33003.0,44004.0,55005.0,66006.0,77007.0,88008.0,99009.0,110010.0,121011.0,132012.0,143013.0,154014.0,165015.0,176016.0,187017.0,198018.0,209019.0,220020.0,231021.0,242022.0,253023.0,264024.0,275025.0,286026.0,297027.0,308028.0,319029.0,330030.0,341031.0,352032.0,363033.0,374034.0,385035.0,396036.0,407037.0,418038.0,429039.0,440040.0,451041.0,462042.0,473043.0,484044.0,495045.0,506046.0,517047.0,528048.0,539049.0,550050.0,561051.0,572052.0,583053.0,594054.0,605055.0,616056.0,627057.0,638058.0,649059.0,660060.0,671061.0,682062.0,693063.0,704064.0,715065.0,726066.0,737067.0,748068.0,759069.0,770070.0,781071.0,792072.0,803073.0,814074.0,825075.0,836076.0,847077.0,858078.0,869079.0,880080.0,891081.0,902082.0,913083.0,924084.0,935085.0,946086.0,957087.0,968088.0,979089.0,990090.0,1001091.0,1012092.0,1023093.0,1034094.0,1045095.0,1056096.0,1067097.0,1078098.0,1089099.0,1100100.0],\"times\":[349042.0,768541.0,1011918.0,1355668.0,1999998.0,2054541.0,2585623.0,2884791.0,4318040.0,4292917.0,4227959.0,4173792.0,5668374.0,6021542.0,6366957.0,6736916.0,8056041.0,8029959.0,7593584.0,7393710.0,8939792.0,9959791.0,11122124.0,12608166.0,11377875.0,12021540.0,11380876.0,11155210.0,10837917.0,12876040.0,13699541.0,16633667.0,15803666.0,16140582.0,15471000.0,14802791.0,14166625.0,15135875.0,14809668.0,19959500.0,19684416.0,20377626.0,18998168.0,18360417.0,17198874.0,17816416.0,18637833.0,24523373.0,24226291.0,23733290.0,22714667.0,21230334.0,21004668.0,20571665.0,22130126.0,23517834.0,28560875.0,27863999.0,26355500.0,25491875.0,26101751.0,24961420.0,27186541.0,26416626.0,33199292.0,32099751.0,31774876.0,30322125.0,30392209.0,28970792.0,30278293.0,30310083.0,34721374.0,35250002.0,34499543.0,35780085.0,33799376.0,33554042.0,31524626.0,33506749.0,33704250.0,41182042.0,40922164.0,39545958.0,37377334.0,37123460.0,35077793.0,38747791.0,38633875.0,44259667.0,42918208.0,43029458.0,40847205.0,41735376.0,40530544.0,44406084.0,43387667.0,45928083.0,47294331.0,45175252.0]}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/100/new/tukey.json",
    "content": "[18.105834979572528,27.37150917863971,52.07997370948553,61.345647908552706]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/100/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/100 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/100</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">39.978 ns</td>\n                                <td>40.648 ns</td>\n                                <td class=\"ci-bound\">41.305 ns</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.5921598</td>\n                                <td>0.6049101</td>\n                                <td class=\"ci-bound\">0.5926649</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">38.775 ns</td>\n                                <td>39.543 ns</td>\n                                <td class=\"ci-bound\">40.296 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">3.4078 ns</td>\n                                <td>3.9118 ns</td>\n                                <td class=\"ci-bound\">4.3567 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">38.758 ns</td>\n                                <td>39.547 ns</td>\n                                <td class=\"ci-bound\">40.359 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">3.1176 ns</td>\n                                <td>4.6263 ns</td>\n                                <td class=\"ci-bound\">5.2746 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−1.8031%</td>\n                            <td>+0.8365%</td>\n                            <td class=\"ci-bound\">+3.5220%</td>\n                            <td>(p = 0.54 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/20/base/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"FlexStr 0.10 (SharedStr - As is)\",\"value_str\":\"20\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/20\",\"directory_name\":\"Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/20\",\"title\":\"Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/20\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/20/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":32.465926097663896,\"upper_bound\":34.11683804100407},\"point_estimate\":33.26337045241353,\"standard_error\":0.42193543089171365},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":32.63349786292711,\"upper_bound\":34.06582596318954},\"point_estimate\":33.462462682788335,\"standard_error\":0.3867085841757712},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.0699607869167274,\"upper_bound\":5.205475509685265},\"point_estimate\":3.9363170600152038,\"standard_error\":0.5581541494098478},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":33.70129714431918,\"upper_bound\":35.177943882801515},\"point_estimate\":34.444750527067455,\"standard_error\":0.3772273887562825},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.2477174550749783,\"upper_bound\":5.497444007561643},\"point_estimate\":4.243683721572856,\"standard_error\":0.6323499041573755}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/20/base/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[14089.0,28178.0,42267.0,56356.0,70445.0,84534.0,98623.0,112712.0,126801.0,140890.0,154979.0,169068.0,183157.0,197246.0,211335.0,225424.0,239513.0,253602.0,267691.0,281780.0,295869.0,309958.0,324047.0,338136.0,352225.0,366314.0,380403.0,394492.0,408581.0,422670.0,436759.0,450848.0,464937.0,479026.0,493115.0,507204.0,521293.0,535382.0,549471.0,563560.0,577649.0,591738.0,605827.0,619916.0,634005.0,648094.0,662183.0,676272.0,690361.0,704450.0,718539.0,732628.0,746717.0,760806.0,774895.0,788984.0,803073.0,817162.0,831251.0,845340.0,859429.0,873518.0,887607.0,901696.0,915785.0,929874.0,943963.0,958052.0,972141.0,986230.0,1000319.0,1014408.0,1028497.0,1042586.0,1056675.0,1070764.0,1084853.0,1098942.0,1113031.0,1127120.0,1141209.0,1155298.0,1169387.0,1183476.0,1197565.0,1211654.0,1225743.0,1239832.0,1253921.0,1268010.0,1282099.0,1296188.0,1310277.0,1324366.0,1338455.0,1352544.0,1366633.0,1380722.0,1394811.0,1408900.0],\"times\":[799499.0,761916.0,1160583.0,1558665.0,2199625.0,3028499.0,2728459.0,3523373.0,3446959.0,3847045.0,4136000.0,4594918.0,5043832.0,5784626.0,5737873.0,6104457.0,6853004.0,6986125.0,7761794.0,8244584.0,8378084.0,8535207.0,12501875.0,12584541.0,13083415.0,12589834.0,12682914.0,12946208.0,13040960.0,13116335.0,13231793.0,13596501.0,13539626.0,13317584.0,17328293.0,17153708.0,17963958.0,18440501.0,18918167.0,19128376.0,19363790.0,20093041.0,20175002.0,21045085.0,21168957.0,24884793.0,24780835.0,24609957.0,24819584.0,23724292.0,23482041.0,24037334.0,24309668.0,23449792.0,23026875.0,22746917.0,25911082.0,27675498.0,28414958.0,29806585.0,30726585.0,30950876.0,33104083.0,34031415.0,34300044.0,34224209.0,33987667.0,34354751.0,37797502.0,36719749.0,36785708.0,35592333.0,36184041.0,34666956.0,33917583.0,33910542.0,33735918.0,32704165.0,32947584.0,37649417.0,37626626.0,36733293.0,39498498.0,39924501.0,40530041.0,46901875.0,48546000.0,47666376.0,48179040.0,46073751.0,47768793.0,49729875.0,47891001.0,47852417.0,46946124.0,47194291.0,44704751.0,44803290.0,43591541.0,42339417.0]}"
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  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/20/base/tukey.json",
    "content": "[12.877880783195522,21.504471468590452,44.50871329631026,53.13530398170519]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/20/change/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.027189036409991617,\"upper_bound\":0.038802253601969205},\"point_estimate\":0.005839928186810894,\"standard_error\":0.016771721768113014},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.042040487532734816,\"upper_bound\":0.022816133795661796},\"point_estimate\":-0.008670285371628506,\"standard_error\":0.017096329436450515}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/20/new/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"FlexStr 0.10 (SharedStr - As is)\",\"value_str\":\"20\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/20\",\"directory_name\":\"Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/20\",\"title\":\"Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/20\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/20/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":32.465926097663896,\"upper_bound\":34.11683804100407},\"point_estimate\":33.26337045241353,\"standard_error\":0.42193543089171365},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":32.63349786292711,\"upper_bound\":34.06582596318954},\"point_estimate\":33.462462682788335,\"standard_error\":0.3867085841757712},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.0699607869167274,\"upper_bound\":5.205475509685265},\"point_estimate\":3.9363170600152038,\"standard_error\":0.5581541494098478},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":33.70129714431918,\"upper_bound\":35.177943882801515},\"point_estimate\":34.444750527067455,\"standard_error\":0.3772273887562825},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.2477174550749783,\"upper_bound\":5.497444007561643},\"point_estimate\":4.243683721572856,\"standard_error\":0.6323499041573755}}"
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    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/20/new/sample.json",
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    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/20/new/tukey.json",
    "content": "[12.877880783195522,21.504471468590452,44.50871329631026,53.13530398170519]"
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  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/20/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/20 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/20</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">33.701 ns</td>\n                                <td>34.445 ns</td>\n                                <td class=\"ci-bound\">35.178 ns</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.3618829</td>\n                                <td>0.3774059</td>\n                                <td class=\"ci-bound\">0.3622913</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">32.466 ns</td>\n                                <td>33.263 ns</td>\n                                <td class=\"ci-bound\">34.117 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">3.2477 ns</td>\n                                <td>4.2437 ns</td>\n                                <td class=\"ci-bound\">5.4974 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">32.633 ns</td>\n                                <td>33.462 ns</td>\n                                <td class=\"ci-bound\">34.066 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">3.0700 ns</td>\n                                <td>3.9363 ns</td>\n                                <td class=\"ci-bound\">5.2055 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−2.7189%</td>\n                            <td>+0.5840%</td>\n                            <td class=\"ci-bound\">+3.8802%</td>\n                            <td>(p = 0.73 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
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    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/500/base/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"FlexStr 0.10 (SharedStr - As is)\",\"value_str\":\"500\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/500\",\"directory_name\":\"Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/500\",\"title\":\"Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/500\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/500/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":46.8387661793291,\"upper_bound\":49.041906968588414},\"point_estimate\":47.9576922859315,\"standard_error\":0.5636636914346886},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":46.75003206393055,\"upper_bound\":49.84308828503777},\"point_estimate\":47.955223205886014,\"standard_error\":0.7691825685527064},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":4.445586338628917,\"upper_bound\":7.094673348939047},\"point_estimate\":5.9803657572573945,\"standard_error\":0.6876275070374762},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":50.09714753877018,\"upper_bound\":52.15204187309517},\"point_estimate\":51.19224382358838,\"standard_error\":0.5262259634487192},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":4.803300811515525,\"upper_bound\":6.438119742565619},\"point_estimate\":5.670223343505682,\"standard_error\":0.4172729636594685}}"
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  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/500/new/tukey.json",
    "content": "[20.62458664494281,32.72056229304306,64.97649735464373,77.07247300274398]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/500/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/500 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/500</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">50.097 ns</td>\n                                <td>51.192 ns</td>\n                                <td class=\"ci-bound\">52.152 ns</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.5730041</td>\n                                <td>0.5885994</td>\n                                <td class=\"ci-bound\">0.5765456</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">46.839 ns</td>\n                                <td>47.958 ns</td>\n                                <td class=\"ci-bound\">49.042 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">4.8033 ns</td>\n                                <td>5.6702 ns</td>\n                                <td class=\"ci-bound\">6.4381 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">46.750 ns</td>\n                                <td>47.955 ns</td>\n                                <td class=\"ci-bound\">49.843 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">4.4456 ns</td>\n                                <td>5.9804 ns</td>\n                                <td class=\"ci-bound\">7.0947 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−9.2286%</td>\n                            <td>−4.4351%</td>\n                            <td class=\"ci-bound\">+0.1865%</td>\n                            <td>(p = 0.08 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/FlexStr 0.10 (SharedStr - As is) Summary - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)</h2>\n        <h3>Violin Plot</h3>\n        <a href=\"violin.svg\">\n            <img src=\"violin.svg\" alt=\"Violin Plot\" />\n        </a>\n        <p>This chart shows the relationship between function/parameter and iteration time. The thickness of the shaded\n            region indicates the probability that a measurement of the given function/parameter would take a particular\n            length of time.</p>\n        <h3>Line Chart</h3>\n        <img src=\"lines.svg\" alt=\"Line Chart\" />\n        <p>This chart shows the mean measured time for each function as the input (or the size of the input) increases.</p>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/0/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/0/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/0/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/10/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/10/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/10/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/20/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/20/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/20/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/100/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/100/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/100/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/500/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/500/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/500/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/0/base/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"FlexStr 0.10 (SharedStr - Optimized)\",\"value_str\":\"0\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/0\",\"directory_name\":\"Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/0\",\"title\":\"Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/0\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/0/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":11.789848306463925,\"upper_bound\":11.966672492685287},\"point_estimate\":11.8731086720579,\"standard_error\":0.045216599917974845},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":11.672473683033903,\"upper_bound\":11.864965555000914},\"point_estimate\":11.726651555929736,\"standard_error\":0.055088741349013946},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.2317457643631268,\"upper_bound\":0.4194348768451378},\"point_estimate\":0.2901299283173439,\"standard_error\":0.046673560508294736},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":11.725634750183204,\"upper_bound\":11.869397270035094},\"point_estimate\":11.79453731804242,\"standard_error\":0.03681304066806461},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.32416545455435175,\"upper_bound\":0.6036719740847015},\"point_estimate\":0.4559274849781959,\"standard_error\":0.07568173193916045}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/0/base/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[59821.0,119642.0,179463.0,239284.0,299105.0,358926.0,418747.0,478568.0,538389.0,598210.0,658031.0,717852.0,777673.0,837494.0,897315.0,957136.0,1016957.0,1076778.0,1136599.0,1196420.0,1256241.0,1316062.0,1375883.0,1435704.0,1495525.0,1555346.0,1615167.0,1674988.0,1734809.0,1794630.0,1854451.0,1914272.0,1974093.0,2033914.0,2093735.0,2153556.0,2213377.0,2273198.0,2333019.0,2392840.0,2452661.0,2512482.0,2572303.0,2632124.0,2691945.0,2751766.0,2811587.0,2871408.0,2931229.0,2991050.0,3050871.0,3110692.0,3170513.0,3230334.0,3290155.0,3349976.0,3409797.0,3469618.0,3529439.0,3589260.0,3649081.0,3708902.0,3768723.0,3828544.0,3888365.0,3948186.0,4008007.0,4067828.0,4127649.0,4187470.0,4247291.0,4307112.0,4366933.0,4426754.0,4486575.0,4546396.0,4606217.0,4666038.0,4725859.0,4785680.0,4845501.0,4905322.0,4965143.0,5024964.0,5084785.0,5144606.0,5204427.0,5264248.0,5324069.0,5383890.0,5443711.0,5503532.0,5563353.0,5623174.0,5682995.0,5742816.0,5802637.0,5862458.0,5922279.0,5982100.0],\"times\":[866582.0,1431083.0,2176207.0,3151541.0,3545126.0,4138667.0,4992334.0,5416999.0,6104708.0,6713418.0,7672291.0,8269583.0,9468626.0,10424543.0,11036500.0,11952249.0,12274540.0,12822583.0,13061875.0,13944666.0,16125418.0,15308000.0,17244541.0,16492210.0,17819083.0,18947001.0,20504126.0,21124334.0,19907460.0,21548915.0,22063040.0,24233790.0,23484291.0,24183417.0,23920791.0,24587209.0,26230625.0,26613665.0,27223541.0,27854792.0,28521208.0,30212878.0,30109126.0,30874960.0,31309915.0,32158292.0,33204667.0,32985751.0,33792124.0,35556541.0,37739500.0,36703290.0,36652416.0,39752291.0,38232127.0,41675834.0,40422334.0,41225042.0,40576334.0,41780376.0,41623290.0,42631917.0,43855666.0,44439250.0,45518207.0,46885374.0,46871083.0,47619875.0,47506498.0,47628791.0,48079126.0,53211376.0,53476958.0,53475376.0,55662834.0,54121208.0,56052125.0,55331376.0,58070375.0,54943624.0,59125167.0,56739084.0,57955501.0,59393665.0,59496001.0,59715747.0,60495500.0,61714084.0,61680833.0,63211042.0,65604790.0,63789084.0,65081918.0,65976751.0,66082085.0,68756415.0,67601836.0,72495542.0,68606040.0,68875667.0]}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/0/base/tukey.json",
    "content": "[10.24438195403427,10.923768709848524,12.735466725353199,13.414853481167452]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/0/change/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.023490533711422783,\"upper_bound\":0.005704871947644707},\"point_estimate\":-0.007520462309735243,\"standard_error\":0.007469517781172232},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.017596835042226207,\"upper_bound\":0.0034008499378308044},\"point_estimate\":-0.008807963580734102,\"standard_error\":0.005481912310330489}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/0/new/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"FlexStr 0.10 (SharedStr - Optimized)\",\"value_str\":\"0\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/0\",\"directory_name\":\"Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/0\",\"title\":\"Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/0\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/0/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":11.789848306463925,\"upper_bound\":11.966672492685287},\"point_estimate\":11.8731086720579,\"standard_error\":0.045216599917974845},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":11.672473683033903,\"upper_bound\":11.864965555000914},\"point_estimate\":11.726651555929736,\"standard_error\":0.055088741349013946},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.2317457643631268,\"upper_bound\":0.4194348768451378},\"point_estimate\":0.2901299283173439,\"standard_error\":0.046673560508294736},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":11.725634750183204,\"upper_bound\":11.869397270035094},\"point_estimate\":11.79453731804242,\"standard_error\":0.03681304066806461},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.32416545455435175,\"upper_bound\":0.6036719740847015},\"point_estimate\":0.4559274849781959,\"standard_error\":0.07568173193916045}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/0/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[59821.0,119642.0,179463.0,239284.0,299105.0,358926.0,418747.0,478568.0,538389.0,598210.0,658031.0,717852.0,777673.0,837494.0,897315.0,957136.0,1016957.0,1076778.0,1136599.0,1196420.0,1256241.0,1316062.0,1375883.0,1435704.0,1495525.0,1555346.0,1615167.0,1674988.0,1734809.0,1794630.0,1854451.0,1914272.0,1974093.0,2033914.0,2093735.0,2153556.0,2213377.0,2273198.0,2333019.0,2392840.0,2452661.0,2512482.0,2572303.0,2632124.0,2691945.0,2751766.0,2811587.0,2871408.0,2931229.0,2991050.0,3050871.0,3110692.0,3170513.0,3230334.0,3290155.0,3349976.0,3409797.0,3469618.0,3529439.0,3589260.0,3649081.0,3708902.0,3768723.0,3828544.0,3888365.0,3948186.0,4008007.0,4067828.0,4127649.0,4187470.0,4247291.0,4307112.0,4366933.0,4426754.0,4486575.0,4546396.0,4606217.0,4666038.0,4725859.0,4785680.0,4845501.0,4905322.0,4965143.0,5024964.0,5084785.0,5144606.0,5204427.0,5264248.0,5324069.0,5383890.0,5443711.0,5503532.0,5563353.0,5623174.0,5682995.0,5742816.0,5802637.0,5862458.0,5922279.0,5982100.0],\"times\":[866582.0,1431083.0,2176207.0,3151541.0,3545126.0,4138667.0,4992334.0,5416999.0,6104708.0,6713418.0,7672291.0,8269583.0,9468626.0,10424543.0,11036500.0,11952249.0,12274540.0,12822583.0,13061875.0,13944666.0,16125418.0,15308000.0,17244541.0,16492210.0,17819083.0,18947001.0,20504126.0,21124334.0,19907460.0,21548915.0,22063040.0,24233790.0,23484291.0,24183417.0,23920791.0,24587209.0,26230625.0,26613665.0,27223541.0,27854792.0,28521208.0,30212878.0,30109126.0,30874960.0,31309915.0,32158292.0,33204667.0,32985751.0,33792124.0,35556541.0,37739500.0,36703290.0,36652416.0,39752291.0,38232127.0,41675834.0,40422334.0,41225042.0,40576334.0,41780376.0,41623290.0,42631917.0,43855666.0,44439250.0,45518207.0,46885374.0,46871083.0,47619875.0,47506498.0,47628791.0,48079126.0,53211376.0,53476958.0,53475376.0,55662834.0,54121208.0,56052125.0,55331376.0,58070375.0,54943624.0,59125167.0,56739084.0,57955501.0,59393665.0,59496001.0,59715747.0,60495500.0,61714084.0,61680833.0,63211042.0,65604790.0,63789084.0,65081918.0,65976751.0,66082085.0,68756415.0,67601836.0,72495542.0,68606040.0,68875667.0]}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/0/new/tukey.json",
    "content": "[10.24438195403427,10.923768709848524,12.735466725353199,13.414853481167452]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/0/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/0 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/0</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">11.726 ns</td>\n                                <td>11.795 ns</td>\n                                <td class=\"ci-bound\">11.869 ns</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.9102143</td>\n                                <td>0.9145561</td>\n                                <td class=\"ci-bound\">0.9094354</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">11.790 ns</td>\n                                <td>11.873 ns</td>\n                                <td class=\"ci-bound\">11.967 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">324.17 ps</td>\n                                <td>455.93 ps</td>\n                                <td class=\"ci-bound\">603.67 ps</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">11.672 ns</td>\n                                <td>11.727 ns</td>\n                                <td class=\"ci-bound\">11.865 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">231.75 ps</td>\n                                <td>290.13 ps</td>\n                                <td class=\"ci-bound\">419.43 ps</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−2.3491%</td>\n                            <td>−0.7520%</td>\n                            <td class=\"ci-bound\">+0.5705%</td>\n                            <td>(p = 0.34 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/10/base/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"FlexStr 0.10 (SharedStr - Optimized)\",\"value_str\":\"10\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/10\",\"directory_name\":\"Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/10\",\"title\":\"Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/10\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/10/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":41.394675639959395,\"upper_bound\":42.987098417195696},\"point_estimate\":42.14464494744718,\"standard_error\":0.4058794686724972},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":39.93452734209411,\"upper_bound\":43.61012722486511},\"point_estimate\":42.87137974481037,\"standard_error\":1.1943596390805837},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.7380526693466654,\"upper_bound\":5.297098641855851},\"point_estimate\":4.717451338389043,\"standard_error\":0.62271076212551},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":43.17620398090479,\"upper_bound\":44.23509319843152},\"point_estimate\":43.73707498334884,\"standard_error\":0.2688409644898111},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.9823119877376794,\"upper_bound\":5.50428583250578},\"point_estimate\":4.08105289431033,\"standard_error\":0.7684223267295737}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/10/base/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[14154.0,28308.0,42462.0,56616.0,70770.0,84924.0,99078.0,113232.0,127386.0,141540.0,155694.0,169848.0,184002.0,198156.0,212310.0,226464.0,240618.0,254772.0,268926.0,283080.0,297234.0,311388.0,325542.0,339696.0,353850.0,368004.0,382158.0,396312.0,410466.0,424620.0,438774.0,452928.0,467082.0,481236.0,495390.0,509544.0,523698.0,537852.0,552006.0,566160.0,580314.0,594468.0,608622.0,622776.0,636930.0,651084.0,665238.0,679392.0,693546.0,707700.0,721854.0,736008.0,750162.0,764316.0,778470.0,792624.0,806778.0,820932.0,835086.0,849240.0,863394.0,877548.0,891702.0,905856.0,920010.0,934164.0,948318.0,962472.0,976626.0,990780.0,1004934.0,1019088.0,1033242.0,1047396.0,1061550.0,1075704.0,1089858.0,1104012.0,1118166.0,1132320.0,1146474.0,1160628.0,1174782.0,1188936.0,1203090.0,1217244.0,1231398.0,1245552.0,1259706.0,1273860.0,1288014.0,1302168.0,1316322.0,1330476.0,1344630.0,1358784.0,1372938.0,1387092.0,1401246.0,1415400.0],\"times\":[958334.0,1082042.0,1645750.0,2697500.0,2778000.0,3825708.0,4298791.0,4355834.0,5203001.0,5652333.0,5962500.0,6519084.0,7371623.0,7518957.0,8100166.0,8684834.0,9504709.0,10022125.0,10239833.0,10826001.0,11331458.0,12179083.0,12791958.0,12909418.0,13503000.0,14083000.0,14542043.0,15501542.0,16362126.0,16473625.0,17126084.0,17620081.0,18122540.0,18473085.0,18815542.0,19466500.0,19801708.0,20623708.0,21520915.0,21555083.0,22130292.0,22960124.0,23084543.0,23792917.0,24318876.0,30805958.0,31836833.0,31596583.0,32123043.0,32762914.0,32652668.0,33450420.0,33106625.0,34134167.0,33659623.0,34032459.0,34776585.0,35205248.0,35129583.0,36396959.0,35116084.0,35757793.0,36208377.0,36735585.0,37083376.0,37092708.0,36549667.0,43249999.0,43625207.0,44053125.0,45579668.0,44858210.0,46499957.0,46916209.0,46832208.0,48122624.0,48031001.0,49347915.0,49103626.0,49906333.0,49997877.0,50946501.0,52454373.0,52515791.0,52890291.0,52800292.0,53944790.0,54016832.0,54411333.0,54786586.0,60692834.0,59533252.0,62333957.0,62135874.0,62731124.0,62599998.0,62870958.0,62696376.0,61996166.0,61883540.0]}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/10/base/tukey.json",
    "content": "[20.42406981145089,29.513347918418898,53.751422870333585,62.84070097730159]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/10/change/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.019963821983583086,\"upper_bound\":0.030538065872427977},\"point_estimate\":0.003855934838305597,\"standard_error\":0.012808585018790073},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.06586725063779097,\"upper_bound\":0.08231370511103786},\"point_estimate\":0.02579080855142646,\"standard_error\":0.03889228346717171}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/10/new/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"FlexStr 0.10 (SharedStr - Optimized)\",\"value_str\":\"10\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/10\",\"directory_name\":\"Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/10\",\"title\":\"Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/10\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/10/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":41.394675639959395,\"upper_bound\":42.987098417195696},\"point_estimate\":42.14464494744718,\"standard_error\":0.4058794686724972},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":39.93452734209411,\"upper_bound\":43.61012722486511},\"point_estimate\":42.87137974481037,\"standard_error\":1.1943596390805837},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.7380526693466654,\"upper_bound\":5.297098641855851},\"point_estimate\":4.717451338389043,\"standard_error\":0.62271076212551},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":43.17620398090479,\"upper_bound\":44.23509319843152},\"point_estimate\":43.73707498334884,\"standard_error\":0.2688409644898111},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.9823119877376794,\"upper_bound\":5.50428583250578},\"point_estimate\":4.08105289431033,\"standard_error\":0.7684223267295737}}"
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  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/10/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[14154.0,28308.0,42462.0,56616.0,70770.0,84924.0,99078.0,113232.0,127386.0,141540.0,155694.0,169848.0,184002.0,198156.0,212310.0,226464.0,240618.0,254772.0,268926.0,283080.0,297234.0,311388.0,325542.0,339696.0,353850.0,368004.0,382158.0,396312.0,410466.0,424620.0,438774.0,452928.0,467082.0,481236.0,495390.0,509544.0,523698.0,537852.0,552006.0,566160.0,580314.0,594468.0,608622.0,622776.0,636930.0,651084.0,665238.0,679392.0,693546.0,707700.0,721854.0,736008.0,750162.0,764316.0,778470.0,792624.0,806778.0,820932.0,835086.0,849240.0,863394.0,877548.0,891702.0,905856.0,920010.0,934164.0,948318.0,962472.0,976626.0,990780.0,1004934.0,1019088.0,1033242.0,1047396.0,1061550.0,1075704.0,1089858.0,1104012.0,1118166.0,1132320.0,1146474.0,1160628.0,1174782.0,1188936.0,1203090.0,1217244.0,1231398.0,1245552.0,1259706.0,1273860.0,1288014.0,1302168.0,1316322.0,1330476.0,1344630.0,1358784.0,1372938.0,1387092.0,1401246.0,1415400.0],\"times\":[958334.0,1082042.0,1645750.0,2697500.0,2778000.0,3825708.0,4298791.0,4355834.0,5203001.0,5652333.0,5962500.0,6519084.0,7371623.0,7518957.0,8100166.0,8684834.0,9504709.0,10022125.0,10239833.0,10826001.0,11331458.0,12179083.0,12791958.0,12909418.0,13503000.0,14083000.0,14542043.0,15501542.0,16362126.0,16473625.0,17126084.0,17620081.0,18122540.0,18473085.0,18815542.0,19466500.0,19801708.0,20623708.0,21520915.0,21555083.0,22130292.0,22960124.0,23084543.0,23792917.0,24318876.0,30805958.0,31836833.0,31596583.0,32123043.0,32762914.0,32652668.0,33450420.0,33106625.0,34134167.0,33659623.0,34032459.0,34776585.0,35205248.0,35129583.0,36396959.0,35116084.0,35757793.0,36208377.0,36735585.0,37083376.0,37092708.0,36549667.0,43249999.0,43625207.0,44053125.0,45579668.0,44858210.0,46499957.0,46916209.0,46832208.0,48122624.0,48031001.0,49347915.0,49103626.0,49906333.0,49997877.0,50946501.0,52454373.0,52515791.0,52890291.0,52800292.0,53944790.0,54016832.0,54411333.0,54786586.0,60692834.0,59533252.0,62333957.0,62135874.0,62731124.0,62599998.0,62870958.0,62696376.0,61996166.0,61883540.0]}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/10/new/tukey.json",
    "content": "[20.42406981145089,29.513347918418898,53.751422870333585,62.84070097730159]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/10/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/10 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/10</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">43.176 ns</td>\n                                <td>43.737 ns</td>\n                                <td class=\"ci-bound\">44.235 ns</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.6958294</td>\n                                <td>0.7066597</td>\n                                <td class=\"ci-bound\">0.6980929</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">41.395 ns</td>\n                                <td>42.145 ns</td>\n                                <td class=\"ci-bound\">42.987 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">2.9823 ns</td>\n                                <td>4.0811 ns</td>\n                                <td class=\"ci-bound\">5.5043 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">39.935 ns</td>\n                                <td>42.871 ns</td>\n                                <td class=\"ci-bound\">43.610 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">2.7381 ns</td>\n                                <td>4.7175 ns</td>\n                                <td class=\"ci-bound\">5.2971 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−1.9964%</td>\n                            <td>+0.3856%</td>\n                            <td class=\"ci-bound\">+3.0538%</td>\n                            <td>(p = 0.76 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/100/base/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"FlexStr 0.10 (SharedStr - Optimized)\",\"value_str\":\"100\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/100\",\"directory_name\":\"Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/100\",\"title\":\"Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/100\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/100/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":64.45155644263835,\"upper_bound\":68.42769317703545},\"point_estimate\":66.16541883865825,\"standard_error\":1.0248855062019215},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":63.73522390436732,\"upper_bound\":66.62622193380922},\"point_estimate\":64.56712870283556,\"standard_error\":0.6719790866662725},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":4.7162676958901955,\"upper_bound\":7.003795453476195},\"point_estimate\":6.02998075905706,\"standard_error\":0.5552267436633247},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":66.3078696420902,\"upper_bound\":73.859340325284},\"point_estimate\":69.4737995676426,\"standard_error\":1.9762521511439337},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":4.800369854888622,\"upper_bound\":15.895120165954244},\"point_estimate\":10.29975414040586,\"standard_error\":3.3786410820852355}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/100/base/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[7705.0,15410.0,23115.0,30820.0,38525.0,46230.0,53935.0,61640.0,69345.0,77050.0,84755.0,92460.0,100165.0,107870.0,115575.0,123280.0,130985.0,138690.0,146395.0,154100.0,161805.0,169510.0,177215.0,184920.0,192625.0,200330.0,208035.0,215740.0,223445.0,231150.0,238855.0,246560.0,254265.0,261970.0,269675.0,277380.0,285085.0,292790.0,300495.0,308200.0,315905.0,323610.0,331315.0,339020.0,346725.0,354430.0,362135.0,369840.0,377545.0,385250.0,392955.0,400660.0,408365.0,416070.0,423775.0,431480.0,439185.0,446890.0,454595.0,462300.0,470005.0,477710.0,485415.0,493120.0,500825.0,508530.0,516235.0,523940.0,531645.0,539350.0,547055.0,554760.0,562465.0,570170.0,577875.0,585580.0,593285.0,600990.0,608695.0,616400.0,624105.0,631810.0,639515.0,647220.0,654925.0,662630.0,670335.0,678040.0,685745.0,693450.0,701155.0,708860.0,716565.0,724270.0,731975.0,739680.0,747385.0,755090.0,762795.0,770500.0],\"times\":[444583.0,1073332.0,1321002.0,1751626.0,2702081.0,2671582.0,3175584.0,3431084.0,4013251.0,4396209.0,4752628.0,6602332.0,7018040.0,6901208.0,7157333.0,7500124.0,7527997.0,9088752.0,9423833.0,9894418.0,10547334.0,10676791.0,11225752.0,12769332.0,12833876.0,13056208.0,12718459.0,13025208.0,13143333.0,14661541.0,15124999.0,15867999.0,17309544.0,17971127.0,17776958.0,19937206.0,19132375.0,18881209.0,18728583.0,18635501.0,18340501.0,19815252.0,20076209.0,20409043.0,24668210.0,24442752.0,24750667.0,25628166.0,25793665.0,24912626.0,24854168.0,24666709.0,23757418.0,25387128.0,25558207.0,26182959.0,31892625.0,31721958.0,31387418.0,32107002.0,31396000.0,30882543.0,30447959.0,30381500.0,29969918.0,30241335.0,30541207.0,32243416.0,38193540.0,37571001.0,37928750.0,36725041.0,37083084.0,36535043.0,36834668.0,35164584.0,35086499.0,38158877.0,39395706.0,49266750.0,45578167.0,44895375.0,46391206.0,46805332.0,45631625.0,99041959.0,45635583.0,45265831.0,47395957.0,46663416.0,66713708.0,57546668.0,52992375.0,52380375.0,50152456.0,49923833.0,49807875.0,48553415.0,49080961.0,49460043.0]}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/100/base/tukey.json",
    "content": "[36.68069344289785,48.82629334701674,81.21455975800043,93.36015966211933]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/100/change/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.00816219083669363,\"upper_bound\":0.07554309373480131},\"point_estimate\":0.03713905300523157,\"standard_error\":0.016862582111422487},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.00014108471837593814,\"upper_bound\":0.05700566934635254},\"point_estimate\":0.021650100658674898,\"standard_error\":0.013868655551019267}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/100/new/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"FlexStr 0.10 (SharedStr - Optimized)\",\"value_str\":\"100\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/100\",\"directory_name\":\"Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/100\",\"title\":\"Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/100\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/100/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":64.45155644263835,\"upper_bound\":68.42769317703545},\"point_estimate\":66.16541883865825,\"standard_error\":1.0248855062019215},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":63.73522390436732,\"upper_bound\":66.62622193380922},\"point_estimate\":64.56712870283556,\"standard_error\":0.6719790866662725},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":4.7162676958901955,\"upper_bound\":7.003795453476195},\"point_estimate\":6.02998075905706,\"standard_error\":0.5552267436633247},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":66.3078696420902,\"upper_bound\":73.859340325284},\"point_estimate\":69.4737995676426,\"standard_error\":1.9762521511439337},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":4.800369854888622,\"upper_bound\":15.895120165954244},\"point_estimate\":10.29975414040586,\"standard_error\":3.3786410820852355}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/100/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[7705.0,15410.0,23115.0,30820.0,38525.0,46230.0,53935.0,61640.0,69345.0,77050.0,84755.0,92460.0,100165.0,107870.0,115575.0,123280.0,130985.0,138690.0,146395.0,154100.0,161805.0,169510.0,177215.0,184920.0,192625.0,200330.0,208035.0,215740.0,223445.0,231150.0,238855.0,246560.0,254265.0,261970.0,269675.0,277380.0,285085.0,292790.0,300495.0,308200.0,315905.0,323610.0,331315.0,339020.0,346725.0,354430.0,362135.0,369840.0,377545.0,385250.0,392955.0,400660.0,408365.0,416070.0,423775.0,431480.0,439185.0,446890.0,454595.0,462300.0,470005.0,477710.0,485415.0,493120.0,500825.0,508530.0,516235.0,523940.0,531645.0,539350.0,547055.0,554760.0,562465.0,570170.0,577875.0,585580.0,593285.0,600990.0,608695.0,616400.0,624105.0,631810.0,639515.0,647220.0,654925.0,662630.0,670335.0,678040.0,685745.0,693450.0,701155.0,708860.0,716565.0,724270.0,731975.0,739680.0,747385.0,755090.0,762795.0,770500.0],\"times\":[444583.0,1073332.0,1321002.0,1751626.0,2702081.0,2671582.0,3175584.0,3431084.0,4013251.0,4396209.0,4752628.0,6602332.0,7018040.0,6901208.0,7157333.0,7500124.0,7527997.0,9088752.0,9423833.0,9894418.0,10547334.0,10676791.0,11225752.0,12769332.0,12833876.0,13056208.0,12718459.0,13025208.0,13143333.0,14661541.0,15124999.0,15867999.0,17309544.0,17971127.0,17776958.0,19937206.0,19132375.0,18881209.0,18728583.0,18635501.0,18340501.0,19815252.0,20076209.0,20409043.0,24668210.0,24442752.0,24750667.0,25628166.0,25793665.0,24912626.0,24854168.0,24666709.0,23757418.0,25387128.0,25558207.0,26182959.0,31892625.0,31721958.0,31387418.0,32107002.0,31396000.0,30882543.0,30447959.0,30381500.0,29969918.0,30241335.0,30541207.0,32243416.0,38193540.0,37571001.0,37928750.0,36725041.0,37083084.0,36535043.0,36834668.0,35164584.0,35086499.0,38158877.0,39395706.0,49266750.0,45578167.0,44895375.0,46391206.0,46805332.0,45631625.0,99041959.0,45635583.0,45265831.0,47395957.0,46663416.0,66713708.0,57546668.0,52992375.0,52380375.0,50152456.0,49923833.0,49807875.0,48553415.0,49080961.0,49460043.0]}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/100/new/tukey.json",
    "content": "[36.68069344289785,48.82629334701674,81.21455975800043,93.36015966211933]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/100/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/100 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/100</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">66.308 ns</td>\n                                <td>69.474 ns</td>\n                                <td class=\"ci-bound\">73.859 ns</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.1171756</td>\n                                <td>0.1226911</td>\n                                <td class=\"ci-bound\">0.1125275</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">64.452 ns</td>\n                                <td>66.165 ns</td>\n                                <td class=\"ci-bound\">68.428 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">4.8004 ns</td>\n                                <td>10.300 ns</td>\n                                <td class=\"ci-bound\">15.895 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">63.735 ns</td>\n                                <td>64.567 ns</td>\n                                <td class=\"ci-bound\">66.626 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">4.7163 ns</td>\n                                <td>6.0300 ns</td>\n                                <td class=\"ci-bound\">7.0038 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">+0.8162%</td>\n                            <td>+3.7139%</td>\n                            <td class=\"ci-bound\">+7.5543%</td>\n                            <td>(p = 0.02 &lt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                Change within noise threshold.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/20/base/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"FlexStr 0.10 (SharedStr - Optimized)\",\"value_str\":\"20\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/20\",\"directory_name\":\"Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/20\",\"title\":\"Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/20\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/20/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":41.220282428869695,\"upper_bound\":42.85875074083424},\"point_estimate\":42.04059490455789,\"standard_error\":0.41872749799047226},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":41.9175769736318,\"upper_bound\":43.40806797361007},\"point_estimate\":43.09645074276631,\"standard_error\":0.4047352588900555},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.903099169363057,\"upper_bound\":5.824615468338691},\"point_estimate\":4.021496846898636,\"standard_error\":0.7572545673423758},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":43.23628902695392,\"upper_bound\":44.78601545375596},\"point_estimate\":44.03295934456171,\"standard_error\":0.39575536098774233},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.7428474412387427,\"upper_bound\":4.658378307321447},\"point_estimate\":4.229012811395098,\"standard_error\":0.23419501019132655}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/20/base/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[12553.0,25106.0,37659.0,50212.0,62765.0,75318.0,87871.0,100424.0,112977.0,125530.0,138083.0,150636.0,163189.0,175742.0,188295.0,200848.0,213401.0,225954.0,238507.0,251060.0,263613.0,276166.0,288719.0,301272.0,313825.0,326378.0,338931.0,351484.0,364037.0,376590.0,389143.0,401696.0,414249.0,426802.0,439355.0,451908.0,464461.0,477014.0,489567.0,502120.0,514673.0,527226.0,539779.0,552332.0,564885.0,577438.0,589991.0,602544.0,615097.0,627650.0,640203.0,652756.0,665309.0,677862.0,690415.0,702968.0,715521.0,728074.0,740627.0,753180.0,765733.0,778286.0,790839.0,803392.0,815945.0,828498.0,841051.0,853604.0,866157.0,878710.0,891263.0,903816.0,916369.0,928922.0,941475.0,954028.0,966581.0,979134.0,991687.0,1004240.0,1016793.0,1029346.0,1041899.0,1054452.0,1067005.0,1079558.0,1092111.0,1104664.0,1117217.0,1129770.0,1142323.0,1154876.0,1167429.0,1179982.0,1192535.0,1205088.0,1217641.0,1230194.0,1242747.0,1255300.0],\"times\":[445752.0,1331125.0,1309959.0,1866668.0,2427169.0,2656790.0,3667208.0,4453584.0,4476541.0,4459124.0,4946207.0,5368333.0,5742752.0,6280583.0,7173166.0,7206874.0,7624168.0,7998167.0,8411874.0,8802958.0,9331541.0,9877917.0,10171208.0,11054834.0,11074875.0,15375501.0,15985957.0,16026501.0,16198958.0,16962416.0,16484584.0,16838123.0,17191917.0,17394751.0,16690751.0,17185084.0,17318957.0,17932251.0,21867499.0,21391375.0,22316792.0,23113918.0,23321418.0,23975665.0,24300293.0,24978751.0,25484623.0,25709835.0,26958041.0,27374251.0,27479084.0,31107041.0,31016544.0,30689208.0,30761002.0,31205833.0,30816958.0,30483622.0,30064085.0,30975208.0,29148083.0,29189916.0,30498665.0,32836126.0,34419001.0,36322460.0,36344415.0,37374461.0,38630958.0,39149877.0,42543458.0,42921167.0,41838584.0,43087832.0,43064249.0,42963126.0,47879916.0,46951668.0,46138251.0,46198334.0,46236544.0,46531207.0,44959750.0,44280916.0,45075751.0,45174917.0,43548707.0,43179793.0,44797624.0,48779039.0,49591917.0,50077748.0,51083625.0,50885124.0,54709416.0,57553706.0,59969751.0,59173208.0,59952959.0,58164249.0]}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/20/base/tukey.json",
    "content": "[17.244927500495415,27.666423622683663,55.457079948518995,65.87857607070724]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/20/change/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.0236681717363096,\"upper_bound\":0.03191036211647522},\"point_estimate\":0.0032281469822643682,\"standard_error\":0.014183555053782458},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.024299418232219705,\"upper_bound\":0.044991134818642475},\"point_estimate\":0.016214445544629363,\"standard_error\":0.018210180468803412}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/20/new/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"FlexStr 0.10 (SharedStr - Optimized)\",\"value_str\":\"20\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/20\",\"directory_name\":\"Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/20\",\"title\":\"Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/20\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/20/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":41.220282428869695,\"upper_bound\":42.85875074083424},\"point_estimate\":42.04059490455789,\"standard_error\":0.41872749799047226},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":41.9175769736318,\"upper_bound\":43.40806797361007},\"point_estimate\":43.09645074276631,\"standard_error\":0.4047352588900555},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.903099169363057,\"upper_bound\":5.824615468338691},\"point_estimate\":4.021496846898636,\"standard_error\":0.7572545673423758},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":43.23628902695392,\"upper_bound\":44.78601545375596},\"point_estimate\":44.03295934456171,\"standard_error\":0.39575536098774233},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.7428474412387427,\"upper_bound\":4.658378307321447},\"point_estimate\":4.229012811395098,\"standard_error\":0.23419501019132655}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/20/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[12553.0,25106.0,37659.0,50212.0,62765.0,75318.0,87871.0,100424.0,112977.0,125530.0,138083.0,150636.0,163189.0,175742.0,188295.0,200848.0,213401.0,225954.0,238507.0,251060.0,263613.0,276166.0,288719.0,301272.0,313825.0,326378.0,338931.0,351484.0,364037.0,376590.0,389143.0,401696.0,414249.0,426802.0,439355.0,451908.0,464461.0,477014.0,489567.0,502120.0,514673.0,527226.0,539779.0,552332.0,564885.0,577438.0,589991.0,602544.0,615097.0,627650.0,640203.0,652756.0,665309.0,677862.0,690415.0,702968.0,715521.0,728074.0,740627.0,753180.0,765733.0,778286.0,790839.0,803392.0,815945.0,828498.0,841051.0,853604.0,866157.0,878710.0,891263.0,903816.0,916369.0,928922.0,941475.0,954028.0,966581.0,979134.0,991687.0,1004240.0,1016793.0,1029346.0,1041899.0,1054452.0,1067005.0,1079558.0,1092111.0,1104664.0,1117217.0,1129770.0,1142323.0,1154876.0,1167429.0,1179982.0,1192535.0,1205088.0,1217641.0,1230194.0,1242747.0,1255300.0],\"times\":[445752.0,1331125.0,1309959.0,1866668.0,2427169.0,2656790.0,3667208.0,4453584.0,4476541.0,4459124.0,4946207.0,5368333.0,5742752.0,6280583.0,7173166.0,7206874.0,7624168.0,7998167.0,8411874.0,8802958.0,9331541.0,9877917.0,10171208.0,11054834.0,11074875.0,15375501.0,15985957.0,16026501.0,16198958.0,16962416.0,16484584.0,16838123.0,17191917.0,17394751.0,16690751.0,17185084.0,17318957.0,17932251.0,21867499.0,21391375.0,22316792.0,23113918.0,23321418.0,23975665.0,24300293.0,24978751.0,25484623.0,25709835.0,26958041.0,27374251.0,27479084.0,31107041.0,31016544.0,30689208.0,30761002.0,31205833.0,30816958.0,30483622.0,30064085.0,30975208.0,29148083.0,29189916.0,30498665.0,32836126.0,34419001.0,36322460.0,36344415.0,37374461.0,38630958.0,39149877.0,42543458.0,42921167.0,41838584.0,43087832.0,43064249.0,42963126.0,47879916.0,46951668.0,46138251.0,46198334.0,46236544.0,46531207.0,44959750.0,44280916.0,45075751.0,45174917.0,43548707.0,43179793.0,44797624.0,48779039.0,49591917.0,50077748.0,51083625.0,50885124.0,54709416.0,57553706.0,59969751.0,59173208.0,59952959.0,58164249.0]}"
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    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/20/new/tukey.json",
    "content": "[17.244927500495415,27.666423622683663,55.457079948518995,65.87857607070724]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/20/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/20 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/20</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">43.236 ns</td>\n                                <td>44.033 ns</td>\n                                <td class=\"ci-bound\">44.786 ns</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.6362225</td>\n                                <td>0.6511545</td>\n                                <td class=\"ci-bound\">0.6377800</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">41.220 ns</td>\n                                <td>42.041 ns</td>\n                                <td class=\"ci-bound\">42.859 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">3.7428 ns</td>\n                                <td>4.2290 ns</td>\n                                <td class=\"ci-bound\">4.6584 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">41.918 ns</td>\n                                <td>43.096 ns</td>\n                                <td class=\"ci-bound\">43.408 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">2.9031 ns</td>\n                                <td>4.0215 ns</td>\n                                <td class=\"ci-bound\">5.8246 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−2.3668%</td>\n                            <td>+0.3228%</td>\n                            <td class=\"ci-bound\">+3.1910%</td>\n                            <td>(p = 0.83 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
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  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/500/base/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"FlexStr 0.10 (SharedStr - Optimized)\",\"value_str\":\"500\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/500\",\"directory_name\":\"Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/500\",\"title\":\"Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/500\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/500/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":104.40937607569941,\"upper_bound\":106.72155968264788},\"point_estimate\":105.61245017872113,\"standard_error\":0.5907212197813526},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":105.60891662917979,\"upper_bound\":108.27535710334138},\"point_estimate\":106.86578318217994,\"standard_error\":0.711911046751635},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.226539742960324,\"upper_bound\":5.438056210247827},\"point_estimate\":4.7425243430620965,\"standard_error\":0.5950985261929387},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":108.18331884986512,\"upper_bound\":109.44584172357256},\"point_estimate\":108.84984974846509,\"standard_error\":0.3205694576370878},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":4.397420668037737,\"upper_bound\":7.293931476652896},\"point_estimate\":5.943853390975401,\"standard_error\":0.738423806763839}}"
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    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/500/base/sample.json",
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    "content": "[83.98201376062161,93.50495501185762,118.89946501515365,128.42240626638966]"
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    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/500/change/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.012274345119784084,\"upper_bound\":0.026749050911722715},\"point_estimate\":0.007498907094483087,\"standard_error\":0.009913960137097722},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.002961898541876451,\"upper_bound\":0.04455695018104344},\"point_estimate\":0.021753826433769774,\"standard_error\":0.01050386933594133}}"
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    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/500/new/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"FlexStr 0.10 (SharedStr - Optimized)\",\"value_str\":\"500\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/500\",\"directory_name\":\"Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/500\",\"title\":\"Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/500\"}"
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    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/500/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":104.40937607569941,\"upper_bound\":106.72155968264788},\"point_estimate\":105.61245017872113,\"standard_error\":0.5907212197813526},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":105.60891662917979,\"upper_bound\":108.27535710334138},\"point_estimate\":106.86578318217994,\"standard_error\":0.711911046751635},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.226539742960324,\"upper_bound\":5.438056210247827},\"point_estimate\":4.7425243430620965,\"standard_error\":0.5950985261929387},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":108.18331884986512,\"upper_bound\":109.44584172357256},\"point_estimate\":108.84984974846509,\"standard_error\":0.3205694576370878},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":4.397420668037737,\"upper_bound\":7.293931476652896},\"point_estimate\":5.943853390975401,\"standard_error\":0.738423806763839}}"
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    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/500/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[4446.0,8892.0,13338.0,17784.0,22230.0,26676.0,31122.0,35568.0,40014.0,44460.0,48906.0,53352.0,57798.0,62244.0,66690.0,71136.0,75582.0,80028.0,84474.0,88920.0,93366.0,97812.0,102258.0,106704.0,111150.0,115596.0,120042.0,124488.0,128934.0,133380.0,137826.0,142272.0,146718.0,151164.0,155610.0,160056.0,164502.0,168948.0,173394.0,177840.0,182286.0,186732.0,191178.0,195624.0,200070.0,204516.0,208962.0,213408.0,217854.0,222300.0,226746.0,231192.0,235638.0,240084.0,244530.0,248976.0,253422.0,257868.0,262314.0,266760.0,271206.0,275652.0,280098.0,284544.0,288990.0,293436.0,297882.0,302328.0,306774.0,311220.0,315666.0,320112.0,324558.0,329004.0,333450.0,337896.0,342342.0,346788.0,351234.0,355680.0,360126.0,364572.0,369018.0,373464.0,377910.0,382356.0,386802.0,391248.0,395694.0,400140.0,404586.0,409032.0,413478.0,417924.0,422370.0,426816.0,431262.0,435708.0,440154.0,444600.0],\"times\":[368208.0,752750.0,1130667.0,1731875.0,1922333.0,2601793.0,3012084.0,3701623.0,3676082.0,4659751.0,5330834.0,5471042.0,6177292.0,6557043.0,7083416.0,7701044.0,8595249.0,8249667.0,9188957.0,9718749.0,9659292.0,10033999.0,10039666.0,10771251.0,11303207.0,12322915.0,12528208.0,12804501.0,13207125.0,13632584.0,14231001.0,14294457.0,15038792.0,15480332.0,16561668.0,16171293.0,16641624.0,16967585.0,17573958.0,18132415.0,18851625.0,19195294.0,19790041.0,20342584.0,20682832.0,22502585.0,23258376.0,23782541.0,23043583.0,23506416.0,23810001.0,24352877.0,26297042.0,24771123.0,26129083.0,26571208.0,26887708.0,27546584.0,28132041.0,29023125.0,29784167.0,30198998.0,29601959.0,30814833.0,31343668.0,31891792.0,32224875.0,32865543.0,33506418.0,34021668.0,34085334.0,33764124.0,35172582.0,35569792.0,36604209.0,38305916.0,37280624.0,37672918.0,38823086.0,39355459.0,38615249.0,40133501.0,40459501.0,40759999.0,40633748.0,42188042.0,42648585.0,43642501.0,43544250.0,43090041.0,44802708.0,46465582.0,46401623.0,45899332.0,46674040.0,47955126.0,47833540.0,47176208.0,47806250.0,50377540.0]}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/500/new/tukey.json",
    "content": "[83.98201376062161,93.50495501185762,118.89946501515365,128.42240626638966]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/500/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/500 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/500</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">108.18 ns</td>\n                                <td>108.85 ns</td>\n                                <td class=\"ci-bound\">109.45 ns</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.9226203</td>\n                                <td>0.9263360</td>\n                                <td class=\"ci-bound\">0.9233628</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">104.41 ns</td>\n                                <td>105.61 ns</td>\n                                <td class=\"ci-bound\">106.72 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">4.3974 ns</td>\n                                <td>5.9439 ns</td>\n                                <td class=\"ci-bound\">7.2939 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">105.61 ns</td>\n                                <td>106.87 ns</td>\n                                <td class=\"ci-bound\">108.28 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">3.2265 ns</td>\n                                <td>4.7425 ns</td>\n                                <td class=\"ci-bound\">5.4381 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−1.2274%</td>\n                            <td>+0.7499%</td>\n                            <td class=\"ci-bound\">+2.6749%</td>\n                            <td>(p = 0.47 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized) Summary - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)</h2>\n        <h3>Violin Plot</h3>\n        <a href=\"violin.svg\">\n            <img src=\"violin.svg\" alt=\"Violin Plot\" />\n        </a>\n        <p>This chart shows the relationship between function/parameter and iteration time. The thickness of the shaded\n            region indicates the probability that a measurement of the given function/parameter would take a particular\n            length of time.</p>\n        <h3>Line Chart</h3>\n        <img src=\"lines.svg\" alt=\"Line Chart\" />\n        <p>This chart shows the mean measured time for each function as the input (or the size of the input) increases.</p>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/0/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/0/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/0/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/10/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/10/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/10/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/20/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/20/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/20/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/100/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/100/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/100/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/500/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/500/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/500/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (LocalStr)/0/base/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"FlexStr 0.9 (LocalStr)\",\"value_str\":\"0\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/FlexStr 0.9 (LocalStr)/0\",\"directory_name\":\"Import as owned and destroy/FlexStr 0.9 (LocalStr)/0\",\"title\":\"Import as owned and destroy/FlexStr 0.9 (LocalStr)/0\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (LocalStr)/0/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.230036525399176,\"upper_bound\":2.293190871196964},\"point_estimate\":2.2605261915116923,\"standard_error\":0.016106382251181297},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.238277739029143,\"upper_bound\":2.3305609369933498},\"point_estimate\":2.308946233205279,\"standard_error\":0.030719055376754838},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.08514269615600371,\"upper_bound\":0.21184993994669743},\"point_estimate\":0.1231680229531777,\"standard_error\":0.04046885438291038},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.277291249494176,\"upper_bound\":2.319367356180497},\"point_estimate\":2.3003993960979936,\"standard_error\":0.01071075933582796},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.12340125717054208,\"upper_bound\":0.20685326034772922},\"point_estimate\":0.16179268067822802,\"standard_error\":0.022559761879553455}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (LocalStr)/0/base/sample.json",
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    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (LocalStr)/0/base/tukey.json",
    "content": "[1.381061753974489,1.7468397360615577,2.7222476882937414,3.08802567038081]"
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    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (LocalStr)/0/change/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.04165855680995015,\"upper_bound\":0.012173625810111265},\"point_estimate\":-0.014132276981773773,\"standard_error\":0.01375777798507212},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.038474959403052345,\"upper_bound\":0.057890086422606624},\"point_estimate\":0.0018226507912151302,\"standard_error\":0.025145842684989338}}"
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  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (LocalStr)/0/new/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"FlexStr 0.9 (LocalStr)\",\"value_str\":\"0\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/FlexStr 0.9 (LocalStr)/0\",\"directory_name\":\"Import as owned and destroy/FlexStr 0.9 (LocalStr)/0\",\"title\":\"Import as owned and destroy/FlexStr 0.9 (LocalStr)/0\"}"
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    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (LocalStr)/0/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.230036525399176,\"upper_bound\":2.293190871196964},\"point_estimate\":2.2605261915116923,\"standard_error\":0.016106382251181297},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.238277739029143,\"upper_bound\":2.3305609369933498},\"point_estimate\":2.308946233205279,\"standard_error\":0.030719055376754838},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.08514269615600371,\"upper_bound\":0.21184993994669743},\"point_estimate\":0.1231680229531777,\"standard_error\":0.04046885438291038},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.277291249494176,\"upper_bound\":2.319367356180497},\"point_estimate\":2.3003993960979936,\"standard_error\":0.01071075933582796},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.12340125717054208,\"upper_bound\":0.20685326034772922},\"point_estimate\":0.16179268067822802,\"standard_error\":0.022559761879553455}}"
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  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (LocalStr)/0/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[139073.0,278146.0,417219.0,556292.0,695365.0,834438.0,973511.0,1112584.0,1251657.0,1390730.0,1529803.0,1668876.0,1807949.0,1947022.0,2086095.0,2225168.0,2364241.0,2503314.0,2642387.0,2781460.0,2920533.0,3059606.0,3198679.0,3337752.0,3476825.0,3615898.0,3754971.0,3894044.0,4033117.0,4172190.0,4311263.0,4450336.0,4589409.0,4728482.0,4867555.0,5006628.0,5145701.0,5284774.0,5423847.0,5562920.0,5701993.0,5841066.0,5980139.0,6119212.0,6258285.0,6397358.0,6536431.0,6675504.0,6814577.0,6953650.0,7092723.0,7231796.0,7370869.0,7509942.0,7649015.0,7788088.0,7927161.0,8066234.0,8205307.0,8344380.0,8483453.0,8622526.0,8761599.0,8900672.0,9039745.0,9178818.0,9317891.0,9456964.0,9596037.0,9735110.0,9874183.0,10013256.0,10152329.0,10291402.0,10430475.0,10569548.0,10708621.0,10847694.0,10986767.0,11125840.0,11264913.0,11403986.0,11543059.0,11682132.0,11821205.0,11960278.0,12099351.0,12238424.0,12377497.0,12516570.0,12655643.0,12794716.0,12933789.0,13072862.0,13211935.0,13351008.0,13490081.0,13629154.0,13768227.0,13907300.0],\"times\":[294041.0,572374.0,855458.0,1167669.0,2156876.0,2325249.0,2166417.0,2591083.0,3015584.0,3446542.0,3460457.0,3958001.0,4264750.0,4403873.0,4749209.0,5316541.0,5327208.0,5838582.0,6013126.0,6272166.0,6652750.0,6848248.0,7381583.0,7739749.0,7835373.0,7516916.0,7807667.0,8102625.0,8407627.0,8697250.0,9128832.0,9466916.0,9651001.0,10026457.0,10317003.0,10655041.0,10943625.0,11274584.0,11464416.0,11787084.0,12088750.0,12510044.0,12771125.0,12907584.0,13197418.0,13423585.0,13866792.0,13971627.0,14249835.0,14621002.0,14732708.0,14991833.0,15308875.0,15692581.0,16015166.0,16297170.0,16469249.0,16727539.0,17102792.0,17385083.0,20507166.0,20802126.0,21217002.0,21239001.0,21902793.0,21729084.0,22276249.0,23178458.0,22680915.0,22994583.0,23485000.0,23648418.0,24279458.0,24123999.0,24814542.0,25048459.0,25192125.0,25573793.0,25887582.0,27350252.0,26281833.0,26695168.0,26794209.0,27205125.0,27604292.0,28191876.0,28462002.0,28491624.0,29014584.0,28961498.0,29581334.0,30007999.0,30355541.0,30597372.0,30551126.0,30877375.0,31630043.0,31599333.0,31807291.0,32536085.0]}"
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  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (LocalStr)/0/new/tukey.json",
    "content": "[1.381061753974489,1.7468397360615577,2.7222476882937414,3.08802567038081]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (LocalStr)/0/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/FlexStr 0.9 (LocalStr)/0 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/FlexStr 0.9 (LocalStr)/0</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">2.2773 ns</td>\n                                <td>2.3004 ns</td>\n                                <td class=\"ci-bound\">2.3194 ns</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.7763045</td>\n                                <td>0.7840777</td>\n                                <td class=\"ci-bound\">0.7788234</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">2.2300 ns</td>\n                                <td>2.2605 ns</td>\n                                <td class=\"ci-bound\">2.2932 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">123.40 ps</td>\n                                <td>161.79 ps</td>\n                                <td class=\"ci-bound\">206.85 ps</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">2.2383 ns</td>\n                                <td>2.3089 ns</td>\n                                <td class=\"ci-bound\">2.3306 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">85.143 ps</td>\n                                <td>123.17 ps</td>\n                                <td class=\"ci-bound\">211.85 ps</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−4.1659%</td>\n                            <td>−1.4132%</td>\n                            <td class=\"ci-bound\">+1.2174%</td>\n                            <td>(p = 0.34 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (LocalStr)/10/base/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"FlexStr 0.9 (LocalStr)\",\"value_str\":\"10\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/FlexStr 0.9 (LocalStr)/10\",\"directory_name\":\"Import as owned and destroy/FlexStr 0.9 (LocalStr)/10\",\"title\":\"Import as owned and destroy/FlexStr 0.9 (LocalStr)/10\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (LocalStr)/10/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":32.14220124209393,\"upper_bound\":33.59720540090409},\"point_estimate\":32.852827556594704,\"standard_error\":0.37047245489733766},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":31.084090732363315,\"upper_bound\":34.85198455873963},\"point_estimate\":33.31921537558806,\"standard_error\":0.9495216962896752},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.539663066425479,\"upper_bound\":5.1398525049779495},\"point_estimate\":4.166250111542805,\"standard_error\":0.6648030082701187},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":33.71115607392955,\"upper_bound\":34.85486983493258},\"point_estimate\":34.29800631347949,\"standard_error\":0.29268730791400066},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.111469356404919,\"upper_bound\":4.491345447838969},\"point_estimate\":3.7274490718265403,\"standard_error\":0.3734801224081636}}"
  },
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    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (LocalStr)/10/new/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"FlexStr 0.9 (LocalStr)\",\"value_str\":\"10\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/FlexStr 0.9 (LocalStr)/10\",\"directory_name\":\"Import as owned and destroy/FlexStr 0.9 (LocalStr)/10\",\"title\":\"Import as owned and destroy/FlexStr 0.9 (LocalStr)/10\"}"
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    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (LocalStr)/10/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":32.14220124209393,\"upper_bound\":33.59720540090409},\"point_estimate\":32.852827556594704,\"standard_error\":0.37047245489733766},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":31.084090732363315,\"upper_bound\":34.85198455873963},\"point_estimate\":33.31921537558806,\"standard_error\":0.9495216962896752},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.539663066425479,\"upper_bound\":5.1398525049779495},\"point_estimate\":4.166250111542805,\"standard_error\":0.6648030082701187},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":33.71115607392955,\"upper_bound\":34.85486983493258},\"point_estimate\":34.29800631347949,\"standard_error\":0.29268730791400066},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.111469356404919,\"upper_bound\":4.491345447838969},\"point_estimate\":3.7274490718265403,\"standard_error\":0.3734801224081636}}"
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    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (LocalStr)/10/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[16817.0,33634.0,50451.0,67268.0,84085.0,100902.0,117719.0,134536.0,151353.0,168170.0,184987.0,201804.0,218621.0,235438.0,252255.0,269072.0,285889.0,302706.0,319523.0,336340.0,353157.0,369974.0,386791.0,403608.0,420425.0,437242.0,454059.0,470876.0,487693.0,504510.0,521327.0,538144.0,554961.0,571778.0,588595.0,605412.0,622229.0,639046.0,655863.0,672680.0,689497.0,706314.0,723131.0,739948.0,756765.0,773582.0,790399.0,807216.0,824033.0,840850.0,857667.0,874484.0,891301.0,908118.0,924935.0,941752.0,958569.0,975386.0,992203.0,1009020.0,1025837.0,1042654.0,1059471.0,1076288.0,1093105.0,1109922.0,1126739.0,1143556.0,1160373.0,1177190.0,1194007.0,1210824.0,1227641.0,1244458.0,1261275.0,1278092.0,1294909.0,1311726.0,1328543.0,1345360.0,1362177.0,1378994.0,1395811.0,1412628.0,1429445.0,1446262.0,1463079.0,1479896.0,1496713.0,1513530.0,1530347.0,1547164.0,1563981.0,1580798.0,1597615.0,1614432.0,1631249.0,1648066.0,1664883.0,1681700.0],\"times\":[834251.0,955376.0,1435543.0,2431289.0,2461293.0,3417416.0,3573626.0,3831668.0,4783543.0,4735833.0,5644874.0,5744374.0,6197875.0,6690373.0,7199375.0,7707459.0,8634249.0,8601458.0,9156833.0,10370790.0,9959210.0,10948790.0,11179916.0,11637293.0,11890625.0,12605666.0,12992292.0,13596417.0,13870583.0,14640707.0,15042998.0,15642041.0,15855292.0,16385418.0,17081790.0,17319043.0,17884751.0,18239459.0,26052916.0,26254666.0,25020249.0,25791250.0,25340582.0,26080373.0,26528873.0,26420583.0,26537292.0,26881170.0,27083792.0,27491331.0,27571207.0,27182540.0,27293334.0,27985960.0,27849293.0,33716667.0,28768249.0,35195043.0,35671581.0,36225250.0,37024375.0,37824750.0,38284166.0,38740167.0,39328209.0,39513333.0,40135458.0,40284750.0,40788208.0,41495293.0,41824043.0,42214709.0,42895918.0,43371831.0,43595208.0,50788543.0,48795664.0,50301041.0,49309331.0,48802418.0,48664331.0,50002415.0,50306540.0,49790294.0,48442626.0,49526500.0,48775168.0,49740208.0,47583917.0,49334084.0,48082790.0,48834666.0,48131789.0,47711917.0,54849500.0,57000333.0,57761043.0,58630749.0,59784082.0,60980542.0]}"
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    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (LocalStr)/10/new/tukey.json",
    "content": "[9.022168172938045,19.00649055275185,45.63135023225532,55.61567261206912]"
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  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (LocalStr)/10/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/FlexStr 0.9 (LocalStr)/10 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/FlexStr 0.9 (LocalStr)/10</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">33.711 ns</td>\n                                <td>34.298 ns</td>\n                                <td class=\"ci-bound\">34.855 ns</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.6232825</td>\n                                <td>0.6358422</td>\n                                <td class=\"ci-bound\">0.6245110</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">32.142 ns</td>\n                                <td>32.853 ns</td>\n                                <td class=\"ci-bound\">33.597 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">3.1115 ns</td>\n                                <td>3.7274 ns</td>\n                                <td class=\"ci-bound\">4.4913 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">31.084 ns</td>\n                                <td>33.319 ns</td>\n                                <td class=\"ci-bound\">34.852 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">2.5397 ns</td>\n                                <td>4.1663 ns</td>\n                                <td class=\"ci-bound\">5.1399 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−3.0537%</td>\n                            <td>+0.1793%</td>\n                            <td class=\"ci-bound\">+3.6517%</td>\n                            <td>(p = 0.92 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (LocalStr)/100/base/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"FlexStr 0.9 (LocalStr)\",\"value_str\":\"100\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/FlexStr 0.9 (LocalStr)/100\",\"directory_name\":\"Import as owned and destroy/FlexStr 0.9 (LocalStr)/100\",\"title\":\"Import as owned and destroy/FlexStr 0.9 (LocalStr)/100\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (LocalStr)/100/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":62.64339702854908,\"upper_bound\":64.45892981413277},\"point_estimate\":63.543663375778195,\"standard_error\":0.46354346385898665},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":61.9361701807229,\"upper_bound\":64.43044640522876},\"point_estimate\":63.251548877522026,\"standard_error\":0.6814851399963953},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.6104246950990793,\"upper_bound\":5.745273807615821},\"point_estimate\":4.987099606188937,\"standard_error\":0.5652831622774553},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":63.6960449163092,\"upper_bound\":65.75880133396674},\"point_estimate\":64.71918721442293,\"standard_error\":0.5265886206945098},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.955194846055947,\"upper_bound\":5.336133157347368},\"point_estimate\":4.670962949307606,\"standard_error\":0.3521537278853598}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (LocalStr)/100/base/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[8500.0,17000.0,25500.0,34000.0,42500.0,51000.0,59500.0,68000.0,76500.0,85000.0,93500.0,102000.0,110500.0,119000.0,127500.0,136000.0,144500.0,153000.0,161500.0,170000.0,178500.0,187000.0,195500.0,204000.0,212500.0,221000.0,229500.0,238000.0,246500.0,255000.0,263500.0,272000.0,280500.0,289000.0,297500.0,306000.0,314500.0,323000.0,331500.0,340000.0,348500.0,357000.0,365500.0,374000.0,382500.0,391000.0,399500.0,408000.0,416500.0,425000.0,433500.0,442000.0,450500.0,459000.0,467500.0,476000.0,484500.0,493000.0,501500.0,510000.0,518500.0,527000.0,535500.0,544000.0,552500.0,561000.0,569500.0,578000.0,586500.0,595000.0,603500.0,612000.0,620500.0,629000.0,637500.0,646000.0,654500.0,663000.0,671500.0,680000.0,688500.0,697000.0,705500.0,714000.0,722500.0,731000.0,739500.0,748000.0,756500.0,765000.0,773500.0,782000.0,790500.0,799000.0,807500.0,816000.0,824500.0,833000.0,841500.0,850000.0],\"times\":[471750.0,1294082.0,1400624.0,1865794.0,3320459.0,3048041.0,3306584.0,4210291.0,4181418.0,4599126.0,6455042.0,6590668.0,7324792.0,7074709.0,7467333.0,8647000.0,9730999.0,9684751.0,10377792.0,10564625.0,11214625.0,12540042.0,12391293.0,12661209.0,12726333.0,13681042.0,12831124.0,15079710.0,14981874.0,17280209.0,17059543.0,17520208.0,18755750.0,18543416.0,18403708.0,18539582.0,18014124.0,19293040.0,19792289.0,20257419.0,24369710.0,24102958.0,24130878.0,25158458.0,24651499.0,24102666.0,24158251.0,24004958.0,24701460.0,25601043.0,25961000.0,30548168.0,30633707.0,31187502.0,31003584.0,30605124.0,29914208.0,29594706.0,28449499.0,30011417.0,30496416.0,31328624.0,37467377.0,37236249.0,37486419.0,36862958.0,35827707.0,34843459.0,34795709.0,34517374.0,37140960.0,37436332.0,44452542.0,43567624.0,43719001.0,42729250.0,42374459.0,41115210.0,42125083.0,41563334.0,42136251.0,44954625.0,43710167.0,50885459.0,49908959.0,49574168.0,49766166.0,48543959.0,48730791.0,48807458.0,47814833.0,49425584.0,48974835.0,50410957.0,56584959.0,55344625.0,54584293.0,56234125.0,55138624.0,63410041.0]}"
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    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (LocalStr)/100/base/tukey.json",
    "content": "[39.408762823160615,49.79726570164116,77.49994004425594,87.88844292273649]"
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    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (LocalStr)/100/change/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.00989039388635373,\"upper_bound\":0.027614055607988613},\"point_estimate\":0.008910267083878765,\"standard_error\":0.009558148720654915},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.02144285202591345,\"upper_bound\":0.03716604106951937},\"point_estimate\":0.008480638607509139,\"standard_error\":0.014617192409225412}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (LocalStr)/100/new/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"FlexStr 0.9 (LocalStr)\",\"value_str\":\"100\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/FlexStr 0.9 (LocalStr)/100\",\"directory_name\":\"Import as owned and destroy/FlexStr 0.9 (LocalStr)/100\",\"title\":\"Import as owned and destroy/FlexStr 0.9 (LocalStr)/100\"}"
  },
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    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (LocalStr)/100/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":62.64339702854908,\"upper_bound\":64.45892981413277},\"point_estimate\":63.543663375778195,\"standard_error\":0.46354346385898665},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":61.9361701807229,\"upper_bound\":64.43044640522876},\"point_estimate\":63.251548877522026,\"standard_error\":0.6814851399963953},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.6104246950990793,\"upper_bound\":5.745273807615821},\"point_estimate\":4.987099606188937,\"standard_error\":0.5652831622774553},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":63.6960449163092,\"upper_bound\":65.75880133396674},\"point_estimate\":64.71918721442293,\"standard_error\":0.5265886206945098},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.955194846055947,\"upper_bound\":5.336133157347368},\"point_estimate\":4.670962949307606,\"standard_error\":0.3521537278853598}}"
  },
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    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (LocalStr)/100/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[8500.0,17000.0,25500.0,34000.0,42500.0,51000.0,59500.0,68000.0,76500.0,85000.0,93500.0,102000.0,110500.0,119000.0,127500.0,136000.0,144500.0,153000.0,161500.0,170000.0,178500.0,187000.0,195500.0,204000.0,212500.0,221000.0,229500.0,238000.0,246500.0,255000.0,263500.0,272000.0,280500.0,289000.0,297500.0,306000.0,314500.0,323000.0,331500.0,340000.0,348500.0,357000.0,365500.0,374000.0,382500.0,391000.0,399500.0,408000.0,416500.0,425000.0,433500.0,442000.0,450500.0,459000.0,467500.0,476000.0,484500.0,493000.0,501500.0,510000.0,518500.0,527000.0,535500.0,544000.0,552500.0,561000.0,569500.0,578000.0,586500.0,595000.0,603500.0,612000.0,620500.0,629000.0,637500.0,646000.0,654500.0,663000.0,671500.0,680000.0,688500.0,697000.0,705500.0,714000.0,722500.0,731000.0,739500.0,748000.0,756500.0,765000.0,773500.0,782000.0,790500.0,799000.0,807500.0,816000.0,824500.0,833000.0,841500.0,850000.0],\"times\":[471750.0,1294082.0,1400624.0,1865794.0,3320459.0,3048041.0,3306584.0,4210291.0,4181418.0,4599126.0,6455042.0,6590668.0,7324792.0,7074709.0,7467333.0,8647000.0,9730999.0,9684751.0,10377792.0,10564625.0,11214625.0,12540042.0,12391293.0,12661209.0,12726333.0,13681042.0,12831124.0,15079710.0,14981874.0,17280209.0,17059543.0,17520208.0,18755750.0,18543416.0,18403708.0,18539582.0,18014124.0,19293040.0,19792289.0,20257419.0,24369710.0,24102958.0,24130878.0,25158458.0,24651499.0,24102666.0,24158251.0,24004958.0,24701460.0,25601043.0,25961000.0,30548168.0,30633707.0,31187502.0,31003584.0,30605124.0,29914208.0,29594706.0,28449499.0,30011417.0,30496416.0,31328624.0,37467377.0,37236249.0,37486419.0,36862958.0,35827707.0,34843459.0,34795709.0,34517374.0,37140960.0,37436332.0,44452542.0,43567624.0,43719001.0,42729250.0,42374459.0,41115210.0,42125083.0,41563334.0,42136251.0,44954625.0,43710167.0,50885459.0,49908959.0,49574168.0,49766166.0,48543959.0,48730791.0,48807458.0,47814833.0,49425584.0,48974835.0,50410957.0,56584959.0,55344625.0,54584293.0,56234125.0,55138624.0,63410041.0]}"
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  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (LocalStr)/100/new/tukey.json",
    "content": "[39.408762823160615,49.79726570164116,77.49994004425594,87.88844292273649]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (LocalStr)/100/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/FlexStr 0.9 (LocalStr)/100 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/FlexStr 0.9 (LocalStr)/100</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">63.696 ns</td>\n                                <td>64.719 ns</td>\n                                <td class=\"ci-bound\">65.759 ns</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.7581993</td>\n                                <td>0.7698348</td>\n                                <td class=\"ci-bound\">0.7578275</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">62.643 ns</td>\n                                <td>63.544 ns</td>\n                                <td class=\"ci-bound\">64.459 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">3.9552 ns</td>\n                                <td>4.6710 ns</td>\n                                <td class=\"ci-bound\">5.3361 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">61.936 ns</td>\n                                <td>63.252 ns</td>\n                                <td class=\"ci-bound\">64.430 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">3.6104 ns</td>\n                                <td>4.9871 ns</td>\n                                <td class=\"ci-bound\">5.7453 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−0.9890%</td>\n                            <td>+0.8910%</td>\n                            <td class=\"ci-bound\">+2.7614%</td>\n                            <td>(p = 0.36 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
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  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (LocalStr)/20/base/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"FlexStr 0.9 (LocalStr)\",\"value_str\":\"20\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/FlexStr 0.9 (LocalStr)/20\",\"directory_name\":\"Import as owned and destroy/FlexStr 0.9 (LocalStr)/20\",\"title\":\"Import as owned and destroy/FlexStr 0.9 (LocalStr)/20\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (LocalStr)/20/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":35.4081060766326,\"upper_bound\":36.98664447650408},\"point_estimate\":36.18151112069723,\"standard_error\":0.40213423690297795},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":35.470943157111975,\"upper_bound\":37.33692924556884},\"point_estimate\":36.57116573993636,\"standard_error\":0.47034314409397115},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.8564831616246367,\"upper_bound\":5.142047934540606},\"point_estimate\":4.240442286751758,\"standard_error\":0.5963002428847185},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":36.505036021877814,\"upper_bound\":38.097610052915144},\"point_estimate\":37.30005550927275,\"standard_error\":0.40544537671302777},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.2485838126122575,\"upper_bound\":4.990781065659196},\"point_estimate\":4.033172863881475,\"standard_error\":0.4695121725587691}}"
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    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (LocalStr)/20/base/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[14503.0,29006.0,43509.0,58012.0,72515.0,87018.0,101521.0,116024.0,130527.0,145030.0,159533.0,174036.0,188539.0,203042.0,217545.0,232048.0,246551.0,261054.0,275557.0,290060.0,304563.0,319066.0,333569.0,348072.0,362575.0,377078.0,391581.0,406084.0,420587.0,435090.0,449593.0,464096.0,478599.0,493102.0,507605.0,522108.0,536611.0,551114.0,565617.0,580120.0,594623.0,609126.0,623629.0,638132.0,652635.0,667138.0,681641.0,696144.0,710647.0,725150.0,739653.0,754156.0,768659.0,783162.0,797665.0,812168.0,826671.0,841174.0,855677.0,870180.0,884683.0,899186.0,913689.0,928192.0,942695.0,957198.0,971701.0,986204.0,1000707.0,1015210.0,1029713.0,1044216.0,1058719.0,1073222.0,1087725.0,1102228.0,1116731.0,1131234.0,1145737.0,1160240.0,1174743.0,1189246.0,1203749.0,1218252.0,1232755.0,1247258.0,1261761.0,1276264.0,1290767.0,1305270.0,1319773.0,1334276.0,1348779.0,1363282.0,1377785.0,1392288.0,1406791.0,1421294.0,1435797.0,1450300.0],\"times\":[807040.0,872540.0,1334793.0,2118251.0,2281210.0,3327501.0,3100877.0,4018332.0,3935668.0,4417877.0,4821831.0,5286207.0,6350251.0,6260334.0,6641707.0,6929667.0,7919753.0,7927333.0,8937292.0,8736208.0,9205333.0,9734749.0,13143167.0,14124081.0,13753584.0,14038125.0,13673084.0,14095001.0,14252833.0,14471125.0,14679541.0,15170458.0,17869417.0,18481710.0,19279501.0,18923998.0,20075458.0,20513043.0,20769085.0,21320916.0,21892456.0,22413793.0,22816374.0,26122999.0,26558083.0,25900542.0,26322249.0,25286624.0,25367333.0,25590374.0,25856625.0,24915792.0,25260166.0,24896499.0,24868497.0,30631249.0,30989376.0,32094835.0,32977251.0,32703834.0,35831039.0,36174542.0,37709750.0,36689627.0,36775501.0,37419291.0,39988958.0,39355542.0,39670040.0,38913123.0,38368748.0,37463666.0,37018250.0,37318166.0,36158249.0,35733167.0,36137125.0,41353251.0,40640372.0,41394665.0,44736750.0,45133457.0,49321126.0,52001209.0,52029333.0,52143878.0,51519207.0,50795335.0,54223499.0,53193875.0,52462375.0,51338333.0,51297208.0,49945750.0,49712583.0,48256626.0,47673209.0,46836002.0,47963085.0,52096250.0]}"
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    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (LocalStr)/20/base/tukey.json",
    "content": "[16.391436823950308,24.704095353096307,46.871184764152304,55.1838432932983]"
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  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (LocalStr)/20/change/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.066770846348462,\"upper_bound\":0.012967844516665798},\"point_estimate\":-0.02447678803468445,\"standard_error\":0.020366615284190943},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.052455570667133314,\"upper_bound\":0.02128010736549757},\"point_estimate\":-0.010481857489007984,\"standard_error\":0.018230981571370743}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (LocalStr)/20/new/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"FlexStr 0.9 (LocalStr)\",\"value_str\":\"20\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/FlexStr 0.9 (LocalStr)/20\",\"directory_name\":\"Import as owned and destroy/FlexStr 0.9 (LocalStr)/20\",\"title\":\"Import as owned and destroy/FlexStr 0.9 (LocalStr)/20\"}"
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    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (LocalStr)/20/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":35.4081060766326,\"upper_bound\":36.98664447650408},\"point_estimate\":36.18151112069723,\"standard_error\":0.40213423690297795},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":35.470943157111975,\"upper_bound\":37.33692924556884},\"point_estimate\":36.57116573993636,\"standard_error\":0.47034314409397115},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.8564831616246367,\"upper_bound\":5.142047934540606},\"point_estimate\":4.240442286751758,\"standard_error\":0.5963002428847185},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":36.505036021877814,\"upper_bound\":38.097610052915144},\"point_estimate\":37.30005550927275,\"standard_error\":0.40544537671302777},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.2485838126122575,\"upper_bound\":4.990781065659196},\"point_estimate\":4.033172863881475,\"standard_error\":0.4695121725587691}}"
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    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (LocalStr)/20/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[14503.0,29006.0,43509.0,58012.0,72515.0,87018.0,101521.0,116024.0,130527.0,145030.0,159533.0,174036.0,188539.0,203042.0,217545.0,232048.0,246551.0,261054.0,275557.0,290060.0,304563.0,319066.0,333569.0,348072.0,362575.0,377078.0,391581.0,406084.0,420587.0,435090.0,449593.0,464096.0,478599.0,493102.0,507605.0,522108.0,536611.0,551114.0,565617.0,580120.0,594623.0,609126.0,623629.0,638132.0,652635.0,667138.0,681641.0,696144.0,710647.0,725150.0,739653.0,754156.0,768659.0,783162.0,797665.0,812168.0,826671.0,841174.0,855677.0,870180.0,884683.0,899186.0,913689.0,928192.0,942695.0,957198.0,971701.0,986204.0,1000707.0,1015210.0,1029713.0,1044216.0,1058719.0,1073222.0,1087725.0,1102228.0,1116731.0,1131234.0,1145737.0,1160240.0,1174743.0,1189246.0,1203749.0,1218252.0,1232755.0,1247258.0,1261761.0,1276264.0,1290767.0,1305270.0,1319773.0,1334276.0,1348779.0,1363282.0,1377785.0,1392288.0,1406791.0,1421294.0,1435797.0,1450300.0],\"times\":[807040.0,872540.0,1334793.0,2118251.0,2281210.0,3327501.0,3100877.0,4018332.0,3935668.0,4417877.0,4821831.0,5286207.0,6350251.0,6260334.0,6641707.0,6929667.0,7919753.0,7927333.0,8937292.0,8736208.0,9205333.0,9734749.0,13143167.0,14124081.0,13753584.0,14038125.0,13673084.0,14095001.0,14252833.0,14471125.0,14679541.0,15170458.0,17869417.0,18481710.0,19279501.0,18923998.0,20075458.0,20513043.0,20769085.0,21320916.0,21892456.0,22413793.0,22816374.0,26122999.0,26558083.0,25900542.0,26322249.0,25286624.0,25367333.0,25590374.0,25856625.0,24915792.0,25260166.0,24896499.0,24868497.0,30631249.0,30989376.0,32094835.0,32977251.0,32703834.0,35831039.0,36174542.0,37709750.0,36689627.0,36775501.0,37419291.0,39988958.0,39355542.0,39670040.0,38913123.0,38368748.0,37463666.0,37018250.0,37318166.0,36158249.0,35733167.0,36137125.0,41353251.0,40640372.0,41394665.0,44736750.0,45133457.0,49321126.0,52001209.0,52029333.0,52143878.0,51519207.0,50795335.0,54223499.0,53193875.0,52462375.0,51338333.0,51297208.0,49945750.0,49712583.0,48256626.0,47673209.0,46836002.0,47963085.0,52096250.0]}"
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    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (LocalStr)/20/new/tukey.json",
    "content": "[16.391436823950308,24.704095353096307,46.871184764152304,55.1838432932983]"
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  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (LocalStr)/20/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/FlexStr 0.9 (LocalStr)/20 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/FlexStr 0.9 (LocalStr)/20</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">36.505 ns</td>\n                                <td>37.300 ns</td>\n                                <td class=\"ci-bound\">38.098 ns</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.4724159</td>\n                                <td>0.4890466</td>\n                                <td class=\"ci-bound\">0.4723133</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">35.408 ns</td>\n                                <td>36.182 ns</td>\n                                <td class=\"ci-bound\">36.987 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">3.2486 ns</td>\n                                <td>4.0332 ns</td>\n                                <td class=\"ci-bound\">4.9908 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">35.471 ns</td>\n                                <td>36.571 ns</td>\n                                <td class=\"ci-bound\">37.337 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">2.8565 ns</td>\n                                <td>4.2404 ns</td>\n                                <td class=\"ci-bound\">5.1420 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−6.6771%</td>\n                            <td>−2.4477%</td>\n                            <td class=\"ci-bound\">+1.2968%</td>\n                            <td>(p = 0.26 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (LocalStr)/500/base/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"FlexStr 0.9 (LocalStr)\",\"value_str\":\"500\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/FlexStr 0.9 (LocalStr)/500\",\"directory_name\":\"Import as owned and destroy/FlexStr 0.9 (LocalStr)/500\",\"title\":\"Import as owned and destroy/FlexStr 0.9 (LocalStr)/500\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (LocalStr)/500/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":102.80918493611402,\"upper_bound\":105.36762135071118},\"point_estimate\":104.12167326845379,\"standard_error\":0.6509209912721251},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":103.70318207318783,\"upper_bound\":105.2850448641203},\"point_estimate\":104.389088293919,\"standard_error\":0.4544209074432965},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.073745801789074,\"upper_bound\":6.5663983724513235},\"point_estimate\":4.989618806613474,\"standard_error\":0.9254669446427741},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":106.51979406156018,\"upper_bound\":109.10940003214462},\"point_estimate\":107.85426229467919,\"standard_error\":0.6604822241197827},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":4.814782189249138,\"upper_bound\":8.10453429615963},\"point_estimate\":6.528843560350775,\"standard_error\":0.8422558771980987}}"
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    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (LocalStr)/500/base/sample.json",
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    "content": "[81.48752966244167,91.3021881381957,117.47461074020643,127.28926921596045]"
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    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (LocalStr)/500/change/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.02960864367502689,\"upper_bound\":0.03076787430260181},\"point_estimate\":0.003941900569855328,\"standard_error\":0.015510209240430888},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.0029068538392882566,\"upper_bound\":0.02100879534708361},\"point_estimate\":0.009610635780182397,\"standard_error\":0.005011020517388033}}"
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    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (LocalStr)/500/new/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"FlexStr 0.9 (LocalStr)\",\"value_str\":\"500\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/FlexStr 0.9 (LocalStr)/500\",\"directory_name\":\"Import as owned and destroy/FlexStr 0.9 (LocalStr)/500\",\"title\":\"Import as owned and destroy/FlexStr 0.9 (LocalStr)/500\"}"
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    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (LocalStr)/500/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":102.80918493611402,\"upper_bound\":105.36762135071118},\"point_estimate\":104.12167326845379,\"standard_error\":0.6509209912721251},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":103.70318207318783,\"upper_bound\":105.2850448641203},\"point_estimate\":104.389088293919,\"standard_error\":0.4544209074432965},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.073745801789074,\"upper_bound\":6.5663983724513235},\"point_estimate\":4.989618806613474,\"standard_error\":0.9254669446427741},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":106.51979406156018,\"upper_bound\":109.10940003214462},\"point_estimate\":107.85426229467919,\"standard_error\":0.6604822241197827},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":4.814782189249138,\"upper_bound\":8.10453429615963},\"point_estimate\":6.528843560350775,\"standard_error\":0.8422558771980987}}"
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    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (LocalStr)/500/new/sample.json",
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  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (LocalStr)/500/new/tukey.json",
    "content": "[81.48752966244167,91.3021881381957,117.47461074020643,127.28926921596045]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (LocalStr)/500/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/FlexStr 0.9 (LocalStr)/500 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/FlexStr 0.9 (LocalStr)/500</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">106.52 ns</td>\n                                <td>107.85 ns</td>\n                                <td class=\"ci-bound\">109.11 ns</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.7993478</td>\n                                <td>0.8099020</td>\n                                <td class=\"ci-bound\">0.8005513</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">102.81 ns</td>\n                                <td>104.12 ns</td>\n                                <td class=\"ci-bound\">105.37 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">4.8148 ns</td>\n                                <td>6.5288 ns</td>\n                                <td class=\"ci-bound\">8.1045 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">103.70 ns</td>\n                                <td>104.39 ns</td>\n                                <td class=\"ci-bound\">105.29 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">3.0737 ns</td>\n                                <td>4.9896 ns</td>\n                                <td class=\"ci-bound\">6.5664 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−2.9609%</td>\n                            <td>+0.3942%</td>\n                            <td class=\"ci-bound\">+3.0768%</td>\n                            <td>(p = 0.83 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (LocalStr)/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/FlexStr 0.9 (LocalStr) Summary - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/FlexStr 0.9 (LocalStr)</h2>\n        <h3>Violin Plot</h3>\n        <a href=\"violin.svg\">\n            <img src=\"violin.svg\" alt=\"Violin Plot\" />\n        </a>\n        <p>This chart shows the relationship between function/parameter and iteration time. The thickness of the shaded\n            region indicates the probability that a measurement of the given function/parameter would take a particular\n            length of time.</p>\n        <h3>Line Chart</h3>\n        <img src=\"lines.svg\" alt=\"Line Chart\" />\n        <p>This chart shows the mean measured time for each function as the input (or the size of the input) increases.</p>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/0/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.9 (LocalStr)/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/0/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/0/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/10/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.9 (LocalStr)/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/10/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/10/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/20/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.9 (LocalStr)/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/20/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/20/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/100/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.9 (LocalStr)/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/100/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/100/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/500/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.9 (LocalStr)/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/500/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/500/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (SharedStr)/0/base/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"FlexStr 0.9 (SharedStr)\",\"value_str\":\"0\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/FlexStr 0.9 (SharedStr)/0\",\"directory_name\":\"Import as owned and destroy/FlexStr 0.9 (SharedStr)/0\",\"title\":\"Import as owned and destroy/FlexStr 0.9 (SharedStr)/0\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (SharedStr)/0/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.381477048739123,\"upper_bound\":2.4588380402978056},\"point_estimate\":2.4180463804432666,\"standard_error\":0.019837796468343334},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.3159871567200994,\"upper_bound\":2.479753870825443},\"point_estimate\":2.445089671712541,\"standard_error\":0.0445333160377881},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.10998504390771698,\"upper_bound\":0.2231740338633625},\"point_estimate\":0.18390114402830277,\"standard_error\":0.029763987951311747},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.4232086831233244,\"upper_bound\":2.469055068598798},\"point_estimate\":2.4480732139110315,\"standard_error\":0.01170460524816769},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.13841166901842136,\"upper_bound\":0.25677314806795054},\"point_estimate\":0.19905664499411255,\"standard_error\":0.030711646411715077}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (SharedStr)/0/base/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[136771.0,273542.0,410313.0,547084.0,683855.0,820626.0,957397.0,1094168.0,1230939.0,1367710.0,1504481.0,1641252.0,1778023.0,1914794.0,2051565.0,2188336.0,2325107.0,2461878.0,2598649.0,2735420.0,2872191.0,3008962.0,3145733.0,3282504.0,3419275.0,3556046.0,3692817.0,3829588.0,3966359.0,4103130.0,4239901.0,4376672.0,4513443.0,4650214.0,4786985.0,4923756.0,5060527.0,5197298.0,5334069.0,5470840.0,5607611.0,5744382.0,5881153.0,6017924.0,6154695.0,6291466.0,6428237.0,6565008.0,6701779.0,6838550.0,6975321.0,7112092.0,7248863.0,7385634.0,7522405.0,7659176.0,7795947.0,7932718.0,8069489.0,8206260.0,8343031.0,8479802.0,8616573.0,8753344.0,8890115.0,9026886.0,9163657.0,9300428.0,9437199.0,9573970.0,9710741.0,9847512.0,9984283.0,10121054.0,10257825.0,10394596.0,10531367.0,10668138.0,10804909.0,10941680.0,11078451.0,11215222.0,11351993.0,11488764.0,11625535.0,11762306.0,11899077.0,12035848.0,12172619.0,12309390.0,12446161.0,12582932.0,12719703.0,12856474.0,12993245.0,13130016.0,13266787.0,13403558.0,13540329.0,13677100.0],\"times\":[310540.0,910085.0,888167.0,1211041.0,2305208.0,1908127.0,2422789.0,2969459.0,3607752.0,3149167.0,3596624.0,4236499.0,4642499.0,4452124.0,5088377.0,5300166.0,5416252.0,6147708.0,6204582.0,6439707.0,6942628.0,7330875.0,7896083.0,8332667.0,8412083.0,7833333.0,8232085.0,8443711.0,8824584.0,9106874.0,9413164.0,9767834.0,10250001.0,10639919.0,10890499.0,11270292.0,11569249.0,11936042.0,12231708.0,12508165.0,12619169.0,12888791.0,13243500.0,13597958.0,13953623.0,14337291.0,14593165.0,14856667.0,15130708.0,15338958.0,15618209.0,15813249.0,16028250.0,16344251.0,16474167.0,17020959.0,17379375.0,17678543.0,17990751.0,18268919.0,18375457.0,22393249.0,21958418.0,22320916.0,22903374.0,23021543.0,23817749.0,23664582.0,23834790.0,24392334.0,24469708.0,24806917.0,25691540.0,25489710.0,26149210.0,26431501.0,26657749.0,27331501.0,27634041.0,27843165.0,27746583.0,28345498.0,28154750.0,28487832.0,28919832.0,29219250.0,29547333.0,29850876.0,30034086.0,30441125.0,30853043.0,31177540.0,32023083.0,31679584.0,32249458.0,32559208.0,32934376.0,32665208.0,33229205.0,33551627.0]}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (SharedStr)/0/base/tukey.json",
    "content": "[1.4725428773504685,1.8658269175264468,2.9145843579957225,3.3078683981717005]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (SharedStr)/0/change/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.017359813669932462,\"upper_bound\":0.03137943918133801},\"point_estimate\":0.007665465977398922,\"standard_error\":0.012336298698336965},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.037620518786308454,\"upper_bound\":0.0784070436323081},\"point_estimate\":0.03585815138538351,\"standard_error\":0.029392027589580084}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (SharedStr)/0/new/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"FlexStr 0.9 (SharedStr)\",\"value_str\":\"0\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/FlexStr 0.9 (SharedStr)/0\",\"directory_name\":\"Import as owned and destroy/FlexStr 0.9 (SharedStr)/0\",\"title\":\"Import as owned and destroy/FlexStr 0.9 (SharedStr)/0\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (SharedStr)/0/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.381477048739123,\"upper_bound\":2.4588380402978056},\"point_estimate\":2.4180463804432666,\"standard_error\":0.019837796468343334},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.3159871567200994,\"upper_bound\":2.479753870825443},\"point_estimate\":2.445089671712541,\"standard_error\":0.0445333160377881},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.10998504390771698,\"upper_bound\":0.2231740338633625},\"point_estimate\":0.18390114402830277,\"standard_error\":0.029763987951311747},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.4232086831233244,\"upper_bound\":2.469055068598798},\"point_estimate\":2.4480732139110315,\"standard_error\":0.01170460524816769},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.13841166901842136,\"upper_bound\":0.25677314806795054},\"point_estimate\":0.19905664499411255,\"standard_error\":0.030711646411715077}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (SharedStr)/0/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[136771.0,273542.0,410313.0,547084.0,683855.0,820626.0,957397.0,1094168.0,1230939.0,1367710.0,1504481.0,1641252.0,1778023.0,1914794.0,2051565.0,2188336.0,2325107.0,2461878.0,2598649.0,2735420.0,2872191.0,3008962.0,3145733.0,3282504.0,3419275.0,3556046.0,3692817.0,3829588.0,3966359.0,4103130.0,4239901.0,4376672.0,4513443.0,4650214.0,4786985.0,4923756.0,5060527.0,5197298.0,5334069.0,5470840.0,5607611.0,5744382.0,5881153.0,6017924.0,6154695.0,6291466.0,6428237.0,6565008.0,6701779.0,6838550.0,6975321.0,7112092.0,7248863.0,7385634.0,7522405.0,7659176.0,7795947.0,7932718.0,8069489.0,8206260.0,8343031.0,8479802.0,8616573.0,8753344.0,8890115.0,9026886.0,9163657.0,9300428.0,9437199.0,9573970.0,9710741.0,9847512.0,9984283.0,10121054.0,10257825.0,10394596.0,10531367.0,10668138.0,10804909.0,10941680.0,11078451.0,11215222.0,11351993.0,11488764.0,11625535.0,11762306.0,11899077.0,12035848.0,12172619.0,12309390.0,12446161.0,12582932.0,12719703.0,12856474.0,12993245.0,13130016.0,13266787.0,13403558.0,13540329.0,13677100.0],\"times\":[310540.0,910085.0,888167.0,1211041.0,2305208.0,1908127.0,2422789.0,2969459.0,3607752.0,3149167.0,3596624.0,4236499.0,4642499.0,4452124.0,5088377.0,5300166.0,5416252.0,6147708.0,6204582.0,6439707.0,6942628.0,7330875.0,7896083.0,8332667.0,8412083.0,7833333.0,8232085.0,8443711.0,8824584.0,9106874.0,9413164.0,9767834.0,10250001.0,10639919.0,10890499.0,11270292.0,11569249.0,11936042.0,12231708.0,12508165.0,12619169.0,12888791.0,13243500.0,13597958.0,13953623.0,14337291.0,14593165.0,14856667.0,15130708.0,15338958.0,15618209.0,15813249.0,16028250.0,16344251.0,16474167.0,17020959.0,17379375.0,17678543.0,17990751.0,18268919.0,18375457.0,22393249.0,21958418.0,22320916.0,22903374.0,23021543.0,23817749.0,23664582.0,23834790.0,24392334.0,24469708.0,24806917.0,25691540.0,25489710.0,26149210.0,26431501.0,26657749.0,27331501.0,27634041.0,27843165.0,27746583.0,28345498.0,28154750.0,28487832.0,28919832.0,29219250.0,29547333.0,29850876.0,30034086.0,30441125.0,30853043.0,31177540.0,32023083.0,31679584.0,32249458.0,32559208.0,32934376.0,32665208.0,33229205.0,33551627.0]}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (SharedStr)/0/new/tukey.json",
    "content": "[1.4725428773504685,1.8658269175264468,2.9145843579957225,3.3078683981717005]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (SharedStr)/0/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/FlexStr 0.9 (SharedStr)/0 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/FlexStr 0.9 (SharedStr)/0</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">2.4232 ns</td>\n                                <td>2.4481 ns</td>\n                                <td class=\"ci-bound\">2.4691 ns</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.7607002</td>\n                                <td>0.7688076</td>\n                                <td class=\"ci-bound\">0.7630170</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">2.3815 ns</td>\n                                <td>2.4180 ns</td>\n                                <td class=\"ci-bound\">2.4588 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">138.41 ps</td>\n                                <td>199.06 ps</td>\n                                <td class=\"ci-bound\">256.77 ps</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">2.3160 ns</td>\n                                <td>2.4451 ns</td>\n                                <td class=\"ci-bound\">2.4798 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">109.99 ps</td>\n                                <td>183.90 ps</td>\n                                <td class=\"ci-bound\">223.17 ps</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−1.7360%</td>\n                            <td>+0.7665%</td>\n                            <td class=\"ci-bound\">+3.1379%</td>\n                            <td>(p = 0.53 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (SharedStr)/10/base/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"FlexStr 0.9 (SharedStr)\",\"value_str\":\"10\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/FlexStr 0.9 (SharedStr)/10\",\"directory_name\":\"Import as owned and destroy/FlexStr 0.9 (SharedStr)/10\",\"title\":\"Import as owned and destroy/FlexStr 0.9 (SharedStr)/10\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (SharedStr)/10/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":31.728386872719593,\"upper_bound\":33.22351877339673},\"point_estimate\":32.45559380245438,\"standard_error\":0.381315942046424},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":30.395984944986857,\"upper_bound\":33.73660565344518},\"point_estimate\":31.70847269391804,\"standard_error\":0.8757872763664815},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.8643776637289107,\"upper_bound\":5.127736490649734},\"point_estimate\":4.649880659951262,\"standard_error\":0.6323908635583724},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":33.12725603986998,\"upper_bound\":34.4373100439948},\"point_estimate\":33.78212033355849,\"standard_error\":0.3339922057158904},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.1527830062827342,\"upper_bound\":4.654066284716856},\"point_estimate\":3.8254189421897555,\"standard_error\":0.4093956456155638}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (SharedStr)/10/base/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[15909.0,31818.0,47727.0,63636.0,79545.0,95454.0,111363.0,127272.0,143181.0,159090.0,174999.0,190908.0,206817.0,222726.0,238635.0,254544.0,270453.0,286362.0,302271.0,318180.0,334089.0,349998.0,365907.0,381816.0,397725.0,413634.0,429543.0,445452.0,461361.0,477270.0,493179.0,509088.0,524997.0,540906.0,556815.0,572724.0,588633.0,604542.0,620451.0,636360.0,652269.0,668178.0,684087.0,699996.0,715905.0,731814.0,747723.0,763632.0,779541.0,795450.0,811359.0,827268.0,843177.0,859086.0,874995.0,890904.0,906813.0,922722.0,938631.0,954540.0,970449.0,986358.0,1002267.0,1018176.0,1034085.0,1049994.0,1065903.0,1081812.0,1097721.0,1113630.0,1129539.0,1145448.0,1161357.0,1177266.0,1193175.0,1209084.0,1224993.0,1240902.0,1256811.0,1272720.0,1288629.0,1304538.0,1320447.0,1336356.0,1352265.0,1368174.0,1384083.0,1399992.0,1415901.0,1431810.0,1447719.0,1463628.0,1479537.0,1495446.0,1511355.0,1527264.0,1543173.0,1559082.0,1574991.0,1590900.0],\"times\":[800167.0,903541.0,1358749.0,1834708.0,2246584.0,2744790.0,3221418.0,4173959.0,4368750.0,4638415.0,5063793.0,5880751.0,5892956.0,6359585.0,6820126.0,7283499.0,8197457.0,8103582.0,8877831.0,9040750.0,9484748.0,10121875.0,10785793.0,10788083.0,11300041.0,12026542.0,12373790.0,12798624.0,13215791.0,13699127.0,14141166.0,14546793.0,14884917.0,15453750.0,15902458.0,16743334.0,16919373.0,17145001.0,17696418.0,18354167.0,25663750.0,26325167.0,25987833.0,26117917.0,26347751.0,26032000.0,26744665.0,26750372.0,26260291.0,26933207.0,26901457.0,27138042.0,26811957.0,27248083.0,27736833.0,27618085.0,27614874.0,28037623.0,27854499.0,28421833.0,35764959.0,36565334.0,35850708.0,36765793.0,36784916.0,37286958.0,38301456.0,38494501.0,38911543.0,39452957.0,40246793.0,40323417.0,40707707.0,41445417.0,41600958.0,42341834.0,42863250.0,43000166.0,43524333.0,43837958.0,50030293.0,49892958.0,50527210.0,50443208.0,48147542.0,49134877.0,49267916.0,49277082.0,48538583.0,49899375.0,48841125.0,47564206.0,47950167.0,48471917.0,47724083.0,47354584.0,48434293.0,47389833.0,47433001.0,48820084.0]}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (SharedStr)/10/base/tukey.json",
    "content": "[9.003532808875896,18.91435926475694,45.34322981377305,55.254056269654086]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (SharedStr)/10/change/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.08460968040274967,\"upper_bound\":0.00804856398815605},\"point_estimate\":-0.03765460940523058,\"standard_error\":0.023641772306301337},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.09964991159535863,\"upper_bound\":0.06290260379749668},\"point_estimate\":-0.03184512567825193,\"standard_error\":0.04240485282590046}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (SharedStr)/10/new/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"FlexStr 0.9 (SharedStr)\",\"value_str\":\"10\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/FlexStr 0.9 (SharedStr)/10\",\"directory_name\":\"Import as owned and destroy/FlexStr 0.9 (SharedStr)/10\",\"title\":\"Import as owned and destroy/FlexStr 0.9 (SharedStr)/10\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (SharedStr)/10/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":31.728386872719593,\"upper_bound\":33.22351877339673},\"point_estimate\":32.45559380245438,\"standard_error\":0.381315942046424},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":30.395984944986857,\"upper_bound\":33.73660565344518},\"point_estimate\":31.70847269391804,\"standard_error\":0.8757872763664815},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.8643776637289107,\"upper_bound\":5.127736490649734},\"point_estimate\":4.649880659951262,\"standard_error\":0.6323908635583724},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":33.12725603986998,\"upper_bound\":34.4373100439948},\"point_estimate\":33.78212033355849,\"standard_error\":0.3339922057158904},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.1527830062827342,\"upper_bound\":4.654066284716856},\"point_estimate\":3.8254189421897555,\"standard_error\":0.4093956456155638}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (SharedStr)/10/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[15909.0,31818.0,47727.0,63636.0,79545.0,95454.0,111363.0,127272.0,143181.0,159090.0,174999.0,190908.0,206817.0,222726.0,238635.0,254544.0,270453.0,286362.0,302271.0,318180.0,334089.0,349998.0,365907.0,381816.0,397725.0,413634.0,429543.0,445452.0,461361.0,477270.0,493179.0,509088.0,524997.0,540906.0,556815.0,572724.0,588633.0,604542.0,620451.0,636360.0,652269.0,668178.0,684087.0,699996.0,715905.0,731814.0,747723.0,763632.0,779541.0,795450.0,811359.0,827268.0,843177.0,859086.0,874995.0,890904.0,906813.0,922722.0,938631.0,954540.0,970449.0,986358.0,1002267.0,1018176.0,1034085.0,1049994.0,1065903.0,1081812.0,1097721.0,1113630.0,1129539.0,1145448.0,1161357.0,1177266.0,1193175.0,1209084.0,1224993.0,1240902.0,1256811.0,1272720.0,1288629.0,1304538.0,1320447.0,1336356.0,1352265.0,1368174.0,1384083.0,1399992.0,1415901.0,1431810.0,1447719.0,1463628.0,1479537.0,1495446.0,1511355.0,1527264.0,1543173.0,1559082.0,1574991.0,1590900.0],\"times\":[800167.0,903541.0,1358749.0,1834708.0,2246584.0,2744790.0,3221418.0,4173959.0,4368750.0,4638415.0,5063793.0,5880751.0,5892956.0,6359585.0,6820126.0,7283499.0,8197457.0,8103582.0,8877831.0,9040750.0,9484748.0,10121875.0,10785793.0,10788083.0,11300041.0,12026542.0,12373790.0,12798624.0,13215791.0,13699127.0,14141166.0,14546793.0,14884917.0,15453750.0,15902458.0,16743334.0,16919373.0,17145001.0,17696418.0,18354167.0,25663750.0,26325167.0,25987833.0,26117917.0,26347751.0,26032000.0,26744665.0,26750372.0,26260291.0,26933207.0,26901457.0,27138042.0,26811957.0,27248083.0,27736833.0,27618085.0,27614874.0,28037623.0,27854499.0,28421833.0,35764959.0,36565334.0,35850708.0,36765793.0,36784916.0,37286958.0,38301456.0,38494501.0,38911543.0,39452957.0,40246793.0,40323417.0,40707707.0,41445417.0,41600958.0,42341834.0,42863250.0,43000166.0,43524333.0,43837958.0,50030293.0,49892958.0,50527210.0,50443208.0,48147542.0,49134877.0,49267916.0,49277082.0,48538583.0,49899375.0,48841125.0,47564206.0,47950167.0,48471917.0,47724083.0,47354584.0,48434293.0,47389833.0,47433001.0,48820084.0]}"
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  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (SharedStr)/10/new/tukey.json",
    "content": "[9.003532808875896,18.91435926475694,45.34322981377305,55.254056269654086]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (SharedStr)/10/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/FlexStr 0.9 (SharedStr)/10 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/FlexStr 0.9 (SharedStr)/10</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">33.127 ns</td>\n                                <td>33.782 ns</td>\n                                <td class=\"ci-bound\">34.437 ns</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.4167658</td>\n                                <td>0.4304004</td>\n                                <td class=\"ci-bound\">0.4167527</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">31.728 ns</td>\n                                <td>32.456 ns</td>\n                                <td class=\"ci-bound\">33.224 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">3.1528 ns</td>\n                                <td>3.8254 ns</td>\n                                <td class=\"ci-bound\">4.6541 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">30.396 ns</td>\n                                <td>31.708 ns</td>\n                                <td class=\"ci-bound\">33.737 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">2.8644 ns</td>\n                                <td>4.6499 ns</td>\n                                <td class=\"ci-bound\">5.1277 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−8.4610%</td>\n                            <td>−3.7655%</td>\n                            <td class=\"ci-bound\">+0.8049%</td>\n                            <td>(p = 0.13 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (SharedStr)/100/base/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"FlexStr 0.9 (SharedStr)\",\"value_str\":\"100\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/FlexStr 0.9 (SharedStr)/100\",\"directory_name\":\"Import as owned and destroy/FlexStr 0.9 (SharedStr)/100\",\"title\":\"Import as owned and destroy/FlexStr 0.9 (SharedStr)/100\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (SharedStr)/100/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":61.13533833158814,\"upper_bound\":62.92536050718777},\"point_estimate\":62.02865730456268,\"standard_error\":0.4560774374970495},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":60.78691807301433,\"upper_bound\":62.70426909785323},\"point_estimate\":61.49183077795145,\"standard_error\":0.4981562559251687},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.000267371190253,\"upper_bound\":5.881264594727211},\"point_estimate\":4.4232883240530185,\"standard_error\":0.7275081926128233},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":61.892018611082406,\"upper_bound\":63.66741732691464},\"point_estimate\":62.77063641733545,\"standard_error\":0.45312643803491226},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.872649852639923,\"upper_bound\":5.286249808074371},\"point_estimate\":4.580457831267838,\"standard_error\":0.36289456279833565}}"
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    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (SharedStr)/100/base/sample.json",
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    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (SharedStr)/100/base/tukey.json",
    "content": "[42.47312439091873,50.99093896949609,73.70511117903573,82.2229257576131]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (SharedStr)/100/change/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.008277998967468062,\"upper_bound\":0.03315697302314179},\"point_estimate\":0.011335255207823858,\"standard_error\":0.010649154943376161},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.008951742491169368,\"upper_bound\":0.03686717928137823},\"point_estimate\":0.008034144612043326,\"standard_error\":0.01186151460845192}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (SharedStr)/100/new/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"FlexStr 0.9 (SharedStr)\",\"value_str\":\"100\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/FlexStr 0.9 (SharedStr)/100\",\"directory_name\":\"Import as owned and destroy/FlexStr 0.9 (SharedStr)/100\",\"title\":\"Import as owned and destroy/FlexStr 0.9 (SharedStr)/100\"}"
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    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (SharedStr)/100/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":61.13533833158814,\"upper_bound\":62.92536050718777},\"point_estimate\":62.02865730456268,\"standard_error\":0.4560774374970495},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":60.78691807301433,\"upper_bound\":62.70426909785323},\"point_estimate\":61.49183077795145,\"standard_error\":0.4981562559251687},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.000267371190253,\"upper_bound\":5.881264594727211},\"point_estimate\":4.4232883240530185,\"standard_error\":0.7275081926128233},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":61.892018611082406,\"upper_bound\":63.66741732691464},\"point_estimate\":62.77063641733545,\"standard_error\":0.45312643803491226},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.872649852639923,\"upper_bound\":5.286249808074371},\"point_estimate\":4.580457831267838,\"standard_error\":0.36289456279833565}}"
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    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (SharedStr)/100/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[7854.0,15708.0,23562.0,31416.0,39270.0,47124.0,54978.0,62832.0,70686.0,78540.0,86394.0,94248.0,102102.0,109956.0,117810.0,125664.0,133518.0,141372.0,149226.0,157080.0,164934.0,172788.0,180642.0,188496.0,196350.0,204204.0,212058.0,219912.0,227766.0,235620.0,243474.0,251328.0,259182.0,267036.0,274890.0,282744.0,290598.0,298452.0,306306.0,314160.0,322014.0,329868.0,337722.0,345576.0,353430.0,361284.0,369138.0,376992.0,384846.0,392700.0,400554.0,408408.0,416262.0,424116.0,431970.0,439824.0,447678.0,455532.0,463386.0,471240.0,479094.0,486948.0,494802.0,502656.0,510510.0,518364.0,526218.0,534072.0,541926.0,549780.0,557634.0,565488.0,573342.0,581196.0,589050.0,596904.0,604758.0,612612.0,620466.0,628320.0,636174.0,644028.0,651882.0,659736.0,667590.0,675444.0,683298.0,691152.0,699006.0,706860.0,714714.0,722568.0,730422.0,738276.0,746130.0,753984.0,761838.0,769692.0,777546.0,785400.0],\"times\":[430667.0,1234085.0,1255208.0,1699500.0,2681875.0,2544290.0,3179582.0,3331458.0,4289918.0,4187249.0,5136876.0,6645668.0,6907082.0,6683124.0,7106209.0,7124874.0,7325959.0,8759041.0,9476749.0,10274583.0,10148748.0,10503250.0,11025584.0,12405334.0,12784958.0,12475042.0,13172583.0,12484375.0,12501959.0,14070585.0,14567625.0,14992084.0,16780042.0,17561123.0,17397708.0,18093543.0,18181333.0,18199375.0,18322665.0,17794041.0,18862419.0,19303793.0,20251999.0,23190664.0,23989835.0,24748999.0,24589749.0,24546916.0,24744293.0,24583332.0,24102542.0,22680749.0,24133333.0,26051209.0,26349292.0,30759333.0,30163750.0,30075625.0,30760041.0,30205836.0,29712086.0,28985791.0,28858792.0,28105290.0,29106209.0,30599667.0,30214040.0,37569960.0,36675876.0,36684293.0,36116916.0,35389666.0,34886914.0,33998209.0,33761959.0,33545291.0,36540000.0,36949335.0,43344542.0,42771625.0,42154501.0,41094126.0,41140540.0,41009002.0,42003750.0,41134502.0,40845751.0,42502709.0,42980623.0,42717833.0,49687583.0,48413502.0,49009125.0,48834209.0,47396749.0,47750623.0,47876085.0,47323626.0,47245957.0,48401834.0]}"
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  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (SharedStr)/100/new/tukey.json",
    "content": "[42.47312439091873,50.99093896949609,73.70511117903573,82.2229257576131]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (SharedStr)/100/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/FlexStr 0.9 (SharedStr)/100 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/FlexStr 0.9 (SharedStr)/100</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">61.892 ns</td>\n                                <td>62.771 ns</td>\n                                <td class=\"ci-bound\">63.667 ns</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.6559550</td>\n                                <td>0.6686538</td>\n                                <td class=\"ci-bound\">0.6554350</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">61.135 ns</td>\n                                <td>62.029 ns</td>\n                                <td class=\"ci-bound\">62.925 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">3.8726 ns</td>\n                                <td>4.5805 ns</td>\n                                <td class=\"ci-bound\">5.2862 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">60.787 ns</td>\n                                <td>61.492 ns</td>\n                                <td class=\"ci-bound\">62.704 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">3.0003 ns</td>\n                                <td>4.4233 ns</td>\n                                <td class=\"ci-bound\">5.8813 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−0.8278%</td>\n                            <td>+1.1335%</td>\n                            <td class=\"ci-bound\">+3.3157%</td>\n                            <td>(p = 0.30 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (SharedStr)/20/base/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"FlexStr 0.9 (SharedStr)\",\"value_str\":\"20\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/FlexStr 0.9 (SharedStr)/20\",\"directory_name\":\"Import as owned and destroy/FlexStr 0.9 (SharedStr)/20\",\"title\":\"Import as owned and destroy/FlexStr 0.9 (SharedStr)/20\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (SharedStr)/20/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":35.62869891012077,\"upper_bound\":37.21640623430225},\"point_estimate\":36.400598078110924,\"standard_error\":0.403196383869325},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":35.61324437504436,\"upper_bound\":37.312710195255164},\"point_estimate\":36.74446670322017,\"standard_error\":0.4084221020726835},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.870076096231797,\"upper_bound\":4.744552542115047},\"point_estimate\":3.835619718625966,\"standard_error\":0.47137845915764887},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":36.997620662836574,\"upper_bound\":38.401368141580896},\"point_estimate\":37.710406190299686,\"standard_error\":0.3576412701390378},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.159123611767248,\"upper_bound\":5.1546505790613875},\"point_estimate\":4.049791201694487,\"standard_error\":0.5509136223084241}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (SharedStr)/20/base/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[14089.0,28178.0,42267.0,56356.0,70445.0,84534.0,98623.0,112712.0,126801.0,140890.0,154979.0,169068.0,183157.0,197246.0,211335.0,225424.0,239513.0,253602.0,267691.0,281780.0,295869.0,309958.0,324047.0,338136.0,352225.0,366314.0,380403.0,394492.0,408581.0,422670.0,436759.0,450848.0,464937.0,479026.0,493115.0,507204.0,521293.0,535382.0,549471.0,563560.0,577649.0,591738.0,605827.0,619916.0,634005.0,648094.0,662183.0,676272.0,690361.0,704450.0,718539.0,732628.0,746717.0,760806.0,774895.0,788984.0,803073.0,817162.0,831251.0,845340.0,859429.0,873518.0,887607.0,901696.0,915785.0,929874.0,943963.0,958052.0,972141.0,986230.0,1000319.0,1014408.0,1028497.0,1042586.0,1056675.0,1070764.0,1084853.0,1098942.0,1113031.0,1127120.0,1141209.0,1155298.0,1169387.0,1183476.0,1197565.0,1211654.0,1225743.0,1239832.0,1253921.0,1268010.0,1282099.0,1296188.0,1310277.0,1324366.0,1338455.0,1352544.0,1366633.0,1380722.0,1394811.0,1408900.0],\"times\":[812625.0,847667.0,1271334.0,2149793.0,2373209.0,2822081.0,3442832.0,3450084.0,3874252.0,4677543.0,5198958.0,5182874.0,5605959.0,6044708.0,6516542.0,6891540.0,7322459.0,7916084.0,8096166.0,8635290.0,9279623.0,9946045.0,13588166.0,13241960.0,13377413.0,13759292.0,14475125.0,14148999.0,14084415.0,14242040.0,14270167.0,14433792.0,14636166.0,17870500.0,18849622.0,18977252.0,19863125.0,20269165.0,20341001.0,21022251.0,21301584.0,21772835.0,22289457.0,22704834.0,23100208.0,27268333.0,26585291.0,26765584.0,27075206.0,26100333.0,26368332.0,25956792.0,25808125.0,26268750.0,25854166.0,25017502.0,28115209.0,29257333.0,29603545.0,29745293.0,30342376.0,33102500.0,36510041.0,36575251.0,36638790.0,37427000.0,37402583.0,37558084.0,40477084.0,39045915.0,39011500.0,37682499.0,37995581.0,37611791.0,36704582.0,36559875.0,35816210.0,35441249.0,37771543.0,40932209.0,41748624.0,42959958.0,42881209.0,45260417.0,47085751.0,52377959.0,51771625.0,50356499.0,51550625.0,51568373.0,53077416.0,53148252.0,52093292.0,50964500.0,50112084.0,50747417.0,48539706.0,52879417.0,54360791.0,48042123.0]}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (SharedStr)/20/base/tukey.json",
    "content": "[17.67280238967404,25.662985280422806,46.970139655752845,54.960322546501615]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (SharedStr)/20/change/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.023918908859197396,\"upper_bound\":0.03699453836132418},\"point_estimate\":0.005965685148533018,\"standard_error\":0.015588497304246381},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.03429660589422845,\"upper_bound\":0.032381629332976836},\"point_estimate\":-0.0033061466665268435,\"standard_error\":0.015773926803734063}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (SharedStr)/20/new/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"FlexStr 0.9 (SharedStr)\",\"value_str\":\"20\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/FlexStr 0.9 (SharedStr)/20\",\"directory_name\":\"Import as owned and destroy/FlexStr 0.9 (SharedStr)/20\",\"title\":\"Import as owned and destroy/FlexStr 0.9 (SharedStr)/20\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (SharedStr)/20/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":35.62869891012077,\"upper_bound\":37.21640623430225},\"point_estimate\":36.400598078110924,\"standard_error\":0.403196383869325},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":35.61324437504436,\"upper_bound\":37.312710195255164},\"point_estimate\":36.74446670322017,\"standard_error\":0.4084221020726835},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.870076096231797,\"upper_bound\":4.744552542115047},\"point_estimate\":3.835619718625966,\"standard_error\":0.47137845915764887},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":36.997620662836574,\"upper_bound\":38.401368141580896},\"point_estimate\":37.710406190299686,\"standard_error\":0.3576412701390378},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.159123611767248,\"upper_bound\":5.1546505790613875},\"point_estimate\":4.049791201694487,\"standard_error\":0.5509136223084241}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (SharedStr)/20/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[14089.0,28178.0,42267.0,56356.0,70445.0,84534.0,98623.0,112712.0,126801.0,140890.0,154979.0,169068.0,183157.0,197246.0,211335.0,225424.0,239513.0,253602.0,267691.0,281780.0,295869.0,309958.0,324047.0,338136.0,352225.0,366314.0,380403.0,394492.0,408581.0,422670.0,436759.0,450848.0,464937.0,479026.0,493115.0,507204.0,521293.0,535382.0,549471.0,563560.0,577649.0,591738.0,605827.0,619916.0,634005.0,648094.0,662183.0,676272.0,690361.0,704450.0,718539.0,732628.0,746717.0,760806.0,774895.0,788984.0,803073.0,817162.0,831251.0,845340.0,859429.0,873518.0,887607.0,901696.0,915785.0,929874.0,943963.0,958052.0,972141.0,986230.0,1000319.0,1014408.0,1028497.0,1042586.0,1056675.0,1070764.0,1084853.0,1098942.0,1113031.0,1127120.0,1141209.0,1155298.0,1169387.0,1183476.0,1197565.0,1211654.0,1225743.0,1239832.0,1253921.0,1268010.0,1282099.0,1296188.0,1310277.0,1324366.0,1338455.0,1352544.0,1366633.0,1380722.0,1394811.0,1408900.0],\"times\":[812625.0,847667.0,1271334.0,2149793.0,2373209.0,2822081.0,3442832.0,3450084.0,3874252.0,4677543.0,5198958.0,5182874.0,5605959.0,6044708.0,6516542.0,6891540.0,7322459.0,7916084.0,8096166.0,8635290.0,9279623.0,9946045.0,13588166.0,13241960.0,13377413.0,13759292.0,14475125.0,14148999.0,14084415.0,14242040.0,14270167.0,14433792.0,14636166.0,17870500.0,18849622.0,18977252.0,19863125.0,20269165.0,20341001.0,21022251.0,21301584.0,21772835.0,22289457.0,22704834.0,23100208.0,27268333.0,26585291.0,26765584.0,27075206.0,26100333.0,26368332.0,25956792.0,25808125.0,26268750.0,25854166.0,25017502.0,28115209.0,29257333.0,29603545.0,29745293.0,30342376.0,33102500.0,36510041.0,36575251.0,36638790.0,37427000.0,37402583.0,37558084.0,40477084.0,39045915.0,39011500.0,37682499.0,37995581.0,37611791.0,36704582.0,36559875.0,35816210.0,35441249.0,37771543.0,40932209.0,41748624.0,42959958.0,42881209.0,45260417.0,47085751.0,52377959.0,51771625.0,50356499.0,51550625.0,51568373.0,53077416.0,53148252.0,52093292.0,50964500.0,50112084.0,50747417.0,48539706.0,52879417.0,54360791.0,48042123.0]}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (SharedStr)/20/new/tukey.json",
    "content": "[17.67280238967404,25.662985280422806,46.970139655752845,54.960322546501615]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (SharedStr)/20/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/FlexStr 0.9 (SharedStr)/20 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/FlexStr 0.9 (SharedStr)/20</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">36.998 ns</td>\n                                <td>37.710 ns</td>\n                                <td class=\"ci-bound\">38.401 ns</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.4549490</td>\n                                <td>0.4707389</td>\n                                <td class=\"ci-bound\">0.4558710</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">35.629 ns</td>\n                                <td>36.401 ns</td>\n                                <td class=\"ci-bound\">37.216 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">3.1591 ns</td>\n                                <td>4.0498 ns</td>\n                                <td class=\"ci-bound\">5.1547 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">35.613 ns</td>\n                                <td>36.744 ns</td>\n                                <td class=\"ci-bound\">37.313 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">2.8701 ns</td>\n                                <td>3.8356 ns</td>\n                                <td class=\"ci-bound\">4.7446 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−2.3919%</td>\n                            <td>+0.5966%</td>\n                            <td class=\"ci-bound\">+3.6995%</td>\n                            <td>(p = 0.70 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (SharedStr)/500/base/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"FlexStr 0.9 (SharedStr)\",\"value_str\":\"500\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/FlexStr 0.9 (SharedStr)/500\",\"directory_name\":\"Import as owned and destroy/FlexStr 0.9 (SharedStr)/500\",\"title\":\"Import as owned and destroy/FlexStr 0.9 (SharedStr)/500\"}"
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    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (SharedStr)/500/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":100.47294654617056,\"upper_bound\":102.87098957173014},\"point_estimate\":101.72742466346106,\"standard_error\":0.6125866755045651},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":102.26390683761925,\"upper_bound\":104.21194779672277},\"point_estimate\":103.54442733996387,\"standard_error\":0.49959485066060383},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.1236193230477793,\"upper_bound\":5.745567725872732},\"point_estimate\":4.156794041144598,\"standard_error\":0.6524847490769501},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":104.22950187610992,\"upper_bound\":105.5766065552291},\"point_estimate\":104.93481384874207,\"standard_error\":0.34330502520530853},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":4.579360607443471,\"upper_bound\":7.524743759824804},\"point_estimate\":6.148063611305268,\"standard_error\":0.7557623895542523}}"
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    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (SharedStr)/500/base/sample.json",
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    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (SharedStr)/500/change/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.002972069778628744,\"upper_bound\":0.031214744788593197},\"point_estimate\":0.014036022786678481,\"standard_error\":0.008715419334192785},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.005098357278062959,\"upper_bound\":0.03607922354248738},\"point_estimate\":0.021181488591605513,\"standard_error\":0.007405863249045624}}"
  },
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    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (SharedStr)/500/new/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"FlexStr 0.9 (SharedStr)\",\"value_str\":\"500\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/FlexStr 0.9 (SharedStr)/500\",\"directory_name\":\"Import as owned and destroy/FlexStr 0.9 (SharedStr)/500\",\"title\":\"Import as owned and destroy/FlexStr 0.9 (SharedStr)/500\"}"
  },
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    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (SharedStr)/500/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":100.47294654617056,\"upper_bound\":102.87098957173014},\"point_estimate\":101.72742466346106,\"standard_error\":0.6125866755045651},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":102.26390683761925,\"upper_bound\":104.21194779672277},\"point_estimate\":103.54442733996387,\"standard_error\":0.49959485066060383},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.1236193230477793,\"upper_bound\":5.745567725872732},\"point_estimate\":4.156794041144598,\"standard_error\":0.6524847490769501},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":104.22950187610992,\"upper_bound\":105.5766065552291},\"point_estimate\":104.93481384874207,\"standard_error\":0.34330502520530853},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":4.579360607443471,\"upper_bound\":7.524743759824804},\"point_estimate\":6.148063611305268,\"standard_error\":0.7557623895542523}}"
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    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (SharedStr)/500/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[4516.0,9032.0,13548.0,18064.0,22580.0,27096.0,31612.0,36128.0,40644.0,45160.0,49676.0,54192.0,58708.0,63224.0,67740.0,72256.0,76772.0,81288.0,85804.0,90320.0,94836.0,99352.0,103868.0,108384.0,112900.0,117416.0,121932.0,126448.0,130964.0,135480.0,139996.0,144512.0,149028.0,153544.0,158060.0,162576.0,167092.0,171608.0,176124.0,180640.0,185156.0,189672.0,194188.0,198704.0,203220.0,207736.0,212252.0,216768.0,221284.0,225800.0,230316.0,234832.0,239348.0,243864.0,248380.0,252896.0,257412.0,261928.0,266444.0,270960.0,275476.0,279992.0,284508.0,289024.0,293540.0,298056.0,302572.0,307088.0,311604.0,316120.0,320636.0,325152.0,329668.0,334184.0,338700.0,343216.0,347732.0,352248.0,356764.0,361280.0,365796.0,370312.0,374828.0,379344.0,383860.0,388376.0,392892.0,397408.0,401924.0,406440.0,410956.0,415472.0,419988.0,424504.0,429020.0,433536.0,438052.0,442568.0,447084.0,451600.0],\"times\":[360917.0,709333.0,1072874.0,1616335.0,1884168.0,2676710.0,3388250.0,3760959.0,3709460.0,4226791.0,4770499.0,5292378.0,5470582.0,5885290.0,6664457.0,7057123.0,7583580.0,7627708.0,8691791.0,9467582.0,9523083.0,9680000.0,10018334.0,11228543.0,11611582.0,11894167.0,11958085.0,12483043.0,12980916.0,14861667.0,14513502.0,15075918.0,15622791.0,16151457.0,15943708.0,15938584.0,17155542.0,17762332.0,18776876.0,17174294.0,18923625.0,20092669.0,19089666.0,19513456.0,20481832.0,21518040.0,21398335.0,22502042.0,22083457.0,22051835.0,22666499.0,23846123.0,24221375.0,23991039.0,25852375.0,26742249.0,27108999.0,26272999.0,28311209.0,27928665.0,28171252.0,28751377.0,29567331.0,31138624.0,30678542.0,32554712.0,31523126.0,32057998.0,32732293.0,33107915.0,32286416.0,33510375.0,34485874.0,35180958.0,35331000.0,36830751.0,36805167.0,37613292.0,39301292.0,38907710.0,38854334.0,39522374.0,39941584.0,39689123.0,40622334.0,39970166.0,40574999.0,42975959.0,42907081.0,42803376.0,42632832.0,43820417.0,46273541.0,43780873.0,44679708.0,46890457.0,47441960.0,46561916.0,48459835.0,48373581.0]}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (SharedStr)/500/new/tukey.json",
    "content": "[79.00311375101097,88.88435658252293,115.2343374665548,125.11558029806676]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (SharedStr)/500/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/FlexStr 0.9 (SharedStr)/500 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/FlexStr 0.9 (SharedStr)/500</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">104.23 ns</td>\n                                <td>104.93 ns</td>\n                                <td class=\"ci-bound\">105.58 ns</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.9053744</td>\n                                <td>0.9100360</td>\n                                <td class=\"ci-bound\">0.9061728</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">100.47 ns</td>\n                                <td>101.73 ns</td>\n                                <td class=\"ci-bound\">102.87 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">4.5794 ns</td>\n                                <td>6.1481 ns</td>\n                                <td class=\"ci-bound\">7.5247 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">102.26 ns</td>\n                                <td>103.54 ns</td>\n                                <td class=\"ci-bound\">104.21 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">3.1236 ns</td>\n                                <td>4.1568 ns</td>\n                                <td class=\"ci-bound\">5.7456 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−0.2972%</td>\n                            <td>+1.4036%</td>\n                            <td class=\"ci-bound\">+3.1215%</td>\n                            <td>(p = 0.11 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/FlexStr 0.9 (SharedStr)/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/FlexStr 0.9 (SharedStr) Summary - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/FlexStr 0.9 (SharedStr)</h2>\n        <h3>Violin Plot</h3>\n        <a href=\"violin.svg\">\n            <img src=\"violin.svg\" alt=\"Violin Plot\" />\n        </a>\n        <p>This chart shows the relationship between function/parameter and iteration time. The thickness of the shaded\n            region indicates the probability that a measurement of the given function/parameter would take a particular\n            length of time.</p>\n        <h3>Line Chart</h3>\n        <img src=\"lines.svg\" alt=\"Line Chart\" />\n        <p>This chart shows the mean measured time for each function as the input (or the size of the input) increases.</p>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/0/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.9 (SharedStr)/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/0/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/0/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/10/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.9 (SharedStr)/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/10/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/10/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/20/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.9 (SharedStr)/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/20/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/20/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/100/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.9 (SharedStr)/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/100/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/100/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/500/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.9 (SharedStr)/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/500/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/500/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/0/base/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"InlineFlexStr 0.1 (InlineStr)\",\"value_str\":\"0\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/0\",\"directory_name\":\"Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/0\",\"title\":\"Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/0\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/0/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":7.251258353021665,\"upper_bound\":7.439443851757329},\"point_estimate\":7.324448437324584,\"standard_error\":0.05086588143814554},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":7.183683868765958,\"upper_bound\":7.265368025182118},\"point_estimate\":7.1918019916586085,\"standard_error\":0.0186782140930602},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.030423999124320412,\"upper_bound\":0.12871352300157987},\"point_estimate\":0.04890576209338276,\"standard_error\":0.02410815102788063},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":7.186439074889523,\"upper_bound\":7.2581568588453855},\"point_estimate\":7.21305844529285,\"standard_error\":0.019467864025873218},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.12836959117501545,\"upper_bound\":0.8502573463856848},\"point_estimate\":0.513688867042218,\"standard_error\":0.2385485231094198}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/0/base/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[84603.0,169206.0,253809.0,338412.0,423015.0,507618.0,592221.0,676824.0,761427.0,846030.0,930633.0,1015236.0,1099839.0,1184442.0,1269045.0,1353648.0,1438251.0,1522854.0,1607457.0,1692060.0,1776663.0,1861266.0,1945869.0,2030472.0,2115075.0,2199678.0,2284281.0,2368884.0,2453487.0,2538090.0,2622693.0,2707296.0,2791899.0,2876502.0,2961105.0,3045708.0,3130311.0,3214914.0,3299517.0,3384120.0,3468723.0,3553326.0,3637929.0,3722532.0,3807135.0,3891738.0,3976341.0,4060944.0,4145547.0,4230150.0,4314753.0,4399356.0,4483959.0,4568562.0,4653165.0,4737768.0,4822371.0,4906974.0,4991577.0,5076180.0,5160783.0,5245386.0,5329989.0,5414592.0,5499195.0,5583798.0,5668401.0,5753004.0,5837607.0,5922210.0,6006813.0,6091416.0,6176019.0,6260622.0,6345225.0,6429828.0,6514431.0,6599034.0,6683637.0,6768240.0,6852843.0,6937446.0,7022049.0,7106652.0,7191255.0,7275858.0,7360461.0,7445064.0,7529667.0,7614270.0,7698873.0,7783476.0,7868079.0,7952682.0,8037285.0,8121888.0,8206491.0,8291094.0,8375697.0,8460300.0],\"times\":[1024416.0,1209416.0,1811917.0,2550625.0,3125707.0,3975044.0,4734500.0,4941835.0,5590916.0,6490458.0,6815166.0,7407709.0,8275709.0,8673083.0,10318169.0,9865334.0,10558332.0,11356749.0,11834540.0,12252627.0,12995708.0,13889168.0,14498711.0,14789460.0,15497291.0,16246959.0,16987752.0,17334751.0,18041042.0,18397125.0,19241750.0,19960957.0,20299166.0,20929292.0,21721084.0,22329416.0,22858750.0,23718125.0,24181959.0,25194085.0,25470666.0,25488002.0,26044541.0,26682000.0,27259126.0,27894498.0,28519876.0,29166374.0,29738164.0,30372624.0,31024499.0,31587500.0,32193000.0,32843125.0,33461709.0,34036209.0,34708458.0,35265250.0,35866333.0,36546960.0,37103458.0,37727083.0,38288956.0,38883542.0,39479291.0,40084416.0,41408583.0,41474749.0,41865249.0,42498748.0,43100251.0,43716583.0,44379666.0,44973540.0,45510998.0,46162625.0,46720874.0,47260251.0,47908873.0,48819085.0,49333043.0,49661458.0,50254876.0,50887584.0,51562750.0,52159418.0,53476458.0,53337375.0,53952167.0,54815917.0,55183334.0,55612334.0,57271708.0,57174584.0,57462167.0,58146958.0,58759584.0,59287916.0,60059042.0,66343875.0]}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/0/base/tukey.json",
    "content": "[6.701140697646534,6.936799253738615,7.565222069984165,7.800880626076246]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/0/change/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.022205529437447625,\"upper_bound\":0.012012975924330876},\"point_estimate\":-0.005919413874838186,\"standard_error\":0.00856799066354067},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.018241786716137187,\"upper_bound\":0.005002314845885758},\"point_estimate\":-0.004836710325759386,\"standard_error\":0.004815816602310718}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/0/new/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"InlineFlexStr 0.1 (InlineStr)\",\"value_str\":\"0\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/0\",\"directory_name\":\"Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/0\",\"title\":\"Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/0\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/0/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":7.251258353021665,\"upper_bound\":7.439443851757329},\"point_estimate\":7.324448437324584,\"standard_error\":0.05086588143814554},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":7.183683868765958,\"upper_bound\":7.265368025182118},\"point_estimate\":7.1918019916586085,\"standard_error\":0.0186782140930602},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.030423999124320412,\"upper_bound\":0.12871352300157987},\"point_estimate\":0.04890576209338276,\"standard_error\":0.02410815102788063},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":7.186439074889523,\"upper_bound\":7.2581568588453855},\"point_estimate\":7.21305844529285,\"standard_error\":0.019467864025873218},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.12836959117501545,\"upper_bound\":0.8502573463856848},\"point_estimate\":0.513688867042218,\"standard_error\":0.2385485231094198}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/0/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[84603.0,169206.0,253809.0,338412.0,423015.0,507618.0,592221.0,676824.0,761427.0,846030.0,930633.0,1015236.0,1099839.0,1184442.0,1269045.0,1353648.0,1438251.0,1522854.0,1607457.0,1692060.0,1776663.0,1861266.0,1945869.0,2030472.0,2115075.0,2199678.0,2284281.0,2368884.0,2453487.0,2538090.0,2622693.0,2707296.0,2791899.0,2876502.0,2961105.0,3045708.0,3130311.0,3214914.0,3299517.0,3384120.0,3468723.0,3553326.0,3637929.0,3722532.0,3807135.0,3891738.0,3976341.0,4060944.0,4145547.0,4230150.0,4314753.0,4399356.0,4483959.0,4568562.0,4653165.0,4737768.0,4822371.0,4906974.0,4991577.0,5076180.0,5160783.0,5245386.0,5329989.0,5414592.0,5499195.0,5583798.0,5668401.0,5753004.0,5837607.0,5922210.0,6006813.0,6091416.0,6176019.0,6260622.0,6345225.0,6429828.0,6514431.0,6599034.0,6683637.0,6768240.0,6852843.0,6937446.0,7022049.0,7106652.0,7191255.0,7275858.0,7360461.0,7445064.0,7529667.0,7614270.0,7698873.0,7783476.0,7868079.0,7952682.0,8037285.0,8121888.0,8206491.0,8291094.0,8375697.0,8460300.0],\"times\":[1024416.0,1209416.0,1811917.0,2550625.0,3125707.0,3975044.0,4734500.0,4941835.0,5590916.0,6490458.0,6815166.0,7407709.0,8275709.0,8673083.0,10318169.0,9865334.0,10558332.0,11356749.0,11834540.0,12252627.0,12995708.0,13889168.0,14498711.0,14789460.0,15497291.0,16246959.0,16987752.0,17334751.0,18041042.0,18397125.0,19241750.0,19960957.0,20299166.0,20929292.0,21721084.0,22329416.0,22858750.0,23718125.0,24181959.0,25194085.0,25470666.0,25488002.0,26044541.0,26682000.0,27259126.0,27894498.0,28519876.0,29166374.0,29738164.0,30372624.0,31024499.0,31587500.0,32193000.0,32843125.0,33461709.0,34036209.0,34708458.0,35265250.0,35866333.0,36546960.0,37103458.0,37727083.0,38288956.0,38883542.0,39479291.0,40084416.0,41408583.0,41474749.0,41865249.0,42498748.0,43100251.0,43716583.0,44379666.0,44973540.0,45510998.0,46162625.0,46720874.0,47260251.0,47908873.0,48819085.0,49333043.0,49661458.0,50254876.0,50887584.0,51562750.0,52159418.0,53476458.0,53337375.0,53952167.0,54815917.0,55183334.0,55612334.0,57271708.0,57174584.0,57462167.0,58146958.0,58759584.0,59287916.0,60059042.0,66343875.0]}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/0/new/tukey.json",
    "content": "[6.701140697646534,6.936799253738615,7.565222069984165,7.800880626076246]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/0/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/0 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/0</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">7.1864 ns</td>\n                                <td>7.2131 ns</td>\n                                <td class=\"ci-bound\">7.2582 ns</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.9693377</td>\n                                <td>0.9706216</td>\n                                <td class=\"ci-bound\">0.9669455</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">7.2513 ns</td>\n                                <td>7.3244 ns</td>\n                                <td class=\"ci-bound\">7.4394 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">128.37 ps</td>\n                                <td>513.69 ps</td>\n                                <td class=\"ci-bound\">850.26 ps</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">7.1837 ns</td>\n                                <td>7.1918 ns</td>\n                                <td class=\"ci-bound\">7.2654 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">30.424 ps</td>\n                                <td>48.906 ps</td>\n                                <td class=\"ci-bound\">128.71 ps</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−2.2206%</td>\n                            <td>−0.5919%</td>\n                            <td class=\"ci-bound\">+1.2013%</td>\n                            <td>(p = 0.54 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/10/base/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"InlineFlexStr 0.1 (InlineStr)\",\"value_str\":\"10\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/10\",\"directory_name\":\"Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/10\",\"title\":\"Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/10\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/10/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":34.79441554388005,\"upper_bound\":36.284235980817904},\"point_estimate\":35.510833522789554,\"standard_error\":0.3800123305529685},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":33.9394538190149,\"upper_bound\":37.03558298867861},\"point_estimate\":35.31847186440393,\"standard_error\":0.8635925501538483},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.0637375591217983,\"upper_bound\":4.955771530637717},\"point_estimate\":4.506313631126542,\"standard_error\":0.5125140333583857},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":36.10984777969444,\"upper_bound\":37.331199411473264},\"point_estimate\":36.72993922831236,\"standard_error\":0.3121450660747379},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.030002488629462,\"upper_bound\":4.833488594256678},\"point_estimate\":3.8242788875504226,\"standard_error\":0.5100776910289498}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/10/base/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[15958.0,31916.0,47874.0,63832.0,79790.0,95748.0,111706.0,127664.0,143622.0,159580.0,175538.0,191496.0,207454.0,223412.0,239370.0,255328.0,271286.0,287244.0,303202.0,319160.0,335118.0,351076.0,367034.0,382992.0,398950.0,414908.0,430866.0,446824.0,462782.0,478740.0,494698.0,510656.0,526614.0,542572.0,558530.0,574488.0,590446.0,606404.0,622362.0,638320.0,654278.0,670236.0,686194.0,702152.0,718110.0,734068.0,750026.0,765984.0,781942.0,797900.0,813858.0,829816.0,845774.0,861732.0,877690.0,893648.0,909606.0,925564.0,941522.0,957480.0,973438.0,989396.0,1005354.0,1021312.0,1037270.0,1053228.0,1069186.0,1085144.0,1101102.0,1117060.0,1133018.0,1148976.0,1164934.0,1180892.0,1196850.0,1212808.0,1228766.0,1244724.0,1260682.0,1276640.0,1292598.0,1308556.0,1324514.0,1340472.0,1356430.0,1372388.0,1388346.0,1404304.0,1420262.0,1436220.0,1452178.0,1468136.0,1484094.0,1500052.0,1516010.0,1531968.0,1547926.0,1563884.0,1579842.0,1595800.0],\"times\":[888042.0,995457.0,1496541.0,2445456.0,2491169.0,3546083.0,3976956.0,4342124.0,4485084.0,5532251.0,5477291.0,6096373.0,7058832.0,7153748.0,7516915.0,8054625.0,8560039.0,9474916.0,9608542.0,9955544.0,10489916.0,10997417.0,11887708.0,11988290.0,12520251.0,13378000.0,13716043.0,14030165.0,14575125.0,15661501.0,15770083.0,16043459.0,16689625.0,17051001.0,17639541.0,18261375.0,18799416.0,19146252.0,19515124.0,20116499.0,27440209.0,28386250.0,27641250.0,27784165.0,27566376.0,28584375.0,28212625.0,28205086.0,29778874.0,28774207.0,29514542.0,29052291.0,29132958.0,29644960.0,28992873.0,29776335.0,29710416.0,29817834.0,32614373.0,36488416.0,37662917.0,38643373.0,38843165.0,39925667.0,40479416.0,39159706.0,40425459.0,42255000.0,42079456.0,41799918.0,42852418.0,43961623.0,44230665.0,44612335.0,45480834.0,46485084.0,46553124.0,47439290.0,46754501.0,47226126.0,53987959.0,54003582.0,53375166.0,53230582.0,52736333.0,53661750.0,53045834.0,53421668.0,53492167.0,53686000.0,52519667.0,53233208.0,53059833.0,52554251.0,52602249.0,53187001.0,52283999.0,52354625.0,51407250.0,58719750.0]}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/10/base/tukey.json",
    "content": "[13.011168276840671,22.423108597881047,47.52161612065539,56.93355644169577]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/10/change/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.022010844592474932,\"upper_bound\":0.03543656013742059},\"point_estimate\":0.006111652655413691,\"standard_error\":0.014598056657434551},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.05642716393641023,\"upper_bound\":0.08160308327385285},\"point_estimate\":0.010781426192513877,\"standard_error\":0.035524018040099616}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/10/new/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"InlineFlexStr 0.1 (InlineStr)\",\"value_str\":\"10\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/10\",\"directory_name\":\"Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/10\",\"title\":\"Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/10\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/10/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":34.79441554388005,\"upper_bound\":36.284235980817904},\"point_estimate\":35.510833522789554,\"standard_error\":0.3800123305529685},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":33.9394538190149,\"upper_bound\":37.03558298867861},\"point_estimate\":35.31847186440393,\"standard_error\":0.8635925501538483},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.0637375591217983,\"upper_bound\":4.955771530637717},\"point_estimate\":4.506313631126542,\"standard_error\":0.5125140333583857},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":36.10984777969444,\"upper_bound\":37.331199411473264},\"point_estimate\":36.72993922831236,\"standard_error\":0.3121450660747379},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.030002488629462,\"upper_bound\":4.833488594256678},\"point_estimate\":3.8242788875504226,\"standard_error\":0.5100776910289498}}"
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  {
    "path": "docs/criterion/Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/10/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[15958.0,31916.0,47874.0,63832.0,79790.0,95748.0,111706.0,127664.0,143622.0,159580.0,175538.0,191496.0,207454.0,223412.0,239370.0,255328.0,271286.0,287244.0,303202.0,319160.0,335118.0,351076.0,367034.0,382992.0,398950.0,414908.0,430866.0,446824.0,462782.0,478740.0,494698.0,510656.0,526614.0,542572.0,558530.0,574488.0,590446.0,606404.0,622362.0,638320.0,654278.0,670236.0,686194.0,702152.0,718110.0,734068.0,750026.0,765984.0,781942.0,797900.0,813858.0,829816.0,845774.0,861732.0,877690.0,893648.0,909606.0,925564.0,941522.0,957480.0,973438.0,989396.0,1005354.0,1021312.0,1037270.0,1053228.0,1069186.0,1085144.0,1101102.0,1117060.0,1133018.0,1148976.0,1164934.0,1180892.0,1196850.0,1212808.0,1228766.0,1244724.0,1260682.0,1276640.0,1292598.0,1308556.0,1324514.0,1340472.0,1356430.0,1372388.0,1388346.0,1404304.0,1420262.0,1436220.0,1452178.0,1468136.0,1484094.0,1500052.0,1516010.0,1531968.0,1547926.0,1563884.0,1579842.0,1595800.0],\"times\":[888042.0,995457.0,1496541.0,2445456.0,2491169.0,3546083.0,3976956.0,4342124.0,4485084.0,5532251.0,5477291.0,6096373.0,7058832.0,7153748.0,7516915.0,8054625.0,8560039.0,9474916.0,9608542.0,9955544.0,10489916.0,10997417.0,11887708.0,11988290.0,12520251.0,13378000.0,13716043.0,14030165.0,14575125.0,15661501.0,15770083.0,16043459.0,16689625.0,17051001.0,17639541.0,18261375.0,18799416.0,19146252.0,19515124.0,20116499.0,27440209.0,28386250.0,27641250.0,27784165.0,27566376.0,28584375.0,28212625.0,28205086.0,29778874.0,28774207.0,29514542.0,29052291.0,29132958.0,29644960.0,28992873.0,29776335.0,29710416.0,29817834.0,32614373.0,36488416.0,37662917.0,38643373.0,38843165.0,39925667.0,40479416.0,39159706.0,40425459.0,42255000.0,42079456.0,41799918.0,42852418.0,43961623.0,44230665.0,44612335.0,45480834.0,46485084.0,46553124.0,47439290.0,46754501.0,47226126.0,53987959.0,54003582.0,53375166.0,53230582.0,52736333.0,53661750.0,53045834.0,53421668.0,53492167.0,53686000.0,52519667.0,53233208.0,53059833.0,52554251.0,52602249.0,53187001.0,52283999.0,52354625.0,51407250.0,58719750.0]}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/10/new/tukey.json",
    "content": "[13.011168276840671,22.423108597881047,47.52161612065539,56.93355644169577]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/10/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/10 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/10</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">36.110 ns</td>\n                                <td>36.730 ns</td>\n                                <td class=\"ci-bound\">37.331 ns</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.5896054</td>\n                                <td>0.6032005</td>\n                                <td class=\"ci-bound\">0.5904013</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">34.794 ns</td>\n                                <td>35.511 ns</td>\n                                <td class=\"ci-bound\">36.284 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">3.0300 ns</td>\n                                <td>3.8243 ns</td>\n                                <td class=\"ci-bound\">4.8335 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">33.939 ns</td>\n                                <td>35.318 ns</td>\n                                <td class=\"ci-bound\">37.036 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">3.0637 ns</td>\n                                <td>4.5063 ns</td>\n                                <td class=\"ci-bound\">4.9558 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−2.2011%</td>\n                            <td>+0.6112%</td>\n                            <td class=\"ci-bound\">+3.5437%</td>\n                            <td>(p = 0.67 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/100/base/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"InlineFlexStr 0.1 (InlineStr)\",\"value_str\":\"100\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/100\",\"directory_name\":\"Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/100\",\"title\":\"Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/100\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/100/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":36.52259361854252,\"upper_bound\":38.221711985463465},\"point_estimate\":37.38515006694002,\"standard_error\":0.43130946514270985},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":36.53382527217794,\"upper_bound\":38.87596906613797},\"point_estimate\":37.731033677647275,\"standard_error\":0.4985305818576538},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.011476893617172,\"upper_bound\":5.6781187491405},\"point_estimate\":4.607634585260368,\"standard_error\":0.7090224888926004},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":38.40603808539562,\"upper_bound\":39.86768625217825},\"point_estimate\":39.14735473580421,\"standard_error\":0.3722929567907313},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.678336476843178,\"upper_bound\":4.929478859334827},\"point_estimate\":4.337489414995687,\"standard_error\":0.31888916908912307}}"
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    "path": "docs/criterion/Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/100/base/sample.json",
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    "content": "[16.05973605575626,25.38854176255292,50.26535698067734,59.594162687474]"
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    "path": "docs/criterion/Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/100/change/estimates.json",
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    "path": "docs/criterion/Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/100/new/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"InlineFlexStr 0.1 (InlineStr)\",\"value_str\":\"100\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/100\",\"directory_name\":\"Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/100\",\"title\":\"Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/100\"}"
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    "path": "docs/criterion/Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/100/new/estimates.json",
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    "path": "docs/criterion/Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/100/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[11376.0,22752.0,34128.0,45504.0,56880.0,68256.0,79632.0,91008.0,102384.0,113760.0,125136.0,136512.0,147888.0,159264.0,170640.0,182016.0,193392.0,204768.0,216144.0,227520.0,238896.0,250272.0,261648.0,273024.0,284400.0,295776.0,307152.0,318528.0,329904.0,341280.0,352656.0,364032.0,375408.0,386784.0,398160.0,409536.0,420912.0,432288.0,443664.0,455040.0,466416.0,477792.0,489168.0,500544.0,511920.0,523296.0,534672.0,546048.0,557424.0,568800.0,580176.0,591552.0,602928.0,614304.0,625680.0,637056.0,648432.0,659808.0,671184.0,682560.0,693936.0,705312.0,716688.0,728064.0,739440.0,750816.0,762192.0,773568.0,784944.0,796320.0,807696.0,819072.0,830448.0,841824.0,853200.0,864576.0,875952.0,887328.0,898704.0,910080.0,921456.0,932832.0,944208.0,955584.0,966960.0,978336.0,989712.0,1001088.0,1012464.0,1023840.0,1035216.0,1046592.0,1057968.0,1069344.0,1080720.0,1092096.0,1103472.0,1114848.0,1126224.0,1137600.0],\"times\":[295833.0,971541.0,858500.0,1146498.0,1847209.0,2052582.0,2303168.0,3275543.0,4250458.0,3965042.0,3979916.0,5232916.0,6115580.0,5954458.0,6142333.0,6302376.0,7653457.0,7425376.0,7163791.0,6758168.0,8487583.0,9151999.0,10436334.0,10315627.0,11116209.0,11202249.0,9851377.0,9542500.0,11190206.0,11513958.0,15136251.0,15127584.0,14862251.0,13956043.0,13734377.0,12755875.0,13849083.0,14248084.0,18416500.0,18584293.0,18942082.0,17744958.0,16616625.0,15435001.0,17118500.0,17225251.0,23166918.0,22509833.0,22322166.0,20978958.0,19306999.0,18597915.0,20950541.0,22442875.0,27813251.0,26798001.0,25290125.0,24529710.0,24502917.0,23163581.0,25616667.0,25529792.0,30989960.0,30733750.0,30616335.0,28220043.0,28718792.0,27679374.0,28656836.0,30661498.0,35252458.0,34712626.0,34500290.0,34130625.0,33644125.0,31301543.0,31725999.0,31900083.0,41010748.0,37798542.0,38720875.0,36862708.0,36707001.0,34902751.0,36608000.0,37093540.0,43271293.0,42754167.0,42013709.0,39129748.0,40529832.0,39102627.0,41624541.0,40404042.0,47956751.0,45668916.0,46851916.0,44137709.0,44871416.0,42993168.0]}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/100/new/tukey.json",
    "content": "[16.05973605575626,25.38854176255292,50.26535698067734,59.594162687474]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/100/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/100 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/100</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">38.406 ns</td>\n                                <td>39.147 ns</td>\n                                <td class=\"ci-bound\">39.868 ns</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.4861221</td>\n                                <td>0.4996165</td>\n                                <td class=\"ci-bound\">0.4868560</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">36.523 ns</td>\n                                <td>37.385 ns</td>\n                                <td class=\"ci-bound\">38.222 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">3.6783 ns</td>\n                                <td>4.3375 ns</td>\n                                <td class=\"ci-bound\">4.9295 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">36.534 ns</td>\n                                <td>37.731 ns</td>\n                                <td class=\"ci-bound\">38.876 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">3.0115 ns</td>\n                                <td>4.6076 ns</td>\n                                <td class=\"ci-bound\">5.6781 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−3.0879%</td>\n                            <td>+0.0461%</td>\n                            <td class=\"ci-bound\">+3.2339%</td>\n                            <td>(p = 0.98 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/20/base/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"InlineFlexStr 0.1 (InlineStr)\",\"value_str\":\"20\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/20\",\"directory_name\":\"Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/20\",\"title\":\"Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/20\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/20/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":36.74496588883076,\"upper_bound\":38.32890294486678},\"point_estimate\":37.5179306082909,\"standard_error\":0.4024504290269697},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":37.17072584376545,\"upper_bound\":38.41391847618801},\"point_estimate\":37.95593456713475,\"standard_error\":0.3365565940548534},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.705776461927957,\"upper_bound\":5.098215306798602},\"point_estimate\":4.047355293199363,\"standard_error\":0.5729998661071557},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":37.9767311142299,\"upper_bound\":39.40980451419369},\"point_estimate\":38.69877850351364,\"standard_error\":0.36583697056573594},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.2091197171014025,\"upper_bound\":5.09753415324587},\"point_estimate\":4.0537910556318755,\"standard_error\":0.5151943900791771}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/20/base/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[14151.0,28302.0,42453.0,56604.0,70755.0,84906.0,99057.0,113208.0,127359.0,141510.0,155661.0,169812.0,183963.0,198114.0,212265.0,226416.0,240567.0,254718.0,268869.0,283020.0,297171.0,311322.0,325473.0,339624.0,353775.0,367926.0,382077.0,396228.0,410379.0,424530.0,438681.0,452832.0,466983.0,481134.0,495285.0,509436.0,523587.0,537738.0,551889.0,566040.0,580191.0,594342.0,608493.0,622644.0,636795.0,650946.0,665097.0,679248.0,693399.0,707550.0,721701.0,735852.0,750003.0,764154.0,778305.0,792456.0,806607.0,820758.0,834909.0,849060.0,863211.0,877362.0,891513.0,905664.0,919815.0,933966.0,948117.0,962268.0,976419.0,990570.0,1004721.0,1018872.0,1033023.0,1047174.0,1061325.0,1075476.0,1089627.0,1103778.0,1117929.0,1132080.0,1146231.0,1160382.0,1174533.0,1188684.0,1202835.0,1216986.0,1231137.0,1245288.0,1259439.0,1273590.0,1287741.0,1301892.0,1316043.0,1330194.0,1344345.0,1358496.0,1372647.0,1386798.0,1400949.0,1415100.0],\"times\":[821624.0,886375.0,1330000.0,2171794.0,2296875.0,2730750.0,3148624.0,4739914.0,4543666.0,4506208.0,4931249.0,5341959.0,5858669.0,6309333.0,6698375.0,7264585.0,7740833.0,8668459.0,8513833.0,8918960.0,9432666.0,10257540.0,13982709.0,13370501.0,13958664.0,14178707.0,14543334.0,14495166.0,14592374.0,14740417.0,14811708.0,15193168.0,15400252.0,19182084.0,19118708.0,19164750.0,20037915.0,20623958.0,20551625.0,21661209.0,21599249.0,22547625.0,23157999.0,23611710.0,23745917.0,27923917.0,27895833.0,27517583.0,28249792.0,27074374.0,26446458.0,27190958.0,26107582.0,25966708.0,26414416.0,27846252.0,31571461.0,31061668.0,32000291.0,32452414.0,34243417.0,33756209.0,37379749.0,38107834.0,37434751.0,38151833.0,39481416.0,40389001.0,42047917.0,40483500.0,40806585.0,39944626.0,40760125.0,40959043.0,38417793.0,37872499.0,37560249.0,37422625.0,41478250.0,42572667.0,44141834.0,45268793.0,43854375.0,44942376.0,46582793.0,53211210.0,52396460.0,53319084.0,52075458.0,53433791.0,55210875.0,52827126.0,53386126.0,53154168.0,51911416.0,51588542.0,50309457.0,50055917.0,49365832.0,48580874.0]}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/20/base/tukey.json",
    "content": "[18.068690747858582,26.252166240611192,48.07476755461815,56.25824304737076]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/20/change/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.026105252079156833,\"upper_bound\":0.029707167923714285},\"point_estimate\":0.0006410881561400572,\"standard_error\":0.014252227764877992},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.025381894707738217,\"upper_bound\":0.03193292530773273},\"point_estimate\":-0.002867014713570093,\"standard_error\":0.014021848037524254}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/20/new/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"InlineFlexStr 0.1 (InlineStr)\",\"value_str\":\"20\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/20\",\"directory_name\":\"Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/20\",\"title\":\"Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/20\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/20/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":36.74496588883076,\"upper_bound\":38.32890294486678},\"point_estimate\":37.5179306082909,\"standard_error\":0.4024504290269697},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":37.17072584376545,\"upper_bound\":38.41391847618801},\"point_estimate\":37.95593456713475,\"standard_error\":0.3365565940548534},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.705776461927957,\"upper_bound\":5.098215306798602},\"point_estimate\":4.047355293199363,\"standard_error\":0.5729998661071557},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":37.9767311142299,\"upper_bound\":39.40980451419369},\"point_estimate\":38.69877850351364,\"standard_error\":0.36583697056573594},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.2091197171014025,\"upper_bound\":5.09753415324587},\"point_estimate\":4.0537910556318755,\"standard_error\":0.5151943900791771}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/20/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[14151.0,28302.0,42453.0,56604.0,70755.0,84906.0,99057.0,113208.0,127359.0,141510.0,155661.0,169812.0,183963.0,198114.0,212265.0,226416.0,240567.0,254718.0,268869.0,283020.0,297171.0,311322.0,325473.0,339624.0,353775.0,367926.0,382077.0,396228.0,410379.0,424530.0,438681.0,452832.0,466983.0,481134.0,495285.0,509436.0,523587.0,537738.0,551889.0,566040.0,580191.0,594342.0,608493.0,622644.0,636795.0,650946.0,665097.0,679248.0,693399.0,707550.0,721701.0,735852.0,750003.0,764154.0,778305.0,792456.0,806607.0,820758.0,834909.0,849060.0,863211.0,877362.0,891513.0,905664.0,919815.0,933966.0,948117.0,962268.0,976419.0,990570.0,1004721.0,1018872.0,1033023.0,1047174.0,1061325.0,1075476.0,1089627.0,1103778.0,1117929.0,1132080.0,1146231.0,1160382.0,1174533.0,1188684.0,1202835.0,1216986.0,1231137.0,1245288.0,1259439.0,1273590.0,1287741.0,1301892.0,1316043.0,1330194.0,1344345.0,1358496.0,1372647.0,1386798.0,1400949.0,1415100.0],\"times\":[821624.0,886375.0,1330000.0,2171794.0,2296875.0,2730750.0,3148624.0,4739914.0,4543666.0,4506208.0,4931249.0,5341959.0,5858669.0,6309333.0,6698375.0,7264585.0,7740833.0,8668459.0,8513833.0,8918960.0,9432666.0,10257540.0,13982709.0,13370501.0,13958664.0,14178707.0,14543334.0,14495166.0,14592374.0,14740417.0,14811708.0,15193168.0,15400252.0,19182084.0,19118708.0,19164750.0,20037915.0,20623958.0,20551625.0,21661209.0,21599249.0,22547625.0,23157999.0,23611710.0,23745917.0,27923917.0,27895833.0,27517583.0,28249792.0,27074374.0,26446458.0,27190958.0,26107582.0,25966708.0,26414416.0,27846252.0,31571461.0,31061668.0,32000291.0,32452414.0,34243417.0,33756209.0,37379749.0,38107834.0,37434751.0,38151833.0,39481416.0,40389001.0,42047917.0,40483500.0,40806585.0,39944626.0,40760125.0,40959043.0,38417793.0,37872499.0,37560249.0,37422625.0,41478250.0,42572667.0,44141834.0,45268793.0,43854375.0,44942376.0,46582793.0,53211210.0,52396460.0,53319084.0,52075458.0,53433791.0,55210875.0,52827126.0,53386126.0,53154168.0,51911416.0,51588542.0,50309457.0,50055917.0,49365832.0,48580874.0]}"
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  {
    "path": "docs/criterion/Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/20/new/tukey.json",
    "content": "[18.068690747858582,26.252166240611192,48.07476755461815,56.25824304737076]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/20/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/20 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/20</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">37.977 ns</td>\n                                <td>38.699 ns</td>\n                                <td class=\"ci-bound\">39.410 ns</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.4482295</td>\n                                <td>0.4646594</td>\n                                <td class=\"ci-bound\">0.4487101</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">36.745 ns</td>\n                                <td>37.518 ns</td>\n                                <td class=\"ci-bound\">38.329 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">3.2091 ns</td>\n                                <td>4.0538 ns</td>\n                                <td class=\"ci-bound\">5.0975 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">37.171 ns</td>\n                                <td>37.956 ns</td>\n                                <td class=\"ci-bound\">38.414 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">2.7058 ns</td>\n                                <td>4.0474 ns</td>\n                                <td class=\"ci-bound\">5.0982 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−2.6105%</td>\n                            <td>+0.0641%</td>\n                            <td class=\"ci-bound\">+2.9707%</td>\n                            <td>(p = 0.96 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
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  {
    "path": "docs/criterion/Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/500/base/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"InlineFlexStr 0.1 (InlineStr)\",\"value_str\":\"500\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/500\",\"directory_name\":\"Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/500\",\"title\":\"Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/500\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/500/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":46.54620997579402,\"upper_bound\":49.325518515466044},\"point_estimate\":47.929151951649686,\"standard_error\":0.7096666832202052},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":45.717959478336404,\"upper_bound\":49.53980277524903},\"point_estimate\":47.68882191362735,\"standard_error\":1.0949315696939912},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":5.727338885628799,\"upper_bound\":8.997021340010305},\"point_estimate\":7.579829130653172,\"standard_error\":0.8162541407820334},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":51.40857082910687,\"upper_bound\":54.52624648924225},\"point_estimate\":53.054500919411,\"standard_error\":0.796920162059359},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":6.178520515688743,\"upper_bound\":8.0180362701597},\"point_estimate\":7.146676038255786,\"standard_error\":0.4708522796093928}}"
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    "content": "[12.286636901823137,27.498419055933066,68.06317146689288,83.27495362100281]"
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    "path": "docs/criterion/Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/500/change/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.03270806869155489,\"upper_bound\":0.05680563335197464},\"point_estimate\":0.01153418259201544,\"standard_error\":0.022767374879005518},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.04772450746031143,\"upper_bound\":0.04815982983526079},\"point_estimate\":-0.0003218383367994404,\"standard_error\":0.025775905210734494}}"
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    "path": "docs/criterion/Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/500/new/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"InlineFlexStr 0.1 (InlineStr)\",\"value_str\":\"500\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/500\",\"directory_name\":\"Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/500\",\"title\":\"Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/500\"}"
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    "path": "docs/criterion/Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/500/new/estimates.json",
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    "path": "docs/criterion/Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/500/new/sample.json",
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  {
    "path": "docs/criterion/Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/500/new/tukey.json",
    "content": "[12.286636901823137,27.498419055933066,68.06317146689288,83.27495362100281]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/500/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/500 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/500</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">51.409 ns</td>\n                                <td>53.055 ns</td>\n                                <td class=\"ci-bound\">54.526 ns</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.4656375</td>\n                                <td>0.4827120</td>\n                                <td class=\"ci-bound\">0.4689627</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">46.546 ns</td>\n                                <td>47.929 ns</td>\n                                <td class=\"ci-bound\">49.326 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">6.1785 ns</td>\n                                <td>7.1467 ns</td>\n                                <td class=\"ci-bound\">8.0180 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">45.718 ns</td>\n                                <td>47.689 ns</td>\n                                <td class=\"ci-bound\">49.540 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">5.7273 ns</td>\n                                <td>7.5798 ns</td>\n                                <td class=\"ci-bound\">8.9970 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−3.2708%</td>\n                            <td>+1.1534%</td>\n                            <td class=\"ci-bound\">+5.6806%</td>\n                            <td>(p = 0.62 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/InlineFlexStr 0.1 (InlineStr) Summary - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)</h2>\n        <h3>Violin Plot</h3>\n        <a href=\"violin.svg\">\n            <img src=\"violin.svg\" alt=\"Violin Plot\" />\n        </a>\n        <p>This chart shows the relationship between function/parameter and iteration time. The thickness of the shaded\n            region indicates the probability that a measurement of the given function/parameter would take a particular\n            length of time.</p>\n        <h3>Line Chart</h3>\n        <img src=\"lines.svg\" alt=\"Line Chart\" />\n        <p>This chart shows the mean measured time for each function as the input (or the size of the input) increases.</p>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/0/report/index.html\">\n                <h4>Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/0/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/0/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/10/report/index.html\">\n                <h4>Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/10/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/10/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/20/report/index.html\">\n                <h4>Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/20/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/20/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/100/report/index.html\">\n                <h4>Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/100/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/100/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/500/report/index.html\">\n                <h4>Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/500/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/500/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Rc_str_/0/base/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"Rc<str>\",\"value_str\":\"0\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/Rc<str>/0\",\"directory_name\":\"Import as owned and destroy/Rc_str_/0\",\"title\":\"Import as owned and destroy/Rc<str>/0\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Rc_str_/0/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":24.54286338615167,\"upper_bound\":24.65101970526463},\"point_estimate\":24.593094153432812,\"standard_error\":0.027506531172970375},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":24.483012291931104,\"upper_bound\":24.587153835668943},\"point_estimate\":24.512038722358213,\"standard_error\":0.025945482097245655},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.13812310177621126,\"upper_bound\":0.23476344785334471},\"point_estimate\":0.18344596093347354,\"standard_error\":0.023145571320929422},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":24.54120789972577,\"upper_bound\":24.622608356176087},\"point_estimate\":24.580976388525972,\"standard_error\":0.020799423639189015},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.17407579880212964,\"upper_bound\":0.38184465991673855},\"point_estimate\":0.27606821587438507,\"standard_error\":0.056008118614581805}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Rc_str_/0/base/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[33845.0,67690.0,101535.0,135380.0,169225.0,203070.0,236915.0,270760.0,304605.0,338450.0,372295.0,406140.0,439985.0,473830.0,507675.0,541520.0,575365.0,609210.0,643055.0,676900.0,710745.0,744590.0,778435.0,812280.0,846125.0,879970.0,913815.0,947660.0,981505.0,1015350.0,1049195.0,1083040.0,1116885.0,1150730.0,1184575.0,1218420.0,1252265.0,1286110.0,1319955.0,1353800.0,1387645.0,1421490.0,1455335.0,1489180.0,1523025.0,1556870.0,1590715.0,1624560.0,1658405.0,1692250.0,1726095.0,1759940.0,1793785.0,1827630.0,1861475.0,1895320.0,1929165.0,1963010.0,1996855.0,2030700.0,2064545.0,2098390.0,2132235.0,2166080.0,2199925.0,2233770.0,2267615.0,2301460.0,2335305.0,2369150.0,2402995.0,2436840.0,2470685.0,2504530.0,2538375.0,2572220.0,2606065.0,2639910.0,2673755.0,2707600.0,2741445.0,2775290.0,2809135.0,2842980.0,2876825.0,2910670.0,2944515.0,2978360.0,3012205.0,3046050.0,3079895.0,3113740.0,3147585.0,3181430.0,3215275.0,3249120.0,3282965.0,3316810.0,3350655.0,3384500.0],\"times\":[891085.0,1672836.0,2458877.0,3455582.0,4261584.0,5073833.0,5862335.0,6734959.0,7418042.0,8288457.0,9210790.0,9948958.0,10730376.0,11718918.0,12454957.0,13263251.0,14022752.0,14823874.0,15761584.0,16775000.0,17523209.0,18184167.0,19077543.0,19866249.0,20611165.0,21775082.0,22361833.0,23442457.0,23916916.0,24711169.0,25590540.0,26419417.0,27378874.0,28466500.0,29277666.0,29705625.0,30587207.0,31530416.0,32276540.0,32989959.0,33842667.0,34656250.0,35549374.0,36742584.0,37180916.0,38485708.0,39182832.0,39595208.0,40501166.0,42046914.0,42104001.0,43506127.0,44186541.0,45050167.0,45363207.0,47719128.0,47044876.0,47994751.0,48758083.0,49600290.0,50205707.0,51417000.0,52315708.0,53012958.0,54119292.0,54710417.0,55740373.0,58018667.0,57522333.0,57776501.0,59097459.0,59608750.0,61632041.0,61503127.0,62287876.0,62866792.0,63797333.0,65750749.0,66107709.0,66227042.0,67830875.0,68150377.0,69115293.0,69888084.0,70137166.0,71714959.0,72544877.0,73435000.0,73723999.0,74608789.0,75822917.0,76037209.0,77942623.0,78118458.0,79593459.0,80248708.0,80329210.0,81205500.0,83056875.0,82955291.0]}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Rc_str_/0/base/tukey.json",
    "content": "[23.545493065489275,23.983620627678683,25.151960793517098,25.590088355706502]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Rc_str_/0/change/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.004373679465354679,\"upper_bound\":0.004888693008841759},\"point_estimate\":0.0007235830050367209,\"standard_error\":0.0023808986692182253},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.0006365407943281776,\"upper_bound\":0.004337071274351345},\"point_estimate\":0.001568840824666129,\"standard_error\":0.0012896182051722542}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Rc_str_/0/new/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"Rc<str>\",\"value_str\":\"0\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/Rc<str>/0\",\"directory_name\":\"Import as owned and destroy/Rc_str_/0\",\"title\":\"Import as owned and destroy/Rc<str>/0\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Rc_str_/0/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":24.54286338615167,\"upper_bound\":24.65101970526463},\"point_estimate\":24.593094153432812,\"standard_error\":0.027506531172970375},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":24.483012291931104,\"upper_bound\":24.587153835668943},\"point_estimate\":24.512038722358213,\"standard_error\":0.025945482097245655},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.13812310177621126,\"upper_bound\":0.23476344785334471},\"point_estimate\":0.18344596093347354,\"standard_error\":0.023145571320929422},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":24.54120789972577,\"upper_bound\":24.622608356176087},\"point_estimate\":24.580976388525972,\"standard_error\":0.020799423639189015},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.17407579880212964,\"upper_bound\":0.38184465991673855},\"point_estimate\":0.27606821587438507,\"standard_error\":0.056008118614581805}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Rc_str_/0/new/sample.json",
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    "content": "[23.545493065489275,23.983620627678683,25.151960793517098,25.590088355706502]"
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  {
    "path": "docs/criterion/Import as owned and destroy/Rc_str_/0/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/Rc&lt;str&gt;/0 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/Rc&lt;str&gt;/0</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">24.541 ns</td>\n                                <td>24.581 ns</td>\n                                <td class=\"ci-bound\">24.623 ns</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.9931353</td>\n                                <td>0.9934958</td>\n                                <td class=\"ci-bound\">0.9931007</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">24.543 ns</td>\n                                <td>24.593 ns</td>\n                                <td class=\"ci-bound\">24.651 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">174.08 ps</td>\n                                <td>276.07 ps</td>\n                                <td class=\"ci-bound\">381.84 ps</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">24.483 ns</td>\n                                <td>24.512 ns</td>\n                                <td class=\"ci-bound\">24.587 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">138.12 ps</td>\n                                <td>183.45 ps</td>\n                                <td class=\"ci-bound\">234.76 ps</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−0.4374%</td>\n                            <td>+0.0724%</td>\n                            <td class=\"ci-bound\">+0.4889%</td>\n                            <td>(p = 0.79 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
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    "path": "docs/criterion/Import as owned and destroy/Rc_str_/10/base/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"Rc<str>\",\"value_str\":\"10\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/Rc<str>/10\",\"directory_name\":\"Import as owned and destroy/Rc_str_/10\",\"title\":\"Import as owned and destroy/Rc<str>/10\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Rc_str_/10/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":53.056023492884286,\"upper_bound\":54.46141955304666},\"point_estimate\":53.75017238124202,\"standard_error\":0.3590694976641455},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":51.229908308213865,\"upper_bound\":54.00395374542981},\"point_estimate\":52.35664790899518,\"standard_error\":0.7170999627349235},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":1.6542959787715408,\"upper_bound\":4.887155929767602},\"point_estimate\":3.2141849111660488,\"standard_error\":0.8854971052356692},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":54.72079962731003,\"upper_bound\":55.999323588077374},\"point_estimate\":55.40826383487982,\"standard_error\":0.3260964900853763},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.181505716153943,\"upper_bound\":3.9669638803549874},\"point_estimate\":3.6024113584113637,\"standard_error\":0.20038292813499894}}"
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    "content": "[30.90386508756557,40.72328763237812,66.90841441854491,76.72783696335745]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Rc_str_/10/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/Rc&lt;str&gt;/10 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/Rc&lt;str&gt;/10</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">54.721 ns</td>\n                                <td>55.408 ns</td>\n                                <td class=\"ci-bound\">55.999 ns</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.7459517</td>\n                                <td>0.7560599</td>\n                                <td class=\"ci-bound\">0.7485618</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">53.056 ns</td>\n                                <td>53.750 ns</td>\n                                <td class=\"ci-bound\">54.461 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">3.1815 ns</td>\n                                <td>3.6024 ns</td>\n                                <td class=\"ci-bound\">3.9670 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">51.230 ns</td>\n                                <td>52.357 ns</td>\n                                <td class=\"ci-bound\">54.004 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">1.6543 ns</td>\n                                <td>3.2142 ns</td>\n                                <td class=\"ci-bound\">4.8872 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−4.3368%</td>\n                            <td>−2.6079%</td>\n                            <td class=\"ci-bound\">−0.7585%</td>\n                            <td>(p = 0.01 &lt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                Change within noise threshold.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Rc_str_/100/base/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"Rc<str>\",\"value_str\":\"100\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/Rc<str>/100\",\"directory_name\":\"Import as owned and destroy/Rc_str_/100\",\"title\":\"Import as owned and destroy/Rc<str>/100\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Rc_str_/100/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":61.565419264758496,\"upper_bound\":63.28389325900981},\"point_estimate\":62.41693408919857,\"standard_error\":0.4376746943141229},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":61.291642092846914,\"upper_bound\":63.59362691149212},\"point_estimate\":62.51199215759358,\"standard_error\":0.6304642887032212},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.453061792177449,\"upper_bound\":5.411907844141861},\"point_estimate\":4.753563102814072,\"standard_error\":0.4963415579518197},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":62.49919538228156,\"upper_bound\":64.08185343643775},\"point_estimate\":63.30080431318207,\"standard_error\":0.403868007813921},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.7162819381033074,\"upper_bound\":5.080158631527956},\"point_estimate\":4.407040623206113,\"standard_error\":0.3491309504213553}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Rc_str_/100/base/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[8632.0,17264.0,25896.0,34528.0,43160.0,51792.0,60424.0,69056.0,77688.0,86320.0,94952.0,103584.0,112216.0,120848.0,129480.0,138112.0,146744.0,155376.0,164008.0,172640.0,181272.0,189904.0,198536.0,207168.0,215800.0,224432.0,233064.0,241696.0,250328.0,258960.0,267592.0,276224.0,284856.0,293488.0,302120.0,310752.0,319384.0,328016.0,336648.0,345280.0,353912.0,362544.0,371176.0,379808.0,388440.0,397072.0,405704.0,414336.0,422968.0,431600.0,440232.0,448864.0,457496.0,466128.0,474760.0,483392.0,492024.0,500656.0,509288.0,517920.0,526552.0,535184.0,543816.0,552448.0,561080.0,569712.0,578344.0,586976.0,595608.0,604240.0,612872.0,621504.0,630136.0,638768.0,647400.0,656032.0,664664.0,673296.0,681928.0,690560.0,699192.0,707824.0,716456.0,725088.0,733720.0,742352.0,750984.0,759616.0,768248.0,776880.0,785512.0,794144.0,802776.0,811408.0,820040.0,828672.0,837304.0,845936.0,854568.0,863200.0],\"times\":[469832.0,1341042.0,1391918.0,1858956.0,2777916.0,3410377.0,3258166.0,3686208.0,4160998.0,4605874.0,6823542.0,6543538.0,7052209.0,7388873.0,7652331.0,8783043.0,9270749.0,9757208.0,10522914.0,10683499.0,10980876.0,12250835.0,12411043.0,12477748.0,12474084.0,13083125.0,13962752.0,14555043.0,15938126.0,17109999.0,17331417.0,18926876.0,18509125.0,18249210.0,18165541.0,18144462.0,18021915.0,19296540.0,19820791.0,23226541.0,23803750.0,23917834.0,24387543.0,24178624.0,23837001.0,23853918.0,22948250.0,23994208.0,24984708.0,25000126.0,30916792.0,30009501.0,30313208.0,30714710.0,29988209.0,29121207.0,28493499.0,28725751.0,29422833.0,30087542.0,36342834.0,37105289.0,36011084.0,36183790.0,35959333.0,34918584.0,34290582.0,33640501.0,36298084.0,36493249.0,36972834.0,43457168.0,42814626.0,41952500.0,41559290.0,40630249.0,42206250.0,41524042.0,40144081.0,42747832.0,42748874.0,43149416.0,48561836.0,48310583.0,48549248.0,48230624.0,47941375.0,49119793.0,46946375.0,45950209.0,48357958.0,49642875.0,54992707.0,54321334.0,54089123.0,55092210.0,54368002.0,53104667.0,54133461.0,53181124.0]}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Rc_str_/100/base/tukey.json",
    "content": "[39.96874182626678,49.61187716614006,75.32690473913547,84.97004007900875]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Rc_str_/100/change/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.047096866172274945,\"upper_bound\":0.011887501738440899},\"point_estimate\":-0.016637843346696712,\"standard_error\":0.015023043257937723},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.023578097977171253,\"upper_bound\":0.027511250515668273},\"point_estimate\":0.004161959831638695,\"standard_error\":0.013128346620204116}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Rc_str_/100/new/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"Rc<str>\",\"value_str\":\"100\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/Rc<str>/100\",\"directory_name\":\"Import as owned and destroy/Rc_str_/100\",\"title\":\"Import as owned and destroy/Rc<str>/100\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Rc_str_/100/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":61.565419264758496,\"upper_bound\":63.28389325900981},\"point_estimate\":62.41693408919857,\"standard_error\":0.4376746943141229},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":61.291642092846914,\"upper_bound\":63.59362691149212},\"point_estimate\":62.51199215759358,\"standard_error\":0.6304642887032212},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.453061792177449,\"upper_bound\":5.411907844141861},\"point_estimate\":4.753563102814072,\"standard_error\":0.4963415579518197},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":62.49919538228156,\"upper_bound\":64.08185343643775},\"point_estimate\":63.30080431318207,\"standard_error\":0.403868007813921},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.7162819381033074,\"upper_bound\":5.080158631527956},\"point_estimate\":4.407040623206113,\"standard_error\":0.3491309504213553}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Rc_str_/100/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[8632.0,17264.0,25896.0,34528.0,43160.0,51792.0,60424.0,69056.0,77688.0,86320.0,94952.0,103584.0,112216.0,120848.0,129480.0,138112.0,146744.0,155376.0,164008.0,172640.0,181272.0,189904.0,198536.0,207168.0,215800.0,224432.0,233064.0,241696.0,250328.0,258960.0,267592.0,276224.0,284856.0,293488.0,302120.0,310752.0,319384.0,328016.0,336648.0,345280.0,353912.0,362544.0,371176.0,379808.0,388440.0,397072.0,405704.0,414336.0,422968.0,431600.0,440232.0,448864.0,457496.0,466128.0,474760.0,483392.0,492024.0,500656.0,509288.0,517920.0,526552.0,535184.0,543816.0,552448.0,561080.0,569712.0,578344.0,586976.0,595608.0,604240.0,612872.0,621504.0,630136.0,638768.0,647400.0,656032.0,664664.0,673296.0,681928.0,690560.0,699192.0,707824.0,716456.0,725088.0,733720.0,742352.0,750984.0,759616.0,768248.0,776880.0,785512.0,794144.0,802776.0,811408.0,820040.0,828672.0,837304.0,845936.0,854568.0,863200.0],\"times\":[469832.0,1341042.0,1391918.0,1858956.0,2777916.0,3410377.0,3258166.0,3686208.0,4160998.0,4605874.0,6823542.0,6543538.0,7052209.0,7388873.0,7652331.0,8783043.0,9270749.0,9757208.0,10522914.0,10683499.0,10980876.0,12250835.0,12411043.0,12477748.0,12474084.0,13083125.0,13962752.0,14555043.0,15938126.0,17109999.0,17331417.0,18926876.0,18509125.0,18249210.0,18165541.0,18144462.0,18021915.0,19296540.0,19820791.0,23226541.0,23803750.0,23917834.0,24387543.0,24178624.0,23837001.0,23853918.0,22948250.0,23994208.0,24984708.0,25000126.0,30916792.0,30009501.0,30313208.0,30714710.0,29988209.0,29121207.0,28493499.0,28725751.0,29422833.0,30087542.0,36342834.0,37105289.0,36011084.0,36183790.0,35959333.0,34918584.0,34290582.0,33640501.0,36298084.0,36493249.0,36972834.0,43457168.0,42814626.0,41952500.0,41559290.0,40630249.0,42206250.0,41524042.0,40144081.0,42747832.0,42748874.0,43149416.0,48561836.0,48310583.0,48549248.0,48230624.0,47941375.0,49119793.0,46946375.0,45950209.0,48357958.0,49642875.0,54992707.0,54321334.0,54089123.0,55092210.0,54368002.0,53104667.0,54133461.0,53181124.0]}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Rc_str_/100/new/tukey.json",
    "content": "[39.96874182626678,49.61187716614006,75.32690473913547,84.97004007900875]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Rc_str_/100/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/Rc&lt;str&gt;/100 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/Rc&lt;str&gt;/100</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">62.499 ns</td>\n                                <td>63.301 ns</td>\n                                <td class=\"ci-bound\">64.082 ns</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.6919610</td>\n                                <td>0.7038983</td>\n                                <td class=\"ci-bound\">0.6925558</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">61.565 ns</td>\n                                <td>62.417 ns</td>\n                                <td class=\"ci-bound\">63.284 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">3.7163 ns</td>\n                                <td>4.4070 ns</td>\n                                <td class=\"ci-bound\">5.0802 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">61.292 ns</td>\n                                <td>62.512 ns</td>\n                                <td class=\"ci-bound\">63.594 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">3.4531 ns</td>\n                                <td>4.7536 ns</td>\n                                <td class=\"ci-bound\">5.4119 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−4.7097%</td>\n                            <td>−1.6638%</td>\n                            <td class=\"ci-bound\">+1.1888%</td>\n                            <td>(p = 0.29 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
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    "path": "docs/criterion/Import as owned and destroy/Rc_str_/20/base/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"Rc<str>\",\"value_str\":\"20\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/Rc<str>/20\",\"directory_name\":\"Import as owned and destroy/Rc_str_/20\",\"title\":\"Import as owned and destroy/Rc<str>/20\"}"
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    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":58.09508059904306,\"upper_bound\":59.519597596970414},\"point_estimate\":58.80367066509432,\"standard_error\":0.3638408779885765},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":58.45476231985123,\"upper_bound\":59.77199700698474},\"point_estimate\":59.335612199246725,\"standard_error\":0.33463591204376775},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.686657023034039,\"upper_bound\":5.155658898579058},\"point_estimate\":4.023708459597181,\"standard_error\":0.6480863558750758},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":59.65557489655121,\"upper_bound\":60.947672640998675},\"point_estimate\":60.30521320129265,\"standard_error\":0.32943687578379754},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.1484814643899743,\"upper_bound\":4.142694379091332},\"point_estimate\":3.653488994354,\"standard_error\":0.25375658011440116}}"
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    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.02133398821070776,\"upper_bound\":0.013037305615249717},\"point_estimate\":-0.003902683323973699,\"standard_error\":0.008779866231938223},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.026257995920550004,\"upper_bound\":0.019399262363624326},\"point_estimate\":-0.010674584459401837,\"standard_error\":0.01142881720523971}}"
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    "path": "docs/criterion/Import as owned and destroy/Rc_str_/20/new/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"Rc<str>\",\"value_str\":\"20\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/Rc<str>/20\",\"directory_name\":\"Import as owned and destroy/Rc_str_/20\",\"title\":\"Import as owned and destroy/Rc<str>/20\"}"
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    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":58.09508059904306,\"upper_bound\":59.519597596970414},\"point_estimate\":58.80367066509432,\"standard_error\":0.3638408779885765},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":58.45476231985123,\"upper_bound\":59.77199700698474},\"point_estimate\":59.335612199246725,\"standard_error\":0.33463591204376775},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":2.686657023034039,\"upper_bound\":5.155658898579058},\"point_estimate\":4.023708459597181,\"standard_error\":0.6480863558750758},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":59.65557489655121,\"upper_bound\":60.947672640998675},\"point_estimate\":60.30521320129265,\"standard_error\":0.32943687578379754},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.1484814643899743,\"upper_bound\":4.142694379091332},\"point_estimate\":3.653488994354,\"standard_error\":0.25375658011440116}}"
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    "path": "docs/criterion/Import as owned and destroy/Rc_str_/20/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[10755.0,21510.0,32265.0,43020.0,53775.0,64530.0,75285.0,86040.0,96795.0,107550.0,118305.0,129060.0,139815.0,150570.0,161325.0,172080.0,182835.0,193590.0,204345.0,215100.0,225855.0,236610.0,247365.0,258120.0,268875.0,279630.0,290385.0,301140.0,311895.0,322650.0,333405.0,344160.0,354915.0,365670.0,376425.0,387180.0,397935.0,408690.0,419445.0,430200.0,440955.0,451710.0,462465.0,473220.0,483975.0,494730.0,505485.0,516240.0,526995.0,537750.0,548505.0,559260.0,570015.0,580770.0,591525.0,602280.0,613035.0,623790.0,634545.0,645300.0,656055.0,666810.0,677565.0,688320.0,699075.0,709830.0,720585.0,731340.0,742095.0,752850.0,763605.0,774360.0,785115.0,795870.0,806625.0,817380.0,828135.0,838890.0,849645.0,860400.0,871155.0,881910.0,892665.0,903420.0,914175.0,924930.0,935685.0,946440.0,957195.0,967950.0,978705.0,989460.0,1000215.0,1010970.0,1021725.0,1032480.0,1043235.0,1053990.0,1064745.0,1075500.0],\"times\":[576790.0,1498166.0,1707167.0,2806207.0,2959000.0,3550709.0,4090166.0,5089418.0,5168000.0,5702210.0,6381416.0,7045707.0,7546706.0,8209417.0,9469082.0,9244084.0,9959498.0,10486665.0,11014044.0,11631001.0,12614791.0,13007833.0,13196042.0,13791250.0,14493666.0,15397957.0,15742667.0,16300499.0,16822335.0,20595001.0,20863251.0,21831666.0,21702252.0,22300708.0,22640001.0,23050501.0,23687333.0,23743042.0,23765750.0,23983211.0,24625791.0,25749541.0,25653665.0,26389960.0,29843628.0,30154917.0,30074709.0,31403418.0,32051667.0,32346710.0,32676792.0,33471209.0,34340416.0,34704251.0,35264169.0,36444499.0,36355711.0,37253374.0,37626583.0,41164250.0,40612250.0,41749707.0,41654501.0,41953585.0,42660001.0,42421249.0,44432750.0,51017752.0,44039125.0,43257250.0,43503790.0,43546125.0,43324874.0,44395793.0,47568957.0,47930000.0,49541500.0,48588333.0,50458957.0,50093875.0,51250417.0,51757457.0,57408875.0,57566541.0,57243543.0,57426961.0,58221832.0,59200542.0,59266958.0,62822209.0,62221666.0,62091833.0,62930876.0,61358167.0,62651293.0,62359835.0,62385043.0,62179999.0,61778586.0,63806083.0]}"
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    "content": "[38.43390643841849,46.91665110452867,69.53730354748915,78.02004821359932]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Rc_str_/20/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/Rc&lt;str&gt;/20 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/Rc&lt;str&gt;/20</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">59.656 ns</td>\n                                <td>60.305 ns</td>\n                                <td class=\"ci-bound\">60.948 ns</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.7671211</td>\n                                <td>0.7771681</td>\n                                <td class=\"ci-bound\">0.7673391</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">58.095 ns</td>\n                                <td>58.804 ns</td>\n                                <td class=\"ci-bound\">59.520 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">3.1485 ns</td>\n                                <td>3.6535 ns</td>\n                                <td class=\"ci-bound\">4.1427 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">58.455 ns</td>\n                                <td>59.336 ns</td>\n                                <td class=\"ci-bound\">59.772 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">2.6867 ns</td>\n                                <td>4.0237 ns</td>\n                                <td class=\"ci-bound\">5.1557 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−2.1334%</td>\n                            <td>−0.3903%</td>\n                            <td class=\"ci-bound\">+1.3037%</td>\n                            <td>(p = 0.67 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Rc_str_/500/base/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"Rc<str>\",\"value_str\":\"500\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/Rc<str>/500\",\"directory_name\":\"Import as owned and destroy/Rc_str_/500\",\"title\":\"Import as owned and destroy/Rc<str>/500\"}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Rc_str_/500/base/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":100.71435356281668,\"upper_bound\":103.1371664951926},\"point_estimate\":101.979578968978,\"standard_error\":0.6186417032457118},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":101.60721306672527,\"upper_bound\":103.98355813599716},\"point_estimate\":102.90072511535926,\"standard_error\":0.6228461443682634},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.348100228984747,\"upper_bound\":5.824611969207249},\"point_estimate\":4.929161557629918,\"standard_error\":0.6645533703928693},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":104.34020307154701,\"upper_bound\":106.15660953638087},\"point_estimate\":105.30515064040962,\"standard_error\":0.4631386178803381},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":4.523330334465586,\"upper_bound\":7.657483659731688},\"point_estimate\":6.183442535582376,\"standard_error\":0.8009739022739261}}"
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    "path": "docs/criterion/Import as owned and destroy/Rc_str_/500/base/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[4551.0,9102.0,13653.0,18204.0,22755.0,27306.0,31857.0,36408.0,40959.0,45510.0,50061.0,54612.0,59163.0,63714.0,68265.0,72816.0,77367.0,81918.0,86469.0,91020.0,95571.0,100122.0,104673.0,109224.0,113775.0,118326.0,122877.0,127428.0,131979.0,136530.0,141081.0,145632.0,150183.0,154734.0,159285.0,163836.0,168387.0,172938.0,177489.0,182040.0,186591.0,191142.0,195693.0,200244.0,204795.0,209346.0,213897.0,218448.0,222999.0,227550.0,232101.0,236652.0,241203.0,245754.0,250305.0,254856.0,259407.0,263958.0,268509.0,273060.0,277611.0,282162.0,286713.0,291264.0,295815.0,300366.0,304917.0,309468.0,314019.0,318570.0,323121.0,327672.0,332223.0,336774.0,341325.0,345876.0,350427.0,354978.0,359529.0,364080.0,368631.0,373182.0,377733.0,382284.0,386835.0,391386.0,395937.0,400488.0,405039.0,409590.0,414141.0,418692.0,423243.0,427794.0,432345.0,436896.0,441447.0,445998.0,450549.0,455100.0],\"times\":[366167.0,709000.0,1146622.0,1413333.0,2177960.0,2464501.0,3408084.0,3336249.0,3854833.0,4200707.0,4810293.0,5564958.0,5876375.0,6611207.0,7099707.0,7619081.0,7846584.0,8389707.0,8976334.0,9276708.0,9496500.0,9710794.0,10749626.0,10838793.0,11332416.0,12390125.0,12879625.0,13327207.0,13054084.0,14154083.0,13989376.0,14234667.0,14749082.0,15394459.0,16361709.0,16822627.0,16650292.0,17197375.0,17992668.0,18471377.0,18542375.0,20034501.0,20530000.0,21051749.0,21110625.0,21808793.0,21385417.0,23427166.0,23332292.0,24454874.0,23409832.0,24607917.0,23511334.0,24749124.0,24454209.0,25434710.0,25741334.0,26582707.0,26881291.0,27116833.0,28434248.0,29980585.0,28855043.0,30090375.0,30625252.0,29093501.0,31781500.0,32086626.0,32704248.0,33251334.0,33496917.0,33255873.0,34073708.0,35453791.0,34681082.0,36686374.0,37827750.0,36982875.0,36439291.0,39381668.0,40095876.0,40946582.0,40665833.0,41031167.0,40991416.0,42009250.0,43092459.0,40999500.0,44184124.0,43998127.0,44443873.0,46138084.0,46497750.0,45987707.0,47348708.0,47906499.0,45796001.0,49226914.0,48631209.0,49554334.0]}"
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    "path": "docs/criterion/Import as owned and destroy/Rc_str_/500/base/tukey.json",
    "content": "[81.35897507385013,90.39220311538276,114.48081122613644,123.51403926766908]"
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    "path": "docs/criterion/Import as owned and destroy/Rc_str_/500/change/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":-0.0013715436873312531,\"upper_bound\":0.031284564963446206},\"point_estimate\":0.014670215901821049,\"standard_error\":0.008303468250592598},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":0.003920413434530978,\"upper_bound\":0.033012227931020474},\"point_estimate\":0.017636863522739077,\"standard_error\":0.007513977489378753}}"
  },
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    "path": "docs/criterion/Import as owned and destroy/Rc_str_/500/new/benchmark.json",
    "content": "{\"group_id\":\"Import as owned and destroy\",\"function_id\":\"Rc<str>\",\"value_str\":\"500\",\"throughput\":null,\"full_id\":\"Import as owned and destroy/Rc<str>/500\",\"directory_name\":\"Import as owned and destroy/Rc_str_/500\",\"title\":\"Import as owned and destroy/Rc<str>/500\"}"
  },
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    "path": "docs/criterion/Import as owned and destroy/Rc_str_/500/new/estimates.json",
    "content": "{\"mean\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":100.71435356281668,\"upper_bound\":103.1371664951926},\"point_estimate\":101.979578968978,\"standard_error\":0.6186417032457118},\"median\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":101.60721306672527,\"upper_bound\":103.98355813599716},\"point_estimate\":102.90072511535926,\"standard_error\":0.6228461443682634},\"median_abs_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":3.348100228984747,\"upper_bound\":5.824611969207249},\"point_estimate\":4.929161557629918,\"standard_error\":0.6645533703928693},\"slope\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":104.34020307154701,\"upper_bound\":106.15660953638087},\"point_estimate\":105.30515064040962,\"standard_error\":0.4631386178803381},\"std_dev\":{\"confidence_interval\":{\"confidence_level\":0.95,\"lower_bound\":4.523330334465586,\"upper_bound\":7.657483659731688},\"point_estimate\":6.183442535582376,\"standard_error\":0.8009739022739261}}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Rc_str_/500/new/sample.json",
    "content": "{\"sampling_mode\":\"Linear\",\"iters\":[4551.0,9102.0,13653.0,18204.0,22755.0,27306.0,31857.0,36408.0,40959.0,45510.0,50061.0,54612.0,59163.0,63714.0,68265.0,72816.0,77367.0,81918.0,86469.0,91020.0,95571.0,100122.0,104673.0,109224.0,113775.0,118326.0,122877.0,127428.0,131979.0,136530.0,141081.0,145632.0,150183.0,154734.0,159285.0,163836.0,168387.0,172938.0,177489.0,182040.0,186591.0,191142.0,195693.0,200244.0,204795.0,209346.0,213897.0,218448.0,222999.0,227550.0,232101.0,236652.0,241203.0,245754.0,250305.0,254856.0,259407.0,263958.0,268509.0,273060.0,277611.0,282162.0,286713.0,291264.0,295815.0,300366.0,304917.0,309468.0,314019.0,318570.0,323121.0,327672.0,332223.0,336774.0,341325.0,345876.0,350427.0,354978.0,359529.0,364080.0,368631.0,373182.0,377733.0,382284.0,386835.0,391386.0,395937.0,400488.0,405039.0,409590.0,414141.0,418692.0,423243.0,427794.0,432345.0,436896.0,441447.0,445998.0,450549.0,455100.0],\"times\":[366167.0,709000.0,1146622.0,1413333.0,2177960.0,2464501.0,3408084.0,3336249.0,3854833.0,4200707.0,4810293.0,5564958.0,5876375.0,6611207.0,7099707.0,7619081.0,7846584.0,8389707.0,8976334.0,9276708.0,9496500.0,9710794.0,10749626.0,10838793.0,11332416.0,12390125.0,12879625.0,13327207.0,13054084.0,14154083.0,13989376.0,14234667.0,14749082.0,15394459.0,16361709.0,16822627.0,16650292.0,17197375.0,17992668.0,18471377.0,18542375.0,20034501.0,20530000.0,21051749.0,21110625.0,21808793.0,21385417.0,23427166.0,23332292.0,24454874.0,23409832.0,24607917.0,23511334.0,24749124.0,24454209.0,25434710.0,25741334.0,26582707.0,26881291.0,27116833.0,28434248.0,29980585.0,28855043.0,30090375.0,30625252.0,29093501.0,31781500.0,32086626.0,32704248.0,33251334.0,33496917.0,33255873.0,34073708.0,35453791.0,34681082.0,36686374.0,37827750.0,36982875.0,36439291.0,39381668.0,40095876.0,40946582.0,40665833.0,41031167.0,40991416.0,42009250.0,43092459.0,40999500.0,44184124.0,43998127.0,44443873.0,46138084.0,46497750.0,45987707.0,47348708.0,47906499.0,45796001.0,49226914.0,48631209.0,49554334.0]}"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Rc_str_/500/new/tukey.json",
    "content": "[81.35897507385013,90.39220311538276,114.48081122613644,123.51403926766908]"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Rc_str_/500/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/Rc&lt;str&gt;/500 - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        th {\n            font-weight: 200\n        }\n\n        th,\n        td {\n            padding-right: 3px;\n            padding-bottom: 3px;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        th.ci-bound {\n            opacity: 0.6\n        }\n\n        td.ci-bound {\n            opacity: 0.5\n        }\n\n        .stats {\n            width: 80%;\n            margin: auto;\n            display: flex;\n        }\n\n        .additional_stats {\n            flex: 0 0 60%\n        }\n\n        .additional_plots {\n            flex: 1\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/Rc&lt;str&gt;/500</h2>\n        <div class=\"absolute\">\n            <section class=\"plots\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"pdf.svg\">\n                                    <img src=\"pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"regression.svg\">\n                                    <img src=\"regression_small.svg\" alt=\"Regression\" width=\"450\" height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </section>\n            <section class=\"stats\">\n                <div class=\"additional_stats\">\n                    <h4>Additional Statistics:</h4>\n                    <table>\n                        <thead>\n                            <tr>\n                                <th></th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                                <th>Estimate</th>\n                                <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            </tr>\n                        </thead>\n                        <tbody>\n                            <tr>\n                                <td>Slope</td>\n                                <td class=\"ci-bound\">104.34 ns</td>\n                                <td>105.31 ns</td>\n                                <td class=\"ci-bound\">106.16 ns</td>\n                            </tr>\n                            <tr>\n                                <td>R&#xb2;</td>\n                                <td class=\"ci-bound\">0.8677235</td>\n                                <td>0.8752999</td>\n                                <td class=\"ci-bound\">0.8693895</td>\n                            </tr>\n                            <tr>\n                                <td>Mean</td>\n                                <td class=\"ci-bound\">100.71 ns</td>\n                                <td>101.98 ns</td>\n                                <td class=\"ci-bound\">103.14 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Standard Deviation\">Std. Dev.</td>\n                                <td class=\"ci-bound\">4.5233 ns</td>\n                                <td>6.1834 ns</td>\n                                <td class=\"ci-bound\">7.6575 ns</td>\n                            </tr>\n                            <tr>\n                                <td>Median</td>\n                                <td class=\"ci-bound\">101.61 ns</td>\n                                <td>102.90 ns</td>\n                                <td class=\"ci-bound\">103.98 ns</td>\n                            </tr>\n                            <tr>\n                                <td title=\"Median Absolute Deviation\">MAD</td>\n                                <td class=\"ci-bound\">3.3481 ns</td>\n                                <td>4.9292 ns</td>\n                                <td class=\"ci-bound\">5.8246 ns</td>\n                            </tr>\n                        </tbody>\n                    </table>\n                </div>\n                <div class=\"additional_plots\">\n                    <h4>Additional Plots:</h4>\n                    <ul>\n                        \n                        <li>\n                            <a href=\"typical.svg\">Typical</a>\n                        </li>\n                        <li>\n                            <a href=\"mean.svg\">Mean</a>\n                        </li>\n                        <li>\n                            <a href=\"SD.svg\">Std. Dev.</a>\n                        </li>\n                        <li>\n                            <a href=\"median.svg\">Median</a>\n                        </li>\n                        <li>\n                            <a href=\"MAD.svg\">MAD</a>\n                        </li>\n                        <li>\n                            <a href=\"slope.svg\">Slope</a>\n                        </li>\n                    </ul>\n                </div>\n            </section>\n            <section class=\"explanation\">\n                <h4>Understanding this report:</h4>\n                <p>The plot on the left displays the average time per iteration for this benchmark. The shaded region\n                    shows the estimated probability of an iteration taking a certain amount of time, while the line\n                    shows the mean. Click on the plot for a larger view showing the outliers.</p>\n                <p>The plot on the right shows the linear regression calculated from the measurements. Each point\n                    represents a sample, though here it shows the total time for the sample rather than time per\n                    iteration. The line is the line of best fit for these measurements.</p>\n                <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#additional-statistics\">the\n                        documentation</a> for more details on the additional statistics.</p>\n            </section>\n        </div>\n        <section class=\"plots\">\n            <h3>Change Since Previous Benchmark</h3>\n            <div class=\"relative\">\n                <table width=\"100%\">\n                    <tbody>\n                        <tr>\n                            <td>\n                                <a href=\"both/pdf.svg\">\n                                    <img src=\"relative_pdf_small.svg\" alt=\"PDF Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                            <td>\n                                <a href=\"both/regression.svg\">\n                                    <img src=\"relative_regression_small.svg\" alt=\"Regression Comparison\" width=\"450\"\n                                        height=\"300\" />\n                                </a>\n                            </td>\n                        </tr>\n                    </tbody>\n                </table>\n            </div>\n        </section>\n        <section class=\"stats\">\n            <div class=\"additional_stats\">\n                <h4>Additional Statistics:</h4>\n                <table>\n                    <thead>\n                        <tr>\n                            <th></th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Lower bound</th>\n                            <th>Estimate</th>\n                            <th title=\"0.95 confidence level\" class=\"ci-bound\">Upper bound</th>\n                            <th></th>\n                        </tr>\n                    </thead>\n                    <tbody>\n                        <tr>\n                            <td>Change in time</td>\n                            <td class=\"ci-bound\">−0.1372%</td>\n                            <td>+1.4670%</td>\n                            <td class=\"ci-bound\">+3.1285%</td>\n                            <td>(p = 0.08 &gt;\n                                0.05)</td>\n                        </tr>\n                    </tbody>\n                </table>\n                No change in performance detected.\n            </div>\n            <div class=\"additional_plots\">\n                <h4>Additional Plots:</h4>\n                <ul>\n                    \n                    <li>\n                        <a href=\"change/mean.svg\">Change in mean</a>\n                    </li>\n                    <li>\n                        <a href=\"change/median.svg\">Change in median</a>\n                    </li>\n                    <li>\n                        <a href=\"change/t-test.svg\">T-Test</a>\n                    </li>\n                </ul>\n            </div>\n        </section>\n        <section class=\"explanation\">\n            <h4>Understanding this report:</h4>\n            <p>The plot on the left shows the probability of the function taking a certain amount of time. The red\n                curve represents the saved measurements from the last time this benchmark was run, while the blue curve\n                shows the measurements from this run. The lines represent the mean time per iteration. Click on the\n                plot for a larger view.</p>\n            <p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement\n                while the blue line shows the current measurement.</p>\n            <p>See <a href=\"https://criterion-rs.github.io/book/user_guide/command_line_output.html#change\">the\n                    documentation</a> for more details on the additional statistics.</p>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/Rc_str_/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy/Rc&lt;str&gt; Summary - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy/Rc&lt;str&gt;</h2>\n        <h3>Violin Plot</h3>\n        <a href=\"violin.svg\">\n            <img src=\"violin.svg\" alt=\"Violin Plot\" />\n        </a>\n        <p>This chart shows the relationship between function/parameter and iteration time. The thickness of the shaded\n            region indicates the probability that a measurement of the given function/parameter would take a particular\n            length of time.</p>\n        <h3>Line Chart</h3>\n        <img src=\"lines.svg\" alt=\"Line Chart\" />\n        <p>This chart shows the mean measured time for each function as the input (or the size of the input) increases.</p>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/Rc_str_/0/report/index.html\">\n                <h4>Import as owned and destroy/Rc&lt;str&gt;/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/Rc_str_/0/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/Rc_str_/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/Rc_str_/0/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/Rc_str_/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/Rc_str_/10/report/index.html\">\n                <h4>Import as owned and destroy/Rc&lt;str&gt;/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/Rc_str_/10/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/Rc_str_/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/Rc_str_/10/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/Rc_str_/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/Rc_str_/20/report/index.html\">\n                <h4>Import as owned and destroy/Rc&lt;str&gt;/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/Rc_str_/20/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/Rc_str_/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/Rc_str_/20/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/Rc_str_/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/Rc_str_/100/report/index.html\">\n                <h4>Import as owned and destroy/Rc&lt;str&gt;/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/Rc_str_/100/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/Rc_str_/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/Rc_str_/100/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/Rc_str_/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../../Import as owned and destroy/Rc_str_/500/report/index.html\">\n                <h4>Import as owned and destroy/Rc&lt;str&gt;/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/Rc_str_/500/report/pdf.svg\">\n                                <img src=\"../../../Import as owned and destroy/Rc_str_/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../../Import as owned and destroy/Rc_str_/500/report/regression.svg\">\n                                <img src=\"../../../Import as owned and destroy/Rc_str_/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/Import as owned and destroy/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Import as owned and destroy Summary - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Import as owned and destroy</h2>\n        <h3>Violin Plot</h3>\n        <a href=\"violin.svg\">\n            <img src=\"violin.svg\" alt=\"Violin Plot\" />\n        </a>\n        <p>This chart shows the relationship between function/parameter and iteration time. The thickness of the shaded\n            region indicates the probability that a measurement of the given function/parameter would take a particular\n            length of time.</p>\n        <h3>Line Chart</h3>\n        <img src=\"lines.svg\" alt=\"Line Chart\" />\n        <p>This chart shows the mean measured time for each function as the input (or the size of the input) increases.</p>\n        <section class=\"plots\">\n            <a href=\"../../Import as owned and destroy/Arc_str_/0/report/index.html\">\n                <h4>Import as owned and destroy/Arc&lt;str&gt;/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/Arc_str_/0/report/pdf.svg\">\n                                <img src=\"../../Import as owned and destroy/Arc_str_/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/Arc_str_/0/report/regression.svg\">\n                                <img src=\"../../Import as owned and destroy/Arc_str_/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Import as owned and destroy/Arc_str_/10/report/index.html\">\n                <h4>Import as owned and destroy/Arc&lt;str&gt;/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/Arc_str_/10/report/pdf.svg\">\n                                <img src=\"../../Import as owned and destroy/Arc_str_/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/Arc_str_/10/report/regression.svg\">\n                                <img src=\"../../Import as owned and destroy/Arc_str_/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Import as owned and destroy/Arc_str_/20/report/index.html\">\n                <h4>Import as owned and destroy/Arc&lt;str&gt;/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/Arc_str_/20/report/pdf.svg\">\n                                <img src=\"../../Import as owned and destroy/Arc_str_/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/Arc_str_/20/report/regression.svg\">\n                                <img src=\"../../Import as owned and destroy/Arc_str_/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Import as owned and destroy/Arc_str_/100/report/index.html\">\n                <h4>Import as owned and destroy/Arc&lt;str&gt;/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/Arc_str_/100/report/pdf.svg\">\n                                <img src=\"../../Import as owned and destroy/Arc_str_/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/Arc_str_/100/report/regression.svg\">\n                                <img src=\"../../Import as owned and destroy/Arc_str_/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Import as owned and destroy/Arc_str_/500/report/index.html\">\n                <h4>Import as owned and destroy/Arc&lt;str&gt;/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/Arc_str_/500/report/pdf.svg\">\n                                <img src=\"../../Import as owned and destroy/Arc_str_/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/Arc_str_/500/report/regression.svg\">\n                                <img src=\"../../Import as owned and destroy/Arc_str_/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Import as owned and destroy/Cow_&#39;_, str_/0/report/index.html\">\n                <h4>Import as owned and destroy/Cow&lt;&#39;_, str&gt;/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/Cow_&#39;_, str_/0/report/pdf.svg\">\n                                <img src=\"../../Import as owned and destroy/Cow_&#39;_, str_/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/Cow_&#39;_, str_/0/report/regression.svg\">\n                                <img src=\"../../Import as owned and destroy/Cow_&#39;_, str_/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Import as owned and destroy/Cow_&#39;_, str_/10/report/index.html\">\n                <h4>Import as owned and destroy/Cow&lt;&#39;_, str&gt;/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/Cow_&#39;_, str_/10/report/pdf.svg\">\n                                <img src=\"../../Import as owned and destroy/Cow_&#39;_, str_/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/Cow_&#39;_, str_/10/report/regression.svg\">\n                                <img src=\"../../Import as owned and destroy/Cow_&#39;_, str_/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Import as owned and destroy/Cow_&#39;_, str_/20/report/index.html\">\n                <h4>Import as owned and destroy/Cow&lt;&#39;_, str&gt;/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/Cow_&#39;_, str_/20/report/pdf.svg\">\n                                <img src=\"../../Import as owned and destroy/Cow_&#39;_, str_/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/Cow_&#39;_, str_/20/report/regression.svg\">\n                                <img src=\"../../Import as owned and destroy/Cow_&#39;_, str_/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Import as owned and destroy/Cow_&#39;_, str_/100/report/index.html\">\n                <h4>Import as owned and destroy/Cow&lt;&#39;_, str&gt;/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/Cow_&#39;_, str_/100/report/pdf.svg\">\n                                <img src=\"../../Import as owned and destroy/Cow_&#39;_, str_/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/Cow_&#39;_, str_/100/report/regression.svg\">\n                                <img src=\"../../Import as owned and destroy/Cow_&#39;_, str_/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Import as owned and destroy/Cow_&#39;_, str_/500/report/index.html\">\n                <h4>Import as owned and destroy/Cow&lt;&#39;_, str&gt;/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/Cow_&#39;_, str_/500/report/pdf.svg\">\n                                <img src=\"../../Import as owned and destroy/Cow_&#39;_, str_/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/Cow_&#39;_, str_/500/report/regression.svg\">\n                                <img src=\"../../Import as owned and destroy/Cow_&#39;_, str_/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/0/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/0/report/pdf.svg\">\n                                <img src=\"../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/0/report/regression.svg\">\n                                <img src=\"../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/10/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/10/report/pdf.svg\">\n                                <img src=\"../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/10/report/regression.svg\">\n                                <img src=\"../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/20/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/20/report/pdf.svg\">\n                                <img src=\"../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/20/report/regression.svg\">\n                                <img src=\"../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/100/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/100/report/pdf.svg\">\n                                <img src=\"../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/100/report/regression.svg\">\n                                <img src=\"../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/500/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/500/report/pdf.svg\">\n                                <img src=\"../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/500/report/regression.svg\">\n                                <img src=\"../../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/0/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/0/report/pdf.svg\">\n                                <img src=\"../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/0/report/regression.svg\">\n                                <img src=\"../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/10/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/10/report/pdf.svg\">\n                                <img src=\"../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/10/report/regression.svg\">\n                                <img src=\"../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/20/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/20/report/pdf.svg\">\n                                <img src=\"../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/20/report/regression.svg\">\n                                <img src=\"../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/100/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/100/report/pdf.svg\">\n                                <img src=\"../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/100/report/regression.svg\">\n                                <img src=\"../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/500/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/500/report/pdf.svg\">\n                                <img src=\"../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/500/report/regression.svg\">\n                                <img src=\"../../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/0/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/0/report/pdf.svg\">\n                                <img src=\"../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/0/report/regression.svg\">\n                                <img src=\"../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/10/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/10/report/pdf.svg\">\n                                <img src=\"../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/10/report/regression.svg\">\n                                <img src=\"../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/20/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/20/report/pdf.svg\">\n                                <img src=\"../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/20/report/regression.svg\">\n                                <img src=\"../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/100/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/100/report/pdf.svg\">\n                                <img src=\"../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/100/report/regression.svg\">\n                                <img src=\"../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/500/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/500/report/pdf.svg\">\n                                <img src=\"../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/500/report/regression.svg\">\n                                <img src=\"../../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/0/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/0/report/pdf.svg\">\n                                <img src=\"../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/0/report/regression.svg\">\n                                <img src=\"../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/10/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/10/report/pdf.svg\">\n                                <img src=\"../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/10/report/regression.svg\">\n                                <img src=\"../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/20/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/20/report/pdf.svg\">\n                                <img src=\"../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/20/report/regression.svg\">\n                                <img src=\"../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/100/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/100/report/pdf.svg\">\n                                <img src=\"../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/100/report/regression.svg\">\n                                <img src=\"../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/500/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/500/report/pdf.svg\">\n                                <img src=\"../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/500/report/regression.svg\">\n                                <img src=\"../../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/0/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.9 (LocalStr)/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/0/report/pdf.svg\">\n                                <img src=\"../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/0/report/regression.svg\">\n                                <img src=\"../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/10/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.9 (LocalStr)/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/10/report/pdf.svg\">\n                                <img src=\"../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/10/report/regression.svg\">\n                                <img src=\"../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/20/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.9 (LocalStr)/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/20/report/pdf.svg\">\n                                <img src=\"../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/20/report/regression.svg\">\n                                <img src=\"../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/100/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.9 (LocalStr)/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/100/report/pdf.svg\">\n                                <img src=\"../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/100/report/regression.svg\">\n                                <img src=\"../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/500/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.9 (LocalStr)/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/500/report/pdf.svg\">\n                                <img src=\"../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/500/report/regression.svg\">\n                                <img src=\"../../Import as owned and destroy/FlexStr 0.9 (LocalStr)/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/0/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.9 (SharedStr)/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/0/report/pdf.svg\">\n                                <img src=\"../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/0/report/regression.svg\">\n                                <img src=\"../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/10/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.9 (SharedStr)/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/10/report/pdf.svg\">\n                                <img src=\"../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/10/report/regression.svg\">\n                                <img src=\"../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/20/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.9 (SharedStr)/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/20/report/pdf.svg\">\n                                <img src=\"../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/20/report/regression.svg\">\n                                <img src=\"../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/100/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.9 (SharedStr)/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/100/report/pdf.svg\">\n                                <img src=\"../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/100/report/regression.svg\">\n                                <img src=\"../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/500/report/index.html\">\n                <h4>Import as owned and destroy/FlexStr 0.9 (SharedStr)/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/500/report/pdf.svg\">\n                                <img src=\"../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/500/report/regression.svg\">\n                                <img src=\"../../Import as owned and destroy/FlexStr 0.9 (SharedStr)/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/0/report/index.html\">\n                <h4>Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/0/report/pdf.svg\">\n                                <img src=\"../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/0/report/regression.svg\">\n                                <img src=\"../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/10/report/index.html\">\n                <h4>Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/10/report/pdf.svg\">\n                                <img src=\"../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/10/report/regression.svg\">\n                                <img src=\"../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/20/report/index.html\">\n                <h4>Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/20/report/pdf.svg\">\n                                <img src=\"../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/20/report/regression.svg\">\n                                <img src=\"../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/100/report/index.html\">\n                <h4>Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/100/report/pdf.svg\">\n                                <img src=\"../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/100/report/regression.svg\">\n                                <img src=\"../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/500/report/index.html\">\n                <h4>Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/500/report/pdf.svg\">\n                                <img src=\"../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/500/report/regression.svg\">\n                                <img src=\"../../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Import as owned and destroy/Rc_str_/0/report/index.html\">\n                <h4>Import as owned and destroy/Rc&lt;str&gt;/0</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/Rc_str_/0/report/pdf.svg\">\n                                <img src=\"../../Import as owned and destroy/Rc_str_/0/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/Rc_str_/0/report/regression.svg\">\n                                <img src=\"../../Import as owned and destroy/Rc_str_/0/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Import as owned and destroy/Rc_str_/10/report/index.html\">\n                <h4>Import as owned and destroy/Rc&lt;str&gt;/10</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/Rc_str_/10/report/pdf.svg\">\n                                <img src=\"../../Import as owned and destroy/Rc_str_/10/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/Rc_str_/10/report/regression.svg\">\n                                <img src=\"../../Import as owned and destroy/Rc_str_/10/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Import as owned and destroy/Rc_str_/20/report/index.html\">\n                <h4>Import as owned and destroy/Rc&lt;str&gt;/20</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/Rc_str_/20/report/pdf.svg\">\n                                <img src=\"../../Import as owned and destroy/Rc_str_/20/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/Rc_str_/20/report/regression.svg\">\n                                <img src=\"../../Import as owned and destroy/Rc_str_/20/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Import as owned and destroy/Rc_str_/100/report/index.html\">\n                <h4>Import as owned and destroy/Rc&lt;str&gt;/100</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/Rc_str_/100/report/pdf.svg\">\n                                <img src=\"../../Import as owned and destroy/Rc_str_/100/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/Rc_str_/100/report/regression.svg\">\n                                <img src=\"../../Import as owned and destroy/Rc_str_/100/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n        <section class=\"plots\">\n            <a href=\"../../Import as owned and destroy/Rc_str_/500/report/index.html\">\n                <h4>Import as owned and destroy/Rc&lt;str&gt;/500</h4>\n            </a>\n            <table width=\"100%\">\n                <tbody>\n                    <tr>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/Rc_str_/500/report/pdf.svg\">\n                                <img src=\"../../Import as owned and destroy/Rc_str_/500/report/pdf_small.svg\" alt=\"PDF of Slope\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                        <td>\n                            <a href=\"../../Import as owned and destroy/Rc_str_/500/report/regression.svg\">\n                                <img src=\"../../Import as owned and destroy/Rc_str_/500/report/regression_small.svg\" alt=\"Regression\" width=\"450\"\n                                    height=\"300\" />\n                            </a>\n                        </td>\n                    </tr>\n                </tbody>\n            </table>\n        </section>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n\n</html>\n"
  },
  {
    "path": "docs/criterion/report/index.html",
    "content": "<!DOCTYPE html>\n<html>\n\n<head>\n    <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n    <title>Index - Criterion.rs</title>\n    <style type=\"text/css\">\n        body {\n            font: 14px Helvetica Neue;\n            text-rendering: optimizelegibility;\n        }\n\n        .body {\n            width: 960px;\n            margin: auto;\n        }\n\n        a:link {\n            color: #1F78B4;\n            text-decoration: none;\n        }\n\n        h2 {\n            font-size: 36px;\n            font-weight: 300;\n        }\n\n        h3 {\n            font-size: 24px;\n            font-weight: 300;\n        }\n\n        #footer {\n            height: 40px;\n            background: #888;\n            color: white;\n            font-size: larger;\n            font-weight: 300;\n        }\n\n        #footer a {\n            color: white;\n            text-decoration: underline;\n        }\n\n        #footer p {\n            text-align: center\n        }\n\n        table {\n            border-collapse: collapse;\n        }\n\n        table,\n        th,\n        td {\n            border: 1px solid #888;\n        }\n    </style>\n</head>\n\n<body>\n    <div class=\"body\">\n        <h2>Criterion.rs Benchmark Index</h2>\n        See individual benchmark pages below for more details.\n        <ul>\n            <li><a href=\"../Clone/report/index.html\">Clone</a></li>\n            \n            <ul>\n                <li>\n                    <table>\n                        <tr>\n                            <th></th>\n                            <th><a href=\"../Clone/Arc_str_/report/index.html\">Arc&lt;str&gt;</a></th>\n                            <th><a href=\"../Clone/FlexStr 0.10 (LocalStr - Boxed)/report/index.html\">FlexStr 0.10 (LocalStr - Boxed)</a></th>\n                            <th><a href=\"../Clone/FlexStr 0.10 (LocalStr - Optimized)/report/index.html\">FlexStr 0.10 (LocalStr - Optimized)</a></th>\n                            <th><a href=\"../Clone/FlexStr 0.10 (SharedStr - Boxed)/report/index.html\">FlexStr 0.10 (SharedStr - Boxed)</a></th>\n                            <th><a href=\"../Clone/FlexStr 0.10 (SharedStr - Optimized)/report/index.html\">FlexStr 0.10 (SharedStr - Optimized)</a></th>\n                            <th><a href=\"../Clone/FlexStr 0.9 (LocalStr)/report/index.html\">FlexStr 0.9 (LocalStr)</a></th>\n                            <th><a href=\"../Clone/FlexStr 0.9 (SharedStr)/report/index.html\">FlexStr 0.9 (SharedStr)</a></th>\n                            <th><a href=\"../Clone/InlineFlexStr 0.1 (InlineStr)/report/index.html\">InlineFlexStr 0.1 (InlineStr)</a></th>\n                            <th><a href=\"../Clone/Rc_str_/report/index.html\">Rc&lt;str&gt;</a></th>\n                            <th><a href=\"../Clone/String/report/index.html\">String</a></th>\n                        </tr>\n                        <tr>\n                            <th><a href=\"../Clone/0/report/index.html\">0</a></th>\n                            <td><a href=\"../Clone/Arc_str_/0/report/index.html\">Clone/Arc&lt;str&gt;/0</a></td>\n                            <td><a href=\"../Clone/FlexStr 0.10 (LocalStr - Boxed)/0/report/index.html\">Clone/FlexStr 0.10 (LocalStr - Boxed)/0</a></td>\n                            <td><a href=\"../Clone/FlexStr 0.10 (LocalStr - Optimized)/0/report/index.html\">Clone/FlexStr 0.10 (LocalStr - Optimized)/0</a></td>\n                            <td><a href=\"../Clone/FlexStr 0.10 (SharedStr - Boxed)/0/report/index.html\">Clone/FlexStr 0.10 (SharedStr - Boxed)/0</a></td>\n                            <td><a href=\"../Clone/FlexStr 0.10 (SharedStr - Optimized)/0/report/index.html\">Clone/FlexStr 0.10 (SharedStr - Optimized)/0</a></td>\n                            <td><a href=\"../Clone/FlexStr 0.9 (LocalStr)/0/report/index.html\">Clone/FlexStr 0.9 (LocalStr)/0</a></td>\n                            <td><a href=\"../Clone/FlexStr 0.9 (SharedStr)/0/report/index.html\">Clone/FlexStr 0.9 (SharedStr)/0</a></td>\n                            <td><a href=\"../Clone/InlineFlexStr 0.1 (InlineStr)/0/report/index.html\">Clone/InlineFlexStr 0.1 (InlineStr)/0</a></td>\n                            <td><a href=\"../Clone/Rc_str_/0/report/index.html\">Clone/Rc&lt;str&gt;/0</a></td>\n                            <td><a href=\"../Clone/String/0/report/index.html\">Clone/String/0</a></td>\n                        </tr>\n                        <tr>\n                            <th><a href=\"../Clone/10/report/index.html\">10</a></th>\n                            <td><a href=\"../Clone/Arc_str_/10/report/index.html\">Clone/Arc&lt;str&gt;/10</a></td>\n                            <td><a href=\"../Clone/FlexStr 0.10 (LocalStr - Boxed)/10/report/index.html\">Clone/FlexStr 0.10 (LocalStr - Boxed)/10</a></td>\n                            <td><a href=\"../Clone/FlexStr 0.10 (LocalStr - Optimized)/10/report/index.html\">Clone/FlexStr 0.10 (LocalStr - Optimized)/10</a></td>\n                            <td><a href=\"../Clone/FlexStr 0.10 (SharedStr - Boxed)/10/report/index.html\">Clone/FlexStr 0.10 (SharedStr - Boxed)/10</a></td>\n                            <td><a href=\"../Clone/FlexStr 0.10 (SharedStr - Optimized)/10/report/index.html\">Clone/FlexStr 0.10 (SharedStr - Optimized)/10</a></td>\n                            <td><a href=\"../Clone/FlexStr 0.9 (LocalStr)/10/report/index.html\">Clone/FlexStr 0.9 (LocalStr)/10</a></td>\n                            <td><a href=\"../Clone/FlexStr 0.9 (SharedStr)/10/report/index.html\">Clone/FlexStr 0.9 (SharedStr)/10</a></td>\n                            <td><a href=\"../Clone/InlineFlexStr 0.1 (InlineStr)/10/report/index.html\">Clone/InlineFlexStr 0.1 (InlineStr)/10</a></td>\n                            <td><a href=\"../Clone/Rc_str_/10/report/index.html\">Clone/Rc&lt;str&gt;/10</a></td>\n                            <td><a href=\"../Clone/String/10/report/index.html\">Clone/String/10</a></td>\n                        </tr>\n                        <tr>\n                            <th><a href=\"../Clone/20/report/index.html\">20</a></th>\n                            <td><a href=\"../Clone/Arc_str_/20/report/index.html\">Clone/Arc&lt;str&gt;/20</a></td>\n                            <td><a href=\"../Clone/FlexStr 0.10 (LocalStr - Boxed)/20/report/index.html\">Clone/FlexStr 0.10 (LocalStr - Boxed)/20</a></td>\n                            <td><a href=\"../Clone/FlexStr 0.10 (LocalStr - Optimized)/20/report/index.html\">Clone/FlexStr 0.10 (LocalStr - Optimized)/20</a></td>\n                            <td><a href=\"../Clone/FlexStr 0.10 (SharedStr - Boxed)/20/report/index.html\">Clone/FlexStr 0.10 (SharedStr - Boxed)/20</a></td>\n                            <td><a href=\"../Clone/FlexStr 0.10 (SharedStr - Optimized)/20/report/index.html\">Clone/FlexStr 0.10 (SharedStr - Optimized)/20</a></td>\n                            <td><a href=\"../Clone/FlexStr 0.9 (LocalStr)/20/report/index.html\">Clone/FlexStr 0.9 (LocalStr)/20</a></td>\n                            <td><a href=\"../Clone/FlexStr 0.9 (SharedStr)/20/report/index.html\">Clone/FlexStr 0.9 (SharedStr)/20</a></td>\n                            <td><a href=\"../Clone/InlineFlexStr 0.1 (InlineStr)/20/report/index.html\">Clone/InlineFlexStr 0.1 (InlineStr)/20</a></td>\n                            <td><a href=\"../Clone/Rc_str_/20/report/index.html\">Clone/Rc&lt;str&gt;/20</a></td>\n                            <td><a href=\"../Clone/String/20/report/index.html\">Clone/String/20</a></td>\n                        </tr>\n                        <tr>\n                            <th><a href=\"../Clone/100/report/index.html\">100</a></th>\n                            <td><a href=\"../Clone/Arc_str_/100/report/index.html\">Clone/Arc&lt;str&gt;/100</a></td>\n                            <td><a href=\"../Clone/FlexStr 0.10 (LocalStr - Boxed)/100/report/index.html\">Clone/FlexStr 0.10 (LocalStr - Boxed)/100</a></td>\n                            <td><a href=\"../Clone/FlexStr 0.10 (LocalStr - Optimized)/100/report/index.html\">Clone/FlexStr 0.10 (LocalStr - Optimized)/100</a></td>\n                            <td><a href=\"../Clone/FlexStr 0.10 (SharedStr - Boxed)/100/report/index.html\">Clone/FlexStr 0.10 (SharedStr - Boxed)/100</a></td>\n                            <td><a href=\"../Clone/FlexStr 0.10 (SharedStr - Optimized)/100/report/index.html\">Clone/FlexStr 0.10 (SharedStr - Optimized)/100</a></td>\n                            <td><a href=\"../Clone/FlexStr 0.9 (LocalStr)/100/report/index.html\">Clone/FlexStr 0.9 (LocalStr)/100</a></td>\n                            <td><a href=\"../Clone/FlexStr 0.9 (SharedStr)/100/report/index.html\">Clone/FlexStr 0.9 (SharedStr)/100</a></td>\n                            <td><a href=\"../Clone/InlineFlexStr 0.1 (InlineStr)/100/report/index.html\">Clone/InlineFlexStr 0.1 (InlineStr)/100</a></td>\n                            <td><a href=\"../Clone/Rc_str_/100/report/index.html\">Clone/Rc&lt;str&gt;/100</a></td>\n                            <td><a href=\"../Clone/String/100/report/index.html\">Clone/String/100</a></td>\n                        </tr>\n                        <tr>\n                            <th><a href=\"../Clone/500/report/index.html\">500</a></th>\n                            <td><a href=\"../Clone/Arc_str_/500/report/index.html\">Clone/Arc&lt;str&gt;/500</a></td>\n                            <td><a href=\"../Clone/FlexStr 0.10 (LocalStr - Boxed)/500/report/index.html\">Clone/FlexStr 0.10 (LocalStr - Boxed)/500</a></td>\n                            <td><a href=\"../Clone/FlexStr 0.10 (LocalStr - Optimized)/500/report/index.html\">Clone/FlexStr 0.10 (LocalStr - Optimized)/500</a></td>\n                            <td><a href=\"../Clone/FlexStr 0.10 (SharedStr - Boxed)/500/report/index.html\">Clone/FlexStr 0.10 (SharedStr - Boxed)/500</a></td>\n                            <td><a href=\"../Clone/FlexStr 0.10 (SharedStr - Optimized)/500/report/index.html\">Clone/FlexStr 0.10 (SharedStr - Optimized)/500</a></td>\n                            <td><a href=\"../Clone/FlexStr 0.9 (LocalStr)/500/report/index.html\">Clone/FlexStr 0.9 (LocalStr)/500</a></td>\n                            <td><a href=\"../Clone/FlexStr 0.9 (SharedStr)/500/report/index.html\">Clone/FlexStr 0.9 (SharedStr)/500</a></td>\n                            <td><a href=\"../Clone/InlineFlexStr 0.1 (InlineStr)/500/report/index.html\">Clone/InlineFlexStr 0.1 (InlineStr)/500</a></td>\n                            <td><a href=\"../Clone/Rc_str_/500/report/index.html\">Clone/Rc&lt;str&gt;/500</a></td>\n                            <td><a href=\"../Clone/String/500/report/index.html\">Clone/String/500</a></td>\n                        </tr>\n                    </table>\n                </li>\n            </ul>\n            <li><a href=\"../Import as borrowed, own and destroy/report/index.html\">Import as borrowed, own and destroy</a></li>\n            \n            <ul>\n                <li>\n                    <table>\n                        <tr>\n                            <th></th>\n                            <th><a href=\"../Import as borrowed, own and destroy/Cow_&#39;_, str_/report/index.html\">Cow&lt;&#39;_, str&gt;</a></th>\n                            <th><a href=\"../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/report/index.html\">FlexStr 0.10 (LocalStr)</a></th>\n                            <th><a href=\"../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/report/index.html\">FlexStr 0.10 (SharedStr)</a></th>\n                        </tr>\n                        <tr>\n                            <th><a href=\"../Import as borrowed, own and destroy/0/report/index.html\">0</a></th>\n                            <td><a href=\"../Import as borrowed, own and destroy/Cow_&#39;_, str_/0/report/index.html\">Import as borrowed, own and destroy/Cow&lt;&#39;_, str&gt;/0</a></td>\n                            <td><a href=\"../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/0/report/index.html\">Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/0</a></td>\n                            <td><a href=\"../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/0/report/index.html\">Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/0</a></td>\n                        </tr>\n                        <tr>\n                            <th><a href=\"../Import as borrowed, own and destroy/10/report/index.html\">10</a></th>\n                            <td><a href=\"../Import as borrowed, own and destroy/Cow_&#39;_, str_/10/report/index.html\">Import as borrowed, own and destroy/Cow&lt;&#39;_, str&gt;/10</a></td>\n                            <td><a href=\"../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/10/report/index.html\">Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/10</a></td>\n                            <td><a href=\"../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/10/report/index.html\">Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/10</a></td>\n                        </tr>\n                        <tr>\n                            <th><a href=\"../Import as borrowed, own and destroy/20/report/index.html\">20</a></th>\n                            <td><a href=\"../Import as borrowed, own and destroy/Cow_&#39;_, str_/20/report/index.html\">Import as borrowed, own and destroy/Cow&lt;&#39;_, str&gt;/20</a></td>\n                            <td><a href=\"../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/20/report/index.html\">Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/20</a></td>\n                            <td><a href=\"../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/20/report/index.html\">Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/20</a></td>\n                        </tr>\n                        <tr>\n                            <th><a href=\"../Import as borrowed, own and destroy/100/report/index.html\">100</a></th>\n                            <td><a href=\"../Import as borrowed, own and destroy/Cow_&#39;_, str_/100/report/index.html\">Import as borrowed, own and destroy/Cow&lt;&#39;_, str&gt;/100</a></td>\n                            <td><a href=\"../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/100/report/index.html\">Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/100</a></td>\n                            <td><a href=\"../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/100/report/index.html\">Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/100</a></td>\n                        </tr>\n                        <tr>\n                            <th><a href=\"../Import as borrowed, own and destroy/500/report/index.html\">500</a></th>\n                            <td><a href=\"../Import as borrowed, own and destroy/Cow_&#39;_, str_/500/report/index.html\">Import as borrowed, own and destroy/Cow&lt;&#39;_, str&gt;/500</a></td>\n                            <td><a href=\"../Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/500/report/index.html\">Import as borrowed, own and destroy/FlexStr 0.10 (LocalStr)/500</a></td>\n                            <td><a href=\"../Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/500/report/index.html\">Import as borrowed, own and destroy/FlexStr 0.10 (SharedStr)/500</a></td>\n                        </tr>\n                    </table>\n                </li>\n            </ul>\n            <li><a href=\"../Import as owned and destroy/report/index.html\">Import as owned and destroy</a></li>\n            \n            <ul>\n                <li>\n                    <table>\n                        <tr>\n                            <th></th>\n                            <th><a href=\"../Import as owned and destroy/Arc_str_/report/index.html\">Arc&lt;str&gt;</a></th>\n                            <th><a href=\"../Import as owned and destroy/Cow_&#39;_, str_/report/index.html\">Cow&lt;&#39;_, str&gt;</a></th>\n                            <th><a href=\"../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/report/index.html\">FlexStr 0.10 (LocalStr - As is)</a></th>\n                            <th><a href=\"../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/report/index.html\">FlexStr 0.10 (LocalStr - Optimized)</a></th>\n                            <th><a href=\"../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/report/index.html\">FlexStr 0.10 (SharedStr - As is)</a></th>\n                            <th><a href=\"../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/report/index.html\">FlexStr 0.10 (SharedStr - Optimized)</a></th>\n                            <th><a href=\"../Import as owned and destroy/FlexStr 0.9 (LocalStr)/report/index.html\">FlexStr 0.9 (LocalStr)</a></th>\n                            <th><a href=\"../Import as owned and destroy/FlexStr 0.9 (SharedStr)/report/index.html\">FlexStr 0.9 (SharedStr)</a></th>\n                            <th><a href=\"../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/report/index.html\">InlineFlexStr 0.1 (InlineStr)</a></th>\n                            <th><a href=\"../Import as owned and destroy/Rc_str_/report/index.html\">Rc&lt;str&gt;</a></th>\n                        </tr>\n                        <tr>\n                            <th><a href=\"../Import as owned and destroy/0/report/index.html\">0</a></th>\n                            <td><a href=\"../Import as owned and destroy/Arc_str_/0/report/index.html\">Import as owned and destroy/Arc&lt;str&gt;/0</a></td>\n                            <td><a href=\"../Import as owned and destroy/Cow_&#39;_, str_/0/report/index.html\">Import as owned and destroy/Cow&lt;&#39;_, str&gt;/0</a></td>\n                            <td><a href=\"../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/0/report/index.html\">Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/0</a></td>\n                            <td><a href=\"../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/0/report/index.html\">Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/0</a></td>\n                            <td><a href=\"../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/0/report/index.html\">Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/0</a></td>\n                            <td><a href=\"../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/0/report/index.html\">Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/0</a></td>\n                            <td><a href=\"../Import as owned and destroy/FlexStr 0.9 (LocalStr)/0/report/index.html\">Import as owned and destroy/FlexStr 0.9 (LocalStr)/0</a></td>\n                            <td><a href=\"../Import as owned and destroy/FlexStr 0.9 (SharedStr)/0/report/index.html\">Import as owned and destroy/FlexStr 0.9 (SharedStr)/0</a></td>\n                            <td><a href=\"../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/0/report/index.html\">Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/0</a></td>\n                            <td><a href=\"../Import as owned and destroy/Rc_str_/0/report/index.html\">Import as owned and destroy/Rc&lt;str&gt;/0</a></td>\n                        </tr>\n                        <tr>\n                            <th><a href=\"../Import as owned and destroy/10/report/index.html\">10</a></th>\n                            <td><a href=\"../Import as owned and destroy/Arc_str_/10/report/index.html\">Import as owned and destroy/Arc&lt;str&gt;/10</a></td>\n                            <td><a href=\"../Import as owned and destroy/Cow_&#39;_, str_/10/report/index.html\">Import as owned and destroy/Cow&lt;&#39;_, str&gt;/10</a></td>\n                            <td><a href=\"../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/10/report/index.html\">Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/10</a></td>\n                            <td><a href=\"../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/10/report/index.html\">Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/10</a></td>\n                            <td><a href=\"../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/10/report/index.html\">Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/10</a></td>\n                            <td><a href=\"../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/10/report/index.html\">Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/10</a></td>\n                            <td><a href=\"../Import as owned and destroy/FlexStr 0.9 (LocalStr)/10/report/index.html\">Import as owned and destroy/FlexStr 0.9 (LocalStr)/10</a></td>\n                            <td><a href=\"../Import as owned and destroy/FlexStr 0.9 (SharedStr)/10/report/index.html\">Import as owned and destroy/FlexStr 0.9 (SharedStr)/10</a></td>\n                            <td><a href=\"../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/10/report/index.html\">Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/10</a></td>\n                            <td><a href=\"../Import as owned and destroy/Rc_str_/10/report/index.html\">Import as owned and destroy/Rc&lt;str&gt;/10</a></td>\n                        </tr>\n                        <tr>\n                            <th><a href=\"../Import as owned and destroy/20/report/index.html\">20</a></th>\n                            <td><a href=\"../Import as owned and destroy/Arc_str_/20/report/index.html\">Import as owned and destroy/Arc&lt;str&gt;/20</a></td>\n                            <td><a href=\"../Import as owned and destroy/Cow_&#39;_, str_/20/report/index.html\">Import as owned and destroy/Cow&lt;&#39;_, str&gt;/20</a></td>\n                            <td><a href=\"../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/20/report/index.html\">Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/20</a></td>\n                            <td><a href=\"../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/20/report/index.html\">Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/20</a></td>\n                            <td><a href=\"../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/20/report/index.html\">Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/20</a></td>\n                            <td><a href=\"../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/20/report/index.html\">Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/20</a></td>\n                            <td><a href=\"../Import as owned and destroy/FlexStr 0.9 (LocalStr)/20/report/index.html\">Import as owned and destroy/FlexStr 0.9 (LocalStr)/20</a></td>\n                            <td><a href=\"../Import as owned and destroy/FlexStr 0.9 (SharedStr)/20/report/index.html\">Import as owned and destroy/FlexStr 0.9 (SharedStr)/20</a></td>\n                            <td><a href=\"../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/20/report/index.html\">Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/20</a></td>\n                            <td><a href=\"../Import as owned and destroy/Rc_str_/20/report/index.html\">Import as owned and destroy/Rc&lt;str&gt;/20</a></td>\n                        </tr>\n                        <tr>\n                            <th><a href=\"../Import as owned and destroy/100/report/index.html\">100</a></th>\n                            <td><a href=\"../Import as owned and destroy/Arc_str_/100/report/index.html\">Import as owned and destroy/Arc&lt;str&gt;/100</a></td>\n                            <td><a href=\"../Import as owned and destroy/Cow_&#39;_, str_/100/report/index.html\">Import as owned and destroy/Cow&lt;&#39;_, str&gt;/100</a></td>\n                            <td><a href=\"../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/100/report/index.html\">Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/100</a></td>\n                            <td><a href=\"../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/100/report/index.html\">Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/100</a></td>\n                            <td><a href=\"../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/100/report/index.html\">Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/100</a></td>\n                            <td><a href=\"../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/100/report/index.html\">Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/100</a></td>\n                            <td><a href=\"../Import as owned and destroy/FlexStr 0.9 (LocalStr)/100/report/index.html\">Import as owned and destroy/FlexStr 0.9 (LocalStr)/100</a></td>\n                            <td><a href=\"../Import as owned and destroy/FlexStr 0.9 (SharedStr)/100/report/index.html\">Import as owned and destroy/FlexStr 0.9 (SharedStr)/100</a></td>\n                            <td><a href=\"../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/100/report/index.html\">Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/100</a></td>\n                            <td><a href=\"../Import as owned and destroy/Rc_str_/100/report/index.html\">Import as owned and destroy/Rc&lt;str&gt;/100</a></td>\n                        </tr>\n                        <tr>\n                            <th><a href=\"../Import as owned and destroy/500/report/index.html\">500</a></th>\n                            <td><a href=\"../Import as owned and destroy/Arc_str_/500/report/index.html\">Import as owned and destroy/Arc&lt;str&gt;/500</a></td>\n                            <td><a href=\"../Import as owned and destroy/Cow_&#39;_, str_/500/report/index.html\">Import as owned and destroy/Cow&lt;&#39;_, str&gt;/500</a></td>\n                            <td><a href=\"../Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/500/report/index.html\">Import as owned and destroy/FlexStr 0.10 (LocalStr - As is)/500</a></td>\n                            <td><a href=\"../Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/500/report/index.html\">Import as owned and destroy/FlexStr 0.10 (LocalStr - Optimized)/500</a></td>\n                            <td><a href=\"../Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/500/report/index.html\">Import as owned and destroy/FlexStr 0.10 (SharedStr - As is)/500</a></td>\n                            <td><a href=\"../Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/500/report/index.html\">Import as owned and destroy/FlexStr 0.10 (SharedStr - Optimized)/500</a></td>\n                            <td><a href=\"../Import as owned and destroy/FlexStr 0.9 (LocalStr)/500/report/index.html\">Import as owned and destroy/FlexStr 0.9 (LocalStr)/500</a></td>\n                            <td><a href=\"../Import as owned and destroy/FlexStr 0.9 (SharedStr)/500/report/index.html\">Import as owned and destroy/FlexStr 0.9 (SharedStr)/500</a></td>\n                            <td><a href=\"../Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/500/report/index.html\">Import as owned and destroy/InlineFlexStr 0.1 (InlineStr)/500</a></td>\n                            <td><a href=\"../Import as owned and destroy/Rc_str_/500/report/index.html\">Import as owned and destroy/Rc&lt;str&gt;/500</a></td>\n                        </tr>\n                    </table>\n                </li>\n            </ul>\n        </ul>\n    </div>\n    <div id=\"footer\">\n        <p>This report was generated by\n            <a href=\"https://github.com/criterion-rs/criterion.rs\">Criterion.rs</a>, a statistics-driven benchmarking\n            library in Rust.</p>\n    </div>\n</body>\n</html>\n"
  },
  {
    "path": "flexstr_support/Cargo.toml",
    "content": "[package]\nname = \"flexstr_support\"\nversion = \"0.1.4\"\nauthors = [\"Scott Meeuwsen <smeeuwsen@gmail.com>\"]\nlicense = \"MIT OR Apache-2.0\"\ndescription = \"Support crate for 'flexstr' and 'inline_flexstr'\"\nrepository = \"https://github.com/nu11ptr/flexstr/flexstr_support\"\ndocumentation = \"https://docs.rs/flexstr_support\"\nkeywords = [\"string\", \"support\"]\ncategories = [\n    \"data-structures\",\n    \"memory-management\",\n    \"no-std\",\n    \"text-processing\",\n]\nreadme = \"README.md\"\nedition = \"2024\"\n\n[features]\ndefault = [\"std\", \"str\"]\n# Does not use and forbids all unsafe code (unless windows_min_unsafe is also enabled, but that only impacts Windows)\nsafe = []\nstd = []\n# Uses the minimum unsafe code possible to support OsStr/Path on Windows. Doesn't impact any other string types or operating systems.\nwin_min_unsafe = [\"safe\"]\n\n# String type features\nbytes = []\ncstr = []\nosstr = [\"std\"]\npath = [\"osstr\"]\nstr = []\n\n[package.metadata.docs.rs]\nfeatures = [\"bytes\", \"cstr\", \"osstr\", \"path\", \"serde\", \"std\", \"str\"]\nrustdoc-args = [\"--cfg\", \"docsrs\"]\n"
  },
  {
    "path": "flexstr_support/README.md",
    "content": "# flexstr_support\n\n[![Crate](https://img.shields.io/crates/v/flexstr_support)](https://crates.io/crates/flexstr_support)\n[![Docs](https://docs.rs/flexstr_support/badge.svg)](https://docs.rs/flexstr_support)\n[![Build](https://github.com/nu11ptr/flexstr/workflows/CI/badge.svg)](https://github.com/nu11ptr/flexstr/actions)\n\nSupport crate for `flexstr` and `flexstr_support`. This probably isn't what you want unless you are trying to add your own string type to these crates.\n\n## Cargo Features\n\n* **safe** = Use all safe functions and add `forbid(unsafe_code)` (performance penalty)\n* **std** = Use `std` (default)\n* **serde** = add `serde` dependency and adds serialization/deserialization\n* **win_min_unsafe** = enables the minimum necessary unsafe code on Windows to support `OsStr`/`Path`. No other string types or operating systems are impacted (implies `safe` feature).\n    * NOTE: The code will refuse to compile if this is not specified when ALL the following conditions are true:\n        * The `safe` feature is enabled\n        * The `osstr` and/or `path` feature(s) are enabled\n        * Compiling for Windows\n\n### String Type Features:\n* **str** = Enable `str`-based strings (default)\n* **bytes** = Enable byte-based strings (`[u8]`)\n* **cstr** = Enable `CStr`-based strings\n* **osstr** = Enable `OsStr`-based strings\n* **path** = Enable `Path`-based strings (implies `osstr` feature)\n\n## Performance\n\nIn general, it performs quite well given that it is mostly just a thin wrapper over the stdlib. See the [benchmarks](../benchmarks/README.md) page for more details.\n\n## AI Usage\n\nThe code was written by hand with care (although AI tab completion was used). Any contributions should be completely understood by the contributor, whether AI assisted or not.\n\n## Status\n\nThis is currently experimental, however, I will be using this at a startup in production code, so it will become production ready at some point.\n\n## Contributions\n\nContributions are welcome so long as they align to my vision for this crate. Currently, it does most of what I want it to do (outside of string construction and mutation, but I'm not ready to start on that yet).\n\n## License\n\nThis project is licensed optionally under either:\n\n* Apache License, Version 2.0, (LICENSE-APACHE\n  or <https://www.apache.org/licenses/LICENSE-2.0>)\n* MIT license (LICENSE-MIT or <https://opensource.org/licenses/MIT>)\n"
  },
  {
    "path": "flexstr_support/src/bytes.rs",
    "content": "use crate::traits::{StringFromBytesMut, StringToFromBytes};\n\n// *** StringToFromBytes ***\n\nimpl StringToFromBytes for [u8] {\n    #[inline]\n    fn bytes_as_self(bytes: &[u8]) -> &Self {\n        bytes\n    }\n\n    #[inline]\n    fn self_as_raw_bytes(&self) -> &[u8] {\n        self\n    }\n}\n\n// *** StringFromBytesMut ***\n\nimpl StringFromBytesMut for [u8] {\n    #[inline]\n    fn bytes_as_self_mut(bytes: &mut [u8]) -> &mut Self {\n        bytes\n    }\n}\n"
  },
  {
    "path": "flexstr_support/src/cstr.rs",
    "content": "use alloc::fmt;\nuse core::ffi::CStr;\n\nuse crate::traits::StringToFromBytes;\n\n// *** InteriorNulError ***\n\n/// Error type returned when a C String has an interior NUL byte.\n#[derive(Debug)]\npub struct InteriorNulError {\n    /// The position of the interior NUL byte\n    pub position: usize,\n}\n\nimpl fmt::Display for InteriorNulError {\n    fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {\n        write!(f, \"Interior NUL byte found at position {}\", self.position)\n    }\n}\n\nimpl core::error::Error for InteriorNulError {}\n\n// *** StringToFromBytes ***\n\nimpl StringToFromBytes for CStr {\n    #[cfg(feature = \"safe\")]\n    #[inline]\n    fn bytes_as_self(bytes: &[u8]) -> &Self {\n        // PANIC SAFETY: We know the bytes are a valid CStr\n        CStr::from_bytes_with_nul(bytes).expect(\"Missing NUL byte\")\n    }\n\n    #[cfg(not(feature = \"safe\"))]\n    #[inline]\n    fn bytes_as_self(bytes: &[u8]) -> &Self {\n        // SAFETY: We know the bytes are a valid CStr\n        unsafe { CStr::from_bytes_with_nul_unchecked(bytes) }\n    }\n\n    #[inline]\n    fn self_as_bytes(&self) -> &[u8] {\n        self.to_bytes()\n    }\n\n    #[inline]\n    fn self_as_raw_bytes(&self) -> &[u8] {\n        self.to_bytes_with_nul()\n    }\n\n    #[inline]\n    fn empty_raw_bytes() -> &'static [u8] {\n        // CStr requires at least a NUL terminator byte\n        &[0]\n    }\n}\n"
  },
  {
    "path": "flexstr_support/src/lib.rs",
    "content": "#![cfg_attr(not(feature = \"std\"), no_std)]\n#![cfg_attr(\n    all(\n        not(all(feature = \"win_min_unsafe\", target_family = \"windows\")),\n        feature = \"safe\"\n    ),\n    forbid(unsafe_code)\n)]\n#![cfg_attr(docsrs, feature(doc_cfg))]\n#![warn(missing_docs)]\n\n//! Support crate for 'flexstr' and 'inline_flexstr'\n\nextern crate alloc;\n\n#[cfg(feature = \"bytes\")]\n/// Module for byte-based strings (`[u8]`)\nmod bytes;\n#[cfg(feature = \"cstr\")]\n/// Module for `CStr`-based strings\nmod cstr;\n#[cfg(all(feature = \"std\", feature = \"osstr\"))]\n/// Module for `OsStr`-based strings\nmod osstr;\n#[cfg(all(feature = \"std\", feature = \"path\"))]\n/// Module for `Path`-based strings\nmod path;\n#[cfg(feature = \"str\")]\n/// Module for `str`-based strings\nmod str;\nmod traits;\n\n#[cfg(feature = \"cstr\")]\npub use cstr::InteriorNulError;\npub use traits::{StringFromBytesMut, StringLike, StringToFromBytes};\n"
  },
  {
    "path": "flexstr_support/src/osstr.rs",
    "content": "use std::ffi::OsStr;\n\nuse crate::traits::StringToFromBytes;\n\n// *** StringToFromBytes ***\n\nimpl StringToFromBytes for OsStr {\n    #[cfg(all(\n        feature = \"safe\",\n        not(feature = \"win_min_unsafe\"),\n        target_family = \"windows\"\n    ))]\n    #[inline]\n    fn bytes_as_self(bytes: &[u8]) -> &Self {\n        // TODO: With a 3rd party crate, we could use: os_str_bytes::OsStrBytes::assert_from_raw_bytes()\n        // But is this any better? They likely use unsafe internally anyway (as of course the std library does as well).\n        compile_error!(\n            \"OsStr/Path support is not available with the 'safe' feature on Windows. Using the 'win_min_unsafe' feature in combination with 'safe' will allow it to compile, but will use a single unsafe call.\"\n        );\n        unreachable!()\n    }\n\n    #[cfg(all(feature = \"safe\", target_family = \"unix\"))]\n    #[inline]\n    fn bytes_as_self(bytes: &[u8]) -> &Self {\n        use std::os::unix::prelude::OsStrExt;\n\n        OsStrExt::from_bytes(bytes)\n    }\n\n    #[cfg(all(feature = \"safe\", target_os = \"wasi\"))]\n    #[inline]\n    fn bytes_as_self(bytes: &[u8]) -> &Self {\n        use std::os::wasi::prelude::OsStrExt;\n\n        OsStrExt::from_bytes(bytes)\n    }\n\n    #[cfg(any(\n        not(feature = \"safe\"),\n        all(feature = \"win_min_unsafe\", target_family = \"windows\")\n    ))]\n    #[inline]\n    fn bytes_as_self(bytes: &[u8]) -> &Self {\n        // SAFETY: We know the bytes are a valid OsStr\n        unsafe { OsStr::from_encoded_bytes_unchecked(bytes) }\n    }\n\n    #[inline]\n    fn self_as_raw_bytes(&self) -> &[u8] {\n        self.as_encoded_bytes()\n    }\n}\n"
  },
  {
    "path": "flexstr_support/src/path.rs",
    "content": "use std::{ffi::OsStr, path::Path};\n\nuse crate::traits::StringToFromBytes;\n\n// *** StringToFromBytes ***\n\nimpl StringToFromBytes for Path {\n    #[inline]\n    fn bytes_as_self(bytes: &[u8]) -> &Self {\n        Path::new(OsStr::bytes_as_self(bytes))\n    }\n\n    #[inline]\n    fn self_as_raw_bytes(&self) -> &[u8] {\n        OsStr::self_as_bytes(self.as_os_str())\n    }\n}\n"
  },
  {
    "path": "flexstr_support/src/str.rs",
    "content": "use crate::traits::{StringFromBytesMut, StringToFromBytes};\n\n// *** StringToFromBytes ***\n\nimpl StringToFromBytes for str {\n    #[cfg(feature = \"safe\")]\n    #[inline]\n    fn bytes_as_self(bytes: &[u8]) -> &Self {\n        // PANIC SAFETY: We know the bytes are valid UTF-8\n        str::from_utf8(bytes).expect(\"Invalid UTF-8\")\n    }\n\n    #[cfg(not(feature = \"safe\"))]\n    #[inline]\n    fn bytes_as_self(bytes: &[u8]) -> &Self {\n        // SAFETY: We know the bytes are valid UTF-8\n        unsafe { str::from_utf8_unchecked(bytes) }\n    }\n\n    #[inline]\n    fn self_as_raw_bytes(&self) -> &[u8] {\n        self.as_bytes()\n    }\n}\n\n// *** StringFromBytesMut ***\n\nimpl StringFromBytesMut for str {\n    #[cfg(feature = \"safe\")]\n    #[inline]\n    fn bytes_as_self_mut(bytes: &mut [u8]) -> &mut Self {\n        // PANIC SAFETY: We know the bytes are valid UTF-8\n        str::from_utf8_mut(bytes).expect(\"Invalid UTF-8\")\n    }\n\n    #[cfg(not(feature = \"safe\"))]\n    #[inline]\n    fn bytes_as_self_mut(bytes: &mut [u8]) -> &mut Self {\n        // SAFETY: We know the bytes are valid UTF-8\n        unsafe { str::from_utf8_unchecked_mut(bytes) }\n    }\n}\n"
  },
  {
    "path": "flexstr_support/src/traits.rs",
    "content": "#[cfg(feature = \"cstr\")]\nuse alloc::ffi::CString;\n#[cfg(all(not(feature = \"std\"), feature = \"bytes\"))]\nuse alloc::vec::Vec;\n#[cfg(not(feature = \"std\"))]\nuse alloc::{borrow::ToOwned, boxed::Box, string::String};\n#[cfg(feature = \"cstr\")]\nuse core::ffi::CStr;\n#[cfg(all(feature = \"std\", feature = \"osstr\"))]\nuse std::ffi::{OsStr, OsString};\n#[cfg(all(feature = \"std\", feature = \"path\"))]\nuse std::path::{Path, PathBuf};\n\n// *** StringToFromBytes ***\n\n/// Trait for string types that can be converted to and from bytes\npub trait StringToFromBytes: ToOwned + 'static {\n    /// Convert bytes to a string type\n    fn bytes_as_self(bytes: &[u8]) -> &Self;\n\n    /// Convert a string type to bytes (excludes nul for CStr)\n    #[inline]\n    fn self_as_bytes(&self) -> &[u8] {\n        self.self_as_raw_bytes()\n    }\n\n    /// Convert a string type to raw bytes (inludes nul for CStr)\n    fn self_as_raw_bytes(&self) -> &[u8];\n\n    /// The raw bytes of an empty value of this type. For most types this is `&[]`,\n    /// but for CStr it is `&[0]` (a single NUL terminator).\n    fn empty_raw_bytes() -> &'static [u8] {\n        &[]\n    }\n}\n\n// *** StringFromBytesMut ***\n\n/// Trait for string types that can be converted from bytes to mutable string reference\npub trait StringFromBytesMut: StringToFromBytes {\n    /// Convert bytes to a mutable string reference\n    fn bytes_as_self_mut(bytes: &mut [u8]) -> &mut Self;\n}\n\n// *** StringLike ***\n\n/// Trait for string types that provide various operations\npub trait StringLike<S: ?Sized + StringToFromBytes>\nwhere\n    Self: Sized,\n{\n    /// Borrow a string reference as `&S`\n    fn as_ref_type(&self) -> &S;\n\n    /// Borrow the string as bytes\n    fn as_bytes(&self) -> &[u8];\n\n    /// Consume a string and convert it to an owned string. `S::to_owned` is called on Borrowed/Inlined/RefCounted variants.\n    /// Boxed variants are converted directly into `S::Owned` (most likely without copy or allocation).\n    fn into_owned_type(self) -> S::Owned\n    where\n        S::Owned: From<Box<S>>;\n\n    /// Convert a string reference to an owned string. `S::to_owned` is called on all variants.\n    fn to_owned_type(&self) -> S::Owned;\n\n    /// Returns true if this is an empty string\n    fn is_empty(&self) -> bool {\n        self.as_bytes().is_empty()\n    }\n\n    /// Returns the length of this string in bytes\n    fn len(&self) -> usize {\n        self.as_bytes().len()\n    }\n\n    /// Borrow the string as an `&str`\n    fn as_str(&self) -> &str\n    where\n        S: AsRef<str>,\n    {\n        self.as_ref_type().as_ref()\n    }\n\n    #[cfg(all(feature = \"std\", feature = \"osstr\"))]\n    /// Borrow the string as an `&OsStr`\n    fn as_os_str(&self) -> &OsStr\n    where\n        S: AsRef<OsStr>,\n    {\n        self.as_ref_type().as_ref()\n    }\n\n    #[cfg(all(feature = \"std\", feature = \"path\"))]\n    /// Borrow the string as a `&Path`\n    fn as_path(&self) -> &Path\n    where\n        S: AsRef<Path>,\n    {\n        self.as_ref_type().as_ref()\n    }\n\n    #[cfg(feature = \"cstr\")]\n    /// Borrow the string as a `&CStr`\n    fn as_c_str(&self) -> &CStr\n    where\n        S: AsRef<CStr>,\n    {\n        self.as_ref_type().as_ref()\n    }\n\n    /// Consume a string and convert it to a [String]\n    fn into_string(self) -> String\n    where\n        S::Owned: Into<String> + From<Box<S>>,\n    {\n        self.into_owned_type().into()\n    }\n\n    #[cfg(all(feature = \"std\", feature = \"osstr\"))]\n    /// Consume a string and convert it to an [OsString]\n    fn into_os_string(self) -> OsString\n    where\n        S::Owned: Into<OsString> + From<Box<S>>,\n    {\n        self.into_owned_type().into()\n    }\n\n    #[cfg(all(feature = \"std\", feature = \"path\"))]\n    /// Consume a string and convert it to a [PathBuf]\n    fn into_path_buf(self) -> PathBuf\n    where\n        S::Owned: Into<PathBuf> + From<Box<S>>,\n    {\n        self.into_owned_type().into()\n    }\n\n    #[cfg(feature = \"cstr\")]\n    /// Consume a string and convert it to a [CString]\n    fn into_c_string(self) -> CString\n    where\n        S::Owned: Into<CString> + From<Box<S>>,\n    {\n        self.into_owned_type().into()\n    }\n\n    #[cfg(feature = \"bytes\")]\n    /// Consume a string and convert it to a [`Vec<u8>`]\n    fn into_vec_bytes(self) -> Vec<u8>\n    where\n        S::Owned: Into<Vec<u8>> + From<Box<S>>,\n    {\n        self.into_owned_type().into()\n    }\n\n    /// Convert a string reference to a [String]\n    fn to_string(&self) -> String\n    where\n        S::Owned: Into<String>,\n    {\n        self.to_owned_type().into()\n    }\n\n    #[cfg(all(feature = \"std\", feature = \"osstr\"))]\n    /// Convert a string reference to an [OsString]\n    fn to_os_string(&self) -> OsString\n    where\n        S::Owned: Into<OsString>,\n    {\n        self.to_owned_type().into()\n    }\n\n    #[cfg(all(feature = \"std\", feature = \"path\"))]\n    /// Convert a string reference to a [PathBuf]\n    fn to_path_buf(&self) -> PathBuf\n    where\n        S::Owned: Into<PathBuf>,\n    {\n        self.to_owned_type().into()\n    }\n\n    #[cfg(feature = \"cstr\")]\n    /// Convert a string reference to a [CString]\n    fn to_c_string(&self) -> CString\n    where\n        S::Owned: Into<CString>,\n    {\n        self.to_owned_type().into()\n    }\n\n    #[cfg(feature = \"bytes\")]\n    /// Convert a string reference to a [`Vec<u8>`]\n    fn to_vec_bytes(&self) -> Vec<u8>\n    where\n        S::Owned: Into<Vec<u8>>,\n    {\n        self.to_owned_type().into()\n    }\n}\n"
  },
  {
    "path": "inline_flexstr/Cargo.toml",
    "content": "[package]\nname = \"inline_flexstr\"\nversion = \"0.1.9\"\nauthors = [\"Scott Meeuwsen <smeeuwsen@gmail.com>\"]\nlicense = \"MIT OR Apache-2.0\"\ndescription = \"A simple to use, copy/clone-efficient inline string type for Rust\"\nrepository = \"https://github.com/nu11ptr/flexstr/inline_flexstr\"\ndocumentation = \"https://docs.rs/inline_flexstr\"\nkeywords = [\"string\", \"inline\"]\ncategories = [\n    \"data-structures\",\n    \"memory-management\",\n    \"no-std\",\n    \"text-processing\",\n]\nreadme = \"README.md\"\nedition = \"2024\"\n\n[features]\ndefault = [\"std\", \"str\"]\nprost = [\"dep:prost\"]\nsqlx_pg_arrays = [\"sqlx\", \"sqlx/postgres\"]\nutoipa = [\"dep:utoipa\"]\nzeroize = [\"dep:zeroize\"]\n# Does not use and forbids all unsafe code (unless windows_min_unsafe is also enabled, but that only impacts Windows)\nsafe = [\"flexstr_support/safe\"]\nstd = [\"flexstr_support/std\", \"serde?/std\", \"prost?/std\"]\n# Uses the minimum unsafe code possible to support OsStr/Path on Windows. Doesn't impact any other string types or operating systems.\nwin_min_unsafe = [\"flexstr_support/win_min_unsafe\", \"safe\"]\n\n# String type features\nbytes = [\"flexstr_support/bytes\"]\ncstr = [\"flexstr_support/cstr\"]\nosstr = [\"flexstr_support/osstr\", \"std\"]\npath = [\"flexstr_support/path\", \"osstr\"]\nstr = [\"flexstr_support/str\"]\n\n[dependencies.flexstr_support]\npath = \"../flexstr_support\"\nversion = \"0.1.4\"\ndefault-features = false\n\n[dependencies.prost]\nversion = \"0.14\"\ndefault-features = false\noptional = true\n\n[dependencies.serde]\nversion = \"1\"\ndefault-features = false\noptional = true\n\n[dependencies.sqlx]\nversion = \"0.8\"\ndefault-features = false\noptional = true\n\n[dependencies.utoipa]\nversion = \"5\"\noptional = true\n\n[dependencies.zeroize]\nversion = \"1\"\ndefault-features = false\noptional = true\n\n[dev-dependencies.serde_json]\nversion = \"1\"\n\n[package.metadata.docs.rs]\nfeatures = [\n    \"bytes\",\n    \"cstr\",\n    \"osstr\",\n    \"path\",\n    \"prost\",\n    \"serde\",\n    \"std\",\n    \"str\",\n    \"utoipa\",\n    \"zeroize\",\n]\nrustdoc-args = [\"--cfg\", \"docsrs\"]\n"
  },
  {
    "path": "inline_flexstr/README.md",
    "content": "# inline_flexstr\n\n[![Crate](https://img.shields.io/crates/v/inline_flexstr)](https://crates.io/crates/inline_flexstr)\n[![Docs](https://docs.rs/inline_flexstr/badge.svg)](https://docs.rs/inline_flexstr)\n[![Build](https://github.com/nu11ptr/flexstr/workflows/CI/badge.svg)](https://github.com/nu11ptr/flexstr/actions)\n[![codecov](https://codecov.io/gh/nu11ptr/flexstr/branch/master/graph/badge.svg?token=yUZ8v2tKPd)](https://codecov.io/gh/nu11ptr/flexstr)\n\nA simple to use, copy/clone-efficient inline string type for Rust\n\n## Overview\n\nA fast inline string crate. Essentially it never allocates on the heap, but is limited currently to strings that are 2 bytes less than 3 machine words in length (10 bytes on 32-bit, 22 bytes on 64-bit). It is generic over all the Rust string types (`str`, `CStr`, `OsStr`, `Path`, `[u8]`).\n\n## Features\n\n* Implements `Copy`\n* O(1) copy/clone\n* Mutable\n* Same size a a `String` (3 words wide, even inside an `Option`)\n* No external dependencies\n    * NOTE: `serde`/`sqlx`/`prost` optional for serialization/deserialization/encode/decode\n* Optional `no_std`\n* Optional `safe` feature that forbids any `unsafe` usage\n    * NOTE: This does induce a performance penalty, as would be expected\n    * NOTE 2: `OsStr`/`Path` support on Windows requires at least one unsafe call (`win_min_unsafe` feature).\n* Handles all Rust string types (`str`, `CStr`, `OsStr`, `Path`, `[u8]`)\n\n## Cargo Features\n\n* **prost** = Enable `prost::Message` implementation for protobuf encoding/decoding\n* **safe** = Use all safe functions and add `forbid(unsafe_code)` (performance penalty)\n* **sqlx** = Enable sqlx encode/decode/type support\n* **sqlx_pg_arrays** = Enable sqlx Postgres array support (implies `sqlx` feature)\n* **std** = Use `std` (default)\n* **serde** = add `serde` dependency and adds serialization/deserialization\n* **win_min_unsafe** = enables the minimum necessary unsafe code on Windows to support `OsStr`/`Path`. No other string types or operating systems are impacted (implies `safe` feature).\n    * NOTE: The code will refuse to compile if this is not specified when ALL the following conditions are true:\n        * The `safe` feature is enabled\n        * The `osstr` and/or `path` feature(s) are enabled\n        * Compiling for Windows\n\n### String Type Features:\n* **str** = Enable `str`-based strings (default)\n* **bytes** = Enable byte-based strings (`[u8]`)\n* **cstr** = Enable `CStr`-based strings\n* **osstr** = Enable `OsStr`-based strings\n* **path** = Enable `Path`-based strings (implies `osstr` feature)\n\n## Example\n\n```rust\nuse inline_flexstr::*;\n\nlet hello: InlineStr = \"hello\".try_into().expect(\"string too long\");\nlet world: InlineCStr = c\"world!\".try_into().expect(\"string too long\");\n\nprintln!(\"{hello} {world:?}\");\n```\n\n## Performance\n\nIn general, it performs quite well given that it is mostly just a thin wrapper over the stdlib. See the [benchmarks](../benchmarks/README.md) page for more details.\n\n## AI Usage\n\nThe code was written by hand with care (although AI tab completion was used). Any contributions should be completely understood by the contributor, whether AI assisted or not.\n\nThe tests on the otherhand were 90%+ generated by AI under my instruction. I've done a cursory review for sanity, but they need more work. Volunteers welcome.\n\n## Status\n\nThis is currently experimental, however, I will be using this at a startup in production code, so it will become production ready at some point.\n\n## Contributions\n\nContributions are welcome so long as they align to my vision for this crate. Currently, it does most of what I want it to do (outside of string construction and mutation, but I'm not ready to start on that yet).\n\n## License\n\nThis project is licensed optionally under either:\n\n* Apache License, Version 2.0, (LICENSE-APACHE\n  or <https://www.apache.org/licenses/LICENSE-2.0>)\n* MIT license (LICENSE-MIT or <https://opensource.org/licenses/MIT>)\n"
  },
  {
    "path": "inline_flexstr/src/bytes.rs",
    "content": "use alloc::borrow::Cow;\n#[cfg(not(feature = \"std\"))]\nuse alloc::vec::Vec;\nuse core::str::FromStr;\n\nuse crate::inline::{InlineFlexStr, TooLongForInlining, inline_partial_eq_impl};\n\nuse flexstr_support::StringToFromBytes;\n\n/// Inline `[u8]` type\npub type InlineBytes = InlineFlexStr<[u8]>;\n\n// *** TryFrom for InlineFlexStr ***\n\n// NOTE: Cannot be implemented generically because of impl<T, U> TryFrom<U> for T where U: Into<T>\nimpl<'s> TryFrom<&'s [u8]> for InlineFlexStr<[u8]> {\n    type Error = TooLongForInlining;\n\n    #[inline]\n    fn try_from(s: &'s [u8]) -> Result<Self, Self::Error> {\n        InlineFlexStr::try_from_type(s)\n    }\n}\n\nimpl<'s> TryFrom<&'s str> for InlineFlexStr<[u8]> {\n    type Error = TooLongForInlining;\n\n    #[inline]\n    fn try_from(s: &'s str) -> Result<Self, Self::Error> {\n        InlineFlexStr::try_from_type(s.as_bytes())\n    }\n}\n\n// *** PartialEq ***\n\ninline_partial_eq_impl!([u8], [u8]);\ninline_partial_eq_impl!(&[u8], [u8]);\ninline_partial_eq_impl!(Vec<u8>, [u8]);\ninline_partial_eq_impl!(Cow<'_, [u8]>, [u8]);\n\n// *** AsRef ***\n\nimpl<S: ?Sized + StringToFromBytes> AsRef<[u8]> for InlineFlexStr<S>\nwhere\n    S: AsRef<[u8]>,\n{\n    fn as_ref(&self) -> &[u8] {\n        self.as_ref_type().as_ref()\n    }\n}\n\n// *** FromStr ***\n\nimpl FromStr for InlineFlexStr<[u8]> {\n    type Err = TooLongForInlining;\n\n    fn from_str(s: &str) -> Result<Self, Self::Err> {\n        InlineFlexStr::try_from_type(s.as_bytes())\n    }\n}\n"
  },
  {
    "path": "inline_flexstr/src/cstr.rs",
    "content": "use alloc::{borrow::Cow, ffi::CString};\nuse core::{\n    ffi::{CStr, FromBytesWithNulError},\n    fmt,\n    str::FromStr,\n};\n\nuse crate::inline::{INLINE_CAPACITY, InlineFlexStr, TooLongForInlining, inline_partial_eq_impl};\n\nuse flexstr_support::{InteriorNulError, StringToFromBytes};\n\n/// Inline `CStr` type\npub type InlineCStr = InlineFlexStr<CStr>;\n\n// *** TooLongOrNulError ***\n\n/// Error type returned when a C String is too long for inline storage or has an interior NUL byte.\n#[derive(Debug)]\npub enum TooLongOrNulError {\n    /// The C String is too long for inline storage\n    TooLong(TooLongForInlining),\n    /// The C String has an interior NUL byte\n    NulError(InteriorNulError),\n}\n\nimpl fmt::Display for TooLongOrNulError {\n    fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {\n        match self {\n            TooLongOrNulError::TooLong(e) => e.fmt(f),\n            TooLongOrNulError::NulError(e) => e.fmt(f),\n        }\n    }\n}\n\nimpl core::error::Error for TooLongOrNulError {}\n\n// *** InlineFlexStr ***\n\nimpl InlineFlexStr<CStr> {\n    fn try_from_bytes_without_nul(bytes: &[u8]) -> Result<Self, TooLongOrNulError> {\n        if bytes.len() < INLINE_CAPACITY {\n            let mut inline = Self::from_bytes(bytes);\n            inline.append_nul_zero();\n            Ok(inline)\n        } else {\n            Err(TooLongOrNulError::TooLong(TooLongForInlining {\n                length: bytes.len(),\n                inline_capacity: INLINE_CAPACITY,\n            }))\n        }\n    }\n\n    /// Attempt to create an inlined string from borrowed bytes with or without a trailing NUL byte.\n    pub fn try_from_bytes_with_or_without_nul(bytes: &[u8]) -> Result<Self, TooLongOrNulError> {\n        match CStr::from_bytes_with_nul(bytes) {\n            Ok(cstr) => Self::try_from_type(cstr).map_err(TooLongOrNulError::TooLong),\n            Err(FromBytesWithNulError::NotNulTerminated) => Self::try_from_bytes_without_nul(bytes),\n            Err(FromBytesWithNulError::InteriorNul { position }) => {\n                Err(TooLongOrNulError::NulError(InteriorNulError { position }))\n            }\n        }\n    }\n\n    /// Borrow the CStr as bytes with a trailing NUL byte\n    #[inline]\n    pub fn as_bytes_with_nul(&self) -> &[u8] {\n        self.as_raw_bytes()\n    }\n}\n\n// *** TryFrom for InlineFlexStr ***\n\n// NOTE: Cannot be implemented generically because of impl<T, U> TryFrom<U> for T where U: Into<T>\nimpl<'s> TryFrom<&'s CStr> for InlineFlexStr<CStr> {\n    type Error = TooLongForInlining;\n\n    #[inline]\n    fn try_from(s: &'s CStr) -> Result<Self, Self::Error> {\n        InlineFlexStr::try_from_type(s)\n    }\n}\n\nimpl<'s> TryFrom<&'s str> for InlineFlexStr<CStr> {\n    type Error = TooLongOrNulError;\n\n    #[inline]\n    fn try_from(s: &'s str) -> Result<Self, Self::Error> {\n        InlineFlexStr::try_from_bytes_with_or_without_nul(s.as_bytes())\n    }\n}\n\nimpl<'s> TryFrom<&'s [u8]> for InlineFlexStr<CStr> {\n    type Error = TooLongOrNulError;\n\n    #[inline]\n    fn try_from(bytes: &'s [u8]) -> Result<Self, Self::Error> {\n        InlineFlexStr::try_from_bytes_with_or_without_nul(bytes)\n    }\n}\n\n// *** PartialEq ***\n\ninline_partial_eq_impl!(CStr, CStr);\ninline_partial_eq_impl!(&CStr, CStr);\ninline_partial_eq_impl!(CString, CStr);\ninline_partial_eq_impl!(Cow<'_, CStr>, CStr);\n\n// *** AsRef ***\n\nimpl<S: ?Sized + StringToFromBytes> AsRef<CStr> for InlineFlexStr<S>\nwhere\n    S: AsRef<CStr>,\n{\n    fn as_ref(&self) -> &CStr {\n        self.as_ref_type().as_ref()\n    }\n}\n\n// *** FromStr ***\n\nimpl FromStr for InlineFlexStr<CStr> {\n    type Err = TooLongOrNulError;\n\n    fn from_str(s: &str) -> Result<Self, Self::Err> {\n        InlineFlexStr::try_from_bytes_with_or_without_nul(s.as_bytes())\n    }\n}\n"
  },
  {
    "path": "inline_flexstr/src/inline.rs",
    "content": "use alloc::borrow::{Borrow, BorrowMut};\n#[cfg(not(feature = \"std\"))]\nuse alloc::{boxed::Box, string::String};\nuse core::cmp::Ordering;\nuse core::fmt;\nuse core::hash::{Hash, Hasher};\nuse core::marker::PhantomData;\nuse core::ops::{Deref, DerefMut, Index, IndexMut};\nuse core::slice::SliceIndex;\n#[cfg(feature = \"std\")]\nuse std::{io, net::ToSocketAddrs};\n\nuse flexstr_support::{StringFromBytesMut, StringLike, StringToFromBytes};\n\n#[cfg(feature = \"serde\")]\nuse serde::{Deserialize, Deserializer, Serialize, Serializer};\n\nmacro_rules! inline_partial_eq_impl {\n    ($type:ty, $str_type:ty) => {\n        impl<S: ?Sized + StringToFromBytes> PartialEq<$type> for InlineFlexStr<S>\n        where\n            S: PartialEq<$str_type>,\n        {\n            fn eq(&self, other: &$type) -> bool {\n                S::eq(self, other)\n            }\n        }\n\n        impl<S: ?Sized + StringToFromBytes> PartialEq<InlineFlexStr<S>> for $type\n        where\n            S: PartialEq<$str_type>,\n        {\n            fn eq(&self, other: &InlineFlexStr<S>) -> bool {\n                S::eq(other, self)\n            }\n        }\n    };\n}\n\npub(crate) use inline_partial_eq_impl;\n\n// This must be the size of the String type minus 2 bytes for the length and discriminator\n/// The capacity of the [InlineFlexStr] type in bytes\npub const INLINE_CAPACITY: usize = size_of::<String>() - 2;\n\n// *** StringTooLongForInlining ***\n\n/// Error type returned when the string is too long for inline storage.\n#[derive(Debug)]\npub struct TooLongForInlining {\n    /// The length of the string\n    pub length: usize,\n    /// The capacity of the inline storage\n    pub inline_capacity: usize,\n}\n\nimpl fmt::Display for TooLongForInlining {\n    fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {\n        write!(\n            f,\n            \"string too long for inline storage: length={} inline_capacity={}\",\n            self.length, self.inline_capacity\n        )\n    }\n}\n\nimpl core::error::Error for TooLongForInlining {}\n\n// *** InlineFlexStr ***\n\n#[doc(alias = \"InlineStr\")]\n#[doc(alias = \"InlineOsStr\")]\n#[doc(alias = \"InlinePath\")]\n#[doc(alias = \"InlineCStr\")]\n#[doc(alias = \"InlineBytes\")]\n/// Inline bytes type - used to store small strings inline\n#[derive(Debug)]\npub struct InlineFlexStr<S: ?Sized + StringToFromBytes> {\n    inline: [u8; INLINE_CAPACITY],\n    len: u8,\n    marker: PhantomData<S>,\n}\n\nimpl<S: ?Sized + StringToFromBytes> InlineFlexStr<S> {\n    /// Attempt to create an inlined string from a borrowed string. Returns `None` if the string is too long.\n    pub fn try_from_type(s: &S) -> Result<Self, TooLongForInlining> {\n        let bytes = S::self_as_raw_bytes(s);\n\n        if bytes.len() <= INLINE_CAPACITY {\n            Ok(Self::from_bytes(bytes))\n        } else {\n            Err(TooLongForInlining {\n                length: bytes.len(),\n                inline_capacity: INLINE_CAPACITY,\n            })\n        }\n    }\n\n    /// Create an empty InlineFlexStr suitable for use after zeroization.\n    /// Uses `S::empty_raw_bytes()` to produce a valid empty value for each type\n    /// (e.g., CStr requires a NUL terminator byte).\n    #[cfg(feature = \"zeroize\")]\n    pub fn zeroed() -> Self {\n        Self::from_bytes(S::empty_raw_bytes())\n    }\n\n    #[cfg(feature = \"safe\")]\n    pub(crate) fn from_bytes(s: &[u8]) -> Self {\n        let mut inline = [0u8; INLINE_CAPACITY];\n        let len = s.len();\n\n        // PANIC SAFETY: Caller responsible for ensuring the slice is not too long\n        inline[..len].copy_from_slice(&s[..len]);\n\n        Self {\n            inline,\n            len: len as u8,\n            marker: PhantomData,\n        }\n    }\n\n    #[cfg(not(feature = \"safe\"))]\n    pub(crate) fn from_bytes(slice: &[u8]) -> Self {\n        // Create an uninitialized array\n        let mut inline = [core::mem::MaybeUninit::<u8>::uninit(); INLINE_CAPACITY];\n        let len = slice.len();\n\n        // SAFETY: There be dragons here! I have carefully inspected the code to ensure that it is safe IF and ONLY IF\n        // len <= INLINE_CAPACITY (this is verified by the caller! which is why this is pub(crate) only).\n        // [u8; N] and [MaybeUninit<u8>; N] are guranteed per docs to have the same size and layout.\n        let inline = unsafe {\n            // Copy the slice data\n            core::ptr::copy_nonoverlapping(slice.as_ptr(), inline.as_mut_ptr() as *mut u8, len);\n\n            // Fill the rest with zeros\n            core::ptr::write_bytes(inline.as_mut_ptr().add(len), 0u8, INLINE_CAPACITY - len);\n\n            // Transmute to a regular array\n            core::mem::transmute::<\n                [core::mem::MaybeUninit<u8>; INLINE_CAPACITY],\n                [u8; INLINE_CAPACITY],\n            >(inline)\n        };\n\n        Self {\n            inline,\n            len: len as u8,\n            marker: PhantomData,\n        }\n    }\n\n    #[cfg(all(feature = \"safe\", feature = \"cstr\"))]\n    #[inline(always)]\n    pub(crate) fn append_nul_zero(&mut self) {\n        // PANIC SAFETY: We know the length is valid and at least one byte shorter than the capacity\n        self.inline[self.len as usize] = 0;\n        self.len += 1;\n    }\n\n    #[cfg(all(not(feature = \"safe\"), feature = \"cstr\"))]\n    #[inline(always)]\n    pub(crate) fn append_nul_zero(&mut self) {\n        // SAFETY: We know the length is valid and at least one byte shorter than the capacity\n        unsafe {\n            *self.inline.get_unchecked_mut(self.len as usize) = 0;\n        }\n        self.len += 1;\n    }\n\n    #[cfg(feature = \"safe\")]\n    /// Borrow the inline bytes as a raw byte slice (NOTE: includes trailing NUL for CStr)\n    pub fn as_raw_bytes(&self) -> &[u8] {\n        &self.inline[..self.len as usize]\n    }\n\n    #[cfg(not(feature = \"safe\"))]\n    /// Borrow the inline bytes as a raw byte slice (NOTE: includes trailing NUL for CStr)\n    pub fn as_raw_bytes(&self) -> &[u8] {\n        // SAFETY: The length cannot be changed after initialization, so we know it is valid\n        unsafe { self.inline.get_unchecked(..self.len as usize) }\n    }\n\n    #[cfg(feature = \"safe\")]\n    fn as_raw_bytes_mut(&mut self) -> &mut [u8] {\n        &mut self.inline[..self.len as usize]\n    }\n\n    #[cfg(not(feature = \"safe\"))]\n    fn as_raw_bytes_mut(&mut self) -> &mut [u8] {\n        // SAFETY: The length cannot be changed after initialization, so we know it is valid\n        unsafe { self.inline.get_unchecked_mut(..self.len as usize) }\n    }\n\n    /// Borrow a string reference as `&S`\n    pub fn as_ref_type(&self) -> &S {\n        S::bytes_as_self(self.as_raw_bytes())\n    }\n\n    /// Borrow the inline bytes as bytes\n    pub fn as_bytes(&self) -> &[u8] {\n        S::self_as_bytes(self.as_ref_type())\n    }\n\n    /// Consume a string and convert it to an owned string.\n    pub fn into_owned_type(self) -> S::Owned\n    where\n        S::Owned: From<Box<S>>,\n    {\n        self.to_owned_type()\n    }\n\n    /// Convert a string reference to an owned string.\n    pub fn to_owned_type(&self) -> S::Owned {\n        self.as_ref_type().to_owned()\n    }\n}\n\nimpl<S: ?Sized + StringFromBytesMut> InlineFlexStr<S> {\n    /// Borrow the inline string as a mutable string reference\n    pub fn as_mut_type(&mut self) -> &mut S {\n        S::bytes_as_self_mut(self.as_raw_bytes_mut())\n    }\n}\n\n// *** StringLike ***\n\nimpl<S: ?Sized + StringToFromBytes + 'static> StringLike<S> for InlineFlexStr<S> {\n    fn as_ref_type(&self) -> &S {\n        <Self>::as_ref_type(self)\n    }\n\n    fn as_bytes(&self) -> &[u8] {\n        <Self>::as_bytes(self)\n    }\n\n    fn into_owned_type(self) -> S::Owned\n    where\n        S::Owned: From<Box<S>>,\n    {\n        <Self>::into_owned_type(self)\n    }\n\n    fn to_owned_type(&self) -> S::Owned {\n        <Self>::to_owned_type(self)\n    }\n}\n\n// *** Default ***\n\nimpl<S: ?Sized + StringToFromBytes> Default for InlineFlexStr<S>\nwhere\n    for<'a> &'a S: Default,\n{\n    fn default() -> Self {\n        Self::from_bytes(S::self_as_raw_bytes(Default::default()))\n    }\n}\n\n// *** Copy ***\n\nimpl<S: ?Sized + StringToFromBytes> Copy for InlineFlexStr<S> {}\n\n// *** Clone ***\n\nimpl<S: ?Sized + StringToFromBytes> Clone for InlineFlexStr<S> {\n    fn clone(&self) -> Self {\n        *self\n    }\n}\n\n// *** Hash ***\n\nimpl<S: ?Sized + StringToFromBytes> Hash for InlineFlexStr<S>\nwhere\n    S: Hash,\n{\n    fn hash<H: Hasher>(&self, state: &mut H) {\n        self.as_ref_type().hash(state);\n    }\n}\n\n// *** AsMut ***\n\nimpl<S: ?Sized + StringFromBytesMut> AsMut<S> for InlineFlexStr<S> {\n    #[inline]\n    fn as_mut(&mut self) -> &mut S {\n        self.as_mut_type()\n    }\n}\n\n// *** Deref<Target = S> ***\n\nimpl<S: ?Sized + StringToFromBytes> Deref for InlineFlexStr<S> {\n    type Target = S;\n\n    fn deref(&self) -> &Self::Target {\n        self.as_ref_type()\n    }\n}\n\n// *** DerefMut ***\n\nimpl<S: ?Sized + StringFromBytesMut> DerefMut for InlineFlexStr<S> {\n    fn deref_mut(&mut self) -> &mut Self::Target {\n        self.as_mut_type()\n    }\n}\n\n// *** Display ***\n\nimpl<S: ?Sized + StringToFromBytes> fmt::Display for InlineFlexStr<S>\nwhere\n    S: fmt::Display,\n{\n    fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {\n        S::fmt(self.as_ref_type(), f)\n    }\n}\n\n// *** Borrow / BorrowMut ***\n\nimpl<S: ?Sized + StringToFromBytes> Borrow<S> for InlineFlexStr<S> {\n    fn borrow(&self) -> &S {\n        self.as_ref_type()\n    }\n}\n\nimpl<S: ?Sized + StringFromBytesMut> BorrowMut<S> for InlineFlexStr<S> {\n    fn borrow_mut(&mut self) -> &mut S {\n        self.as_mut_type()\n    }\n}\n\n// *** PartialEq / Eq ***\n\nimpl<S: ?Sized + StringToFromBytes> PartialEq for InlineFlexStr<S>\nwhere\n    S: PartialEq,\n{\n    fn eq(&self, other: &Self) -> bool {\n        S::eq(self.as_ref_type(), other.as_ref_type())\n    }\n}\n\nimpl<S: ?Sized + StringToFromBytes> Eq for InlineFlexStr<S> where S: Eq {}\n\n// *** PartialOrd / Ord ***\n\nimpl<S: ?Sized + StringToFromBytes> PartialOrd for InlineFlexStr<S>\nwhere\n    S: PartialOrd,\n{\n    fn partial_cmp(&self, other: &Self) -> Option<Ordering> {\n        S::partial_cmp(self.as_ref_type(), other.as_ref_type())\n    }\n}\n\nimpl<S: ?Sized + StringToFromBytes> Ord for InlineFlexStr<S>\nwhere\n    S: Ord,\n{\n    fn cmp(&self, other: &Self) -> Ordering {\n        S::cmp(self.as_ref_type(), other.as_ref_type())\n    }\n}\n\n// *** Index / IndexMut ***\n\nimpl<S: ?Sized + StringToFromBytes, I: SliceIndex<S>> Index<I> for InlineFlexStr<S>\nwhere\n    S: Index<I>,\n{\n    type Output = S::Output;\n\n    fn index(&self, index: I) -> &Self::Output {\n        S::index(self.as_ref_type(), index)\n    }\n}\n\nimpl<S: ?Sized + StringFromBytesMut, I: SliceIndex<S>> IndexMut<I> for InlineFlexStr<S>\nwhere\n    S: IndexMut<I>,\n{\n    fn index_mut(&mut self, index: I) -> &mut Self::Output {\n        S::index_mut(self.as_mut_type(), index)\n    }\n}\n\n// *** ToSocketAddrs ***\n\n#[cfg(feature = \"std\")]\nimpl<S: ?Sized + StringToFromBytes> ToSocketAddrs for InlineFlexStr<S>\nwhere\n    S: ToSocketAddrs,\n{\n    type Iter = <S as ToSocketAddrs>::Iter;\n\n    fn to_socket_addrs(&self) -> io::Result<<S as ToSocketAddrs>::Iter> {\n        self.as_ref_type().to_socket_addrs()\n    }\n}\n\n// *** Serialize ***\n\n#[cfg(feature = \"serde\")]\nimpl<S: ?Sized + StringToFromBytes> Serialize for InlineFlexStr<S>\nwhere\n    S: Serialize,\n{\n    fn serialize<SER: Serializer>(&self, serializer: SER) -> Result<SER::Ok, SER::Error> {\n        S::serialize(self.as_ref_type(), serializer)\n    }\n}\n\n// *** Zeroize ***\n\n#[cfg(feature = \"zeroize\")]\nimpl<S: ?Sized + StringToFromBytes> zeroize::Zeroize for InlineFlexStr<S> {\n    fn zeroize(&mut self) {\n        self.inline.zeroize();\n        self.len.zeroize();\n    }\n}\n\n// *** Deserialize ***\n\n#[cfg(feature = \"serde\")]\nimpl<'de, S: ?Sized + StringToFromBytes> Deserialize<'de> for InlineFlexStr<S>\nwhere\n    Box<S>: Deserialize<'de>,\n{\n    fn deserialize<D: Deserializer<'de>>(deserializer: D) -> Result<Self, D::Error> {\n        // TODO: This is inefficent, we should ideally deserialize directly into the InlineFlexStr type.\n        // However, Deserialize is not implmented for all types of &S, so likely that would mean\n        // a non-generic implementation for each type of S, likely via a Visitor pattern. That also\n        // means we'd have to understand how serde serializes each type, and this might be brittle if\n        // that ever changes (for example, OsStr is a bit special). For now, this is a quick way to\n        // make it work, albeit at the cost of an allocation and a copy.\n        let s = Box::deserialize(deserializer)?;\n\n        InlineFlexStr::try_from_type(&*s).map_err(|_| {\n            let bytes = S::self_as_raw_bytes(&*s);\n            serde::de::Error::invalid_length(bytes.len(), &\"string too long for inline storage\")\n        })\n    }\n}\n"
  },
  {
    "path": "inline_flexstr/src/lib.rs",
    "content": "#![cfg_attr(not(feature = \"std\"), no_std)]\n#![cfg_attr(\n    all(\n        not(all(feature = \"win_min_unsafe\", target_family = \"windows\")),\n        feature = \"safe\"\n    ),\n    forbid(unsafe_code)\n)]\n#![cfg_attr(docsrs, feature(doc_cfg))]\n#![warn(missing_docs)]\n\n//! A simple to use, copy/clone-efficient inline string type for Rust\n\nextern crate alloc;\n\n#[cfg(feature = \"cstr\")]\n#[doc = include_str!(\"../README.md\")]\nmod readme_tests {}\n\n#[cfg(feature = \"bytes\")]\n/// Module for byte-based strings (`[u8]`)\nmod bytes;\n#[cfg(feature = \"cstr\")]\n/// Module for `CStr`-based strings\nmod cstr;\n/// Module for inline strings\nmod inline;\n#[cfg(all(feature = \"std\", feature = \"osstr\"))]\n/// Module for `OsStr`-based strings\nmod osstr;\n#[cfg(all(feature = \"std\", feature = \"path\"))]\n/// Module for `Path`-based strings\nmod path;\n#[cfg(feature = \"str\")]\n/// Module for `str`-based strings\nmod str;\n\n#[cfg(feature = \"bytes\")]\npub use bytes::InlineBytes;\n#[cfg(feature = \"cstr\")]\npub use cstr::{InlineCStr, TooLongOrNulError};\n#[cfg(feature = \"cstr\")]\npub use flexstr_support::InteriorNulError;\npub use flexstr_support::StringLike;\n#[cfg(all(feature = \"std\", feature = \"osstr\"))]\npub use osstr::InlineOsStr;\n#[cfg(all(feature = \"std\", feature = \"path\"))]\npub use path::InlinePath;\n#[cfg(feature = \"str\")]\npub use str::{InlineStr, TooLongOrUtf8Error};\n\npub use inline::{INLINE_CAPACITY, InlineFlexStr, TooLongForInlining};\n"
  },
  {
    "path": "inline_flexstr/src/osstr.rs",
    "content": "use alloc::borrow::Cow;\nuse core::str::FromStr;\nuse std::ffi::{OsStr, OsString};\nuse std::path::Path;\n\nuse crate::inline::{InlineFlexStr, TooLongForInlining, inline_partial_eq_impl};\n\nuse flexstr_support::StringToFromBytes;\n\n/// Inline `OsStr` type\npub type InlineOsStr = InlineFlexStr<OsStr>;\n\n// *** TryFrom for InlineFlexStr ***\n\n// NOTE: Cannot be implemented generically because of impl<T, U> TryFrom<U> for T where U: Into<T>\nimpl<'s> TryFrom<&'s OsStr> for InlineFlexStr<OsStr> {\n    type Error = TooLongForInlining;\n\n    #[inline]\n    fn try_from(s: &'s OsStr) -> Result<Self, Self::Error> {\n        InlineFlexStr::try_from_type(s)\n    }\n}\n\nimpl<'s> TryFrom<&'s str> for InlineFlexStr<OsStr> {\n    type Error = TooLongForInlining;\n\n    #[inline]\n    fn try_from(s: &'s str) -> Result<Self, Self::Error> {\n        InlineFlexStr::try_from_type(OsStr::new(s))\n    }\n}\n\nimpl<'s> TryFrom<&'s Path> for InlineFlexStr<OsStr> {\n    type Error = TooLongForInlining;\n\n    #[inline]\n    fn try_from(p: &'s Path) -> Result<Self, Self::Error> {\n        InlineFlexStr::try_from_type(p.as_os_str())\n    }\n}\n\n// *** PartialEq ***\n\ninline_partial_eq_impl!(OsStr, OsStr);\ninline_partial_eq_impl!(&OsStr, OsStr);\ninline_partial_eq_impl!(OsString, OsStr);\ninline_partial_eq_impl!(Cow<'_, OsStr>, OsStr);\n\n// *** AsRef ***\n\nimpl<S: ?Sized + StringToFromBytes> AsRef<OsStr> for InlineFlexStr<S>\nwhere\n    S: AsRef<OsStr>,\n{\n    fn as_ref(&self) -> &OsStr {\n        self.as_ref_type().as_ref()\n    }\n}\n\n// *** FromStr ***\n\nimpl FromStr for InlineFlexStr<OsStr> {\n    type Err = TooLongForInlining;\n\n    fn from_str(s: &str) -> Result<Self, Self::Err> {\n        InlineFlexStr::try_from_type(OsStr::new(s))\n    }\n}\n"
  },
  {
    "path": "inline_flexstr/src/path.rs",
    "content": "use alloc::borrow::Cow;\nuse core::str::FromStr;\nuse std::{\n    ffi::OsStr,\n    path::{Path, PathBuf},\n};\n\nuse crate::inline::{InlineFlexStr, TooLongForInlining, inline_partial_eq_impl};\n\nuse flexstr_support::StringToFromBytes;\n\n/// Inline `Path` type\npub type InlinePath = InlineFlexStr<Path>;\n\n// *** TryFrom for InlineFlexStr ***\n\n// NOTE: Cannot be implemented generically because of impl<T, U> TryFrom<U> for T where U: Into<T>\nimpl<'s> TryFrom<&'s Path> for InlineFlexStr<Path> {\n    type Error = TooLongForInlining;\n\n    #[inline]\n    fn try_from(s: &'s Path) -> Result<Self, Self::Error> {\n        InlineFlexStr::try_from_type(s)\n    }\n}\n\nimpl<'s> TryFrom<&'s str> for InlineFlexStr<Path> {\n    type Error = TooLongForInlining;\n\n    #[inline]\n    fn try_from(s: &'s str) -> Result<Self, Self::Error> {\n        InlineFlexStr::try_from_type(Path::new(s))\n    }\n}\n\nimpl<'s> TryFrom<&'s OsStr> for InlineFlexStr<Path> {\n    type Error = TooLongForInlining;\n\n    #[inline]\n    fn try_from(s: &'s OsStr) -> Result<Self, Self::Error> {\n        InlineFlexStr::try_from_type(Path::new(s))\n    }\n}\n\n// *** PartialEq ***\n\ninline_partial_eq_impl!(Path, Path);\ninline_partial_eq_impl!(&Path, Path);\ninline_partial_eq_impl!(PathBuf, Path);\ninline_partial_eq_impl!(Cow<'_, Path>, Path);\n\n// *** AsRef ***\n\nimpl<S: ?Sized + StringToFromBytes> AsRef<Path> for InlineFlexStr<S>\nwhere\n    S: AsRef<Path>,\n{\n    fn as_ref(&self) -> &Path {\n        self.as_ref_type().as_ref()\n    }\n}\n\n// *** FromStr ***\n\nimpl FromStr for InlineFlexStr<Path> {\n    type Err = TooLongForInlining;\n\n    fn from_str(s: &str) -> Result<Self, Self::Err> {\n        InlineFlexStr::try_from_type(Path::new(s))\n    }\n}\n"
  },
  {
    "path": "inline_flexstr/src/str.rs",
    "content": "use alloc::{borrow::Cow, fmt, string::String};\nuse core::{\n    error::Error,\n    str::{FromStr, Utf8Error},\n};\n#[cfg(feature = \"std\")]\nuse std::{ffi::OsStr, path::Path};\n\nuse crate::inline::{InlineFlexStr, TooLongForInlining, inline_partial_eq_impl};\n\nuse flexstr_support::StringToFromBytes;\n\n/// Inline `str` type\npub type InlineStr = InlineFlexStr<str>;\n\n// *** TooLongOrUtf8Error ***\n\n/// Error type returned when a string is too long for inline storage or has an invalid UTF-8 sequence.\n#[derive(Debug)]\npub enum TooLongOrUtf8Error {\n    /// The string is too long for inline storage\n    TooLong(TooLongForInlining),\n    /// The string has an invalid UTF-8 sequence\n    Utf8Error(Utf8Error),\n}\n\nimpl fmt::Display for TooLongOrUtf8Error {\n    fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {\n        match self {\n            TooLongOrUtf8Error::TooLong(e) => e.fmt(f),\n            TooLongOrUtf8Error::Utf8Error(e) => e.fmt(f),\n        }\n    }\n}\n\nimpl Error for TooLongOrUtf8Error {}\n\n// *** TryFrom for InlineFlexStr ***\n\n// NOTE: Cannot be implemented generically because of impl<T, U> TryFrom<U> for T where U: Into<T>\nimpl<'s> TryFrom<&'s str> for InlineFlexStr<str> {\n    type Error = TooLongForInlining;\n\n    #[inline]\n    fn try_from(s: &'s str) -> Result<Self, Self::Error> {\n        InlineFlexStr::try_from_type(s)\n    }\n}\n\nimpl<'s> TryFrom<&'s [u8]> for InlineFlexStr<str> {\n    type Error = TooLongOrUtf8Error;\n\n    #[inline]\n    fn try_from(s: &'s [u8]) -> Result<Self, Self::Error> {\n        match str::from_utf8(s) {\n            Ok(s) => InlineFlexStr::try_from_type(s).map_err(TooLongOrUtf8Error::TooLong),\n            Err(e) => Err(TooLongOrUtf8Error::Utf8Error(e)),\n        }\n    }\n}\n\n#[cfg(feature = \"std\")]\nimpl<'s> TryFrom<&'s OsStr> for InlineFlexStr<str> {\n    type Error = TooLongOrUtf8Error;\n\n    #[inline]\n    fn try_from(s: &'s OsStr) -> Result<Self, Self::Error> {\n        match s.try_into() {\n            Ok(s) => InlineFlexStr::try_from_type(s).map_err(TooLongOrUtf8Error::TooLong),\n            Err(e) => Err(TooLongOrUtf8Error::Utf8Error(e)),\n        }\n    }\n}\n\n#[cfg(feature = \"std\")]\nimpl<'s> TryFrom<&'s Path> for InlineFlexStr<str> {\n    type Error = TooLongOrUtf8Error;\n\n    #[inline]\n    fn try_from(s: &'s Path) -> Result<Self, Self::Error> {\n        match s.as_os_str().try_into() {\n            Ok(s) => InlineFlexStr::try_from_type(s).map_err(TooLongOrUtf8Error::TooLong),\n            Err(e) => Err(TooLongOrUtf8Error::Utf8Error(e)),\n        }\n    }\n}\n\n// *** PartialEq ***\n\ninline_partial_eq_impl!(str, str);\ninline_partial_eq_impl!(&str, str);\ninline_partial_eq_impl!(String, str);\ninline_partial_eq_impl!(Cow<'_, str>, str);\n\n// *** AsRef ***\n\nimpl<S: ?Sized + StringToFromBytes> AsRef<str> for InlineFlexStr<S>\nwhere\n    S: AsRef<str>,\n{\n    fn as_ref(&self) -> &str {\n        self.as_ref_type().as_ref()\n    }\n}\n\n// *** FromStr ***\n\nimpl FromStr for InlineFlexStr<str> {\n    type Err = TooLongForInlining;\n\n    #[inline]\n    fn from_str(s: &str) -> Result<Self, Self::Err> {\n        InlineFlexStr::try_from_type(s)\n    }\n}\n\n// *** Prost ***\n\n#[cfg(feature = \"prost\")]\n#[allow(deprecated)] // DecodeError::new is deprecated in prost 0.14 with no public replacement yet\nimpl prost::Message for InlineFlexStr<str> {\n    fn encode_raw(&self, buf: &mut impl prost::bytes::BufMut)\n    where\n        Self: Sized,\n    {\n        buf.put_slice(self.as_ref_type().as_bytes());\n    }\n\n    fn merge_field(\n        &mut self,\n        tag: u32,\n        wire_type: prost::encoding::WireType,\n        buf: &mut impl prost::bytes::Buf,\n        ctx: prost::encoding::DecodeContext,\n    ) -> Result<(), prost::DecodeError>\n    where\n        Self: Sized,\n    {\n        prost::encoding::skip_field(wire_type, tag, buf, ctx)\n    }\n\n    fn encoded_len(&self) -> usize {\n        self.as_ref_type().len()\n    }\n\n    fn clear(&mut self) {\n        *self = Default::default();\n    }\n\n    fn merge(&mut self, mut buf: impl prost::bytes::Buf) -> Result<(), prost::DecodeError>\n    where\n        Self: Sized,\n    {\n        let bytes = buf.copy_to_bytes(buf.remaining());\n        let s = core::str::from_utf8(&bytes)\n            .map_err(|_| prost::DecodeError::new(\"invalid UTF-8 in string field\"))?;\n        *self = InlineFlexStr::try_from_type(s)\n            .map_err(|_| prost::DecodeError::new(\"string too long for inline storage\"))?;\n        Ok(())\n    }\n\n    fn merge_length_delimited(\n        &mut self,\n        mut buf: impl prost::bytes::Buf,\n    ) -> Result<(), prost::DecodeError>\n    where\n        Self: Sized,\n    {\n        let len = prost::encoding::decode_varint(&mut buf)? as usize;\n        if buf.remaining() < len {\n            return Err(prost::DecodeError::new(\"buffer underflow\"));\n        }\n        self.merge(buf.take(len))\n    }\n}\n\n// *** SQLx ***\n\n#[cfg(feature = \"sqlx\")]\nimpl<'r, DB: sqlx::Database> sqlx::Decode<'r, DB> for InlineFlexStr<str>\nwhere\n    &'r str: sqlx::Decode<'r, DB>,\n{\n    fn decode(\n        value: <DB as sqlx::Database>::ValueRef<'r>,\n    ) -> Result<Self, sqlx::error::BoxDynError> {\n        let value = <&str as sqlx::Decode<DB>>::decode(value)?;\n        Ok(value.try_into()?)\n    }\n}\n\n#[cfg(feature = \"sqlx\")]\nimpl<'r, DB: sqlx::Database> sqlx::Encode<'r, DB> for InlineFlexStr<str>\nwhere\n    String: sqlx::Encode<'r, DB>,\n{\n    fn encode_by_ref(\n        &self,\n        buf: &mut <DB as sqlx::Database>::ArgumentBuffer<'r>,\n    ) -> Result<sqlx::encode::IsNull, sqlx::error::BoxDynError> {\n        // There might be a more efficient way to do this (or not?), but the lifetimes seem to be constraining\n        // us to using an owned type here. Works at the cost of an allocation/copy.\n        <String as sqlx::Encode<'r, DB>>::encode(self.to_string(), buf)\n    }\n\n    fn size_hint(&self) -> usize {\n        self.len()\n    }\n}\n\n#[cfg(feature = \"sqlx\")]\nimpl<DB: sqlx::Database> sqlx::Type<DB> for InlineFlexStr<str>\nwhere\n    str: sqlx::Type<DB>,\n{\n    fn type_info() -> <DB as sqlx::Database>::TypeInfo {\n        <str as sqlx::Type<DB>>::type_info()\n    }\n\n    fn compatible(ty: &<DB as sqlx::Database>::TypeInfo) -> bool {\n        <str as sqlx::Type<DB>>::compatible(ty)\n    }\n}\n\n#[cfg(all(feature = \"sqlx\", feature = \"sqlx_pg_arrays\"))]\nimpl sqlx::postgres::PgHasArrayType for InlineFlexStr<str>\nwhere\n    for<'a> &'a str: sqlx::postgres::PgHasArrayType,\n{\n    fn array_type_info() -> sqlx::postgres::PgTypeInfo {\n        <&str as sqlx::postgres::PgHasArrayType>::array_type_info()\n    }\n\n    fn array_compatible(ty: &sqlx::postgres::PgTypeInfo) -> bool {\n        <&str as sqlx::postgres::PgHasArrayType>::array_compatible(ty)\n    }\n}\n\n// *** Utoipa ***\n\n#[cfg(feature = \"utoipa\")]\nimpl utoipa::PartialSchema for InlineFlexStr<str> {\n    fn schema() -> utoipa::openapi::RefOr<utoipa::openapi::schema::Schema> {\n        utoipa::openapi::schema::ObjectBuilder::new()\n            .schema_type(utoipa::openapi::schema::SchemaType::new(\n                utoipa::openapi::schema::Type::String,\n            ))\n            .into()\n    }\n}\n\n#[cfg(feature = \"utoipa\")]\nimpl utoipa::ToSchema for InlineFlexStr<str> {\n    fn name() -> Cow<'static, str> {\n        Cow::Borrowed(\"String\")\n    }\n}\n"
  },
  {
    "path": "inline_flexstr/tests/common/as_ref.rs",
    "content": "#![allow(dead_code)]\n\nuse inline_flexstr::InlineFlexStr;\n\n/// Test AsRef<[u8]> for InlineFlexStr<[u8]>\n/// Input should be small enough to inline\n#[cfg(feature = \"bytes\")]\npub fn test_as_ref_bytes(s: &'static [u8]) {\n    let inline_str = InlineFlexStr::<[u8]>::try_from_type(s)\n        .expect(\"test input should be small enough to inline\");\n    let bytes_ref: &[u8] = inline_str.as_ref();\n    assert_eq!(bytes_ref, s);\n}\n\n/// Test AsRef<OsStr> for InlineFlexStr<OsStr>\n/// Input should be small enough to inline\n#[cfg(all(feature = \"std\", feature = \"osstr\"))]\npub fn test_as_ref_osstr(s: &'static std::ffi::OsStr) {\n    let inline_str = InlineFlexStr::<std::ffi::OsStr>::try_from_type(s)\n        .expect(\"test input should be small enough to inline\");\n    let os_str_ref: &std::ffi::OsStr = inline_str.as_ref();\n    assert_eq!(os_str_ref, s);\n}\n\n/// Test AsRef<Path> for InlineFlexStr<Path>\n/// Input should be small enough to inline\n#[cfg(all(feature = \"std\", feature = \"path\"))]\npub fn test_as_ref_path(s: &'static std::path::Path) {\n    let inline_str = InlineFlexStr::<std::path::Path>::try_from_type(s)\n        .expect(\"test input should be small enough to inline\");\n    let path_ref: &std::path::Path = inline_str.as_ref();\n    assert_eq!(path_ref, s);\n}\n\n/// Test AsRef<CStr> for InlineFlexStr<CStr>\n/// Input should be small enough to inline\n#[cfg(feature = \"cstr\")]\npub fn test_as_ref_cstr(s: &'static core::ffi::CStr) {\n    let inline_str = InlineFlexStr::<core::ffi::CStr>::try_from_type(s)\n        .expect(\"test input should be small enough to inline\");\n    let cstr_ref: &core::ffi::CStr = inline_str.as_ref();\n    assert_eq!(cstr_ref.to_bytes(), s.to_bytes());\n}\n\n/// Test AsRef<str> for InlineFlexStr<str>\n/// Input should be small enough to inline\n#[cfg(feature = \"str\")]\npub fn test_as_ref_str(s: &'static str) {\n    let inline_str = InlineFlexStr::<str>::try_from_type(s)\n        .expect(\"test input should be small enough to inline\");\n    let str_ref: &str = inline_str.as_ref();\n    assert_eq!(str_ref, s);\n}\n"
  },
  {
    "path": "inline_flexstr/tests/common/basic.rs",
    "content": "#![allow(dead_code)]\n\nuse core::fmt;\nuse flexstr_support::{StringLike, StringToFromBytes};\nuse inline_flexstr::InlineFlexStr;\n\n/// Test creation from inline string\npub fn test_creation_from_inline<S>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n{\n    let inline_str = InlineFlexStr::try_from_type(s).unwrap();\n    assert_eq!(inline_str.as_ref_type(), s);\n}\n\n/// Test empty string creation\npub fn test_empty<S>(empty: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes,\n    InlineFlexStr<S>: StringLike<S>,\n{\n    let inline_str = InlineFlexStr::try_from_type(empty).unwrap();\n    assert!(StringLike::is_empty(&inline_str));\n    assert_eq!(StringLike::len(&inline_str), 0);\n}\n\n/// Test accessor methods\npub fn test_accessors<S>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n    InlineFlexStr<S>: StringLike<S>,\n{\n    let inline_str = InlineFlexStr::try_from_type(s).unwrap();\n\n    // Test as_ref_type\n    assert_eq!(inline_str.as_ref_type(), s);\n\n    // Test as_bytes\n    let bytes = inline_str.as_bytes();\n    assert_eq!(bytes, S::self_as_bytes(s));\n\n    // Test as_raw_bytes\n    let raw_bytes = inline_str.as_raw_bytes();\n    assert_eq!(raw_bytes, S::self_as_raw_bytes(s));\n\n    // Test len\n    assert_eq!(StringLike::len(&inline_str), s.self_as_bytes().len());\n\n    // Test is_empty\n    assert_eq!(\n        StringLike::is_empty(&inline_str),\n        s.self_as_bytes().is_empty()\n    );\n}\n\n/// Test cloning\npub fn test_clone<S>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + PartialEq + fmt::Debug,\n{\n    // Input should be small enough to inline\n    let inline_str =\n        InlineFlexStr::try_from_type(s).expect(\"test input should be small enough to inline\");\n    let cloned = inline_str;\n    assert_eq!(inline_str, cloned);\n}\n\n/// Test Default implementation\n/// Note: This test is only applicable for types where `&S: Default`\npub fn test_default<S>()\nwhere\n    S: ?Sized + StringToFromBytes,\n    for<'a> &'a S: Default,\n    InlineFlexStr<S>: StringLike<S>,\n{\n    let inline_str = InlineFlexStr::default();\n    assert!(StringLike::is_empty(&inline_str));\n}\n"
  },
  {
    "path": "inline_flexstr/tests/common/borrow.rs",
    "content": "#![allow(dead_code)]\n\nuse core::borrow::BorrowMut;\nuse core::fmt;\nuse flexstr_support::{StringFromBytesMut, StringToFromBytes};\nuse inline_flexstr::InlineFlexStr;\n\n/// Test BorrowMut implementation for InlineFlexStr\npub fn test_borrow_mut<S>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + StringFromBytesMut + PartialEq + fmt::Debug,\n{\n    // Input should be small enough to inline\n    let mut inline_str =\n        InlineFlexStr::try_from_type(s).expect(\"test input should be small enough to inline\");\n\n    // Test BorrowMut::borrow_mut() returns &mut S\n    // For inlined strings, the pointer will be different (data is copied), but values should be equal\n    let borrowed_mut: &mut S = inline_str.borrow_mut();\n    assert_eq!(borrowed_mut, s);\n}\n"
  },
  {
    "path": "inline_flexstr/tests/common/comparison.rs",
    "content": "#![allow(dead_code)]\n\nuse core::fmt;\nuse flexstr_support::StringToFromBytes;\nuse inline_flexstr::InlineFlexStr;\n\n/// Test PartialEq implementation\npub fn test_partial_eq<S>(s1: &'static S, s2: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + PartialEq + fmt::Debug,\n{\n    // Inputs should be small enough to inline\n    let inline_str1 =\n        InlineFlexStr::try_from_type(s1).expect(\"test input should be small enough to inline\");\n    let inline_str2 =\n        InlineFlexStr::try_from_type(s2).expect(\"test input should be small enough to inline\");\n\n    // Test equality\n    if s1 == s2 {\n        assert_eq!(inline_str1, inline_str2);\n    } else {\n        assert!(inline_str1 != inline_str2);\n    }\n}\n\n/// Test Eq implementation\npub fn test_eq<S>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + PartialEq + Eq + fmt::Debug,\n{\n    // Input should be small enough to inline\n    let inline_str1 =\n        InlineFlexStr::try_from_type(s).expect(\"test input should be small enough to inline\");\n    let inline_str2 =\n        InlineFlexStr::try_from_type(s).expect(\"test input should be small enough to inline\");\n\n    // Eq requires reflexivity, symmetry, transitivity\n    // Reflexivity: a == a\n    assert_eq!(inline_str1, inline_str2); // Symmetry\n    assert_eq!(inline_str2, inline_str1); // Symmetry\n}\n\n/// Test PartialOrd implementation\npub fn test_partial_ord<S>(s1: &'static S, s2: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + PartialOrd,\n{\n    // Inputs should be small enough to inline\n    let inline_str1 =\n        InlineFlexStr::try_from_type(s1).expect(\"test input should be small enough to inline\");\n    let inline_str2 =\n        InlineFlexStr::try_from_type(s2).expect(\"test input should be small enough to inline\");\n\n    // Test inputs should be comparable (partial_cmp should return Some)\n    let ord = s1\n        .partial_cmp(s2)\n        .expect(\"test inputs should be comparable\");\n    assert_eq!(inline_str1.partial_cmp(&inline_str2), Some(ord));\n}\n\n/// Test Ord implementation\npub fn test_ord<S>(s1: &'static S, s2: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + Ord,\n{\n    // Inputs should be small enough to inline\n    let inline_str1 =\n        InlineFlexStr::try_from_type(s1).expect(\"test input should be small enough to inline\");\n    let inline_str2 =\n        InlineFlexStr::try_from_type(s2).expect(\"test input should be small enough to inline\");\n\n    assert_eq!(inline_str1.cmp(&inline_str2), s1.cmp(s2));\n}\n\n/// Test Hash implementation consistency\npub fn test_hash<S>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + core::hash::Hash,\n{\n    use core::hash::{Hash, Hasher};\n    use std::collections::hash_map::DefaultHasher;\n\n    // Input should be small enough to inline\n    let inline_str1 =\n        InlineFlexStr::try_from_type(s).expect(\"test input should be small enough to inline\");\n    let mut hasher1 = DefaultHasher::new();\n    inline_str1.hash(&mut hasher1);\n    let hash1 = hasher1.finish();\n\n    // Test that copying produces same hash\n    let inline_str2 = inline_str1;\n    let mut hasher2 = DefaultHasher::new();\n    inline_str2.hash(&mut hasher2);\n    let hash2 = hasher2.finish();\n    assert_eq!(hash1, hash2);\n}\n\n/// Test comparison with &S\npub fn test_comparison_with_ref<S>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n{\n    // Input should be small enough to inline\n    let inline_str =\n        InlineFlexStr::try_from_type(s).expect(\"test input should be small enough to inline\");\n\n    // Test equality with &S - compare through as_ref_type\n    assert_eq!(inline_str.as_ref_type(), s);\n}\n\n/// Test comparison with S::Owned\npub fn test_comparison_with_owned<S>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n    S::Owned: PartialEq + AsRef<S>,\n{\n    // Input should be small enough to inline\n    let inline_str =\n        InlineFlexStr::try_from_type(s).expect(\"test input should be small enough to inline\");\n    let owned = s.to_owned();\n\n    assert_eq!(inline_str.as_ref_type(), owned.as_ref());\n}\n\n/// Test PartialEq with owned types (String, Cow, etc.) for InlineFlexStr\npub fn test_partial_eq_with_owned_types<S>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + PartialEq + fmt::Debug,\n    S::Owned: PartialEq<S> + AsRef<S>,\n{\n    use alloc::borrow::Cow;\n\n    // Input should be small enough to inline\n    let inline_str =\n        InlineFlexStr::try_from_type(s).expect(\"test input should be small enough to inline\");\n    let owned: S::Owned = s.to_owned();\n\n    // Test InlineFlexStr == S::Owned (through PartialEq implementation)\n    assert_eq!(inline_str.as_ref_type(), owned.as_ref());\n    // Test reverse comparison: S::Owned == InlineFlexStr\n    assert_eq!(owned.as_ref(), inline_str.as_ref_type());\n\n    // Test with Cow::Owned\n    let cow_owned: Cow<'_, S> = Cow::Owned(owned);\n    assert_eq!(inline_str.as_ref_type(), cow_owned.as_ref());\n    assert_eq!(cow_owned.as_ref(), inline_str.as_ref_type());\n\n    // Test with Cow::Borrowed\n    let cow_borrowed: Cow<'_, S> = Cow::Borrowed(s);\n    assert_eq!(inline_str.as_ref_type(), cow_borrowed.as_ref());\n    assert_eq!(cow_borrowed.as_ref(), inline_str.as_ref_type());\n}\n"
  },
  {
    "path": "inline_flexstr/tests/common/conversion.rs",
    "content": "#![allow(dead_code)]\n\nuse core::fmt;\nuse flexstr_support::{StringLike, StringToFromBytes};\nuse inline_flexstr::InlineFlexStr;\n\n/// Test to_owned_type conversion\npub fn test_to_owned_type<S>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n    S::Owned: PartialEq + AsRef<S>,\n    InlineFlexStr<S>: StringLike<S>,\n{\n    // Input should be small enough to inline\n    let inline_str =\n        InlineFlexStr::try_from_type(s).expect(\"test input should be small enough to inline\");\n    let owned = StringLike::to_owned_type(&inline_str);\n    assert_eq!(owned.as_ref(), s);\n}\n\n/// Test into_owned_type conversion\npub fn test_into_owned_type<S>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + PartialEq + fmt::Debug,\n    S::Owned: PartialEq + AsRef<S> + From<Box<S>>,\n    InlineFlexStr<S>: StringLike<S>,\n{\n    // Input should be small enough to inline\n    let inline_str =\n        InlineFlexStr::try_from_type(s).expect(\"test input should be small enough to inline\");\n\n    let owned = StringLike::into_owned_type(inline_str);\n    assert_eq!(owned.as_ref(), s);\n}\n"
  },
  {
    "path": "inline_flexstr/tests/common/cstr_specific.rs",
    "content": "#![allow(dead_code)]\n\nuse core::ffi::CStr;\nuse inline_flexstr::{InlineFlexStr, TooLongOrNulError};\n\n/// Test InlineFlexStr::try_from_bytes_with_or_without_nul with valid CStr (with NUL)\npub fn test_try_from_bytes_with_nul() {\n    let bytes = b\"test\\0\";\n    let inline_str = InlineFlexStr::<CStr>::try_from_bytes_with_or_without_nul(bytes).unwrap();\n    assert_eq!(inline_str.as_ref_type(), c\"test\");\n}\n\n/// Test InlineFlexStr::try_from_bytes_with_or_without_nul with bytes without NUL\npub fn test_try_from_bytes_without_nul() {\n    let bytes = b\"test\";\n    let inline_str = InlineFlexStr::<CStr>::try_from_bytes_with_or_without_nul(bytes).unwrap();\n    // Should have NUL appended\n    assert_eq!(inline_str.as_bytes_with_nul(), b\"test\\0\");\n}\n\n/// Test InlineFlexStr::try_from_bytes_with_or_without_nul with interior NUL\npub fn test_try_from_bytes_interior_nul() {\n    let bytes = b\"te\\0st\";\n    let err = InlineFlexStr::<CStr>::try_from_bytes_with_or_without_nul(bytes).unwrap_err();\n    match err {\n        TooLongOrNulError::NulError(e) => assert_eq!(e.position, 2),\n        _ => panic!(\"Expected NulError\"),\n    }\n}\n\n/// Test InlineFlexStr::try_from_bytes_with_or_without_nul with too long string\npub fn test_try_from_bytes_too_long() {\n    let long_bytes = vec![b'x'; inline_flexstr::INLINE_CAPACITY];\n    let err = InlineFlexStr::<CStr>::try_from_bytes_with_or_without_nul(&long_bytes).unwrap_err();\n    match err {\n        TooLongOrNulError::TooLong(e) => {\n            assert_eq!(e.length, inline_flexstr::INLINE_CAPACITY);\n            assert_eq!(e.inline_capacity, inline_flexstr::INLINE_CAPACITY);\n        }\n        _ => panic!(\"Expected TooLong error\"),\n    }\n}\n\n/// Test as_bytes_with_nul\npub fn test_as_bytes_with_nul(cstr: &'static CStr) {\n    // Input should be small enough to inline\n    let inline_str =\n        InlineFlexStr::try_from_type(cstr).expect(\"test input should be small enough to inline\");\n    let bytes = inline_str.as_bytes_with_nul();\n    assert_eq!(bytes, cstr.to_bytes_with_nul());\n}\n"
  },
  {
    "path": "inline_flexstr/tests/common/display.rs",
    "content": "#![allow(dead_code)]\n\nuse core::fmt;\nuse flexstr_support::StringToFromBytes;\nuse inline_flexstr::InlineFlexStr;\n\n/// Test Display implementation for InlineFlexStr\npub fn test_display<S>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Display + fmt::Debug,\n{\n    // Input should be small enough to inline\n    let inline_str =\n        InlineFlexStr::try_from_type(s).expect(\"test input should be small enough to inline\");\n\n    // Format both the original and InlineFlexStr\n    let original_fmt = format!(\"{}\", s);\n    let inline_fmt = format!(\"{}\", inline_str);\n\n    assert_eq!(original_fmt, inline_fmt);\n}\n"
  },
  {
    "path": "inline_flexstr/tests/common/edge_cases.rs",
    "content": "#![allow(dead_code)]\n\nuse core::fmt;\nuse flexstr_support::{StringLike, StringToFromBytes};\nuse inline_flexstr::{InlineFlexStr, TooLongForInlining};\n\n/// Test empty string operations\npub fn test_empty_string<S>(empty: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + PartialEq + fmt::Debug,\n    InlineFlexStr<S>: StringLike<S>,\n{\n    let inline_str = InlineFlexStr::try_from_type(empty).unwrap();\n\n    assert!(StringLike::is_empty(&inline_str));\n    assert_eq!(StringLike::len(&inline_str), 0);\n\n    // Test empty string can be copied\n    let cloned = inline_str;\n    assert_eq!(inline_str, cloned);\n}\n\n/// Test capacity boundary - string at exact capacity\n/// Input must be exactly at INLINE_CAPACITY\npub fn test_capacity_boundary_exact<S>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n{\n    let bytes = s.self_as_raw_bytes();\n    assert_eq!(\n        bytes.len(),\n        inline_flexstr::INLINE_CAPACITY,\n        \"test input must be exactly at capacity\"\n    );\n\n    let inline_str =\n        InlineFlexStr::try_from_type(s).expect(\"string at exact capacity should inline\");\n    assert_eq!(inline_str.as_ref_type(), s);\n}\n\n/// Test capacity boundary - string one byte over capacity\n/// Input must be smaller than INLINE_CAPACITY\npub fn test_capacity_boundary_overflow<S>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n{\n    let bytes = s.self_as_raw_bytes();\n    assert!(\n        bytes.len() < inline_flexstr::INLINE_CAPACITY,\n        \"test input must be smaller than capacity\"\n    );\n\n    // Since bytes.len() < INLINE_CAPACITY, bytes.len() <= INLINE_CAPACITY is always true\n    // So try_from_type should always succeed\n    let _inline_str =\n        InlineFlexStr::try_from_type(s).expect(\"string smaller than capacity should succeed\");\n}\n\n/// Test TryFrom error cases - too long\n// Type parameter intentionally unused - kept for API consistency with other test functions\n#[allow(unused)]\npub fn test_try_from_too_long() {\n    // Create a string that's definitely too long\n    // This is tricky to do generically, so we'll test the error type\n    let _long_bytes = [0u8; inline_flexstr::INLINE_CAPACITY + 1];\n\n    // Try to create from bytes if possible\n    // This will depend on the specific string type\n    // For now, we'll just verify the error type exists\n    let err = TooLongForInlining {\n        length: inline_flexstr::INLINE_CAPACITY + 1,\n        inline_capacity: inline_flexstr::INLINE_CAPACITY,\n    };\n\n    assert_eq!(err.length, inline_flexstr::INLINE_CAPACITY + 1);\n    assert_eq!(err.inline_capacity, inline_flexstr::INLINE_CAPACITY);\n}\n\n/// Test various string lengths\npub fn test_various_lengths<S>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + PartialEq + fmt::Debug,\n    InlineFlexStr<S>: StringLike<S>,\n{\n    let bytes = s.self_as_bytes();\n    let len = bytes.len();\n\n    // Input should be small enough to inline\n    let inline_str =\n        InlineFlexStr::try_from_type(s).expect(\"test input should be small enough to inline\");\n\n    // Test length matches\n    assert_eq!(StringLike::len(&inline_str), len);\n\n    // Test empty check\n    assert_eq!(StringLike::is_empty(&inline_str), len == 0);\n}\n\n/// Test special content (if applicable)\npub fn test_special_content<S>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + PartialEq,\n{\n    // Input should be small enough to inline\n    let inline_str =\n        InlineFlexStr::try_from_type(s).expect(\"test input should be small enough to inline\");\n\n    // Test that special characters/content are preserved\n    let bytes = inline_str.as_bytes();\n    assert_eq!(bytes, s.self_as_bytes());\n\n    // Test that raw bytes match\n    let raw_bytes = inline_str.as_raw_bytes();\n    assert_eq!(raw_bytes, s.self_as_raw_bytes());\n}\n\n/// Test clone\npub fn test_clone<S>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + PartialEq + fmt::Debug,\n{\n    // Input should be small enough to inline\n    let inline_str =\n        InlineFlexStr::try_from_type(s).expect(\"test input should be small enough to inline\");\n    let cloned = inline_str;\n    assert_eq!(inline_str, cloned);\n}\n\n/// Test try_from_type error when string is too long\n/// Input must be larger than INLINE_CAPACITY\npub fn test_try_from_type_too_long<S>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug,\n{\n    let bytes = S::self_as_raw_bytes(s);\n    assert!(\n        bytes.len() > inline_flexstr::INLINE_CAPACITY,\n        \"test input must be too long to inline\"\n    );\n\n    let err = InlineFlexStr::try_from_type(s).unwrap_err();\n    assert_eq!(err.length, bytes.len());\n    assert_eq!(err.inline_capacity, inline_flexstr::INLINE_CAPACITY);\n}\n\n/// Test as_mut_type() for mutable string types\n#[cfg(feature = \"str\")]\npub fn test_as_mut_type_str() {\n    let mut inline_str = InlineFlexStr::<str>::try_from_type(\"test\").unwrap();\n    let mut_ref = inline_str.as_mut_type();\n    // Test that we can mutate\n    // Test input should be non-empty\n\n    let bytes = unsafe { mut_ref.as_bytes_mut() };\n    assert!(!bytes.is_empty(), \"test input should be non-empty\");\n    bytes[0] = b'T';\n    assert_eq!(inline_str.as_ref_type(), \"Test\");\n}\n\n/// Test as_mut_type() for [u8]\n#[cfg(feature = \"bytes\")]\npub fn test_as_mut_type_bytes() {\n    let mut inline_str = InlineFlexStr::<[u8]>::try_from_type(b\"test\").unwrap();\n    let mut_ref = inline_str.as_mut_type();\n    // Test that we can mutate\n    // Test input should be non-empty\n    let bytes = mut_ref;\n    assert!(!bytes.is_empty(), \"test input should be non-empty\");\n    bytes[0] = b'T';\n    assert_eq!(inline_str.as_ref_type(), b\"Test\");\n}\n"
  },
  {
    "path": "inline_flexstr/tests/common/errors.rs",
    "content": "#![allow(dead_code)]\n\nuse core::fmt;\nuse inline_flexstr::TooLongForInlining;\n\n#[cfg(feature = \"str\")]\nuse inline_flexstr::TooLongOrUtf8Error;\n\n#[cfg(feature = \"cstr\")]\nuse flexstr_support::InteriorNulError;\n#[cfg(feature = \"cstr\")]\nuse inline_flexstr::TooLongOrNulError;\n\n/// Test Display implementation for error types\npub fn test_error_display<E>(error: E)\nwhere\n    E: fmt::Display + fmt::Debug,\n{\n    let display_str = format!(\"{}\", error);\n    let debug_str = format!(\"{:?}\", error);\n\n    // Display should produce a non-empty string\n    assert!(!display_str.is_empty());\n    // Debug should also produce a non-empty string\n    assert!(!debug_str.is_empty());\n}\n\n/// Test TooLongForInlining error\npub fn test_too_long_for_inlining() {\n    let err = TooLongForInlining {\n        length: 100,\n        inline_capacity: 30,\n    };\n\n    // Test that the error message contains relevant information\n    let msg = format!(\"{}\", err);\n    assert!(msg.contains(\"too long\"));\n    assert!(msg.contains(\"100\"));\n    assert!(msg.contains(\"30\"));\n\n    test_error_display(err);\n}\n\n/// Test TooLongOrUtf8Error::TooLong variant\n#[cfg(feature = \"str\")]\npub fn test_too_long_or_utf8_error_too_long() {\n    let err = TooLongOrUtf8Error::TooLong(TooLongForInlining {\n        length: 100,\n        inline_capacity: 30,\n    });\n\n    test_error_display(err);\n}\n\n/// Test TooLongOrUtf8Error::Utf8Error variant\n#[cfg(feature = \"str\")]\npub fn test_too_long_or_utf8_error_utf8() {\n    // Create an invalid UTF-8 sequence\n    let invalid_utf8: &[u8] =\n        unsafe { core::slice::from_raw_parts([0xFFu8, 0xFFu8, 0xFFu8].as_ptr(), 3) };\n    let utf8_err = str::from_utf8(invalid_utf8).unwrap_err();\n\n    let err = TooLongOrUtf8Error::Utf8Error(utf8_err);\n    test_error_display(err);\n}\n\n/// Test InteriorNulError\n#[cfg(feature = \"cstr\")]\npub fn test_interior_nul_error() {\n    let err = InteriorNulError { position: 5 };\n\n    let msg = format!(\"{}\", err);\n    assert!(msg.contains(\"Interior NUL\"));\n    assert!(msg.contains(\"5\"));\n\n    test_error_display(err);\n}\n\n/// Test TooLongOrNulError::TooLong variant\n#[cfg(feature = \"cstr\")]\npub fn test_too_long_or_nul_error_too_long() {\n    let err = TooLongOrNulError::TooLong(TooLongForInlining {\n        length: 100,\n        inline_capacity: 30,\n    });\n\n    test_error_display(err);\n}\n\n/// Test TooLongOrNulError::NulError variant\n#[cfg(feature = \"cstr\")]\npub fn test_too_long_or_nul_error_nul() {\n    let err = TooLongOrNulError::NulError(InteriorNulError { position: 3 });\n\n    test_error_display(err);\n}\n"
  },
  {
    "path": "inline_flexstr/tests/common/from_str.rs",
    "content": "#![allow(dead_code)]\n\nuse core::fmt;\nuse core::str::FromStr;\nuse flexstr_support::StringToFromBytes;\nuse inline_flexstr::InlineFlexStr;\n\n/// Test FromStr success for InlineFlexStr\npub fn test_from_str_success<S>(s: &str)\nwhere\n    InlineFlexStr<S>: FromStr,\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n    <InlineFlexStr<S> as FromStr>::Err: fmt::Debug,\n{\n    let inline_str = InlineFlexStr::from_str(s).unwrap();\n    assert_eq!(inline_str.as_ref_type(), inline_str.as_ref_type()); // Basic sanity check\n}\n\n/// Test FromStr error for InlineFlexStr (too long)\n/// Input should be too long to inline, causing an error\npub fn test_from_str_error_too_long<S>(s: &str)\nwhere\n    InlineFlexStr<S>: FromStr,\n    S: ?Sized + StringToFromBytes + fmt::Debug,\n    <InlineFlexStr<S> as FromStr>::Err: fmt::Debug + fmt::Display,\n{\n    let err = InlineFlexStr::from_str(s).expect_err(\"test input should be too long to inline\");\n    // Test that error can be displayed\n    let _ = format!(\"{}\", err);\n}\n\n/// Test FromStr for InlineFlexStr<[u8]> success\n#[cfg(feature = \"bytes\")]\npub fn test_from_str_bytes_success() {\n    let inline_str = InlineFlexStr::<[u8]>::from_str(\"test\").unwrap();\n    assert_eq!(inline_str.as_ref_type(), b\"test\");\n}\n\n/// Test FromStr for InlineFlexStr<[u8]> error (too long)\n#[cfg(feature = \"bytes\")]\npub fn test_from_str_bytes_error() {\n    let long_str = \"x\".repeat(inline_flexstr::INLINE_CAPACITY + 1);\n    let err = InlineFlexStr::<[u8]>::from_str(&long_str).unwrap_err();\n    assert_eq!(err.length, inline_flexstr::INLINE_CAPACITY + 1);\n    assert_eq!(err.inline_capacity, inline_flexstr::INLINE_CAPACITY);\n}\n\n/// Test FromStr for InlineFlexStr<OsStr> success\n#[cfg(all(feature = \"std\", feature = \"osstr\"))]\npub fn test_from_str_osstr_success() {\n    use std::ffi::OsStr;\n\n    let inline_str = InlineFlexStr::<OsStr>::from_str(\"test\").unwrap();\n    assert_eq!(inline_str.as_ref_type(), OsStr::new(\"test\"));\n}\n\n/// Test FromStr for InlineFlexStr<OsStr> error (too long)\n#[cfg(all(feature = \"std\", feature = \"osstr\"))]\npub fn test_from_str_osstr_error() {\n    let long_str = \"x\".repeat(inline_flexstr::INLINE_CAPACITY + 1);\n    let err = InlineFlexStr::<std::ffi::OsStr>::from_str(&long_str).unwrap_err();\n    assert_eq!(err.length, inline_flexstr::INLINE_CAPACITY + 1);\n    assert_eq!(err.inline_capacity, inline_flexstr::INLINE_CAPACITY);\n}\n\n/// Test FromStr for InlineFlexStr<Path> success\n#[cfg(all(feature = \"std\", feature = \"path\"))]\npub fn test_from_str_path_success() {\n    use std::path::Path;\n\n    let inline_str = InlineFlexStr::<Path>::from_str(\"test\").unwrap();\n    assert_eq!(inline_str.as_ref_type(), Path::new(\"test\"));\n}\n\n/// Test FromStr for InlineFlexStr<Path> error (too long)\n#[cfg(all(feature = \"std\", feature = \"path\"))]\npub fn test_from_str_path_error() {\n    let long_str = \"x\".repeat(inline_flexstr::INLINE_CAPACITY + 1);\n    let err = InlineFlexStr::<std::path::Path>::from_str(&long_str).unwrap_err();\n    assert_eq!(err.length, inline_flexstr::INLINE_CAPACITY + 1);\n    assert_eq!(err.inline_capacity, inline_flexstr::INLINE_CAPACITY);\n}\n\n/// Test FromStr for InlineFlexStr<CStr> success\n#[cfg(feature = \"cstr\")]\npub fn test_from_str_cstr_success() {\n    let inline_str = InlineFlexStr::<core::ffi::CStr>::from_str(\"test\").unwrap();\n    assert_eq!(inline_str.as_ref_type().to_bytes(), b\"test\");\n}\n\n/// Test FromStr for InlineFlexStr<CStr> error (interior NUL or too long)\n#[cfg(feature = \"cstr\")]\npub fn test_from_str_cstr_error() {\n    use inline_flexstr::TooLongOrNulError;\n\n    // String with interior NUL should fail - use a string that fits in 32-bit capacity (10 bytes)\n    // \"ab\\0cd\" is 5 bytes, which fits in both 32-bit and 64-bit capacity\n    let result: Result<InlineFlexStr<core::ffi::CStr>, TooLongOrNulError> =\n        InlineFlexStr::from_str(\"ab\\0cd\");\n    result.unwrap_err();\n\n    // String too long should fail\n    let long_str = \"x\".repeat(inline_flexstr::INLINE_CAPACITY + 1);\n    let result: Result<InlineFlexStr<core::ffi::CStr>, TooLongOrNulError> =\n        InlineFlexStr::from_str(&long_str);\n    result.unwrap_err();\n}\n"
  },
  {
    "path": "inline_flexstr/tests/common/index.rs",
    "content": "#![allow(dead_code)]\n\nuse core::fmt;\nuse flexstr_support::{StringFromBytesMut, StringToFromBytes};\nuse inline_flexstr::InlineFlexStr;\n\n/// Test Index implementation for InlineFlexStr\n/// This tests that InlineFlexStr can be dereferenced to &S, which is required for Index\npub fn test_index<S>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + PartialEq + fmt::Debug,\n{\n    // Input should be small enough to inline\n    let inline_str =\n        InlineFlexStr::try_from_type(s).expect(\"test input should be small enough to inline\");\n\n    // Test that we can deref to get &S (required for Index trait)\n    // For inlined strings, the pointer will be different (data is copied), but values should be equal\n    let original_ref: &S = s;\n    let inline_ref: &S = &inline_str;\n\n    // Verify the references are equal via PartialEq (not pointer equality)\n    assert_eq!(original_ref, inline_ref);\n}\n\n/// Test IndexMut implementation for InlineFlexStr\n/// This tests that InlineFlexStr can be dereferenced mutably to &mut S, which is required for IndexMut\npub fn test_index_mut<S>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + StringFromBytesMut + PartialEq + fmt::Debug,\n{\n    // Input should be small enough to inline\n    let mut inline_str =\n        InlineFlexStr::try_from_type(s).expect(\"test input should be small enough to inline\");\n\n    // Test that we can deref mutably to get &mut S (required for IndexMut trait)\n    // The mutable reference should initially equal the original\n    let original_ref: &S = s;\n    let inline_ref: &mut S = &mut inline_str;\n\n    // Verify the mutable reference equals the original via PartialEq\n    assert_eq!(original_ref, inline_ref);\n}\n"
  },
  {
    "path": "inline_flexstr/tests/common/mod.rs",
    "content": "pub mod as_ref;\npub mod basic;\npub mod borrow;\npub mod comparison;\npub mod conversion;\n#[cfg(feature = \"cstr\")]\npub mod cstr_specific;\npub mod display;\npub mod edge_cases;\npub mod errors;\npub mod from_str;\npub mod index;\n#[cfg(feature = \"serde\")]\npub mod serialize;\n#[cfg(feature = \"std\")]\npub mod socket;\npub mod stringlike;\npub mod try_from;\n#[cfg(feature = \"zeroize\")]\npub mod zeroize;\n"
  },
  {
    "path": "inline_flexstr/tests/common/serialize.rs",
    "content": "#![allow(dead_code)]\n\nuse core::fmt;\nuse flexstr_support::StringToFromBytes;\nuse inline_flexstr::InlineFlexStr;\nuse serde::{Deserialize, Serialize};\n\npub fn serialize_deserialize_test<'s, F, S>(s: &'static S)\nwhere\n    F: TryFrom<&'s S> + PartialEq + Serialize + for<'de> Deserialize<'de> + fmt::Debug,\n    <F as TryFrom<&'s S>>::Error: fmt::Debug,\n    S: ?Sized + StringToFromBytes + Serialize + fmt::Debug + PartialEq,\n    Box<S>: for<'de> Deserialize<'de>,\n{\n    let expected_str: F = s.try_into().unwrap();\n    let serialized = serde_json::to_value(&expected_str).unwrap();\n    let expected_json = serde_json::to_value(s).unwrap();\n    assert_eq!(expected_json, serialized);\n\n    let deserialized: F = serde_json::from_value(serialized).unwrap();\n    assert_eq!(expected_str, deserialized);\n}\n\n/// Test deserialization error path when string is too long for inline storage\n#[cfg(feature = \"str\")]\npub fn test_deserialize_error_str() {\n    // Create a string that's definitely too long\n    let long_string = \"x\".repeat(inline_flexstr::INLINE_CAPACITY + 1);\n    let boxed: Box<str> = long_string.into_boxed_str();\n\n    // Serialize it\n    let serialized = serde_json::to_string(&boxed).unwrap();\n\n    // Try to deserialize into InlineFlexStr - should fail\n    let result: Result<InlineFlexStr<str>, _> = serde_json::from_str(&serialized);\n    result.unwrap_err();\n}\n"
  },
  {
    "path": "inline_flexstr/tests/common/socket.rs",
    "content": "#![allow(dead_code)]\n\nuse flexstr_support::StringToFromBytes;\nuse inline_flexstr::InlineFlexStr;\nuse std::net::ToSocketAddrs;\n\n/// Test ToSocketAddrs implementation for InlineFlexStr\npub fn test_to_socket_addrs<S>(addr: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + ToSocketAddrs,\n{\n    // Input should be small enough to inline\n    let inline_str =\n        InlineFlexStr::try_from_type(addr).expect(\"test input should be small enough to inline\");\n\n    // Test ToSocketAddrs\n    let mut iter = inline_str.to_socket_addrs().unwrap();\n    assert!(iter.next().is_some());\n    assert!(iter.next().is_none());\n}\n"
  },
  {
    "path": "inline_flexstr/tests/common/stringlike.rs",
    "content": "#![allow(dead_code)]\n\nuse core::fmt;\nuse flexstr_support::{StringLike, StringToFromBytes};\nuse inline_flexstr::InlineFlexStr;\n\n/// Test as_str() method for str types\n#[cfg(feature = \"str\")]\npub fn test_as_str<S>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + AsRef<str> + PartialEq,\n    InlineFlexStr<S>: StringLike<S>,\n{\n    // Input should be small enough to inline\n    let inline_str =\n        InlineFlexStr::try_from_type(s).expect(\"test input should be small enough to inline\");\n    let str_ref = StringLike::as_str(&inline_str);\n    assert_eq!(str_ref, s.as_ref());\n}\n\n/// Test as_os_str() method for OsStr types\n#[cfg(all(feature = \"std\", feature = \"osstr\"))]\npub fn test_as_os_str<S>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + AsRef<std::ffi::OsStr> + PartialEq,\n    InlineFlexStr<S>: StringLike<S>,\n{\n    // Input should be small enough to inline\n    let inline_str =\n        InlineFlexStr::try_from_type(s).expect(\"test input should be small enough to inline\");\n    let os_str_ref = StringLike::as_os_str(&inline_str);\n    assert_eq!(os_str_ref, s.as_ref());\n}\n\n/// Test as_path() method for Path types\n#[cfg(all(feature = \"std\", feature = \"path\"))]\npub fn test_as_path<S>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + AsRef<std::path::Path> + PartialEq,\n    InlineFlexStr<S>: StringLike<S>,\n{\n    // Input should be small enough to inline\n    let inline_str =\n        InlineFlexStr::try_from_type(s).expect(\"test input should be small enough to inline\");\n    let path_ref = StringLike::as_path(&inline_str);\n    assert_eq!(path_ref, s.as_ref());\n}\n\n/// Test as_c_str() method for CStr types\n#[cfg(feature = \"cstr\")]\npub fn test_as_c_str<S>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + AsRef<core::ffi::CStr> + PartialEq,\n    InlineFlexStr<S>: StringLike<S>,\n{\n    // Input should be small enough to inline\n    let inline_str =\n        InlineFlexStr::try_from_type(s).expect(\"test input should be small enough to inline\");\n    let c_str_ref = StringLike::as_c_str(&inline_str);\n    assert_eq!(c_str_ref, s.as_ref());\n}\n\n/// Test into_string() method\n#[cfg(feature = \"str\")]\npub fn test_into_string<S>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n    S::Owned: Into<String> + From<alloc::boxed::Box<S>> + AsRef<S>,\n    InlineFlexStr<S>: StringLike<S>,\n{\n    // Input should be small enough to inline\n    let inline_str =\n        InlineFlexStr::try_from_type(s).expect(\"test input should be small enough to inline\");\n    let string = StringLike::into_string(inline_str);\n    assert_eq!(string, s.to_owned().into());\n}\n\n/// Test to_string() method\n#[cfg(feature = \"str\")]\npub fn test_to_string<S>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n    S::Owned: Into<String>,\n    InlineFlexStr<S>: StringLike<S>,\n{\n    // Input should be small enough to inline\n    let inline_str =\n        InlineFlexStr::try_from_type(s).expect(\"test input should be small enough to inline\");\n    let string = StringLike::to_string(&inline_str);\n    assert_eq!(string, s.to_owned().into());\n}\n\n/// Test into_os_string() method\n#[cfg(all(feature = \"std\", feature = \"osstr\"))]\npub fn test_into_os_string<S>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n    S::Owned: Into<std::ffi::OsString> + From<alloc::boxed::Box<S>> + AsRef<S>,\n    InlineFlexStr<S>: StringLike<S>,\n{\n    // Input should be small enough to inline\n    let inline_str =\n        InlineFlexStr::try_from_type(s).expect(\"test input should be small enough to inline\");\n    let os_string = StringLike::into_os_string(inline_str);\n    assert_eq!(os_string, s.to_owned().into());\n}\n\n/// Test to_os_string() method\n#[cfg(all(feature = \"std\", feature = \"osstr\"))]\npub fn test_to_os_string<S>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n    S::Owned: Into<std::ffi::OsString>,\n    InlineFlexStr<S>: StringLike<S>,\n{\n    // Input should be small enough to inline\n    let inline_str =\n        InlineFlexStr::try_from_type(s).expect(\"test input should be small enough to inline\");\n    let os_string = StringLike::to_os_string(&inline_str);\n    assert_eq!(os_string, s.to_owned().into());\n}\n\n/// Test into_path_buf() method\n#[cfg(all(feature = \"std\", feature = \"path\"))]\npub fn test_into_path_buf<S>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n    S::Owned: Into<std::path::PathBuf> + From<alloc::boxed::Box<S>> + AsRef<S>,\n    InlineFlexStr<S>: StringLike<S>,\n{\n    // Input should be small enough to inline\n    let inline_str =\n        InlineFlexStr::try_from_type(s).expect(\"test input should be small enough to inline\");\n    let path_buf = StringLike::into_path_buf(inline_str);\n    assert_eq!(path_buf, s.to_owned().into());\n}\n\n/// Test to_path_buf() method\n#[cfg(all(feature = \"std\", feature = \"path\"))]\npub fn test_to_path_buf<S>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n    S::Owned: Into<std::path::PathBuf>,\n    InlineFlexStr<S>: StringLike<S>,\n{\n    // Input should be small enough to inline\n    let inline_str =\n        InlineFlexStr::try_from_type(s).expect(\"test input should be small enough to inline\");\n    let path_buf = StringLike::to_path_buf(&inline_str);\n    assert_eq!(path_buf, s.to_owned().into());\n}\n\n/// Test into_c_string() method\n#[cfg(feature = \"cstr\")]\npub fn test_into_c_string<S>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n    S::Owned: Into<alloc::ffi::CString> + From<alloc::boxed::Box<S>> + AsRef<S>,\n    InlineFlexStr<S>: StringLike<S>,\n{\n    // Input should be small enough to inline\n    let inline_str =\n        InlineFlexStr::try_from_type(s).expect(\"test input should be small enough to inline\");\n    let c_string = StringLike::into_c_string(inline_str);\n    assert_eq!(\n        c_string.as_bytes_with_nul(),\n        s.to_owned().into().as_bytes_with_nul()\n    );\n}\n\n/// Test to_c_string() method\n#[cfg(feature = \"cstr\")]\npub fn test_to_c_string<S>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n    S::Owned: Into<alloc::ffi::CString>,\n    InlineFlexStr<S>: StringLike<S>,\n{\n    // Input should be small enough to inline\n    let inline_str =\n        InlineFlexStr::try_from_type(s).expect(\"test input should be small enough to inline\");\n    let c_string = StringLike::to_c_string(&inline_str);\n    let expected: alloc::ffi::CString = s.to_owned().into();\n    assert_eq!(c_string.as_bytes_with_nul(), expected.as_bytes_with_nul());\n}\n\n/// Test into_vec_bytes() method\n#[cfg(feature = \"bytes\")]\npub fn test_into_vec_bytes<S>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n    S::Owned: Into<alloc::vec::Vec<u8>> + From<alloc::boxed::Box<S>> + AsRef<S>,\n    InlineFlexStr<S>: StringLike<S>,\n{\n    // Input should be small enough to inline\n    let inline_str =\n        InlineFlexStr::try_from_type(s).expect(\"test input should be small enough to inline\");\n    let vec_bytes = StringLike::into_vec_bytes(inline_str);\n    assert_eq!(vec_bytes, s.to_owned().into());\n}\n\n/// Test to_vec_bytes() method\n#[cfg(feature = \"bytes\")]\npub fn test_to_vec_bytes<S>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n    S::Owned: Into<alloc::vec::Vec<u8>>,\n    InlineFlexStr<S>: StringLike<S>,\n{\n    // Input should be small enough to inline\n    let inline_str =\n        InlineFlexStr::try_from_type(s).expect(\"test input should be small enough to inline\");\n    let vec_bytes = StringLike::to_vec_bytes(&inline_str);\n    assert_eq!(vec_bytes, s.to_owned().into());\n}\n"
  },
  {
    "path": "inline_flexstr/tests/common/try_from.rs",
    "content": "#![allow(dead_code)]\n\nuse core::fmt;\nuse flexstr_support::StringToFromBytes;\nuse inline_flexstr::InlineFlexStr;\n\n/// Test TryFrom success path for InlineFlexStr\npub fn test_try_from_success<T, S>(value: T)\nwhere\n    T: core::convert::TryInto<InlineFlexStr<S>>,\n    T::Error: fmt::Debug,\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n{\n    let inline_str: InlineFlexStr<S> = value.try_into().unwrap();\n    assert_eq!(inline_str.as_ref_type(), inline_str.as_ref_type()); // Basic sanity check\n}\n\n/// Test TryFrom error path for InlineFlexStr\npub fn test_try_from_error<T, S>(value: T)\nwhere\n    T: core::convert::TryInto<InlineFlexStr<S>>,\n    T::Error: fmt::Debug + fmt::Display,\n    S: ?Sized + StringToFromBytes + fmt::Debug,\n{\n    let result: Result<InlineFlexStr<S>, T::Error> = value.try_into();\n    let err = result.unwrap_err();\n    // Test that error can be displayed\n    let _ = format!(\"{}\", err);\n}\n\n/// Test TryFrom<&[u8]> for InlineFlexStr<[u8]> with too long string\n#[cfg(feature = \"bytes\")]\npub fn test_try_from_bytes_too_long() {\n    // Create a byte slice that's definitely too long\n    let long_bytes = vec![0u8; inline_flexstr::INLINE_CAPACITY + 1];\n    let result: Result<InlineFlexStr<[u8]>, inline_flexstr::TooLongForInlining> =\n        long_bytes.as_slice().try_into();\n    let err = result.unwrap_err();\n    assert_eq!(err.length, inline_flexstr::INLINE_CAPACITY + 1);\n    assert_eq!(err.inline_capacity, inline_flexstr::INLINE_CAPACITY);\n}\n\n/// Test TryFrom<&str> for InlineFlexStr<[u8]> with too long string\n#[cfg(feature = \"bytes\")]\npub fn test_try_from_str_too_long() {\n    // Create a string that's definitely too long\n    let long_str = \"x\".repeat(inline_flexstr::INLINE_CAPACITY + 1);\n    let result: Result<InlineFlexStr<[u8]>, inline_flexstr::TooLongForInlining> =\n        long_str.as_str().try_into();\n    let _err = result.unwrap_err();\n}\n\n/// Test TryFrom<&OsStr> for InlineFlexStr<OsStr> with too long string\n#[cfg(all(feature = \"std\", feature = \"osstr\"))]\npub fn test_try_from_osstr_too_long() {\n    use std::ffi::OsStr;\n\n    // Create an OsStr that's definitely too long\n    let long_str = \"x\".repeat(inline_flexstr::INLINE_CAPACITY + 1);\n    let os_str = OsStr::new(&long_str);\n    let result: Result<InlineFlexStr<OsStr>, inline_flexstr::TooLongForInlining> =\n        os_str.try_into();\n    let _err = result.unwrap_err();\n}\n\n/// Test TryFrom<&str> for InlineFlexStr<OsStr> with too long string\n#[cfg(all(feature = \"std\", feature = \"osstr\"))]\npub fn test_try_from_str_osstr_too_long() {\n    // Create a string that's definitely too long\n    let long_str = \"x\".repeat(inline_flexstr::INLINE_CAPACITY + 1);\n    let result: Result<InlineFlexStr<std::ffi::OsStr>, inline_flexstr::TooLongForInlining> =\n        long_str.as_str().try_into();\n    let _err = result.unwrap_err();\n}\n\n/// Test TryFrom<&Path> for InlineFlexStr<OsStr> with too long string\n#[cfg(all(feature = \"std\", feature = \"osstr\", feature = \"path\"))]\npub fn test_try_from_path_osstr_too_long() {\n    use std::path::Path;\n\n    // Create a path that's definitely too long\n    let long_str = \"x\".repeat(inline_flexstr::INLINE_CAPACITY + 1);\n    let path = Path::new(&long_str);\n    let result: Result<InlineFlexStr<std::ffi::OsStr>, inline_flexstr::TooLongForInlining> =\n        path.try_into();\n    let _err = result.unwrap_err();\n}\n\n/// Test TryFrom<&Path> for InlineFlexStr<Path> with too long string\n#[cfg(all(feature = \"std\", feature = \"path\"))]\npub fn test_try_from_path_too_long() {\n    use std::path::Path;\n\n    // Create a path that's definitely too long\n    let long_str = \"x\".repeat(inline_flexstr::INLINE_CAPACITY + 1);\n    let path = Path::new(&long_str);\n    let result: Result<InlineFlexStr<Path>, inline_flexstr::TooLongForInlining> = path.try_into();\n    let _err = result.unwrap_err();\n}\n\n/// Test TryFrom<&str> for InlineFlexStr<Path> with too long string\n#[cfg(all(feature = \"std\", feature = \"path\"))]\npub fn test_try_from_str_path_too_long() {\n    // Create a string that's definitely too long\n    let long_str = \"x\".repeat(inline_flexstr::INLINE_CAPACITY + 1);\n    let result: Result<InlineFlexStr<std::path::Path>, inline_flexstr::TooLongForInlining> =\n        long_str.as_str().try_into();\n    let _err = result.unwrap_err();\n}\n\n/// Test TryFrom<&OsStr> for InlineFlexStr<Path> with too long string\n#[cfg(all(feature = \"std\", feature = \"path\"))]\npub fn test_try_from_osstr_path_too_long() {\n    use std::ffi::OsStr;\n\n    // Create an OsStr that's definitely too long\n    let long_str = \"x\".repeat(inline_flexstr::INLINE_CAPACITY + 1);\n    let os_str = OsStr::new(&long_str);\n    let result: Result<InlineFlexStr<std::path::Path>, inline_flexstr::TooLongForInlining> =\n        os_str.try_into();\n    let _err = result.unwrap_err();\n}\n\n/// Test TryFrom<&str> for InlineFlexStr<CStr>\n#[cfg(feature = \"cstr\")]\npub fn test_try_from_str_cstr() {\n    use inline_flexstr::TooLongOrNulError;\n\n    // Valid CStr (no interior NUL, small enough)\n    let s: &str = \"test\";\n    let result: Result<InlineFlexStr<core::ffi::CStr>, TooLongOrNulError> = s.try_into();\n    let inline_str = result.unwrap();\n    assert_eq!(inline_str.as_ref_type().to_bytes(), b\"test\");\n\n    // Invalid CStr (interior NUL) - use a string that fits in 32-bit capacity (10 bytes)\n    // \"ab\\0cd\" is 5 bytes, which fits in both 32-bit and 64-bit capacity\n    let s_with_nul: &str = \"ab\\0cd\";\n    let result: Result<InlineFlexStr<core::ffi::CStr>, TooLongOrNulError> = s_with_nul.try_into();\n    result.unwrap_err();\n\n    // Too long\n    let long_str = \"x\".repeat(inline_flexstr::INLINE_CAPACITY + 1);\n    let result: Result<InlineFlexStr<core::ffi::CStr>, TooLongOrNulError> =\n        long_str.as_str().try_into();\n    result.unwrap_err();\n}\n\n/// Test TryFrom<&[u8]> for InlineFlexStr<CStr>\n#[cfg(feature = \"cstr\")]\npub fn test_try_from_bytes_cstr() {\n    use inline_flexstr::TooLongOrNulError;\n\n    // Valid CStr (no interior NUL, small enough)\n    let bytes: &[u8] = b\"test\";\n    let result: Result<InlineFlexStr<core::ffi::CStr>, TooLongOrNulError> = bytes.try_into();\n    let inline_str = result.unwrap();\n    assert_eq!(inline_str.as_ref_type().to_bytes(), b\"test\");\n\n    // Invalid CStr (interior NUL) - use bytes that fit in 32-bit capacity (10 bytes)\n    // b\"ab\\0cd\" is 5 bytes, which fits in both 32-bit and 64-bit capacity\n    let bytes_with_nul: &[u8] = b\"ab\\0cd\";\n    let result: Result<InlineFlexStr<core::ffi::CStr>, TooLongOrNulError> =\n        bytes_with_nul.try_into();\n    result.unwrap_err();\n\n    // Too long\n    let long_bytes = vec![b'x'; inline_flexstr::INLINE_CAPACITY + 1];\n    let result: Result<InlineFlexStr<core::ffi::CStr>, TooLongOrNulError> =\n        long_bytes.as_slice().try_into();\n    result.unwrap_err();\n}\n\n/// Test TryFrom<&[u8]> for InlineFlexStr<str>\n#[cfg(feature = \"str\")]\npub fn test_try_from_bytes_str() {\n    use inline_flexstr::TooLongOrUtf8Error;\n\n    // Valid UTF-8 bytes, small enough\n    let bytes: &[u8] = b\"test\";\n    let result: Result<InlineFlexStr<str>, TooLongOrUtf8Error> = bytes.try_into();\n    let inline_str = result.unwrap();\n    assert_eq!(inline_str.as_ref_type(), \"test\");\n\n    // Invalid UTF-8 bytes\n    let invalid_bytes: &[u8] = &[0xFF, 0xFF, 0xFF];\n    let result: Result<InlineFlexStr<str>, TooLongOrUtf8Error> = invalid_bytes.try_into();\n    result.unwrap_err();\n\n    // Too long\n    let long_bytes = vec![b'x'; inline_flexstr::INLINE_CAPACITY + 1];\n    let result: Result<InlineFlexStr<str>, TooLongOrUtf8Error> = long_bytes.as_slice().try_into();\n    result.unwrap_err();\n}\n\n/// Test TryFrom<&OsStr> for InlineFlexStr<str>\n#[cfg(all(feature = \"str\", feature = \"std\"))]\npub fn test_try_from_osstr_str() {\n    use inline_flexstr::TooLongOrUtf8Error;\n    use std::ffi::OsStr;\n\n    // Valid UTF-8 OsStr, small enough\n    let os_str = OsStr::new(\"test\");\n    let result: Result<InlineFlexStr<str>, TooLongOrUtf8Error> = os_str.try_into();\n    let inline_str = result.unwrap();\n    assert_eq!(inline_str.as_ref_type(), \"test\");\n\n    // Too long\n    let long_str = \"x\".repeat(inline_flexstr::INLINE_CAPACITY + 1);\n    let os_str = OsStr::new(&long_str);\n    let result: Result<InlineFlexStr<str>, TooLongOrUtf8Error> = os_str.try_into();\n    result.unwrap_err();\n}\n\n/// Test TryFrom<&Path> for InlineFlexStr<str>\n#[cfg(all(feature = \"str\", feature = \"std\"))]\npub fn test_try_from_path_str() {\n    use inline_flexstr::TooLongOrUtf8Error;\n    use std::path::Path;\n\n    // Valid UTF-8 Path, small enough\n    let path = Path::new(\"test\");\n    let result: Result<InlineFlexStr<str>, TooLongOrUtf8Error> = path.try_into();\n    let inline_str = result.unwrap();\n    assert_eq!(inline_str.as_ref_type(), \"test\");\n\n    // Too long\n    let long_str = \"x\".repeat(inline_flexstr::INLINE_CAPACITY + 1);\n    let path = Path::new(&long_str);\n    let result: Result<InlineFlexStr<str>, TooLongOrUtf8Error> = path.try_into();\n    result.unwrap_err();\n}\n"
  },
  {
    "path": "inline_flexstr/tests/common/zeroize.rs",
    "content": "#![allow(dead_code)]\n\nuse core::fmt;\nuse flexstr_support::StringToFromBytes;\nuse inline_flexstr::InlineFlexStr;\nuse zeroize::Zeroize;\n\n/// Test that InlineFlexStr has zero-length raw bytes after zeroize\npub fn test_zeroize_empty_after<S>(s: &S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n{\n    let mut inline = InlineFlexStr::try_from_type(s).expect(\"test input should be small enough\");\n    assert!(\n        !inline.as_raw_bytes().is_empty(),\n        \"test input must be non-empty\"\n    );\n\n    inline.zeroize();\n\n    // Check raw bytes directly — InlineFlexStr::zeroize() zeros everything including len,\n    // which produces a maximally secure but potentially invalid-for-interpretation state\n    // (e.g., CStr requires a NUL terminator). FlexStr::zeroize() handles this by replacing\n    // with InlineFlexStr::zeroed() which produces a valid empty value.\n    assert!(inline.as_raw_bytes().is_empty());\n}\n\n/// Test that all raw bytes of InlineFlexStr are zeroed after zeroize\npub fn test_zeroize_bytes_cleared<S>(s: &S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n{\n    let mut inline = InlineFlexStr::try_from_type(s).expect(\"test input should be small enough\");\n\n    // Verify we have non-zero data\n    assert!(\n        !S::self_as_raw_bytes(s).is_empty(),\n        \"test input must be non-empty\"\n    );\n\n    // Get a raw pointer to the struct's memory (struct is on the stack, still alive after zeroize)\n    let ptr = &inline as *const InlineFlexStr<S> as *const u8;\n    let size = core::mem::size_of::<InlineFlexStr<S>>();\n\n    inline.zeroize();\n\n    // Read the raw bytes of the struct — it's still alive on the stack\n    let bytes = unsafe { core::slice::from_raw_parts(ptr, size) };\n    assert!(\n        bytes.iter().all(|&b| b == 0),\n        \"all bytes of InlineFlexStr should be zero after zeroize, got: {bytes:?}\"\n    );\n}\n"
  },
  {
    "path": "inline_flexstr/tests/test_bytes.rs",
    "content": "#![cfg(feature = \"bytes\")]\n\nextern crate alloc;\n\n#[cfg(feature = \"serde\")]\nuse inline_flexstr::InlineBytes;\n\nmod common;\n\n// *** Serialize/Deserialize Tests ***\n\n#[cfg(feature = \"serde\")]\n#[test]\nfn serialize_deserialize_test_inline_bytes() {\n    common::serialize::serialize_deserialize_test::<InlineBytes, [u8]>(b\"test\");\n}\n\n// *** Basic Tests ***\n\n#[test]\nfn test_creation_from_inline_bytes() {\n    common::basic::test_creation_from_inline::<[u8]>(b\"test\");\n}\n\n#[test]\nfn test_empty_bytes() {\n    common::basic::test_empty::<[u8]>(b\"\");\n}\n\n#[test]\nfn test_accessors_bytes() {\n    common::basic::test_accessors::<[u8]>(b\"test\");\n}\n\n#[test]\nfn test_clone_bytes() {\n    common::basic::test_clone::<[u8]>(b\"test\");\n}\n\n#[test]\nfn test_default_bytes() {\n    common::basic::test_default::<[u8]>();\n}\n\n// *** Conversion Tests ***\n\n#[test]\nfn test_to_owned_type_bytes() {\n    common::conversion::test_to_owned_type::<[u8]>(b\"test\");\n}\n\n#[test]\nfn test_into_owned_type_bytes() {\n    common::conversion::test_into_owned_type::<[u8]>(b\"test\");\n}\n\n// *** Comparison Tests ***\n\n#[test]\nfn test_partial_eq_bytes() {\n    common::comparison::test_partial_eq::<[u8]>(b\"test\", b\"test\");\n    common::comparison::test_partial_eq::<[u8]>(b\"test\", b\"other\");\n}\n\n#[test]\nfn test_eq_bytes() {\n    common::comparison::test_eq::<[u8]>(b\"test\");\n}\n\n#[test]\nfn test_partial_ord_bytes() {\n    common::comparison::test_partial_ord::<[u8]>(b\"a\", b\"b\");\n}\n\n#[test]\nfn test_ord_bytes() {\n    common::comparison::test_ord::<[u8]>(b\"a\", b\"b\");\n}\n\n#[test]\nfn test_comparison_with_ref_bytes() {\n    common::comparison::test_comparison_with_ref::<[u8]>(b\"test\");\n}\n\n#[test]\nfn test_comparison_with_owned_bytes() {\n    common::comparison::test_comparison_with_owned::<[u8]>(b\"test\");\n}\n\n// *** Edge Case Tests ***\n\n#[test]\nfn test_empty_string_bytes() {\n    common::edge_cases::test_empty_string::<[u8]>(b\"\");\n}\n\n#[test]\nfn test_various_lengths_bytes() {\n    common::edge_cases::test_various_lengths::<[u8]>(b\"test\");\n    common::edge_cases::test_various_lengths::<[u8]>(b\"\");\n    common::edge_cases::test_various_lengths::<[u8]>(b\"a\");\n}\n\n#[test]\nfn test_special_content_bytes() {\n    common::edge_cases::test_special_content::<[u8]>(b\"test\");\n}\n\n#[test]\nfn test_clone_bytes_edge() {\n    common::edge_cases::test_clone::<[u8]>(b\"test\");\n}\n\n// *** Error Tests ***\n\n#[test]\nfn test_too_long_for_inlining() {\n    common::errors::test_too_long_for_inlining();\n}\n\n// *** StringLike Tests ***\n\n#[test]\nfn test_into_vec_bytes() {\n    common::stringlike::test_into_vec_bytes::<[u8]>(b\"test\");\n}\n\n#[test]\nfn test_to_vec_bytes() {\n    common::stringlike::test_to_vec_bytes::<[u8]>(b\"test\");\n}\n\n// *** TryFrom Tests ***\n\n#[test]\nfn test_try_from_bytes_too_long() {\n    common::try_from::test_try_from_bytes_too_long();\n}\n\n#[test]\nfn test_try_from_str_too_long() {\n    common::try_from::test_try_from_str_too_long();\n}\n\n// *** FromStr Tests ***\n\n#[test]\nfn test_from_str_bytes_success() {\n    common::from_str::test_from_str_bytes_success();\n}\n\n#[test]\nfn test_from_str_bytes_error() {\n    common::from_str::test_from_str_bytes_error();\n}\n\n// *** Zeroize Tests ***\n\n#[cfg(feature = \"zeroize\")]\n#[test]\nfn test_zeroize_empty_after_bytes() {\n    common::zeroize::test_zeroize_empty_after::<[u8]>(b\"test\");\n}\n\n#[cfg(feature = \"zeroize\")]\n#[test]\nfn test_zeroize_bytes_cleared_bytes() {\n    common::zeroize::test_zeroize_bytes_cleared::<[u8]>(b\"test\");\n}\n\n// *** AsRef Tests ***\n\n#[test]\nfn test_as_ref_bytes() {\n    common::as_ref::test_as_ref_bytes(b\"test\");\n}\n"
  },
  {
    "path": "inline_flexstr/tests/test_cstr.rs",
    "content": "#![cfg(feature = \"cstr\")]\n\nextern crate alloc;\n\n#[cfg(feature = \"serde\")]\nuse inline_flexstr::InlineCStr;\n\nuse core::ffi::CStr;\n\nmod common;\n\n// *** Serialize/Deserialize Tests ***\n\n#[cfg(feature = \"serde\")]\n#[test]\nfn serialize_deserialize_test_inline_cstr() {\n    common::serialize::serialize_deserialize_test::<InlineCStr, CStr>(c\"test\");\n}\n\n// *** Basic Tests ***\n\n#[test]\nfn test_creation_from_inline_cstr() {\n    common::basic::test_creation_from_inline::<CStr>(c\"test\");\n}\n\n#[test]\nfn test_empty_cstr() {\n    common::basic::test_empty::<CStr>(c\"\");\n}\n\n#[test]\nfn test_accessors_cstr() {\n    common::basic::test_accessors::<CStr>(c\"test\");\n}\n\n#[test]\nfn test_clone_cstr() {\n    common::basic::test_clone::<CStr>(c\"test\");\n}\n\n#[test]\nfn test_default_cstr() {\n    common::basic::test_default::<CStr>();\n}\n\n// *** Conversion Tests ***\n\n#[test]\nfn test_to_owned_type_cstr() {\n    common::conversion::test_to_owned_type::<CStr>(c\"test\");\n}\n\n#[test]\nfn test_into_owned_type_cstr() {\n    common::conversion::test_into_owned_type::<CStr>(c\"test\");\n}\n\n// *** Comparison Tests ***\n\n#[test]\nfn test_partial_eq_cstr() {\n    common::comparison::test_partial_eq::<CStr>(c\"test\", c\"test\");\n    common::comparison::test_partial_eq::<CStr>(c\"test\", c\"other\");\n}\n\n#[test]\nfn test_eq_cstr() {\n    common::comparison::test_eq::<CStr>(c\"test\");\n}\n\n#[test]\nfn test_comparison_with_ref_cstr() {\n    common::comparison::test_comparison_with_ref::<CStr>(c\"test\");\n}\n\n#[test]\nfn test_comparison_with_owned_cstr() {\n    common::comparison::test_comparison_with_owned::<CStr>(c\"test\");\n}\n\n#[test]\nfn test_partial_eq_with_owned_types_cstr() {\n    common::comparison::test_partial_eq_with_owned_types::<CStr>(c\"test\");\n}\n\n// *** Edge Case Tests ***\n\n#[test]\nfn test_empty_string_cstr() {\n    common::edge_cases::test_empty_string::<CStr>(c\"\");\n}\n\n#[test]\nfn test_various_lengths_cstr() {\n    common::edge_cases::test_various_lengths::<CStr>(c\"test\");\n    common::edge_cases::test_various_lengths::<CStr>(c\"\");\n}\n\n#[test]\nfn test_special_content_cstr() {\n    common::edge_cases::test_special_content::<CStr>(c\"test\");\n}\n\n#[test]\nfn test_clone_cstr_edge() {\n    common::edge_cases::test_clone::<CStr>(c\"test\");\n}\n\n// *** Error Tests ***\n\n#[test]\nfn test_too_long_for_inlining() {\n    common::errors::test_too_long_for_inlining();\n}\n\n#[test]\nfn test_interior_nul_error() {\n    common::errors::test_interior_nul_error();\n}\n\n#[test]\nfn test_too_long_or_nul_error_too_long() {\n    common::errors::test_too_long_or_nul_error_too_long();\n}\n\n#[test]\nfn test_too_long_or_nul_error_nul() {\n    common::errors::test_too_long_or_nul_error_nul();\n}\n\n// *** StringLike Tests ***\n\n#[test]\nfn test_as_c_str() {\n    common::stringlike::test_as_c_str::<CStr>(c\"test\");\n}\n\n#[test]\nfn test_into_c_string() {\n    common::stringlike::test_into_c_string::<CStr>(c\"test\");\n}\n\n#[test]\nfn test_to_c_string() {\n    common::stringlike::test_to_c_string::<CStr>(c\"test\");\n}\n\n// *** TryFrom Tests ***\n\n#[test]\nfn test_try_from_str_cstr() {\n    common::try_from::test_try_from_str_cstr();\n}\n\n#[test]\nfn test_try_from_bytes_cstr() {\n    common::try_from::test_try_from_bytes_cstr();\n}\n\n// *** FromStr Tests ***\n\n#[test]\nfn test_from_str_cstr_success() {\n    common::from_str::test_from_str_cstr_success();\n}\n\n#[test]\nfn test_from_str_cstr_error() {\n    common::from_str::test_from_str_cstr_error();\n}\n\n// *** AsRef Tests ***\n\n#[test]\nfn test_as_ref_cstr() {\n    common::as_ref::test_as_ref_cstr(c\"test\");\n}\n\n// *** Zeroize Tests ***\n\n#[cfg(feature = \"zeroize\")]\n#[test]\nfn test_zeroize_empty_after_cstr() {\n    common::zeroize::test_zeroize_empty_after::<CStr>(c\"test\");\n}\n\n#[cfg(feature = \"zeroize\")]\n#[test]\nfn test_zeroize_bytes_cleared_cstr() {\n    common::zeroize::test_zeroize_bytes_cleared::<CStr>(c\"test\");\n}\n\n// *** CStr Specific Tests ***\n\n#[test]\nfn test_try_from_bytes_with_nul() {\n    common::cstr_specific::test_try_from_bytes_with_nul();\n}\n\n#[test]\nfn test_try_from_bytes_without_nul() {\n    common::cstr_specific::test_try_from_bytes_without_nul();\n}\n\n#[test]\nfn test_try_from_bytes_interior_nul() {\n    common::cstr_specific::test_try_from_bytes_interior_nul();\n}\n\n#[test]\nfn test_try_from_bytes_too_long() {\n    common::cstr_specific::test_try_from_bytes_too_long();\n}\n\n#[test]\nfn test_as_bytes_with_nul() {\n    common::cstr_specific::test_as_bytes_with_nul(c\"test\");\n}\n"
  },
  {
    "path": "inline_flexstr/tests/test_osstr.rs",
    "content": "#![cfg(all(feature = \"std\", feature = \"osstr\"))]\n\nextern crate alloc;\n\n#[cfg(feature = \"serde\")]\nuse inline_flexstr::InlineOsStr;\n\nuse std::ffi::OsStr;\n\nmod common;\n\n// *** Serialize/Deserialize Tests ***\n\n#[cfg(feature = \"serde\")]\n#[test]\nfn serialize_deserialize_test_inline_osstr() {\n    common::serialize::serialize_deserialize_test::<InlineOsStr, OsStr>(OsStr::new(\"test\"));\n}\n\n// *** Basic Tests ***\n\n#[test]\nfn test_creation_from_inline_osstr() {\n    common::basic::test_creation_from_inline::<OsStr>(OsStr::new(\"test\"));\n}\n\n#[test]\nfn test_empty_osstr() {\n    common::basic::test_empty::<OsStr>(OsStr::new(\"\"));\n}\n\n#[test]\nfn test_accessors_osstr() {\n    common::basic::test_accessors::<OsStr>(OsStr::new(\"test\"));\n}\n\n#[test]\nfn test_clone_osstr() {\n    common::basic::test_clone::<OsStr>(OsStr::new(\"test\"));\n}\n\n#[test]\nfn test_default_osstr() {\n    common::basic::test_default::<OsStr>();\n}\n\n// *** Conversion Tests ***\n\n#[test]\nfn test_to_owned_type_osstr() {\n    common::conversion::test_to_owned_type::<OsStr>(OsStr::new(\"test\"));\n}\n\n#[test]\nfn test_into_owned_type_osstr() {\n    common::conversion::test_into_owned_type::<OsStr>(OsStr::new(\"test\"));\n}\n\n// *** Comparison Tests ***\n\n#[test]\nfn test_partial_eq_osstr() {\n    common::comparison::test_partial_eq::<OsStr>(OsStr::new(\"test\"), OsStr::new(\"test\"));\n    common::comparison::test_partial_eq::<OsStr>(OsStr::new(\"test\"), OsStr::new(\"other\"));\n}\n\n#[test]\nfn test_eq_osstr() {\n    common::comparison::test_eq::<OsStr>(OsStr::new(\"test\"));\n}\n\n#[test]\nfn test_comparison_with_ref_osstr() {\n    common::comparison::test_comparison_with_ref::<OsStr>(OsStr::new(\"test\"));\n}\n\n#[test]\nfn test_comparison_with_owned_osstr() {\n    common::comparison::test_comparison_with_owned::<OsStr>(OsStr::new(\"test\"));\n}\n\n// *** Edge Case Tests ***\n\n#[test]\nfn test_empty_string_osstr() {\n    common::edge_cases::test_empty_string::<OsStr>(OsStr::new(\"\"));\n}\n\n#[test]\nfn test_various_lengths_osstr() {\n    common::edge_cases::test_various_lengths::<OsStr>(OsStr::new(\"test\"));\n    common::edge_cases::test_various_lengths::<OsStr>(OsStr::new(\"\"));\n}\n\n#[test]\nfn test_special_content_osstr() {\n    common::edge_cases::test_special_content::<OsStr>(OsStr::new(\"test\"));\n}\n\n#[test]\nfn test_clone_osstr_edge() {\n    common::edge_cases::test_clone::<OsStr>(OsStr::new(\"test\"));\n}\n\n// *** Error Tests ***\n\n#[test]\nfn test_too_long_for_inlining() {\n    common::errors::test_too_long_for_inlining();\n}\n\n// *** StringLike Tests ***\n\n#[test]\nfn test_as_os_str() {\n    common::stringlike::test_as_os_str::<OsStr>(OsStr::new(\"test\"));\n}\n\n#[test]\nfn test_into_os_string() {\n    common::stringlike::test_into_os_string::<OsStr>(OsStr::new(\"test\"));\n}\n\n#[test]\nfn test_to_os_string() {\n    common::stringlike::test_to_os_string::<OsStr>(OsStr::new(\"test\"));\n}\n\n// *** TryFrom Tests ***\n\n#[test]\nfn test_try_from_osstr_too_long() {\n    common::try_from::test_try_from_osstr_too_long();\n}\n\n#[test]\nfn test_try_from_str_osstr_too_long() {\n    common::try_from::test_try_from_str_osstr_too_long();\n}\n\n// *** FromStr Tests ***\n\n#[test]\nfn test_from_str_osstr_success() {\n    common::from_str::test_from_str_osstr_success();\n}\n\n#[test]\nfn test_from_str_osstr_error() {\n    common::from_str::test_from_str_osstr_error();\n}\n\n// *** Zeroize Tests ***\n\n#[cfg(feature = \"zeroize\")]\n#[test]\nfn test_zeroize_empty_after_osstr() {\n    common::zeroize::test_zeroize_empty_after::<OsStr>(OsStr::new(\"test\"));\n}\n\n#[cfg(feature = \"zeroize\")]\n#[test]\nfn test_zeroize_bytes_cleared_osstr() {\n    common::zeroize::test_zeroize_bytes_cleared::<OsStr>(OsStr::new(\"test\"));\n}\n\n// *** AsRef Tests ***\n\n#[test]\nfn test_as_ref_osstr() {\n    common::as_ref::test_as_ref_osstr(OsStr::new(\"test\"));\n}\n"
  },
  {
    "path": "inline_flexstr/tests/test_path.rs",
    "content": "#![cfg(all(feature = \"std\", feature = \"path\"))]\n\nextern crate alloc;\n\n#[cfg(feature = \"serde\")]\nuse inline_flexstr::InlinePath;\n\nuse std::path::Path;\n\nmod common;\n\n// *** Serialize/Deserialize Tests ***\n\n#[cfg(feature = \"serde\")]\n#[test]\nfn serialize_deserialize_test_inline_path() {\n    common::serialize::serialize_deserialize_test::<InlinePath, Path>(Path::new(\"test\"));\n}\n\n// *** Basic Tests ***\n\n#[test]\nfn test_creation_from_inline_path() {\n    common::basic::test_creation_from_inline::<Path>(Path::new(\"test\"));\n}\n\n#[test]\nfn test_empty_path() {\n    common::basic::test_empty::<Path>(Path::new(\"\"));\n}\n\n#[test]\nfn test_accessors_path() {\n    common::basic::test_accessors::<Path>(Path::new(\"test\"));\n}\n\n#[test]\nfn test_clone_path() {\n    common::basic::test_clone::<Path>(Path::new(\"test\"));\n}\n\n// Path doesn't implement Default, so skip this test\n// #[test]\n// fn test_default_path() {\n//     common::basic::test_default::<Path>();\n// }\n\n// *** Conversion Tests ***\n\n#[test]\nfn test_to_owned_type_path() {\n    common::conversion::test_to_owned_type::<Path>(Path::new(\"test\"));\n}\n\n#[test]\nfn test_into_owned_type_path() {\n    common::conversion::test_into_owned_type::<Path>(Path::new(\"test\"));\n}\n\n// *** Comparison Tests ***\n\n#[test]\nfn test_partial_eq_path() {\n    common::comparison::test_partial_eq::<Path>(Path::new(\"test\"), Path::new(\"test\"));\n    common::comparison::test_partial_eq::<Path>(Path::new(\"test\"), Path::new(\"other\"));\n}\n\n#[test]\nfn test_eq_path() {\n    common::comparison::test_eq::<Path>(Path::new(\"test\"));\n}\n\n#[test]\nfn test_comparison_with_ref_path() {\n    common::comparison::test_comparison_with_ref::<Path>(Path::new(\"test\"));\n}\n\n#[test]\nfn test_comparison_with_owned_path() {\n    common::comparison::test_comparison_with_owned::<Path>(Path::new(\"test\"));\n}\n\n// *** Edge Case Tests ***\n\n#[test]\nfn test_empty_string_path() {\n    common::edge_cases::test_empty_string::<Path>(Path::new(\"\"));\n}\n\n#[test]\nfn test_various_lengths_path() {\n    common::edge_cases::test_various_lengths::<Path>(Path::new(\"test\"));\n    common::edge_cases::test_various_lengths::<Path>(Path::new(\"\"));\n}\n\n#[test]\nfn test_special_content_path() {\n    common::edge_cases::test_special_content::<Path>(Path::new(\"test\"));\n}\n\n#[test]\nfn test_clone_path_edge() {\n    common::edge_cases::test_clone::<Path>(Path::new(\"test\"));\n}\n\n// *** Error Tests ***\n\n#[test]\nfn test_too_long_for_inlining() {\n    common::errors::test_too_long_for_inlining();\n}\n\n// *** StringLike Tests ***\n\n#[test]\nfn test_as_path() {\n    common::stringlike::test_as_path::<Path>(Path::new(\"test\"));\n}\n\n#[test]\nfn test_into_path_buf() {\n    common::stringlike::test_into_path_buf::<Path>(Path::new(\"test\"));\n}\n\n#[test]\nfn test_to_path_buf() {\n    common::stringlike::test_to_path_buf::<Path>(Path::new(\"test\"));\n}\n\n// *** TryFrom Tests ***\n\n#[test]\nfn test_try_from_path_too_long() {\n    common::try_from::test_try_from_path_too_long();\n}\n\n#[test]\nfn test_try_from_str_path_too_long() {\n    common::try_from::test_try_from_str_path_too_long();\n}\n\n#[test]\nfn test_try_from_osstr_path_too_long() {\n    common::try_from::test_try_from_osstr_path_too_long();\n}\n\n// *** FromStr Tests ***\n\n#[test]\nfn test_from_str_path_success() {\n    common::from_str::test_from_str_path_success();\n}\n\n#[test]\nfn test_from_str_path_error() {\n    common::from_str::test_from_str_path_error();\n}\n\n// *** Zeroize Tests ***\n\n#[cfg(feature = \"zeroize\")]\n#[test]\nfn test_zeroize_empty_after_path() {\n    common::zeroize::test_zeroize_empty_after::<Path>(Path::new(\"test\"));\n}\n\n#[cfg(feature = \"zeroize\")]\n#[test]\nfn test_zeroize_bytes_cleared_path() {\n    common::zeroize::test_zeroize_bytes_cleared::<Path>(Path::new(\"test\"));\n}\n\n// *** AsRef Tests ***\n\n#[test]\nfn test_as_ref_path() {\n    common::as_ref::test_as_ref_path(Path::new(\"test\"));\n}\n"
  },
  {
    "path": "inline_flexstr/tests/test_str.rs",
    "content": "#![cfg(feature = \"str\")]\n\nextern crate alloc;\n\n#[cfg(feature = \"serde\")]\nuse inline_flexstr::InlineStr;\n\nmod common;\n\n// *** Serialize/Deserialize Tests ***\n\n#[cfg(feature = \"serde\")]\n#[test]\nfn serialize_deserialize_test_inline_str() {\n    common::serialize::serialize_deserialize_test::<InlineStr, str>(\"test\");\n}\n\n// *** Basic Tests ***\n\n#[test]\nfn test_creation_from_inline_str() {\n    common::basic::test_creation_from_inline::<str>(\"test\");\n}\n\n#[test]\nfn test_empty_str() {\n    common::basic::test_empty::<str>(\"\");\n}\n\n#[test]\nfn test_accessors_str() {\n    common::basic::test_accessors::<str>(\"test\");\n}\n\n#[test]\nfn test_clone_str() {\n    common::basic::test_clone::<str>(\"test\");\n}\n\n#[test]\nfn test_default_str() {\n    common::basic::test_default::<str>();\n}\n\n// *** Conversion Tests ***\n\n#[test]\nfn test_to_owned_type_str() {\n    common::conversion::test_to_owned_type::<str>(\"test\");\n}\n\n#[test]\nfn test_into_owned_type_str() {\n    common::conversion::test_into_owned_type::<str>(\"test\");\n}\n\n// *** Comparison Tests ***\n\n#[test]\nfn test_partial_eq_str() {\n    common::comparison::test_partial_eq::<str>(\"test\", \"test\");\n    common::comparison::test_partial_eq::<str>(\"test\", \"other\");\n}\n\n#[test]\nfn test_eq_str() {\n    common::comparison::test_eq::<str>(\"test\");\n}\n\n#[test]\nfn test_partial_ord_str() {\n    common::comparison::test_partial_ord::<str>(\"a\", \"b\");\n}\n\n#[test]\nfn test_ord_str() {\n    common::comparison::test_ord::<str>(\"a\", \"b\");\n}\n\n#[test]\nfn test_hash_str() {\n    common::comparison::test_hash::<str>(\"test\");\n}\n\n#[test]\nfn test_comparison_with_ref_str() {\n    common::comparison::test_comparison_with_ref::<str>(\"test\");\n}\n\n#[test]\nfn test_comparison_with_owned_str() {\n    common::comparison::test_comparison_with_owned::<str>(\"test\");\n}\n\n#[test]\nfn test_partial_eq_with_owned_types_str() {\n    common::comparison::test_partial_eq_with_owned_types::<str>(\"test\");\n}\n\n// *** Edge Case Tests ***\n\n#[test]\nfn test_empty_string_str() {\n    common::edge_cases::test_empty_string::<str>(\"\");\n}\n\n#[test]\nfn test_capacity_boundary_exact_str() {\n    // Create a string exactly at capacity\n    let s = \"a\".repeat(inline_flexstr::INLINE_CAPACITY);\n    let s_static: &'static str = Box::leak(s.into_boxed_str());\n    common::edge_cases::test_capacity_boundary_exact::<str>(s_static);\n}\n\n#[test]\nfn test_capacity_boundary_overflow_str() {\n    common::edge_cases::test_capacity_boundary_overflow::<str>(\"test\");\n}\n\n#[test]\nfn test_try_from_too_long_str() {\n    common::edge_cases::test_try_from_too_long();\n}\n\n#[test]\nfn test_various_lengths_str() {\n    common::edge_cases::test_various_lengths::<str>(\"test\");\n    common::edge_cases::test_various_lengths::<str>(\"\");\n    common::edge_cases::test_various_lengths::<str>(\"a\");\n}\n\n#[test]\nfn test_special_content_str() {\n    common::edge_cases::test_special_content::<str>(\"test\");\n    // Use a string that fits in both 32-bit (10 bytes) and 64-bit (22 bytes) capacity\n    // \"hello\\n\" is 6 bytes, which fits in both\n    common::edge_cases::test_special_content::<str>(\"hello\\n\");\n    common::edge_cases::test_special_content::<str>(\"🚀\");\n}\n\n#[test]\nfn test_clone_str_edge() {\n    common::edge_cases::test_clone::<str>(\"test\");\n}\n\n// *** Error Tests ***\n\n#[test]\nfn test_too_long_for_inlining() {\n    common::errors::test_too_long_for_inlining();\n}\n\n#[test]\nfn test_too_long_or_utf8_error_too_long() {\n    common::errors::test_too_long_or_utf8_error_too_long();\n}\n\n#[test]\nfn test_too_long_or_utf8_error_utf8() {\n    common::errors::test_too_long_or_utf8_error_utf8();\n}\n\n// *** StringLike Tests ***\n\n#[test]\nfn test_as_str() {\n    common::stringlike::test_as_str::<str>(\"test\");\n}\n\n#[test]\nfn test_into_string() {\n    common::stringlike::test_into_string::<str>(\"test\");\n}\n\n#[test]\nfn test_to_string() {\n    common::stringlike::test_to_string::<str>(\"test\");\n}\n\n// *** TryFrom Tests ***\n\n#[cfg(feature = \"std\")]\n#[test]\nfn test_try_from_osstr_str() {\n    common::try_from::test_try_from_osstr_str();\n}\n\n#[cfg(feature = \"std\")]\n#[test]\nfn test_try_from_path_str() {\n    common::try_from::test_try_from_path_str();\n}\n\n#[test]\nfn test_try_from_bytes_str() {\n    common::try_from::test_try_from_bytes_str();\n}\n\n// *** FromStr Tests ***\n\n#[test]\nfn test_from_str_success() {\n    common::from_str::test_from_str_success::<str>(\"test\");\n}\n\n// *** Display Tests ***\n\n#[test]\nfn test_display_str() {\n    common::display::test_display::<str>(\"test\");\n}\n\n// *** Borrow Tests ***\n\n#[test]\nfn test_borrow_mut_str() {\n    common::borrow::test_borrow_mut::<str>(\"test\");\n}\n\n// *** Index Tests ***\n\n#[test]\nfn test_index_str() {\n    common::index::test_index::<str>(\"test\");\n}\n\n#[test]\nfn test_index_mut_str() {\n    common::index::test_index_mut::<str>(\"test\");\n}\n\n// *** ToSocketAddrs Tests ***\n\n#[cfg(feature = \"std\")]\n#[test]\nfn test_to_socket_addrs_str() {\n    common::socket::test_to_socket_addrs::<str>(\"[::]:8080\");\n}\n\n// *** AsRef Tests ***\n\n#[test]\nfn test_as_ref_str() {\n    common::as_ref::test_as_ref_str(\"test\");\n}\n\n// *** Zeroize Tests ***\n\n#[cfg(feature = \"zeroize\")]\n#[test]\nfn test_zeroize_empty_after_str() {\n    common::zeroize::test_zeroize_empty_after::<str>(\"test\");\n}\n\n#[cfg(feature = \"zeroize\")]\n#[test]\nfn test_zeroize_bytes_cleared_str() {\n    common::zeroize::test_zeroize_bytes_cleared::<str>(\"test\");\n}\n\n// *** Serialize Tests ***\n\n#[cfg(feature = \"serde\")]\n#[test]\nfn test_deserialize_error_str() {\n    common::serialize::test_deserialize_error_str();\n}\n"
  },
  {
    "path": "justfile",
    "content": "std_features := \"bytes,cstr,osstr,path,serde,sqlx,sqlx_pg_arrays\"\nnostd_features := \"bytes,cstr,serde,str\"\nsafe_features := if os() == \"windows\" { \"safe,win_min_unsafe\" } else { \"safe\" }\n\ntest *PARAMS:\n    cargo nextest run -F {{std_features}} --workspace {{PARAMS}}\n\ntest_nostd *PARAMS:\n    cargo nextest run --no-default-features -F {{nostd_features}} --workspace {{PARAMS}}\n\ntest_safe *PARAMS:\n    cargo nextest run -F {{std_features}},{{safe_features}} --workspace {{PARAMS}}\n\ntest_nostd_safe *PARAMS:\n    cargo nextest run --no-default-features -F {{nostd_features}},{{safe_features}} --workspace {{PARAMS}}\n\nopen_docs $RUSTDOCFLAGS=\"--cfg docsrs --cap-lints allow\":\n    cargo +nightly doc -F {{std_features}} --workspace --open\n\ncover:\n    cargo llvm-cov nextest -F {{std_features}} --workspace\n\ncover_report:\n    cargo llvm-cov nextest --output-path codecov.json --codecov -F {{std_features}} --workspace\n\nmiri $MIRIFLAGS=\"-Zmiri-ignore-leaks\":\n    cargo +nightly miri nextest run -F {{std_features}} --workspace\n\nclippy:\n    cargo clippy -F {{std_features}} --workspace --all-targets -- -D warnings\n"
  },
  {
    "path": "src/bytes.rs",
    "content": "#[cfg(not(feature = \"std\"))]\nuse alloc::vec::Vec;\nuse alloc::{borrow::Cow, rc::Rc, sync::Arc};\nuse core::{convert::Infallible, str::FromStr};\n\nuse crate::flex::{FlexStr, RefCounted, RefCountedMut, partial_eq_impl, ref_counted_mut_impl};\n\nuse flexstr_support::StringToFromBytes;\n\n/// Local `[u8]` type (NOTE: This can't be shared between threads)\npub type LocalBytes = FlexStr<'static, [u8], Rc<[u8]>>;\n\n/// Shared `[u8]` type\npub type SharedBytes = FlexStr<'static, [u8], Arc<[u8]>>;\n\n/// Local `[u8]` type that can optionally hold borrows (NOTE: This can't be shared between threads)\npub type LocalBytesRef<'s> = FlexStr<'s, [u8], Rc<[u8]>>;\n\n/// Shared `[u8]` type that can optionally hold borrows\npub type SharedBytesRef<'s> = FlexStr<'s, [u8], Arc<[u8]>>;\n\nconst _: () = assert!(\n    size_of::<Option<LocalBytes>>() <= size_of::<Vec<u8>>(),\n    \"Option<LocalBytes> must be less than or equal to the size of Vec<u8>\"\n);\nconst _: () = assert!(\n    size_of::<Option<SharedBytes>>() <= size_of::<Vec<u8>>(),\n    \"Option<SharedBytes> must be less than or equal to the size of Vec<u8>\"\n);\n\n// *** RefCountedMut ***\n\nref_counted_mut_impl!([u8]);\n\n// *** From for FlexStr ***\n\n// NOTE: Cannot be implemented generically because of impl<T> From<T> for T\nimpl<'s, R: RefCounted<[u8]>> From<Vec<u8>> for FlexStr<'s, [u8], R> {\n    fn from(v: Vec<u8>) -> Self {\n        FlexStr::from_owned(v)\n    }\n}\n\nimpl<'s, R: RefCounted<[u8]>> From<&'s str> for FlexStr<'s, [u8], R> {\n    fn from(s: &'s str) -> Self {\n        FlexStr::from_borrowed(s.as_bytes())\n    }\n}\n\n// *** PartialEq ***\n\npartial_eq_impl!([u8], [u8]);\npartial_eq_impl!(&[u8], [u8]);\npartial_eq_impl!(Vec<u8>, [u8]);\npartial_eq_impl!(Cow<'s, [u8]>, [u8]);\n\n// *** AsRef ***\n\nimpl<'s, S: ?Sized + StringToFromBytes, R: RefCounted<S>> AsRef<[u8]> for FlexStr<'s, S, R>\nwhere\n    S: AsRef<[u8]>,\n{\n    fn as_ref(&self) -> &[u8] {\n        self.as_ref_type().as_ref()\n    }\n}\n\n// *** FromStr ***\n\nimpl<R: RefCounted<[u8]>> FromStr for FlexStr<'static, [u8], R> {\n    type Err = Infallible;\n\n    fn from_str(s: &str) -> Result<Self, Self::Err> {\n        Ok(FlexStr::from_borrowed(s.as_bytes()).into_owned())\n    }\n}\n"
  },
  {
    "path": "src/cstr.rs",
    "content": "use alloc::{borrow::Cow, ffi::CString, rc::Rc, sync::Arc};\nuse core::{\n    ffi::{CStr, FromBytesWithNulError},\n    str::FromStr,\n};\n\nuse crate::flex::{\n    FlexStr, ImmutableBytes, RefCounted, RefCountedMut, partial_eq_impl, ref_counted_mut_impl,\n};\n\npub use flexstr_support::InteriorNulError;\nuse flexstr_support::StringToFromBytes;\nuse inline_flexstr::{InlineFlexStr, TooLongOrNulError};\n\n/// Local `CStr` type (NOTE: This can't be shared between threads)\npub type LocalCStr = FlexStr<'static, CStr, Rc<CStr>>;\n\n/// Shared `CStr` type\npub type SharedCStr = FlexStr<'static, CStr, Arc<CStr>>;\n\n/// Local `CStr` type that can optionally hold borrows (NOTE: This can't be shared between threads)\npub type LocalCStrRef<'s> = FlexStr<'s, CStr, Rc<CStr>>;\n\n/// Shared `CStr` type that can optionally hold borrows\npub type SharedCStrRef<'s> = FlexStr<'s, CStr, Arc<CStr>>;\n\n// NOTE: This one is a bit different because CString is just a Box<[u8]>. Instead of equal size,\n// we should be at most one machine word larger.\nconst _: () = assert!(\n    size_of::<Option<LocalCStr>>() <= size_of::<CString>() + size_of::<usize>(),\n    \"Option<LocalCStr> must be less than or equal to the size of CString plus one machine word\"\n);\nconst _: () = assert!(\n    size_of::<Option<SharedCStr>>() <= size_of::<CString>() + size_of::<usize>(),\n    \"Option<SharedCStr> must be less than or equal to the size of CString plus one machine word\"\n);\n\n// *** FlexStr ***\n\nimpl<'s, R: RefCounted<CStr>> FlexStr<'s, CStr, R> {\n    fn from_bytes_without_nul(bytes: &'s [u8]) -> Self {\n        // NOTE: This will scan the string for interior NUL bytes _twice_. Consider optionally\n        // making InlineFlexStr::try_from_bytes_without_nul unsafe and using it conditionally here.\n        match InlineFlexStr::try_from_bytes_with_or_without_nul(bytes) {\n            Ok(inline) => FlexStr::from_inline(inline),\n            // Finally, fallback to creating a new CString so nul zero is appended\n            Err(TooLongOrNulError::TooLong(_)) => FlexStr::from_owned(\n                #[cfg(feature = \"safe\")]\n                // PANIC SAFETY: We already tested for interior NUL bytes\n                CString::new(bytes).expect(\"Unexpected interior NUL byte\"),\n                #[cfg(not(feature = \"safe\"))]\n                // SAFETY: We already tested for interior NUL bytes\n                unsafe {\n                    CString::from_vec_unchecked(bytes.into())\n                },\n            ),\n            // PANIC SAFETY: We already tested for interior NUL bytes from the function that called this one\n            Err(TooLongOrNulError::NulError(e)) => {\n                unreachable!(\"Interior NUL byte found at position {}\", e.position)\n            }\n        }\n    }\n\n    /// Attempt to create a CStr from borrowed bytes with or without a trailing NUL byte.\n    pub fn try_from_bytes_with_or_without_nul(bytes: &'s [u8]) -> Result<Self, InteriorNulError> {\n        match CStr::from_bytes_with_nul(bytes) {\n            // If it is already a valid CStr, then just borrow it\n            Ok(cstr) => Ok(FlexStr::from_borrowed(cstr)),\n            // Otherwise try and inline it, adding a nul zero\n            Err(FromBytesWithNulError::NotNulTerminated) => Ok(Self::from_bytes_without_nul(bytes)),\n            Err(FromBytesWithNulError::InteriorNul { position }) => {\n                Err(InteriorNulError { position })\n            }\n        }\n    }\n\n    /// Borrow the CStr as bytes with a trailing NUL byte\n    #[inline]\n    pub fn as_bytes_with_nul(&self) -> &[u8] {\n        self.as_raw_bytes()\n    }\n}\n\n// *** ImmutableBytes ***\n\nimpl ImmutableBytes for CStr {}\n\n// *** RefCountedMut ***\n\nref_counted_mut_impl!(CStr);\n\n// *** From<CString> ***\n\n// NOTE: Cannot be implemented generically because of impl<T> From<T> for T\nimpl<'s, R: RefCounted<CStr>> From<CString> for FlexStr<'s, CStr, R> {\n    fn from(s: CString) -> Self {\n        FlexStr::from_owned(s)\n    }\n}\n\n// *** TryFrom for FlexStr ***\n\nimpl<'s, R: RefCounted<CStr>> TryFrom<&'s str> for FlexStr<'s, CStr, R> {\n    type Error = InteriorNulError;\n\n    #[inline]\n    fn try_from(s: &'s str) -> Result<Self, Self::Error> {\n        FlexStr::try_from_bytes_with_or_without_nul(s.as_bytes())\n    }\n}\n\nimpl<'s, R: RefCounted<CStr>> TryFrom<&'s [u8]> for FlexStr<'s, CStr, R> {\n    type Error = InteriorNulError;\n\n    #[inline]\n    fn try_from(bytes: &'s [u8]) -> Result<Self, Self::Error> {\n        FlexStr::try_from_bytes_with_or_without_nul(bytes)\n    }\n}\n\n// *** PartialEq ***\n\npartial_eq_impl!(CStr, CStr);\npartial_eq_impl!(&CStr, CStr);\npartial_eq_impl!(CString, CStr);\npartial_eq_impl!(Cow<'s, CStr>, CStr);\n\n// *** AsRef ***\n\nimpl<'s, S: ?Sized + StringToFromBytes, R: RefCounted<S>> AsRef<CStr> for FlexStr<'s, S, R>\nwhere\n    S: AsRef<CStr>,\n{\n    fn as_ref(&self) -> &CStr {\n        self.as_ref_type().as_ref()\n    }\n}\n\n// *** FromStr ***\n\nimpl<R: RefCounted<CStr>> FromStr for FlexStr<'static, CStr, R> {\n    type Err = InteriorNulError;\n\n    fn from_str(s: &str) -> Result<Self, Self::Err> {\n        FlexStr::try_from_bytes_with_or_without_nul(s.as_bytes()).map(FlexStr::into_owned)\n    }\n}\n"
  },
  {
    "path": "src/flex.rs",
    "content": "use alloc::borrow::{Borrow, Cow};\n#[cfg(not(feature = \"std\"))]\nuse alloc::{borrow::ToOwned, boxed::Box};\nuse alloc::{rc::Rc, sync::Arc};\nuse core::cmp::Ordering;\nuse core::fmt;\nuse core::hash::{Hash, Hasher};\nuse core::ops::{Deref, Index};\nuse core::slice::SliceIndex;\n#[cfg(feature = \"std\")]\nuse std::{io, net::ToSocketAddrs};\n\nuse flexstr_support::{StringFromBytesMut, StringLike, StringToFromBytes};\nuse inline_flexstr::InlineFlexStr;\n#[cfg(feature = \"serde\")]\nuse serde::{Deserialize, Deserializer, Serialize, Serializer};\n\n// *** Macros ***\n\nmacro_rules! partial_eq_impl {\n    ($type:ty, $str_type:ty) => {\n        impl<'s, S: ?Sized + StringToFromBytes, R: RefCounted<S>> PartialEq<$type>\n            for FlexStr<'s, S, R>\n        where\n            S: PartialEq<$str_type>,\n        {\n            fn eq(&self, other: &$type) -> bool {\n                S::eq(self, other)\n            }\n        }\n\n        impl<'s, S: ?Sized + StringToFromBytes, R: RefCounted<S>> PartialEq<FlexStr<'s, S, R>>\n            for $type\n        where\n            S: PartialEq<$str_type>,\n        {\n            fn eq(&self, other: &FlexStr<'s, S, R>) -> bool {\n                S::eq(other, self)\n            }\n        }\n    };\n}\n\npub(crate) use partial_eq_impl;\n\nmacro_rules! ref_counted_mut_impl {\n    ($str_type:ty) => {\n        // NOTE: Cannot be implemented generically because CloneToUninit is needed\n        // as a bound to `S`, but is unstable.\n        impl RefCountedMut<$str_type> for Arc<$str_type> {\n            #[inline]\n            fn to_mut(&mut self) -> &mut $str_type {\n                Arc::make_mut(self)\n            }\n\n            #[inline]\n            fn as_mut(&mut self) -> &mut $str_type {\n                // PANIC SAFETY: We only use this when we know the Arc is newly created\n                Arc::get_mut(self).expect(\"Arc is shared\")\n            }\n\n            #[inline]\n            fn try_as_mut(&mut self) -> Option<&mut $str_type> {\n                Arc::get_mut(self)\n            }\n        }\n\n        // NOTE: Cannot be implemented generically because CloneToUninit is needed\n        // as a bound to `S`, but is unstable.\n        impl RefCountedMut<$str_type> for Rc<$str_type> {\n            #[inline]\n            fn to_mut(&mut self) -> &mut $str_type {\n                Rc::make_mut(self)\n            }\n\n            #[inline]\n            fn as_mut(&mut self) -> &mut $str_type {\n                // PANIC SAFETY: We only use this when we know the Rc is newly created\n                Rc::get_mut(self).expect(\"Rc is shared\")\n            }\n\n            #[inline]\n            fn try_as_mut(&mut self) -> Option<&mut $str_type> {\n                Rc::get_mut(self)\n            }\n        }\n    };\n}\n\npub(crate) use ref_counted_mut_impl;\n\n// *** ImmutableBytes ***\n\n/// Marker trait for string types that don't provide conversion from bytes to mutable string reference\npub trait ImmutableBytes: StringToFromBytes {}\n\n// *** RefCounted ***\n\n/// Trait for storage that can be reference counted\npub trait RefCounted<S: ?Sized + StringToFromBytes>:\n    Deref<Target = S> + for<'a> From<&'a S> + Clone\n{\n}\n\nimpl<S, R> RefCounted<S> for R\nwhere\n    R: Deref<Target = S> + for<'a> From<&'a S> + Clone,\n    S: ?Sized + StringToFromBytes,\n{\n}\n\n/// Trait for storage that can be reference counted and mutable\npub trait RefCountedMut<S: ?Sized + StringToFromBytes>: RefCounted<S> {\n    /// Borrow the string as a mutable string reference, allocating and copying first, if needed.\n    fn to_mut(&mut self) -> &mut S;\n\n    /// Borrow the string as a mutable string reference. It will panic if the string is shared.\n    fn as_mut(&mut self) -> &mut S;\n\n    /// Try to borrow the string as a mutable string reference. Returns `None` if the data is shared.\n    fn try_as_mut(&mut self) -> Option<&mut S> {\n        None\n    }\n}\n\n// *** ToOwnedFlexStr ***\n\n/// Trait for types that can be converted to an owned FlexStr\npub trait ToOwnedFlexStr<R, S>\nwhere\n    R: RefCounted<S>,\n    S: ?Sized + StringToFromBytes,\n{\n    /// Convert a borrowed string to an owned FlexStr\n    fn to_owned_opt(&self) -> FlexStr<'static, S, R>;\n}\n\nimpl<R, S> ToOwnedFlexStr<R, S> for S\nwhere\n    R: RefCounted<S>,\n    S: ?Sized + StringToFromBytes,\n{\n    fn to_owned_opt(&self) -> FlexStr<'static, S, R> {\n        FlexStr::from_borrowed(self).into_owned()\n    }\n}\n\n// *** IntoOptimizedFlexStr ***\n\n/// Trait for types that can be converted to an optimized FlexStr\npub trait IntoOptimizedFlexStr<R, S>\nwhere\n    R: RefCounted<S>,\n    S: ?Sized + StringToFromBytes,\n    Box<S>: From<S::Owned>,\n{\n    /// Convert a string to an optimized FlexStr\n    fn into_opt(self) -> FlexStr<'static, S, R>;\n}\n\nimpl<R, S> IntoOptimizedFlexStr<R, S> for S::Owned\nwhere\n    R: RefCounted<S>,\n    S: ?Sized + StringToFromBytes,\n    Box<S>: From<S::Owned>,\n{\n    fn into_opt(self) -> FlexStr<'static, S, R> {\n        FlexStr::from_owned(self).optimize()\n    }\n}\n\n// *** FlexStr ***\n\n#[doc(alias = \"SharedStr\")]\n#[doc(alias = \"LocalStr\")]\n#[doc(alias = \"SharedOsStr\")]\n#[doc(alias = \"LocalOsStr\")]\n#[doc(alias = \"SharedPath\")]\n#[doc(alias = \"LocalPath\")]\n#[doc(alias = \"SharedCStr\")]\n#[doc(alias = \"LocalCStr\")]\n#[doc(alias = \"SharedBytes\")]\n#[doc(alias = \"LocalBytes\")]\n/// Flexible string type that can store a borrowed string, an inline string, a reference counted string, or a boxed string\n#[derive(Debug)]\npub enum FlexStr<'s, S: ?Sized + StringToFromBytes, R: RefCounted<S>> {\n    /// Borrowed string - borrowed strings are imported as `&S`\n    Borrowed(&'s S),\n    /// Inline string - owned strings that are small enough to be stored inline\n    Inlined(InlineFlexStr<S>),\n    /// Reference counted string - owned strings that are too large for inline storage\n    RefCounted(R),\n    /// Boxed string - heap allocated strings are imported as `Box<S>`\n    Boxed(Box<S>),\n}\n\nimpl<'s, S: ?Sized + StringToFromBytes, R: RefCounted<S>> FlexStr<'s, S, R>\nwhere\n    for<'a> &'a S: Default,\n{\n    /// Create a new empty string. This is a Borrowed variant.\n    pub fn empty() -> FlexStr<'s, S, R> {\n        FlexStr::Borrowed(Default::default())\n    }\n}\n\nimpl<'s, S: ?Sized + StringToFromBytes, R: RefCounted<S>> FlexStr<'s, S, R> {\n    fn copy(&self) -> FlexStr<'s, S, R> {\n        match self {\n            FlexStr::Borrowed(s) => FlexStr::Borrowed(s),\n            FlexStr::Inlined(s) => FlexStr::Inlined(*s),\n            FlexStr::RefCounted(s) => FlexStr::RefCounted(s.clone()),\n            FlexStr::Boxed(s) => FlexStr::copy_into_owned(s),\n        }\n    }\n}\n\nimpl<'s, S: ?Sized + StringToFromBytes, R: RefCounted<S>> FlexStr<'s, S, R>\nwhere\n    Box<S>: From<S::Owned>,\n{\n    /// Create a new string from an owned string (most likely without copy or allocation).\n    /// The result is a Boxed variant.\n    pub fn from_owned(s: S::Owned) -> FlexStr<'static, S, R> {\n        FlexStr::Boxed(s.into())\n    }\n}\n\nimpl<'s, S: ?Sized + StringToFromBytes, R: RefCounted<S>> FlexStr<'s, S, R> {\n    /// Create a new string from a borrowed string. This is a const fn because it does not allocate\n    /// and results in a Borrowed variant.\n    pub const fn from_borrowed(s: &'s S) -> FlexStr<'s, S, R> {\n        FlexStr::Borrowed(s)\n    }\n\n    /// Create a new string from an inline string. This results in an Inlined variant.\n    pub fn from_inline(s: InlineFlexStr<S>) -> FlexStr<'s, S, R> {\n        FlexStr::Inlined(s)\n    }\n\n    /// Create a new string from a reference counted string. This results in a RefCounted variant.\n    pub fn from_ref_counted(s: R) -> FlexStr<'s, S, R> {\n        FlexStr::RefCounted(s)\n    }\n\n    /// Create a new string from a boxed string. This results in a Boxed variant.\n    pub fn from_boxed(s: Box<S>) -> FlexStr<'s, S, R> {\n        FlexStr::Boxed(s)\n    }\n\n    /// Returns true if this is a borrowed string\n    pub fn is_borrowed(&self) -> bool {\n        matches!(self, FlexStr::Borrowed(_))\n    }\n\n    /// Returns true if this is an inlined string\n    pub fn is_inlined(&self) -> bool {\n        matches!(self, FlexStr::Inlined(_))\n    }\n\n    /// Returns true if this is a reference counted string\n    pub fn is_ref_counted(&self) -> bool {\n        matches!(self, FlexStr::RefCounted(_))\n    }\n\n    /// Returns true if this is a boxed string\n    pub fn is_boxed(&self) -> bool {\n        matches!(self, FlexStr::Boxed(_))\n    }\n\n    /// Returns true if this is a string that is on the heap\n    pub fn is_on_heap(&self) -> bool {\n        matches!(self, FlexStr::RefCounted(_) | FlexStr::Boxed(_))\n    }\n\n    /// Returns true if this is a string that is off the heap\n    pub fn is_off_heap(&self) -> bool {\n        matches!(self, FlexStr::Borrowed(_) | FlexStr::Inlined(_))\n    }\n\n    fn copy_into_owned(s: &S) -> FlexStr<'static, S, R> {\n        match InlineFlexStr::try_from_type(s) {\n            Ok(inline) => FlexStr::Inlined(inline),\n            Err(_) => FlexStr::RefCounted(s.into()),\n        }\n    }\n\n    /// Optimize the string variant. This is a no-op for Inlined/Borrowed variants. RefCounted\n    /// strings will attempt to inline, but otherwise be left as ref counted. Boxed strings will\n    /// attempt to inline, but otherwise be converted to a ref counted string.\n    pub fn optimize(self) -> FlexStr<'s, S, R> {\n        match self {\n            // This should be inlined or ref counted\n            FlexStr::Boxed(s) => Self::copy_into_owned(&s),\n            // There is probably a reason this is ref counted, but we can try to inline it first\n            FlexStr::RefCounted(s) => match InlineFlexStr::try_from_type(&*s) {\n                Ok(inline) => FlexStr::Inlined(inline),\n                Err(_) => FlexStr::RefCounted(s),\n            },\n            // Borrowed and inlined strings are already optimized\n            _ => self,\n        }\n    }\n\n    /// Convert a string reference to an owned string. Inlined/RefCounted variants are cloned,\n    /// Borrowed/Boxed variants are copied into a new Inlined or RefCounted owned string.\n    pub fn to_owned(&self) -> FlexStr<'static, S, R> {\n        match self {\n            FlexStr::Borrowed(s) => FlexStr::copy_into_owned(s),\n            FlexStr::Inlined(s) => FlexStr::Inlined(*s),\n            FlexStr::RefCounted(s) => FlexStr::RefCounted(s.clone()),\n            FlexStr::Boxed(s) => FlexStr::copy_into_owned(s),\n        }\n    }\n\n    /// Consume a string and convert it to an owned string. Inlined/RefCounted/Boxed variants\n    /// are moved, Borrowed variants are copied into a new Inlined or RefCounted owned string.\n    pub fn into_owned(self) -> FlexStr<'static, S, R> {\n        match self {\n            FlexStr::Borrowed(s) => FlexStr::copy_into_owned(s),\n            FlexStr::Inlined(s) => FlexStr::Inlined(s),\n            FlexStr::RefCounted(s) => FlexStr::RefCounted(s),\n            FlexStr::Boxed(s) => FlexStr::Boxed(s),\n        }\n    }\n\n    /// Borrow a string reference as `&S`\n    pub fn as_ref_type(&self) -> &S {\n        match self {\n            FlexStr::Borrowed(s) => s,\n            FlexStr::Inlined(s) => s,\n            FlexStr::RefCounted(s) => s,\n            FlexStr::Boxed(s) => s,\n        }\n    }\n\n    /// Convert a string reference to an owned string. `S::to_owned` is called on all variants.\n    pub fn to_owned_type(&self) -> S::Owned {\n        match self {\n            FlexStr::Borrowed(s) => <S as ToOwned>::to_owned(s),\n            FlexStr::Inlined(s) => <S as ToOwned>::to_owned(s),\n            FlexStr::RefCounted(s) => <S as ToOwned>::to_owned(s),\n            FlexStr::Boxed(s) => <S as ToOwned>::to_owned(s),\n        }\n    }\n\n    /// Borrow the string as a raw byte slice (NOTE: includes trailing NUL for CStr)\n    pub fn as_raw_bytes(&self) -> &[u8] {\n        match self {\n            FlexStr::Borrowed(s) => S::self_as_raw_bytes(s),\n            FlexStr::Inlined(s) => s.as_raw_bytes(),\n            FlexStr::RefCounted(s) => S::self_as_raw_bytes(s),\n            FlexStr::Boxed(s) => S::self_as_raw_bytes(s),\n        }\n    }\n\n    /// Borrow the string as bytes\n    pub fn as_bytes(&self) -> &[u8] {\n        match self {\n            FlexStr::Borrowed(s) => S::self_as_bytes(s),\n            FlexStr::Inlined(s) => s.as_bytes(),\n            FlexStr::RefCounted(s) => S::self_as_bytes(s),\n            FlexStr::Boxed(s) => S::self_as_bytes(s),\n        }\n    }\n}\n\nimpl<'s, S: ?Sized + StringToFromBytes, R: RefCounted<S>> FlexStr<'s, S, R>\nwhere\n    S::Owned: From<Box<S>>,\n{\n    /// Consume a string and convert it to an owned string. `S::to_owned` is called on Borrowed/Inlined/RefCounted variants.\n    /// Boxed variants are converted directly into `S::Owned` (most likely without copy or allocation).\n    pub fn into_owned_type(self) -> S::Owned {\n        match self {\n            FlexStr::Borrowed(s) => <S as ToOwned>::to_owned(s),\n            FlexStr::Inlined(s) => <S as ToOwned>::to_owned(&s),\n            FlexStr::RefCounted(s) => <S as ToOwned>::to_owned(&s),\n            FlexStr::Boxed(s) => s.into(),\n        }\n    }\n}\n\n// NOTE: This implementation is the \"slow path\" for types that are ImmutableBytes (iow, cannot mutate their raw bytes)\nimpl<'s, S: ?Sized + ImmutableBytes, R: RefCountedMut<S>> FlexStr<'s, S, R> {\n    /// Borrow the string as a mutable string reference, converting if needed. If the string is Borrowed,\n    /// it is made into a reference counted string first. RefCounted variants will allocate + copy\n    /// if they are shared. In all other cases, the string is borrowed as a mutable reference\n    /// directly.\n    pub fn to_mut_type_fallback(&mut self) -> &mut S {\n        match self {\n            // Borrowed strings can't be made mutable - we need to own it first\n            // ImmutableBytes strings can't mutate inlined strings, so ref count it\n            FlexStr::Borrowed(s) => {\n                *self = FlexStr::RefCounted((&**s).into());\n                match self {\n                    // We know this is brand new, so it is safe to share mutably immediately\n                    FlexStr::RefCounted(s) => s.as_mut(),\n                    _ => unreachable!(\"Unexpected variant\"),\n                }\n            }\n            // ImmutableBytes strings must be converted before being made mutable\n            FlexStr::Inlined(s) => {\n                *self = FlexStr::RefCounted((&**s).into());\n                match self {\n                    // We know this is brand new, so it is safe to share mutably immediately\n                    FlexStr::RefCounted(s) => s.as_mut(),\n                    _ => unreachable!(\"Unexpected variant\"),\n                }\n            }\n            // Since this might be shared, we need to check before just sharing as mutable\n            FlexStr::RefCounted(s) => s.to_mut(),\n            // Boxed strings can be made mutable directly\n            FlexStr::Boxed(s) => s.as_mut(),\n        }\n    }\n}\n\n// NOTE: This implementation is the \"fast path\" for types that provide direct mutable access to their bytes\nimpl<'s, S: ?Sized + StringFromBytesMut, R: RefCountedMut<S>> FlexStr<'s, S, R> {\n    /// Borrow the string as a mutable string reference, converting if needed. If the string is borrowed,\n    /// it is made into an owned string first. RefCounted variants will allocate + copy\n    /// if they are shared. In all other cases, the string is borrowed as a mutable reference\n    /// directly.\n    pub fn to_mut_type(&mut self) -> &mut S {\n        match self {\n            // Borrowed strings can't be made mutable - we need to own it first\n            FlexStr::Borrowed(s) => {\n                *self = FlexStr::copy_into_owned(s);\n                // copy_into_owned will never return a borrowed variant\n                match self {\n                    FlexStr::Inlined(s) => s.as_mut_type(),\n                    FlexStr::RefCounted(s) => s.as_mut(),\n                    _ => {\n                        // PANIC SAFETY: copy_into_owned will never return a borrowed/boxed variant\n                        unreachable!(\"Unexpected borrowed/boxed variant\");\n                    }\n                }\n            }\n            // Inlined strings can be made mutable directly\n            FlexStr::Inlined(s) => s.as_mut_type(),\n            // Since this might be shared, we need to check before just sharing as mutable\n            FlexStr::RefCounted(s) => s.to_mut(),\n            // Boxed strings can be made mutable directly\n            FlexStr::Boxed(s) => s.as_mut(),\n        }\n    }\n}\n\nimpl<'s, S: ?Sized + StringToFromBytes> FlexStr<'s, S, Arc<S>>\nwhere\n    Arc<S>: for<'a> From<&'a S>,\n    Rc<S>: for<'a> From<&'a S>,\n{\n    /// Convert a shared string reference to a local string. The Borrowed/Inlined variants are copied,\n    /// RefCounted is copied into a new allocation, and Boxed is copied into an Inlined or RefCounted variant.\n    pub fn to_local(&self) -> FlexStr<'s, S, Rc<S>> {\n        match self {\n            FlexStr::Borrowed(s) => FlexStr::Borrowed(s),\n            FlexStr::Inlined(s) => FlexStr::Inlined(*s),\n            FlexStr::RefCounted(s) => FlexStr::RefCounted(Rc::from(s)),\n            FlexStr::Boxed(s) => FlexStr::copy_into_owned(s),\n        }\n    }\n\n    /// Consume a shared string and convert it to a local string. The Borrowed/Inlined/Boxed variants are moved,\n    /// and RefCounted is copied into a new allocation.\n    pub fn into_local(self) -> FlexStr<'s, S, Rc<S>> {\n        match self {\n            FlexStr::Borrowed(s) => FlexStr::Borrowed(s),\n            FlexStr::Inlined(s) => FlexStr::Inlined(s),\n            FlexStr::RefCounted(s) => FlexStr::RefCounted(Rc::from(&s)),\n            FlexStr::Boxed(s) => FlexStr::Boxed(s),\n        }\n    }\n}\n\nimpl<'s, S: ?Sized + StringToFromBytes> FlexStr<'s, S, Rc<S>>\nwhere\n    Rc<S>: for<'a> From<&'a S>,\n    Arc<S>: for<'a> From<&'a S>,\n{\n    /// Convert a local string reference to a shared string. The Borrowed/Inlined variants are copied,\n    /// RefCounted is copied into a new allocation, and Boxed is copied into an Inlined or RefCounted variant.\n    pub fn to_shared(&self) -> FlexStr<'s, S, Arc<S>> {\n        match self {\n            FlexStr::Borrowed(s) => FlexStr::Borrowed(s),\n            FlexStr::Inlined(s) => FlexStr::Inlined(*s),\n            FlexStr::RefCounted(s) => FlexStr::RefCounted(Arc::from(s)),\n            FlexStr::Boxed(s) => FlexStr::copy_into_owned(s),\n        }\n    }\n\n    /// Consume a local string and convert it to a shared string. The Borrowed/Inlined/Boxed variants are moved,\n    /// and RefCounted is copied into a new allocation.\n    pub fn into_shared(self) -> FlexStr<'s, S, Arc<S>> {\n        match self {\n            FlexStr::Borrowed(s) => FlexStr::Borrowed(s),\n            FlexStr::Inlined(s) => FlexStr::Inlined(s),\n            FlexStr::RefCounted(s) => FlexStr::RefCounted(Arc::from(&s)),\n            FlexStr::Boxed(s) => FlexStr::Boxed(s),\n        }\n    }\n}\n\n// *** StringLike ***\n\nimpl<S: ?Sized + StringToFromBytes, R: RefCounted<S>> StringLike<S> for FlexStr<'_, S, R> {\n    fn as_ref_type(&self) -> &S {\n        <Self>::as_ref_type(self)\n    }\n\n    fn as_bytes(&self) -> &[u8] {\n        <Self>::as_bytes(self)\n    }\n\n    fn into_owned_type(self) -> S::Owned\n    where\n        S::Owned: From<Box<S>>,\n    {\n        <Self>::into_owned_type(self)\n    }\n\n    fn to_owned_type(&self) -> S::Owned {\n        <Self>::to_owned_type(self)\n    }\n}\n\n// *** Default ***\n\nimpl<'s, S: ?Sized + StringToFromBytes, R: RefCounted<S>> Default for FlexStr<'s, S, R>\nwhere\n    for<'a> &'a S: Default,\n{\n    /// Create a new string from a default value\n    fn default() -> FlexStr<'s, S, R> {\n        FlexStr::empty()\n    }\n}\n\n// *** From ***\n\nimpl<'s, S: ?Sized + StringToFromBytes, R: RefCounted<S>> From<&'s S> for FlexStr<'s, S, R> {\n    fn from(s: &'s S) -> Self {\n        FlexStr::from_borrowed(s)\n    }\n}\n\n// NOTE: Could not be implemented more generically because of From<S::Owned>\nimpl<'s, S: ?Sized + StringToFromBytes> From<Rc<S>> for FlexStr<'s, S, Rc<S>>\nwhere\n    Rc<S>: for<'a> From<&'a S>,\n{\n    fn from(s: Rc<S>) -> Self {\n        FlexStr::from_ref_counted(s)\n    }\n}\n\n// NOTE: Could not be implemented more generically because of From<S::Owned>\nimpl<'s, S: ?Sized + StringToFromBytes> From<Arc<S>> for FlexStr<'s, S, Arc<S>>\nwhere\n    Arc<S>: for<'a> From<&'a S>,\n{\n    fn from(s: Arc<S>) -> Self {\n        FlexStr::from_ref_counted(s)\n    }\n}\n\nimpl<'s, S: ?Sized + StringToFromBytes, R: RefCounted<S>> From<Box<S>> for FlexStr<'s, S, R> {\n    fn from(s: Box<S>) -> Self {\n        FlexStr::from_boxed(s)\n    }\n}\n\nimpl<'s, S: ?Sized + StringToFromBytes, R: RefCounted<S>> From<InlineFlexStr<S>>\n    for FlexStr<'s, S, R>\n{\n    fn from(s: InlineFlexStr<S>) -> Self {\n        FlexStr::from_inline(s)\n    }\n}\n\nimpl<'s, S: ?Sized + StringToFromBytes, R: RefCounted<S>> From<Cow<'s, S>> for FlexStr<'s, S, R>\nwhere\n    Box<S>: From<S::Owned>,\n{\n    fn from(s: Cow<'s, S>) -> Self {\n        match s {\n            Cow::Borrowed(s) => FlexStr::from_borrowed(s),\n            Cow::Owned(s) => FlexStr::from_owned(s),\n        }\n    }\n}\n\n// *** Clone ***\n\nimpl<'s, S: ?Sized + StringToFromBytes, R: RefCounted<S>> Clone for FlexStr<'s, S, R> {\n    fn clone(&self) -> Self {\n        self.copy()\n    }\n}\n\n// *** Hash ***\n\nimpl<'s, S: ?Sized + StringToFromBytes, R: RefCounted<S>> Hash for FlexStr<'s, S, R>\nwhere\n    S: Hash,\n{\n    fn hash<H: Hasher>(&self, state: &mut H) {\n        self.as_ref_type().hash(state);\n    }\n}\n\n// *** Deref<Target = S> ***\n\nimpl<'s, S: ?Sized + StringToFromBytes, R: RefCounted<S>> Deref for FlexStr<'s, S, R> {\n    type Target = S;\n\n    fn deref(&self) -> &Self::Target {\n        self.as_ref_type()\n    }\n}\n\n// *** Display ***\n\nimpl<'s, S: ?Sized + StringToFromBytes, R: RefCounted<S>> fmt::Display for FlexStr<'s, S, R>\nwhere\n    S: fmt::Display,\n{\n    fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {\n        S::fmt(self.as_ref_type(), f)\n    }\n}\n\n// *** Borrow ***\n\nimpl<'s, S: ?Sized + StringToFromBytes, R: RefCounted<S>> Borrow<S> for FlexStr<'s, S, R> {\n    fn borrow(&self) -> &S {\n        self.as_ref_type()\n    }\n}\n\n// *** PartialEq / Eq ***\n\nimpl<'s, S: ?Sized + StringToFromBytes, R: RefCounted<S>> PartialEq for FlexStr<'s, S, R>\nwhere\n    S: PartialEq,\n{\n    fn eq(&self, other: &Self) -> bool {\n        S::eq(self.as_ref_type(), other.as_ref_type())\n    }\n}\n\nimpl<'s, S: ?Sized + StringToFromBytes, R: RefCounted<S>> Eq for FlexStr<'s, S, R> where S: Eq {}\n\n// *** PartialOrd / Ord ***\n\nimpl<'s, S: ?Sized + StringToFromBytes, R: RefCounted<S>> PartialOrd for FlexStr<'s, S, R>\nwhere\n    S: PartialOrd,\n{\n    fn partial_cmp(&self, other: &Self) -> Option<Ordering> {\n        S::partial_cmp(self.as_ref_type(), other.as_ref_type())\n    }\n}\n\nimpl<'s, S: ?Sized + StringToFromBytes, R: RefCounted<S>> Ord for FlexStr<'s, S, R>\nwhere\n    S: Ord,\n{\n    fn cmp(&self, other: &Self) -> Ordering {\n        S::cmp(self.as_ref_type(), other.as_ref_type())\n    }\n}\n\n// *** Index ***\n\nimpl<'s, S: ?Sized + StringToFromBytes, R: RefCounted<S>, I: SliceIndex<S>> Index<I>\n    for FlexStr<'s, S, R>\nwhere\n    S: Index<I>,\n{\n    type Output = S::Output;\n\n    fn index(&self, index: I) -> &Self::Output {\n        S::index(self.as_ref_type(), index)\n    }\n}\n\n// *** ToSocketAddrs ***\n\n#[cfg(feature = \"std\")]\nimpl<'s, S: ?Sized + StringToFromBytes, R: RefCounted<S>> ToSocketAddrs for FlexStr<'s, S, R>\nwhere\n    S: ToSocketAddrs,\n{\n    type Iter = <S as ToSocketAddrs>::Iter;\n\n    fn to_socket_addrs(&self) -> io::Result<<S as ToSocketAddrs>::Iter> {\n        self.as_ref_type().to_socket_addrs()\n    }\n}\n\n// *** Serialize ***\n\n#[cfg(feature = \"serde\")]\nimpl<'s, S: ?Sized + StringToFromBytes, R: RefCounted<S>> Serialize for FlexStr<'s, S, R>\nwhere\n    S: Serialize,\n{\n    fn serialize<SER: Serializer>(&self, serializer: SER) -> Result<SER::Ok, SER::Error> {\n        S::serialize(self.as_ref_type(), serializer)\n    }\n}\n\n// *** Deserialize ***\n\n#[cfg(feature = \"serde\")]\nimpl<'de, S: ?Sized + StringToFromBytes, R: RefCounted<S>> Deserialize<'de>\n    for FlexStr<'static, S, R>\nwhere\n    Box<S>: Deserialize<'de>,\n{\n    fn deserialize<D: Deserializer<'de>>(deserializer: D) -> Result<Self, D::Error> {\n        // TODO: See TODO in InlineFlexStr::deserialize for more details.\n        // This one isn't as egregious since Boxed isn't inherently wrong here.\n        Box::deserialize(deserializer)\n            .map(FlexStr::Boxed)\n            .map(FlexStr::optimize)\n    }\n}\n\n// *** Zeroize ***\n\n/// Zero the raw bytes of a DST behind a mutable reference.\n///\n/// The zeroed value remains valid for all supported string types: all-zero bytes\n/// produce valid `str` (NUL is valid UTF-8), `[u8]`, `CStr` (NUL terminator),\n/// `OsStr`, and `Path`. None of these types have `Drop` impls, so subsequent\n/// deallocation (via Box/Arc/Rc drop) only needs the pointer and size.\n#[cfg(feature = \"zeroize\")]\nfn zeroize_raw_bytes<S: ?Sized + StringToFromBytes>(s: &mut S) {\n    let len = S::self_as_raw_bytes(s).len();\n    let ptr = s as *mut S as *mut u8;\n    // SAFETY: We have exclusive ownership (`&mut S`). The pointer and length are valid\n    // because we obtained them from the living reference.\n    unsafe {\n        zeroize::Zeroize::zeroize(core::slice::from_raw_parts_mut(ptr, len));\n    }\n}\n\n#[cfg(feature = \"zeroize\")]\nimpl<'s, S: ?Sized + StringToFromBytes, R: RefCountedMut<S>> zeroize::TryZeroize\n    for FlexStr<'s, S, R>\n{\n    fn try_zeroize(&mut self) -> bool {\n        match self {\n            FlexStr::Inlined(s) => {\n                zeroize::Zeroize::zeroize(s);\n            }\n            FlexStr::Boxed(s) => {\n                zeroize_raw_bytes(&mut **s);\n            }\n            FlexStr::RefCounted(rc) => {\n                if let Some(s) = rc.try_as_mut() {\n                    zeroize_raw_bytes(s);\n                } else {\n                    // Shared reference — cannot zero the underlying data\n                    return false;\n                }\n            }\n            // Borrowed data is not owned by us — cannot zero\n            FlexStr::Borrowed(_) => return false,\n        }\n        *self = FlexStr::Inlined(InlineFlexStr::zeroed());\n        true\n    }\n}\n"
  },
  {
    "path": "src/lib.rs",
    "content": "#![cfg_attr(not(feature = \"std\"), no_std)]\n#![cfg_attr(\n    all(\n        not(all(feature = \"win_min_unsafe\", target_family = \"windows\")),\n        feature = \"safe\"\n    ),\n    forbid(unsafe_code)\n)]\n#![cfg_attr(docsrs, feature(doc_cfg))]\n#![warn(missing_docs)]\n\n//! A flexible, simple to use, immutable, clone-efficient [String] replacement for Rust\n\n#[cfg(all(feature = \"safe\", feature = \"zeroize\"))]\ncompile_error!(\n    \"The `zeroize` and `safe` features are incompatible. Secure memory zeroing requires unsafe code.\"\n);\n\nextern crate alloc;\n\n#[doc = include_str!(\"../README.md\")]\nmod readme_tests {}\n\n#[cfg(feature = \"bytes\")]\n/// Module for byte-based strings (`[u8]`)\npub mod bytes;\n#[cfg(feature = \"cstr\")]\n/// Module for `CStr`-based strings\npub mod cstr;\nmod flex;\n#[cfg(all(feature = \"std\", feature = \"osstr\"))]\n/// Module for `OsStr`-based strings\npub mod osstr;\n#[cfg(all(feature = \"std\", feature = \"path\"))]\n/// Module for `Path`-based strings\npub mod path;\n#[cfg(feature = \"str\")]\n/// Module for `str`-based strings\npub mod str;\n\n#[cfg(feature = \"bytes\")]\npub use bytes::{LocalBytes, SharedBytes};\n#[cfg(feature = \"cstr\")]\npub use cstr::{LocalCStr, SharedCStr};\npub use flex::{\n    FlexStr, ImmutableBytes, IntoOptimizedFlexStr, RefCounted, RefCountedMut, ToOwnedFlexStr,\n};\n#[cfg(feature = \"cstr\")]\npub use flexstr_support::InteriorNulError;\npub use flexstr_support::StringLike;\n#[cfg(all(feature = \"std\", feature = \"osstr\"))]\npub use osstr::{LocalOsStr, SharedOsStr};\n#[cfg(all(feature = \"std\", feature = \"path\"))]\npub use path::{LocalPath, SharedPath};\n#[cfg(feature = \"str\")]\npub use str::{LocalStr, SharedStr};\n"
  },
  {
    "path": "src/osstr.rs",
    "content": "use alloc::{borrow::Cow, rc::Rc, sync::Arc};\nuse core::{convert::Infallible, str::FromStr};\nuse std::ffi::{OsStr, OsString};\nuse std::path::Path;\n#[cfg(feature = \"path\")]\nuse std::path::PathBuf;\n\nuse crate::flex::{\n    FlexStr, ImmutableBytes, RefCounted, RefCountedMut, partial_eq_impl, ref_counted_mut_impl,\n};\n\nuse flexstr_support::StringToFromBytes;\n\n/// Local `OsStr` type (NOTE: This can't be shared between threads)\npub type LocalOsStr = FlexStr<'static, OsStr, Rc<OsStr>>;\n\n/// Shared `OsStr` type\npub type SharedOsStr = FlexStr<'static, OsStr, Arc<OsStr>>;\n\n/// Local `OsStr` type that can optionally hold borrows (NOTE: This can't be shared between threads)\npub type LocalOsStrRef<'s> = FlexStr<'s, OsStr, Rc<OsStr>>;\n\n/// Shared `OsStr` type that can optionally hold borrows\npub type SharedOsStrRef<'s> = FlexStr<'s, OsStr, Arc<OsStr>>;\n\nconst _: () = assert!(\n    size_of::<Option<LocalOsStr>>() <= size_of::<OsString>(),\n    \"Option<LocalOsStr> must be less than or equal to the size of OsString\"\n);\nconst _: () = assert!(\n    size_of::<Option<SharedOsStr>>() <= size_of::<OsString>(),\n    \"Option<SharedOsStr> must be less than or equal to the size of OsString\"\n);\n\n// *** ImmutableBytes ***\n\nimpl ImmutableBytes for OsStr {}\n\n// *** RefCountedMut ***\n\nref_counted_mut_impl!(OsStr);\n\n// *** From for FlexStr ***\n\n// NOTE: Cannot be implemented generically because of impl<T> From<T> for T\nimpl<'s, R: RefCounted<OsStr>> From<OsString> for FlexStr<'s, OsStr, R> {\n    fn from(s: OsString) -> Self {\n        FlexStr::from_owned(s)\n    }\n}\n\nimpl<'s, R: RefCounted<OsStr>> From<String> for FlexStr<'s, OsStr, R> {\n    fn from(s: String) -> Self {\n        FlexStr::from_owned(s.into())\n    }\n}\n\n#[cfg(feature = \"path\")]\nimpl<'s, R: RefCounted<OsStr>> From<PathBuf> for FlexStr<'s, OsStr, R> {\n    fn from(p: PathBuf) -> Self {\n        FlexStr::from_owned(p.into())\n    }\n}\n\nimpl<'s, R: RefCounted<OsStr>> From<&'s str> for FlexStr<'s, OsStr, R> {\n    fn from(s: &'s str) -> Self {\n        FlexStr::from_borrowed(OsStr::new(s))\n    }\n}\n\nimpl<'s, R: RefCounted<OsStr>> From<&'s Path> for FlexStr<'s, OsStr, R> {\n    fn from(p: &'s Path) -> Self {\n        FlexStr::from_borrowed(p.as_os_str())\n    }\n}\n\n// *** PartialEq ***\n\npartial_eq_impl!(OsStr, OsStr);\npartial_eq_impl!(&OsStr, OsStr);\npartial_eq_impl!(OsString, OsStr);\npartial_eq_impl!(Cow<'s, OsStr>, OsStr);\n\n// *** AsRef ***\n\nimpl<'s, S: ?Sized + StringToFromBytes, R: RefCounted<S>> AsRef<OsStr> for FlexStr<'s, S, R>\nwhere\n    S: AsRef<OsStr>,\n{\n    fn as_ref(&self) -> &OsStr {\n        self.as_ref_type().as_ref()\n    }\n}\n\n// *** FromStr ***\n\nimpl<R: RefCounted<OsStr>> FromStr for FlexStr<'static, OsStr, R> {\n    type Err = Infallible;\n\n    fn from_str(s: &str) -> Result<Self, Self::Err> {\n        Ok(FlexStr::from_borrowed(OsStr::new(s)).into_owned())\n    }\n}\n"
  },
  {
    "path": "src/path.rs",
    "content": "use alloc::{borrow::Cow, rc::Rc, sync::Arc};\nuse core::{convert::Infallible, str::FromStr};\nuse std::{\n    ffi::{OsStr, OsString},\n    path::{Path, PathBuf},\n};\n\nuse crate::flex::{\n    FlexStr, ImmutableBytes, RefCounted, RefCountedMut, partial_eq_impl, ref_counted_mut_impl,\n};\n\nuse flexstr_support::StringToFromBytes;\n\n/// Local `Path` type (NOTE: This can't be shared between threads)\npub type LocalPath = FlexStr<'static, Path, Rc<Path>>;\n\n/// Shared `Path` type\npub type SharedPath = FlexStr<'static, Path, Arc<Path>>;\n\n/// Local `Path` type that can optionally hold borrows (NOTE: This can't be shared between threads)\npub type LocalPathRef<'s> = FlexStr<'s, Path, Rc<Path>>;\n\n/// Shared `Path` type that can optionally hold borrows\npub type SharedPathRef<'s> = FlexStr<'s, Path, Arc<Path>>;\n\nconst _: () = assert!(\n    size_of::<Option<LocalPath>>() <= size_of::<PathBuf>(),\n    \"Option<LocalPath> must be less than or equal to the size of PathBuf\"\n);\nconst _: () = assert!(\n    size_of::<Option<SharedPath>>() <= size_of::<PathBuf>(),\n    \"Option<SharedPath> must be less than or equal to the size of PathBuf\"\n);\n\n// *** ImmutableBytes ***\n\nimpl ImmutableBytes for Path {}\n\n// *** RefCountedMut ***\n\nref_counted_mut_impl!(Path);\n\n// *** From for FlexStr ***\n\n// NOTE: Cannot be implemented generically because of impl<T> From<T> for T\nimpl<'s, R: RefCounted<Path>> From<PathBuf> for FlexStr<'s, Path, R> {\n    fn from(p: PathBuf) -> Self {\n        FlexStr::from_owned(p)\n    }\n}\n\nimpl<'s, R: RefCounted<Path>> From<String> for FlexStr<'s, Path, R> {\n    fn from(s: String) -> Self {\n        FlexStr::from_owned(s.into())\n    }\n}\n\nimpl<'s, R: RefCounted<Path>> From<OsString> for FlexStr<'s, Path, R> {\n    fn from(s: OsString) -> Self {\n        FlexStr::from_owned(s.into())\n    }\n}\n\nimpl<'s, R: RefCounted<Path>> From<&'s str> for FlexStr<'s, Path, R> {\n    fn from(s: &'s str) -> Self {\n        FlexStr::from_borrowed(Path::new(s))\n    }\n}\n\nimpl<'s, R: RefCounted<Path>> From<&'s OsStr> for FlexStr<'s, Path, R> {\n    fn from(s: &'s OsStr) -> Self {\n        FlexStr::from_borrowed(Path::new(s))\n    }\n}\n\n// *** PartialEq ***\n\npartial_eq_impl!(Path, Path);\npartial_eq_impl!(&Path, Path);\npartial_eq_impl!(PathBuf, Path);\npartial_eq_impl!(Cow<'s, Path>, Path);\n\n// *** AsRef ***\n\nimpl<'s, S: ?Sized + StringToFromBytes, R: RefCounted<S>> AsRef<Path> for FlexStr<'s, S, R>\nwhere\n    S: AsRef<Path>,\n{\n    fn as_ref(&self) -> &Path {\n        self.as_ref_type().as_ref()\n    }\n}\n\n// *** FromStr ***\n\nimpl<R: RefCounted<Path>> FromStr for FlexStr<'static, Path, R> {\n    type Err = Infallible;\n\n    fn from_str(s: &str) -> Result<Self, Self::Err> {\n        Ok(FlexStr::from_borrowed(Path::new(s)).into_owned())\n    }\n}\n"
  },
  {
    "path": "src/str.rs",
    "content": "use alloc::{\n    borrow::Cow,\n    ffi::{CString, IntoStringError},\n    rc::Rc,\n    string::{FromUtf8Error, String},\n    sync::Arc,\n    vec::Vec,\n};\nuse core::{\n    convert::Infallible,\n    str::{FromStr, Utf8Error},\n};\n#[cfg(feature = \"std\")]\nuse std::{ffi::OsStr, path::Path};\n\nuse crate::flex::{FlexStr, RefCounted, RefCountedMut, partial_eq_impl, ref_counted_mut_impl};\n\nuse flexstr_support::StringToFromBytes;\n\n/// Local `str` type (NOTE: This can't be shared between threads)\npub type LocalStr = FlexStr<'static, str, Rc<str>>;\n\n/// Shared `str` type\npub type SharedStr = FlexStr<'static, str, Arc<str>>;\n\n/// Local `str` type that can optionally hold borrows (NOTE: This can't be shared between threads)\npub type LocalStrRef<'s> = FlexStr<'s, str, Rc<str>>;\n\n/// Shared `str` type that can optionally hold borrows\npub type SharedStrRef<'s> = FlexStr<'s, str, Arc<str>>;\n\nconst _: () = assert!(\n    size_of::<Option<LocalStr>>() <= size_of::<String>(),\n    \"Option<LocalStr> must be less than or equal to the size of String\"\n);\nconst _: () = assert!(\n    size_of::<Option<SharedStr>>() <= size_of::<String>(),\n    \"Option<SharedStr> must be less than or equal to the size of String\"\n);\n\n// *** RefCountedMut ***\n\nref_counted_mut_impl!(str);\n\n// *** From<String> ***\n\n// NOTE: Cannot be implemented generically because of impl<T> From<T> for T\nimpl<'s, R: RefCounted<str>> From<String> for FlexStr<'s, str, R> {\n    fn from(s: String) -> Self {\n        FlexStr::from_owned(s)\n    }\n}\n\n// *** TryFrom for FlexStr ***\n\nimpl<'s, R: RefCounted<str>> TryFrom<&'s [u8]> for FlexStr<'s, str, R> {\n    type Error = Utf8Error;\n\n    #[inline]\n    fn try_from(s: &'s [u8]) -> Result<Self, Self::Error> {\n        Ok(FlexStr::from_borrowed(str::from_utf8(s)?))\n    }\n}\n\n#[cfg(feature = \"std\")]\nimpl<'s, R: RefCounted<str>> TryFrom<&'s OsStr> for FlexStr<'s, str, R> {\n    type Error = Utf8Error;\n\n    #[inline]\n    fn try_from(s: &'s OsStr) -> Result<Self, Self::Error> {\n        Ok(FlexStr::from_borrowed(s.try_into()?))\n    }\n}\n\n#[cfg(feature = \"std\")]\nimpl<'s, R: RefCounted<str>> TryFrom<&'s Path> for FlexStr<'s, str, R> {\n    type Error = Utf8Error;\n\n    #[inline]\n    fn try_from(s: &'s Path) -> Result<Self, Self::Error> {\n        Ok(FlexStr::from_borrowed(s.as_os_str().try_into()?))\n    }\n}\n\nimpl<R: RefCounted<str>> TryFrom<Vec<u8>> for FlexStr<'static, str, R> {\n    type Error = FromUtf8Error;\n\n    #[inline]\n    fn try_from(s: Vec<u8>) -> Result<Self, Self::Error> {\n        Ok(FlexStr::from_owned(s.try_into()?))\n    }\n}\n\nimpl<R: RefCounted<str>> TryFrom<CString> for FlexStr<'static, str, R> {\n    type Error = IntoStringError;\n\n    #[inline]\n    fn try_from(s: CString) -> Result<Self, Self::Error> {\n        Ok(FlexStr::from_owned(s.try_into()?))\n    }\n}\n\n// *** PartialEq ***\n\npartial_eq_impl!(str, str);\npartial_eq_impl!(&str, str);\npartial_eq_impl!(String, str);\npartial_eq_impl!(Cow<'s, str>, str);\n\n// *** AsRef ***\n\nimpl<'s, S: ?Sized + StringToFromBytes, R: RefCounted<S>> AsRef<str> for FlexStr<'s, S, R>\nwhere\n    S: AsRef<str>,\n{\n    fn as_ref(&self) -> &str {\n        self.as_ref_type().as_ref()\n    }\n}\n\n// *** FromStr ***\n\nimpl<R: RefCounted<str>> FromStr for FlexStr<'static, str, R> {\n    type Err = Infallible;\n\n    fn from_str(s: &str) -> Result<Self, Self::Err> {\n        Ok(FlexStr::from_borrowed(s).into_owned())\n    }\n}\n\n// *** Prost ***\n\n#[cfg(feature = \"prost\")]\n#[allow(deprecated)] // DecodeError::new is deprecated in prost 0.14 with no public replacement yet\nimpl<R: RefCounted<str>> prost::Message for FlexStr<'static, str, R>\nwhere\n    Self: Default + Send + Sync,\n{\n    fn encode_raw(&self, buf: &mut impl prost::bytes::BufMut)\n    where\n        Self: Sized,\n    {\n        buf.put_slice(self.as_ref_type().as_bytes());\n    }\n\n    fn merge_field(\n        &mut self,\n        tag: u32,\n        wire_type: prost::encoding::WireType,\n        buf: &mut impl prost::bytes::Buf,\n        ctx: prost::encoding::DecodeContext,\n    ) -> Result<(), prost::DecodeError>\n    where\n        Self: Sized,\n    {\n        prost::encoding::skip_field(wire_type, tag, buf, ctx)\n    }\n\n    fn encoded_len(&self) -> usize {\n        self.as_ref_type().len()\n    }\n\n    fn clear(&mut self) {\n        *self = Default::default();\n    }\n\n    fn merge(&mut self, mut buf: impl prost::bytes::Buf) -> Result<(), prost::DecodeError>\n    where\n        Self: Sized,\n    {\n        let bytes = buf.copy_to_bytes(buf.remaining());\n        let s = core::str::from_utf8(&bytes)\n            .map_err(|_| prost::DecodeError::new(\"invalid UTF-8 in string field\"))?;\n        *self = FlexStr::from_borrowed(s).into_owned();\n        Ok(())\n    }\n\n    fn merge_length_delimited(\n        &mut self,\n        mut buf: impl prost::bytes::Buf,\n    ) -> Result<(), prost::DecodeError>\n    where\n        Self: Sized,\n    {\n        let len = prost::encoding::decode_varint(&mut buf)? as usize;\n        if buf.remaining() < len {\n            return Err(prost::DecodeError::new(\"buffer underflow\"));\n        }\n        self.merge(buf.take(len))\n    }\n}\n\n// *** SQLx ***\n\n#[cfg(feature = \"sqlx\")]\nimpl<'r, 's, DB: sqlx::Database, R: RefCounted<str>> sqlx::Decode<'r, DB> for FlexStr<'s, str, R>\nwhere\n    &'r str: sqlx::Decode<'r, DB>,\n{\n    fn decode(\n        value: <DB as sqlx::Database>::ValueRef<'r>,\n    ) -> Result<Self, sqlx::error::BoxDynError> {\n        let value = <&str as sqlx::Decode<DB>>::decode(value)?;\n        let s: FlexStr<'_, str, R> = value.into();\n        Ok(s.into_owned())\n    }\n}\n\n#[cfg(feature = \"sqlx\")]\nimpl<'r, 's, DB: sqlx::Database, R: RefCounted<str>> sqlx::Encode<'r, DB> for FlexStr<'s, str, R>\nwhere\n    String: sqlx::Encode<'r, DB>,\n{\n    fn encode_by_ref(\n        &self,\n        buf: &mut <DB as sqlx::Database>::ArgumentBuffer<'r>,\n    ) -> Result<sqlx::encode::IsNull, sqlx::error::BoxDynError> {\n        // There might be a more efficient way to do this (or not?), but the lifetimes seem to be constraining\n        // us to using an owned type here. Works at the cost of an allocation/copy.\n        <String as sqlx::Encode<'r, DB>>::encode(self.to_string(), buf)\n    }\n\n    fn encode(\n        self,\n        buf: &mut <DB as sqlx::Database>::ArgumentBuffer<'r>,\n    ) -> Result<sqlx::encode::IsNull, sqlx::error::BoxDynError>\n    where\n        Self: Sized,\n    {\n        use flexstr_support::StringLike as _;\n\n        // This won't allocate IF this is a boxed string\n        <String as sqlx::Encode<'r, DB>>::encode(self.into_string(), buf)\n    }\n\n    fn size_hint(&self) -> usize {\n        self.len()\n    }\n}\n\n#[cfg(feature = \"sqlx\")]\nimpl<'s, DB: sqlx::Database, R: RefCounted<str>> sqlx::Type<DB> for FlexStr<'s, str, R>\nwhere\n    str: sqlx::Type<DB>,\n{\n    fn type_info() -> <DB as sqlx::Database>::TypeInfo {\n        <str as sqlx::Type<DB>>::type_info()\n    }\n\n    fn compatible(ty: &<DB as sqlx::Database>::TypeInfo) -> bool {\n        <str as sqlx::Type<DB>>::compatible(ty)\n    }\n}\n\n#[cfg(all(feature = \"sqlx\", feature = \"sqlx_pg_arrays\"))]\nimpl<'s, R: RefCounted<str>> sqlx::postgres::PgHasArrayType for FlexStr<'s, str, R>\nwhere\n    for<'a> &'a str: sqlx::postgres::PgHasArrayType,\n{\n    fn array_type_info() -> sqlx::postgres::PgTypeInfo {\n        <&str as sqlx::postgres::PgHasArrayType>::array_type_info()\n    }\n\n    fn array_compatible(ty: &sqlx::postgres::PgTypeInfo) -> bool {\n        <&str as sqlx::postgres::PgHasArrayType>::array_compatible(ty)\n    }\n}\n\n// *** Utoipa ***\n\n#[cfg(feature = \"utoipa\")]\nimpl<'s, R: RefCounted<str>> utoipa::PartialSchema for FlexStr<'s, str, R> {\n    fn schema() -> utoipa::openapi::RefOr<utoipa::openapi::schema::Schema> {\n        utoipa::openapi::schema::ObjectBuilder::new()\n            .schema_type(utoipa::openapi::schema::SchemaType::new(\n                utoipa::openapi::schema::Type::String,\n            ))\n            .into()\n    }\n}\n\n#[cfg(feature = \"utoipa\")]\nimpl<'s, R: RefCounted<str>> utoipa::ToSchema for FlexStr<'s, str, R> {\n    fn name() -> Cow<'static, str> {\n        Cow::Borrowed(\"String\")\n    }\n}\n"
  },
  {
    "path": "tests/common/as_ref.rs",
    "content": "#![allow(dead_code)]\n\nuse flexstr::{FlexStr, RefCounted};\n\n/// Test AsRef<[u8]> for FlexStr<[u8], R>\n#[cfg(feature = \"bytes\")]\npub fn test_as_ref_bytes_flex_str<R>(s: &'static [u8])\nwhere\n    R: RefCounted<[u8]>,\n{\n    let flex_str: FlexStr<'_, [u8], R> = FlexStr::from_borrowed(s);\n    let bytes_ref: &[u8] = flex_str.as_ref();\n    assert_eq!(bytes_ref, s);\n}\n\n/// Test AsRef<OsStr> for FlexStr<OsStr, R>\n#[cfg(all(feature = \"std\", feature = \"osstr\"))]\npub fn test_as_ref_osstr_flex_str<R>(s: &'static std::ffi::OsStr)\nwhere\n    R: RefCounted<std::ffi::OsStr>,\n{\n    let flex_str: FlexStr<'_, std::ffi::OsStr, R> = FlexStr::from_borrowed(s);\n    let os_str_ref: &std::ffi::OsStr = flex_str.as_ref();\n    assert_eq!(os_str_ref, s);\n}\n\n/// Test AsRef<Path> for FlexStr<Path, R>\n#[cfg(all(feature = \"std\", feature = \"path\"))]\npub fn test_as_ref_path_flex_str<R>(s: &'static std::path::Path)\nwhere\n    R: RefCounted<std::path::Path>,\n{\n    let flex_str: FlexStr<'_, std::path::Path, R> = FlexStr::from_borrowed(s);\n    let path_ref: &std::path::Path = flex_str.as_ref();\n    assert_eq!(path_ref, s);\n}\n\n/// Test AsRef<CStr> for FlexStr<CStr, R>\n#[cfg(feature = \"cstr\")]\npub fn test_as_ref_cstr_flex_str<R>(s: &'static core::ffi::CStr)\nwhere\n    R: RefCounted<core::ffi::CStr>,\n{\n    let flex_str: FlexStr<'_, core::ffi::CStr, R> = FlexStr::from_borrowed(s);\n    let cstr_ref: &core::ffi::CStr = flex_str.as_ref();\n    assert_eq!(cstr_ref.to_bytes(), s.to_bytes());\n}\n\n/// Test AsRef<str> for FlexStr<str, R>\n#[cfg(feature = \"str\")]\npub fn test_as_ref_str_flex_str<R>(s: &'static str)\nwhere\n    R: RefCounted<str>,\n{\n    let flex_str: FlexStr<'_, str, R> = FlexStr::from_borrowed(s);\n    let str_ref: &str = flex_str.as_ref();\n    assert_eq!(str_ref, s);\n}\n"
  },
  {
    "path": "tests/common/basic.rs",
    "content": "#![allow(dead_code)]\n\nuse core::fmt;\nuse flexstr::{FlexStr, RefCounted, StringLike};\nuse flexstr_support::StringToFromBytes;\nuse inline_flexstr::InlineFlexStr;\n\n/// Test creation from borrowed string\npub fn test_creation_from_borrowed<S, R>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n    R: RefCounted<S>,\n{\n    let flex_str: FlexStr<'_, S, R> = FlexStr::from_borrowed(s);\n    assert!(flex_str.is_borrowed());\n    assert_eq!(flex_str.as_ref_type(), s);\n}\n\n/// Test creation from owned string\npub fn test_creation_from_owned<S, R>(owned: S::Owned)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n    R: RefCounted<S>,\n    Box<S>: From<S::Owned>,\n    S::Owned: AsRef<S>,\n{\n    let flex_str: FlexStr<'static, S, R> = FlexStr::from_owned(owned.as_ref().to_owned());\n    assert!(flex_str.is_boxed());\n    assert_eq!(flex_str.as_ref_type(), owned.as_ref());\n}\n\n/// Test creation from inline string\npub fn test_creation_from_inline<S, R>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n    R: RefCounted<S>,\n{\n    let inline_str = InlineFlexStr::try_from_type(s).unwrap();\n    let flex_str: FlexStr<'_, S, R> = FlexStr::from_inline(inline_str);\n    assert!(flex_str.is_inlined());\n    assert_eq!(flex_str.as_ref_type(), s);\n}\n\n/// Test creation from reference counted string\npub fn test_creation_from_ref_counted<S, R>(s: R)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n    R: RefCounted<S>,\n{\n    let flex_str: FlexStr<'_, S, R> = FlexStr::from_ref_counted(s.clone());\n    assert!(flex_str.is_ref_counted());\n    assert_eq!(flex_str.as_ref_type(), &*s);\n}\n\n/// Test creation from boxed string\npub fn test_creation_from_boxed<S, R>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n    R: RefCounted<S>,\n    Box<S>: From<S::Owned>,\n    S::Owned: AsRef<S>,\n{\n    let boxed = Box::from(s.to_owned());\n    let flex_str: FlexStr<'_, S, R> = FlexStr::from_boxed(boxed);\n    assert!(flex_str.is_boxed());\n    assert_eq!(flex_str.as_ref_type(), s);\n}\n\n/// Test empty string creation\npub fn test_empty<S, R>(empty: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes,\n    R: RefCounted<S>,\n    FlexStr<'static, S, R>: StringLike<S>,\n{\n    let flex_str: FlexStr<'_, S, R> = FlexStr::from_borrowed(empty);\n    assert!(flex_str.is_borrowed());\n    assert!(StringLike::is_empty(&flex_str));\n    assert_eq!(StringLike::len(&flex_str), 0);\n}\n\n/// Test accessor methods\npub fn test_accessors<S, R>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n    R: RefCounted<S>,\n    FlexStr<'static, S, R>: StringLike<S>,\n{\n    let flex_str: FlexStr<'_, S, R> = FlexStr::from_borrowed(s);\n\n    // Test as_ref_type\n    assert_eq!(flex_str.as_ref_type(), s);\n\n    // Test as_bytes\n    let bytes = flex_str.as_bytes();\n    assert_eq!(bytes, S::self_as_bytes(s));\n\n    // Test as_raw_bytes\n    let raw_bytes = flex_str.as_raw_bytes();\n    assert_eq!(raw_bytes, S::self_as_raw_bytes(s));\n\n    // Test len\n    assert_eq!(StringLike::len(&flex_str), s.self_as_bytes().len());\n\n    // Test is_empty\n    assert_eq!(\n        StringLike::is_empty(&flex_str),\n        s.self_as_bytes().is_empty()\n    );\n}\n\n/// Test cloning for all variants\npub fn test_clone_all_variants<S, R>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + PartialEq + fmt::Debug,\n    R: RefCounted<S> + fmt::Debug,\n    Box<S>: From<S::Owned>,\n    S::Owned: AsRef<S>,\n{\n    // Test clone for borrowed\n    let borrowed: FlexStr<'_, S, R> = FlexStr::from_borrowed(s);\n    let cloned = borrowed.clone();\n    assert_eq!(borrowed, cloned);\n\n    // Test clone for inlined (input should be small enough to inline)\n    let inline_str =\n        InlineFlexStr::try_from_type(s).expect(\"test input should be small enough to inline\");\n    let inlined: FlexStr<'_, S, R> = FlexStr::from_inline(inline_str);\n    let cloned = inlined.clone();\n    assert_eq!(inlined, cloned);\n\n    // Test clone for ref counted\n    let rc: R = s.into();\n    let ref_counted: FlexStr<'_, S, R> = FlexStr::from_ref_counted(rc.clone());\n    let cloned = ref_counted.clone();\n    assert_eq!(ref_counted, cloned);\n\n    // Test clone for boxed\n    let boxed: FlexStr<'_, S, R> = FlexStr::from_boxed(Box::from(s.to_owned()));\n    let cloned = boxed.clone();\n    assert_eq!(boxed, cloned);\n}\n\n/// Test Default implementation\n/// Note: This test is only applicable for types where `&S: Default`\npub fn test_default<S, R>()\nwhere\n    S: ?Sized + StringToFromBytes,\n    R: RefCounted<S>,\n    for<'a> &'a S: Default,\n    FlexStr<'static, S, R>: StringLike<S>,\n{\n    let flex_str = FlexStr::default();\n    assert!(flex_str.is_borrowed());\n    assert!(StringLike::is_empty(&flex_str));\n}\n"
  },
  {
    "path": "tests/common/borrow.rs",
    "content": "#![allow(dead_code)]\n\nuse core::borrow::Borrow;\nuse flexstr::{FlexStr, RefCounted};\nuse flexstr_support::StringToFromBytes;\n\n/// Test Borrow implementation for FlexStr\npub fn test_borrow<S, R>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes,\n    R: RefCounted<S>,\n{\n    let flex_str: FlexStr<'_, S, R> = FlexStr::from_borrowed(s);\n\n    // Test Borrow::borrow() returns &S\n    let borrowed: &S = flex_str.borrow();\n    assert_eq!(borrowed as *const S, s as *const S);\n}\n"
  },
  {
    "path": "tests/common/comparison.rs",
    "content": "#![allow(dead_code)]\n\nuse core::fmt;\nuse flexstr::{FlexStr, RefCounted};\nuse flexstr_support::StringToFromBytes;\nuse inline_flexstr::InlineFlexStr;\n\n// Remove Debug requirement from R where not needed\n\n/// Test PartialEq implementation\npub fn test_partial_eq<S, R>(s1: &'static S, s2: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + PartialEq + fmt::Debug,\n    R: RefCounted<S> + fmt::Debug,\n    Box<S>: From<S::Owned>,\n    S::Owned: AsRef<S>,\n{\n    let flex_str1: FlexStr<'_, S, R> = FlexStr::from_borrowed(s1);\n    let flex_str2: FlexStr<'_, S, R> = FlexStr::from_borrowed(s2);\n\n    // Test equality\n    if s1 == s2 {\n        assert_eq!(flex_str1, flex_str2);\n    } else {\n        assert!(flex_str1 != flex_str2);\n    }\n\n    // Test equality across variants (input should be small enough to inline)\n    let inline_str =\n        InlineFlexStr::try_from_type(s1).expect(\"test input should be small enough to inline\");\n    let inlined: FlexStr<'_, S, R> = FlexStr::from_inline(inline_str);\n    assert_eq!(flex_str1, inlined);\n}\n\n/// Test Eq implementation\npub fn test_eq<S, R>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + PartialEq + Eq + fmt::Debug,\n    R: RefCounted<S> + fmt::Debug,\n    Box<S>: From<S::Owned>,\n    S::Owned: AsRef<S>,\n{\n    let flex_str1: FlexStr<'_, S, R> = FlexStr::from_borrowed(s);\n    let flex_str2: FlexStr<'_, S, R> = FlexStr::from_borrowed(s);\n\n    // Eq requires reflexivity, symmetry, transitivity\n    // Reflexivity: a == a\n    assert_eq!(flex_str1, flex_str2); // Symmetry\n    assert_eq!(flex_str2, flex_str1); // Symmetry\n}\n\n/// Test PartialOrd implementation\npub fn test_partial_ord<S, R>(s1: &'static S, s2: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + PartialOrd,\n    R: RefCounted<S>,\n{\n    let flex_str1: FlexStr<'_, S, R> = FlexStr::from_borrowed(s1);\n    let flex_str2: FlexStr<'_, S, R> = FlexStr::from_borrowed(s2);\n\n    // Test inputs should be comparable (partial_cmp should return Some)\n    let ord = s1\n        .partial_cmp(s2)\n        .expect(\"test inputs should be comparable\");\n    assert_eq!(flex_str1.partial_cmp(&flex_str2), Some(ord));\n}\n\n/// Test Ord implementation\npub fn test_ord<S, R>(s1: &'static S, s2: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + Ord,\n    R: RefCounted<S>,\n{\n    let flex_str1: FlexStr<'_, S, R> = FlexStr::from_borrowed(s1);\n    let flex_str2: FlexStr<'_, S, R> = FlexStr::from_borrowed(s2);\n\n    assert_eq!(flex_str1.cmp(&flex_str2), s1.cmp(s2));\n}\n\n/// Test Hash implementation consistency\npub fn test_hash<S, R>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + core::hash::Hash,\n    R: RefCounted<S>,\n    Box<S>: From<S::Owned>,\n    S::Owned: AsRef<S>,\n{\n    use core::hash::{Hash, Hasher};\n    use std::collections::hash_map::DefaultHasher;\n\n    // Test that different variants hash to the same value\n    let borrowed: FlexStr<'_, S, R> = FlexStr::from_borrowed(s);\n    let mut hasher1 = DefaultHasher::new();\n    borrowed.hash(&mut hasher1);\n    let hash1 = hasher1.finish();\n\n    // Input should be small enough to inline\n    let inline_str =\n        InlineFlexStr::try_from_type(s).expect(\"test input should be small enough to inline\");\n    let inlined: FlexStr<'_, S, R> = FlexStr::from_inline(inline_str);\n    let mut hasher2 = DefaultHasher::new();\n    inlined.hash(&mut hasher2);\n    let hash2 = hasher2.finish();\n    assert_eq!(hash1, hash2);\n\n    // Test that ref_counted variant hashes the same\n    // Test input should be non-empty\n    assert!(\n        !s.self_as_bytes().is_empty(),\n        \"test input should be non-empty\"\n    );\n    let rc: R = s.into();\n    let ref_counted: FlexStr<'_, S, R> = FlexStr::from_ref_counted(rc);\n    let mut hasher3 = DefaultHasher::new();\n    ref_counted.hash(&mut hasher3);\n    let hash3 = hasher3.finish();\n    assert_eq!(hash1, hash3);\n}\n\n/// Test comparison with &S\npub fn test_comparison_with_ref<S, R>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n    R: RefCounted<S>,\n{\n    let flex_str: FlexStr<'_, S, R> = FlexStr::from_borrowed(s);\n\n    // Test equality with &S - compare through as_ref_type\n    assert_eq!(flex_str.as_ref_type(), s);\n}\n\n/// Test comparison with S::Owned\npub fn test_comparison_with_owned<S, R>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n    R: RefCounted<S>,\n    S::Owned: PartialEq + AsRef<S>,\n{\n    let flex_str: FlexStr<'_, S, R> = FlexStr::from_borrowed(s);\n    let owned = s.to_owned();\n\n    assert_eq!(flex_str.as_ref_type(), owned.as_ref());\n}\n\n/// Test comparison with InlineFlexStr\npub fn test_comparison_with_inline<S, R>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n    R: RefCounted<S>,\n{\n    // Input should be small enough to inline\n    let inline_str =\n        InlineFlexStr::try_from_type(s).expect(\"test input should be small enough to inline\");\n    let flex_str: FlexStr<'_, S, R> = FlexStr::from_borrowed(s);\n\n    assert_eq!(flex_str.as_ref_type(), inline_str.as_ref_type());\n}\n\n/// Test PartialEq with owned types (String, Cow, etc.) for FlexStr\npub fn test_partial_eq_with_owned_types<S, R>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + PartialEq + fmt::Debug,\n    R: RefCounted<S> + fmt::Debug,\n    S::Owned: PartialEq<S> + AsRef<S>,\n    Box<S>: From<S::Owned>,\n{\n    use alloc::borrow::Cow;\n\n    let flex_str: FlexStr<'_, S, R> = FlexStr::from_borrowed(s);\n    let owned: S::Owned = s.to_owned();\n\n    // Test FlexStr == S::Owned (through PartialEq implementation)\n    assert_eq!(flex_str.as_ref_type(), owned.as_ref());\n    // Test reverse comparison: S::Owned == FlexStr\n    assert_eq!(owned.as_ref(), flex_str.as_ref_type());\n\n    // Test with Cow::Owned\n    let cow_owned: Cow<'_, S> = Cow::Owned(owned);\n    assert_eq!(flex_str.as_ref_type(), cow_owned.as_ref());\n    assert_eq!(cow_owned.as_ref(), flex_str.as_ref_type());\n\n    // Test with Cow::Borrowed\n    let cow_borrowed: Cow<'_, S> = Cow::Borrowed(s);\n    assert_eq!(flex_str.as_ref_type(), cow_borrowed.as_ref());\n    assert_eq!(cow_borrowed.as_ref(), flex_str.as_ref_type());\n}\n"
  },
  {
    "path": "tests/common/conversion.rs",
    "content": "#![allow(dead_code)]\n\nuse core::fmt;\nuse flexstr::{FlexStr, RefCounted, StringLike};\nuse flexstr_support::StringToFromBytes;\nuse inline_flexstr::InlineFlexStr;\n\n/// Test to_owned conversion\npub fn test_to_owned<S, R>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n    R: RefCounted<S>,\n    Box<S>: From<S::Owned>,\n    S::Owned: AsRef<S>,\n{\n    let borrowed: FlexStr<'_, S, R> = FlexStr::from_borrowed(s);\n    let owned = borrowed.to_owned();\n    assert_eq!(owned.as_ref_type(), s);\n    assert!(matches!(\n        owned,\n        FlexStr::Inlined(_) | FlexStr::RefCounted(_)\n    ));\n}\n\n/// Test into_owned conversion\npub fn test_into_owned<S, R>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n    R: RefCounted<S>,\n    Box<S>: From<S::Owned>,\n    S::Owned: AsRef<S>,\n{\n    let borrowed: FlexStr<'_, S, R> = FlexStr::from_borrowed(s);\n    let owned = borrowed.into_owned();\n    assert_eq!(owned.as_ref_type(), s);\n    assert!(!owned.is_borrowed());\n}\n\n/// Test to_owned_type conversion\npub fn test_to_owned_type<S, R>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n    R: RefCounted<S>,\n    S::Owned: PartialEq + AsRef<S>,\n    FlexStr<'static, S, R>: StringLike<S>,\n{\n    let flex_str: FlexStr<'_, S, R> = FlexStr::from_borrowed(s);\n    let owned = StringLike::to_owned_type(&flex_str);\n    assert_eq!(owned.as_ref(), s);\n}\n\n/// Test into_owned_type conversion\npub fn test_into_owned_type<S, R>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + PartialEq + fmt::Debug,\n    R: RefCounted<S>,\n    Box<S>: From<S::Owned>,\n    S::Owned: PartialEq + AsRef<S> + From<Box<S>>,\n    FlexStr<'static, S, R>: StringLike<S>,\n{\n    let flex_str: FlexStr<'_, S, R> = FlexStr::from_borrowed(s);\n    let owned = StringLike::into_owned_type(flex_str);\n    assert_eq!(owned.as_ref(), s);\n}\n\n/// Test to_local conversion (from Shared to Local)\npub fn test_to_local<S>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n    alloc::sync::Arc<S>: for<'a> From<&'a S>,\n    alloc::rc::Rc<S>: for<'a> From<&'a S>,\n{\n    use alloc::sync::Arc;\n\n    let shared: FlexStr<'_, S, Arc<S>> = FlexStr::from_borrowed(s);\n    let local = shared.to_local();\n    assert_eq!(local.as_ref_type(), s);\n    assert!(local.is_borrowed() || local.is_inlined() || local.is_ref_counted());\n}\n\n/// Test into_local conversion (from Shared to Local)\npub fn test_into_local<S>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n    alloc::sync::Arc<S>: for<'a> From<&'a S>,\n    alloc::rc::Rc<S>: for<'a> From<&'a S>,\n{\n    use alloc::sync::Arc;\n\n    let shared: FlexStr<'_, S, Arc<S>> = FlexStr::from_borrowed(s);\n    let local = shared.into_local();\n    assert_eq!(local.as_ref_type(), s);\n}\n\n/// Test to_shared conversion (from Local to Shared)\npub fn test_to_shared<S>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n    alloc::sync::Arc<S>: for<'a> From<&'a S>,\n    alloc::rc::Rc<S>: for<'a> From<&'a S>,\n{\n    use alloc::rc::Rc;\n\n    let local: FlexStr<'_, S, Rc<S>> = FlexStr::from_borrowed(s);\n    let shared = local.to_shared();\n    assert_eq!(shared.as_ref_type(), s);\n    assert!(shared.is_borrowed() || shared.is_inlined() || shared.is_ref_counted());\n}\n\n/// Test into_shared conversion (from Local to Shared)\npub fn test_into_shared<S>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n    alloc::sync::Arc<S>: for<'a> From<&'a S>,\n    alloc::rc::Rc<S>: for<'a> From<&'a S>,\n{\n    use alloc::rc::Rc;\n\n    let local: FlexStr<'_, S, Rc<S>> = FlexStr::from_borrowed(s);\n    let shared = local.into_shared();\n    assert_eq!(shared.as_ref_type(), s);\n}\n\n/// Test optimize method\npub fn test_optimize<S, R>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n    R: RefCounted<S>,\n    Box<S>: From<S::Owned>,\n    S::Owned: AsRef<S>,\n{\n    // Test optimize on boxed (should convert to inlined or ref_counted)\n    let boxed: FlexStr<'_, S, R> = FlexStr::from_boxed(Box::from(s.to_owned()));\n    let optimized = boxed.optimize();\n    assert_eq!(optimized.as_ref_type(), s);\n    assert!(matches!(\n        optimized,\n        FlexStr::Inlined(_) | FlexStr::RefCounted(_)\n    ));\n\n    // Test optimize on borrowed (should stay borrowed)\n    let borrowed: FlexStr<'_, S, R> = FlexStr::from_borrowed(s);\n    let optimized = borrowed.optimize();\n    assert_eq!(optimized.as_ref_type(), s);\n    assert!(optimized.is_borrowed());\n}\n\n/// Test From<&S> implementation\npub fn test_from_borrowed_ref<S, R>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n    R: RefCounted<S>,\n{\n    let flex_str: FlexStr<'_, S, R> = s.into();\n    assert!(flex_str.is_borrowed());\n    assert_eq!(flex_str.as_ref_type(), s);\n}\n\n/// Test From<Box<S>> implementation\npub fn test_from_box<S, R>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n    R: RefCounted<S>,\n    Box<S>: From<S::Owned>,\n    S::Owned: AsRef<S>,\n{\n    let boxed = Box::from(s.to_owned());\n    let flex_str: FlexStr<'_, S, R> = boxed.into();\n    assert!(flex_str.is_boxed());\n    assert_eq!(flex_str.as_ref_type(), s);\n}\n\n/// Test From<InlineFlexStr> implementation\npub fn test_from_inline_flex_str<S, R>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n    R: RefCounted<S>,\n{\n    // Input should be small enough to inline\n    let inline_str =\n        InlineFlexStr::try_from_type(s).expect(\"test input should be small enough to inline\");\n    let flex_str: FlexStr<'_, S, R> = inline_str.into();\n    assert!(flex_str.is_inlined());\n    assert_eq!(flex_str.as_ref_type(), s);\n}\n\n/// Test From<Cow> implementation\npub fn test_from_cow<S, R>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n    R: RefCounted<S>,\n    Box<S>: From<S::Owned>,\n    S::Owned: AsRef<S>,\n{\n    use alloc::borrow::Cow;\n\n    // Test Cow::Borrowed\n    let cow: Cow<'_, S> = Cow::Borrowed(s);\n    let flex_str: FlexStr<'_, S, R> = cow.into();\n    assert!(flex_str.is_borrowed());\n    assert_eq!(flex_str.as_ref_type(), s);\n\n    // Test Cow::Owned\n    let cow: Cow<'_, S> = Cow::Owned(s.to_owned());\n    let flex_str: FlexStr<'_, S, R> = cow.into();\n    assert!(flex_str.is_boxed());\n    assert_eq!(flex_str.as_ref_type(), s);\n}\n"
  },
  {
    "path": "tests/common/cstr_specific.rs",
    "content": "#![allow(dead_code)]\n\nuse core::ffi::CStr;\nuse flexstr::{FlexStr, RefCounted};\n\n/// Test try_from_bytes_with_or_without_nul with valid CStr (with NUL)\npub fn test_try_from_bytes_with_nul<R>()\nwhere\n    R: RefCounted<CStr>,\n{\n    let bytes = b\"test\\0\";\n    let flex_str = FlexStr::<'_, CStr, R>::try_from_bytes_with_or_without_nul(bytes).unwrap();\n    assert_eq!(flex_str.as_ref_type(), c\"test\");\n}\n\n/// Test try_from_bytes_with_or_without_nul with bytes without NUL\npub fn test_try_from_bytes_without_nul<R>()\nwhere\n    R: RefCounted<CStr>,\n{\n    let bytes = b\"test\";\n    let flex_str = FlexStr::<'_, CStr, R>::try_from_bytes_with_or_without_nul(bytes).unwrap();\n    // Should have NUL appended\n    assert_eq!(flex_str.as_bytes_with_nul(), b\"test\\0\");\n}\n\n/// Test try_from_bytes_with_or_without_nul with interior NUL\npub fn test_try_from_bytes_interior_nul<R>()\nwhere\n    R: RefCounted<CStr> + core::fmt::Debug,\n{\n    let bytes = b\"te\\0st\";\n    let err = FlexStr::<'_, CStr, R>::try_from_bytes_with_or_without_nul(bytes).unwrap_err();\n    assert_eq!(err.position, 2);\n}\n\n/// Test as_bytes_with_nul\npub fn test_as_bytes_with_nul<R>(cstr: &'static CStr)\nwhere\n    R: RefCounted<CStr>,\n{\n    let flex_str: FlexStr<'_, CStr, R> = FlexStr::from_borrowed(cstr);\n    let bytes = flex_str.as_bytes_with_nul();\n    assert_eq!(bytes, cstr.to_bytes_with_nul());\n}\n"
  },
  {
    "path": "tests/common/display.rs",
    "content": "#![allow(dead_code)]\n\nuse core::fmt;\nuse flexstr::{FlexStr, RefCounted};\nuse flexstr_support::StringToFromBytes;\n\n/// Test Display implementation for FlexStr\npub fn test_display<S, R>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Display + fmt::Debug,\n    R: RefCounted<S>,\n{\n    let flex_str: FlexStr<'_, S, R> = FlexStr::from_borrowed(s);\n\n    // Format both the original and FlexStr\n    let original_fmt = format!(\"{}\", s);\n    let flex_fmt = format!(\"{}\", flex_str);\n\n    assert_eq!(original_fmt, flex_fmt);\n}\n"
  },
  {
    "path": "tests/common/edge_cases.rs",
    "content": "#![allow(dead_code)]\n\nuse core::fmt;\nuse flexstr::{FlexStr, RefCounted, StringLike};\nuse flexstr_support::StringToFromBytes;\nuse inline_flexstr::{INLINE_CAPACITY, InlineFlexStr, TooLongForInlining};\n\n/// Test empty string operations\npub fn test_empty_string<S, R>(empty: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + PartialEq + fmt::Debug,\n    R: RefCounted<S> + fmt::Debug,\n    FlexStr<'static, S, R>: StringLike<S>,\n    Box<S>: From<S::Owned>,\n    S::Owned: AsRef<S>,\n{\n    let flex_str: FlexStr<'_, S, R> = FlexStr::from_borrowed(empty);\n\n    assert!(StringLike::is_empty(&flex_str));\n    assert_eq!(StringLike::len(&flex_str), 0);\n    assert!(flex_str.is_borrowed());\n\n    // Test empty string can be cloned\n    let cloned = flex_str.clone();\n    assert_eq!(flex_str, cloned);\n\n    // Test empty string can be converted to owned\n    let owned = flex_str.to_owned();\n    assert_eq!(owned.as_ref_type(), empty);\n    assert!(StringLike::is_empty(&owned));\n}\n\n/// Test capacity boundary - string at exact capacity\n/// Input must be exactly at INLINE_CAPACITY\npub fn test_capacity_boundary_exact<S, R>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n    R: RefCounted<S>,\n{\n    let bytes = s.self_as_raw_bytes();\n    assert_eq!(\n        bytes.len(),\n        INLINE_CAPACITY,\n        \"test input must be exactly at capacity\"\n    );\n\n    let inline_str =\n        InlineFlexStr::try_from_type(s).expect(\"string at exact capacity should inline\");\n    let flex_str: FlexStr<'_, S, R> = FlexStr::from_inline(inline_str);\n    assert!(flex_str.is_inlined());\n    assert_eq!(flex_str.as_ref_type(), s);\n}\n\n/// Test capacity boundary - string one byte over capacity\n/// Input must be smaller than INLINE_CAPACITY\npub fn test_capacity_boundary_overflow<S>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n{\n    let bytes = s.self_as_raw_bytes();\n    assert!(\n        bytes.len() < INLINE_CAPACITY,\n        \"test input must be smaller than capacity\"\n    );\n\n    // Since bytes.len() < INLINE_CAPACITY, bytes.len() <= INLINE_CAPACITY is always true\n    // So try_from_type should always succeed\n    let _inline_str =\n        InlineFlexStr::try_from_type(s).expect(\"string smaller than capacity should succeed\");\n}\n\n/// Test TryFrom error cases - too long\n// Type parameter intentionally unused - kept for API consistency with other test functions\n#[allow(unused)]\npub fn test_try_from_too_long() {\n    // Create a string that's definitely too long\n    // This is tricky to do generically, so we'll test the error type\n    let _long_bytes = [0u8; INLINE_CAPACITY + 1];\n\n    // Try to create from bytes if possible\n    // This will depend on the specific string type\n    // For now, we'll just verify the error type exists\n    let err = TooLongForInlining {\n        length: INLINE_CAPACITY + 1,\n        inline_capacity: INLINE_CAPACITY,\n    };\n\n    assert_eq!(err.length, INLINE_CAPACITY + 1);\n    assert_eq!(err.inline_capacity, INLINE_CAPACITY);\n}\n\n/// Test various string lengths\npub fn test_various_lengths<S, R>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + PartialEq + fmt::Debug,\n    R: RefCounted<S>,\n    FlexStr<'static, S, R>: StringLike<S>,\n{\n    let bytes = s.self_as_bytes();\n    let len = bytes.len();\n\n    let flex_str: FlexStr<'_, S, R> = FlexStr::from_borrowed(s);\n\n    // Test length matches\n    assert_eq!(StringLike::len(&flex_str), len);\n\n    // Test empty check\n    assert_eq!(StringLike::is_empty(&flex_str), len == 0);\n\n    // Test that we can always create a borrowed variant\n    assert!(flex_str.is_borrowed());\n\n    // Test that we can convert to owned regardless of length\n    let owned = flex_str.to_owned();\n    assert_eq!(StringLike::len(&owned), len);\n    assert_eq!(owned.as_ref_type(), s);\n}\n\n/// Test special content (if applicable)\npub fn test_special_content<S, R>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + PartialEq,\n    R: RefCounted<S>,\n{\n    let flex_str: FlexStr<'_, S, R> = FlexStr::from_borrowed(s);\n\n    // Test that special characters/content are preserved\n    let bytes = flex_str.as_bytes();\n    assert_eq!(bytes, s.self_as_bytes());\n\n    // Test that raw bytes match\n    let raw_bytes = flex_str.as_raw_bytes();\n    assert_eq!(raw_bytes, s.self_as_raw_bytes());\n\n    // Test conversion preserves content\n    let owned = flex_str.to_owned();\n    assert_eq!(owned.as_bytes(), bytes);\n    assert_eq!(owned.as_raw_bytes(), raw_bytes);\n}\n\n/// Test clone with different variants\npub fn test_clone_variants<S, R>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + PartialEq + fmt::Debug,\n    R: RefCounted<S> + fmt::Debug,\n    Box<S>: From<S::Owned>,\n    S::Owned: AsRef<S>,\n{\n    // Test clone of borrowed\n    let borrowed: FlexStr<'_, S, R> = FlexStr::from_borrowed(s);\n    let cloned = borrowed.clone();\n    assert_eq!(borrowed, cloned);\n\n    // Test clone of inlined (input should be small enough to inline)\n    let inline_str =\n        InlineFlexStr::try_from_type(s).expect(\"test input should be small enough to inline\");\n    let inlined: FlexStr<'_, S, R> = FlexStr::from_inline(inline_str);\n    let cloned = inlined.clone();\n    assert_eq!(inlined, cloned);\n\n    // Test clone of ref_counted\n    let rc: R = s.into();\n    let ref_counted: FlexStr<'_, S, R> = FlexStr::from_ref_counted(rc.clone());\n    let cloned = ref_counted.clone();\n    assert_eq!(ref_counted, cloned);\n\n    // Test clone of boxed\n    let boxed: FlexStr<'_, S, R> = FlexStr::from_boxed(Box::from(s.to_owned()));\n    let cloned = boxed.clone();\n    assert!(matches!(\n        cloned,\n        FlexStr::Inlined(_) | FlexStr::RefCounted(_)\n    ));\n    assert_eq!(boxed, cloned);\n}\n"
  },
  {
    "path": "tests/common/errors.rs",
    "content": "#![allow(dead_code)]\n\nuse core::fmt;\nuse inline_flexstr::TooLongForInlining;\n\n#[cfg(feature = \"str\")]\nuse inline_flexstr::TooLongOrUtf8Error;\n\n#[cfg(feature = \"cstr\")]\nuse flexstr::InteriorNulError;\n#[cfg(feature = \"cstr\")]\nuse inline_flexstr::TooLongOrNulError;\n\n/// Test Display implementation for error types\npub fn test_error_display<E>(error: E)\nwhere\n    E: fmt::Display + fmt::Debug,\n{\n    let display_str = format!(\"{}\", error);\n    let debug_str = format!(\"{:?}\", error);\n\n    // Display should produce a non-empty string\n    assert!(!display_str.is_empty());\n    // Debug should also produce a non-empty string\n    assert!(!debug_str.is_empty());\n}\n\n/// Test TooLongForInlining error\npub fn test_too_long_for_inlining() {\n    let err = TooLongForInlining {\n        length: 100,\n        inline_capacity: 30,\n    };\n\n    // Test that the error message contains relevant information\n    let msg = format!(\"{}\", err);\n    assert!(msg.contains(\"too long\"));\n    assert!(msg.contains(\"100\"));\n    assert!(msg.contains(\"30\"));\n\n    test_error_display(err);\n}\n\n/// Test TooLongOrUtf8Error::TooLong variant\n#[cfg(feature = \"str\")]\npub fn test_too_long_or_utf8_error_too_long() {\n    let err = TooLongOrUtf8Error::TooLong(TooLongForInlining {\n        length: 100,\n        inline_capacity: 30,\n    });\n\n    test_error_display(err);\n}\n\n/// Test TooLongOrUtf8Error::Utf8Error variant\n#[cfg(feature = \"str\")]\npub fn test_too_long_or_utf8_error_utf8() {\n    // Create an invalid UTF-8 sequence\n    let invalid_utf8: &[u8] =\n        unsafe { core::slice::from_raw_parts([0xFFu8, 0xFFu8, 0xFFu8].as_ptr(), 3) };\n    let utf8_err = str::from_utf8(invalid_utf8).unwrap_err();\n\n    let err = TooLongOrUtf8Error::Utf8Error(utf8_err);\n    test_error_display(err);\n}\n\n/// Test InteriorNulError\n#[cfg(feature = \"cstr\")]\npub fn test_interior_nul_error() {\n    let err = InteriorNulError { position: 5 };\n\n    let msg = format!(\"{}\", err);\n    assert!(msg.contains(\"Interior NUL\"));\n    assert!(msg.contains(\"5\"));\n\n    test_error_display(err);\n}\n\n/// Test TooLongOrNulError::TooLong variant\n#[cfg(feature = \"cstr\")]\npub fn test_too_long_or_nul_error_too_long() {\n    let err = TooLongOrNulError::TooLong(TooLongForInlining {\n        length: 100,\n        inline_capacity: 30,\n    });\n\n    test_error_display(err);\n}\n\n/// Test TooLongOrNulError::NulError variant\n#[cfg(feature = \"cstr\")]\npub fn test_too_long_or_nul_error_nul() {\n    let err = TooLongOrNulError::NulError(InteriorNulError { position: 3 });\n\n    test_error_display(err);\n}\n"
  },
  {
    "path": "tests/common/from.rs",
    "content": "#![allow(dead_code)]\n\nuse core::fmt;\nuse flexstr::{FlexStr, RefCounted};\nuse flexstr_support::StringToFromBytes;\n\n/// Test From implementation\npub fn test_from<'s, T, S, R>(value: T)\nwhere\n    T: Into<FlexStr<'s, S, R>> + fmt::Debug,\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n    R: RefCounted<S>,\n    S::Owned: AsRef<S>,\n{\n    let flex_str: FlexStr<'s, S, R> = value.into();\n    // Basic sanity check - the conversion should succeed\n    assert_eq!(flex_str.as_ref_type(), flex_str.as_ref_type());\n}\n\n/// Test From<String> for FlexStr<str, R>\n#[cfg(feature = \"str\")]\npub fn test_from_string_str<R>()\nwhere\n    R: RefCounted<str>,\n{\n    use alloc::string::String;\n\n    let s = String::from(\"test\");\n    let flex_str: FlexStr<'_, str, R> = s.into();\n    assert_eq!(flex_str.as_ref_type(), \"test\");\n}\n\n/// Test From<Vec<u8>> for FlexStr<[u8], R>\n#[cfg(feature = \"bytes\")]\npub fn test_from_vec_bytes<R>()\nwhere\n    R: RefCounted<[u8]>,\n{\n    let v = alloc::vec![1u8, 2u8, 3u8];\n    let flex_str: FlexStr<'_, [u8], R> = v.into();\n    assert_eq!(flex_str.as_ref_type(), &[1u8, 2u8, 3u8][..]);\n}\n\n/// Test From<&str> for FlexStr<[u8], R>\n#[cfg(feature = \"bytes\")]\npub fn test_from_str_bytes<R>()\nwhere\n    R: RefCounted<[u8]>,\n{\n    let s = \"test\";\n    let flex_str: FlexStr<'_, [u8], R> = s.into();\n    assert_eq!(flex_str.as_ref_type(), b\"test\");\n}\n\n/// Test From<OsString> for FlexStr<OsStr, R>\n#[cfg(all(feature = \"std\", feature = \"osstr\"))]\npub fn test_from_os_string<R>()\nwhere\n    R: RefCounted<std::ffi::OsStr>,\n{\n    use std::ffi::OsString;\n\n    let os_string: OsString = OsString::from(\"test\");\n    let flex_str: FlexStr<'_, std::ffi::OsStr, R> = os_string.into();\n    assert_eq!(flex_str.as_ref_type(), std::ffi::OsStr::new(\"test\"));\n}\n\n/// Test From<String> for FlexStr<OsStr, R>\n#[cfg(all(feature = \"std\", feature = \"osstr\"))]\npub fn test_from_string_osstr<R>()\nwhere\n    R: RefCounted<std::ffi::OsStr>,\n{\n    let s = String::from(\"test\");\n    let flex_str: FlexStr<'_, std::ffi::OsStr, R> = s.into();\n    assert_eq!(flex_str.as_ref_type(), std::ffi::OsStr::new(\"test\"));\n}\n\n/// Test From<PathBuf> for FlexStr<OsStr, R>\n#[cfg(all(feature = \"std\", feature = \"osstr\", feature = \"path\"))]\npub fn test_from_path_buf_osstr<R>()\nwhere\n    R: RefCounted<std::ffi::OsStr>,\n{\n    use std::path::PathBuf;\n\n    let path_buf = PathBuf::from(\"test\");\n    let flex_str: FlexStr<'_, std::ffi::OsStr, R> = path_buf.into();\n    assert_eq!(flex_str.as_ref_type(), std::ffi::OsStr::new(\"test\"));\n}\n\n/// Test From<&str> for FlexStr<OsStr, R>\n#[cfg(all(feature = \"std\", feature = \"osstr\"))]\npub fn test_from_str_ref_osstr<R>()\nwhere\n    R: RefCounted<std::ffi::OsStr>,\n{\n    let s = \"test\";\n    let flex_str: FlexStr<'_, std::ffi::OsStr, R> = s.into();\n    assert_eq!(flex_str.as_ref_type(), std::ffi::OsStr::new(\"test\"));\n}\n\n/// Test From<&Path> for FlexStr<OsStr, R>\n#[cfg(all(feature = \"std\", feature = \"osstr\", feature = \"path\"))]\npub fn test_from_path_ref_osstr<R>()\nwhere\n    R: RefCounted<std::ffi::OsStr>,\n{\n    use std::path::Path;\n\n    let path = Path::new(\"test\");\n    let flex_str: FlexStr<'_, std::ffi::OsStr, R> = path.into();\n    assert_eq!(flex_str.as_ref_type(), std::ffi::OsStr::new(\"test\"));\n}\n\n/// Test From<PathBuf> for FlexStr<Path, R>\n#[cfg(all(feature = \"std\", feature = \"path\"))]\npub fn test_from_path_buf<R>()\nwhere\n    R: RefCounted<std::path::Path>,\n{\n    use std::path::{Path, PathBuf};\n\n    let path_buf = PathBuf::from(\"test\");\n    let flex_str: FlexStr<'_, Path, R> = path_buf.into();\n    assert_eq!(flex_str.as_ref_type(), Path::new(\"test\"));\n}\n\n/// Test From<String> for FlexStr<Path, R>\n#[cfg(all(feature = \"std\", feature = \"path\"))]\npub fn test_from_string_path<R>()\nwhere\n    R: RefCounted<std::path::Path>,\n{\n    use std::path::Path;\n\n    let s = String::from(\"test\");\n    let flex_str: FlexStr<'_, Path, R> = s.into();\n    assert_eq!(flex_str.as_ref_type(), Path::new(\"test\"));\n}\n\n/// Test From<OsString> for FlexStr<Path, R>\n#[cfg(all(feature = \"std\", feature = \"path\"))]\npub fn test_from_os_string_path<R>()\nwhere\n    R: RefCounted<std::path::Path>,\n{\n    use std::ffi::OsString;\n    use std::path::Path;\n\n    let os_string = OsString::from(\"test\");\n    let flex_str: FlexStr<'_, Path, R> = os_string.into();\n    assert_eq!(flex_str.as_ref_type(), Path::new(\"test\"));\n}\n\n/// Test From<&str> for FlexStr<Path, R>\n#[cfg(all(feature = \"std\", feature = \"path\"))]\npub fn test_from_str_ref_path<R>()\nwhere\n    R: RefCounted<std::path::Path>,\n{\n    use std::path::Path;\n\n    let s = \"test\";\n    let flex_str: FlexStr<'_, Path, R> = s.into();\n    assert_eq!(flex_str.as_ref_type(), Path::new(\"test\"));\n}\n\n/// Test From<&OsStr> for FlexStr<Path, R>\n#[cfg(all(feature = \"std\", feature = \"path\"))]\npub fn test_from_osstr_ref_path<R>()\nwhere\n    R: RefCounted<std::path::Path>,\n{\n    use std::ffi::OsStr;\n    use std::path::Path;\n\n    let os_str = OsStr::new(\"test\");\n    let flex_str: FlexStr<'_, Path, R> = os_str.into();\n    assert_eq!(flex_str.as_ref_type(), Path::new(\"test\"));\n}\n"
  },
  {
    "path": "tests/common/from_str.rs",
    "content": "#![allow(dead_code)]\n\nuse core::fmt;\nuse core::str::FromStr;\nuse flexstr::{FlexStr, RefCounted};\nuse flexstr_support::StringToFromBytes;\n\n/// Test FromStr success for FlexStr\npub fn test_from_str_flex_str_success<S, R>(s: &str)\nwhere\n    FlexStr<'static, S, R>: FromStr<Err = core::convert::Infallible>,\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n    R: RefCounted<S>,\n    S::Owned: AsRef<S>,\n{\n    let flex_str = FlexStr::from_str(s).unwrap();\n    assert_eq!(flex_str.as_ref_type(), flex_str.as_ref_type()); // Basic sanity check\n}\n\n/// Test FromStr for FlexStr<[u8], R>\n#[cfg(feature = \"bytes\")]\npub fn test_from_str_bytes_success<R>()\nwhere\n    R: RefCounted<[u8]>,\n{\n    let flex_str = FlexStr::<'static, [u8], R>::from_str(\"test\").unwrap();\n    assert_eq!(flex_str.as_ref_type(), b\"test\");\n}\n\n/// Test FromStr for FlexStr<OsStr, R>\n#[cfg(all(feature = \"std\", feature = \"osstr\"))]\npub fn test_from_str_osstr_success<R>()\nwhere\n    R: RefCounted<std::ffi::OsStr>,\n{\n    use std::ffi::OsStr;\n\n    let flex_str = FlexStr::<'static, OsStr, R>::from_str(\"test\").unwrap();\n    assert_eq!(flex_str.as_ref_type(), OsStr::new(\"test\"));\n}\n\n/// Test FromStr for FlexStr<Path, R>\n#[cfg(all(feature = \"std\", feature = \"path\"))]\npub fn test_from_str_path_success<R>()\nwhere\n    R: RefCounted<std::path::Path>,\n{\n    use std::path::Path;\n\n    let flex_str = FlexStr::<'static, Path, R>::from_str(\"test\").unwrap();\n    assert_eq!(flex_str.as_ref_type(), Path::new(\"test\"));\n}\n\n/// Test FromStr for FlexStr<CStr, R> success\n#[cfg(feature = \"cstr\")]\npub fn test_from_str_cstr_success<R>()\nwhere\n    R: RefCounted<core::ffi::CStr> + fmt::Debug,\n{\n    use flexstr::FlexStr;\n\n    let flex_str = FlexStr::<'static, core::ffi::CStr, R>::from_str(\"test\").unwrap();\n    assert_eq!(flex_str.as_ref_type().to_bytes(), b\"test\");\n}\n\n/// Test FromStr for FlexStr<CStr, R> error (interior NUL)\n#[cfg(feature = \"cstr\")]\npub fn test_from_str_cstr_error<R>()\nwhere\n    R: RefCounted<core::ffi::CStr> + fmt::Debug,\n{\n    use flexstr::{FlexStr, InteriorNulError};\n\n    // String with interior NUL should fail\n    let result: Result<FlexStr<'static, core::ffi::CStr, R>, InteriorNulError> =\n        FlexStr::from_str(\"test\\0middle\");\n    result.unwrap_err();\n}\n"
  },
  {
    "path": "tests/common/index.rs",
    "content": "#![allow(dead_code)]\n\nuse core::fmt;\nuse flexstr::{FlexStr, RefCounted};\nuse flexstr_support::StringToFromBytes;\n\n/// Test Index implementation for FlexStr\n/// This tests that FlexStr can be dereferenced to &S, which is required for Index\npub fn test_index<S, R>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + PartialEq + fmt::Debug,\n    R: RefCounted<S>,\n{\n    let flex_str: FlexStr<'_, S, R> = FlexStr::from_borrowed(s);\n\n    // Test that we can deref to get &S (required for Index trait)\n    // The dereferenced values should be equal, not necessarily the same pointer\n    let original_ref: &S = s;\n    let flex_ref: &S = &flex_str;\n\n    // Verify the references are equal via PartialEq (not pointer equality)\n    assert_eq!(original_ref, flex_ref);\n}\n"
  },
  {
    "path": "tests/common/inline_edge_cases.rs",
    "content": "#![allow(dead_code)]\n\nuse core::fmt;\nuse flexstr::{FlexStr, RefCounted};\nuse flexstr_support::StringToFromBytes;\nuse inline_flexstr::INLINE_CAPACITY;\n\n/// Test optimize() path where RefCounted is converted to Inlined\n/// Input must be small enough to inline (<= INLINE_CAPACITY)\npub fn test_optimize_ref_counted_to_inlined<S, R>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n    R: RefCounted<S>,\n{\n    let bytes = S::self_as_raw_bytes(s);\n    assert!(\n        bytes.len() <= INLINE_CAPACITY,\n        \"test input must be small enough to inline\"\n    );\n\n    let rc: R = s.into();\n    let ref_counted: FlexStr<'_, S, R> = FlexStr::from_ref_counted(rc);\n    let optimized = ref_counted.optimize();\n\n    // Should be inlined after optimization\n    assert!(optimized.is_inlined());\n    assert_eq!(optimized.as_ref_type(), s);\n}\n\n/// Test optimize() path where RefCounted stays RefCounted (too large)\n/// Input must be too large to inline (> INLINE_CAPACITY)\npub fn test_optimize_ref_counted_stays_ref_counted<S, R>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n    R: RefCounted<S>,\n{\n    let bytes = S::self_as_raw_bytes(s);\n    assert!(\n        bytes.len() > INLINE_CAPACITY,\n        \"test input must be too large to inline\"\n    );\n\n    let rc: R = s.into();\n    let ref_counted: FlexStr<'_, S, R> = FlexStr::from_ref_counted(rc.clone());\n    let optimized = ref_counted.optimize();\n\n    // Should stay as ref_counted\n    assert!(optimized.is_ref_counted());\n    assert_eq!(optimized.as_ref_type(), s);\n}\n"
  },
  {
    "path": "tests/common/mod.rs",
    "content": "pub mod as_ref;\npub mod basic;\npub mod borrow;\npub mod comparison;\npub mod conversion;\n#[cfg(feature = \"cstr\")]\npub mod cstr_specific;\npub mod display;\npub mod edge_cases;\npub mod errors;\npub mod from;\npub mod from_str;\npub mod index;\npub mod inline_edge_cases;\n#[cfg(any(feature = \"str\", feature = \"bytes\"))]\npub mod mutate;\n#[cfg(any(feature = \"cstr\", feature = \"osstr\", feature = \"path\"))]\npub mod mutate_fallback;\n#[cfg(feature = \"prost\")]\npub mod prost;\n#[cfg(feature = \"serde\")]\npub mod serialize;\n#[cfg(feature = \"std\")]\npub mod socket;\npub mod storage;\npub mod stringlike;\npub mod try_from;\n#[cfg(feature = \"utoipa\")]\npub mod utoipa;\n#[cfg(feature = \"zeroize\")]\npub mod zeroize;\n"
  },
  {
    "path": "tests/common/mutate.rs",
    "content": "use core::fmt;\n\nuse flexstr::{FlexStr, RefCountedMut};\nuse flexstr_support::StringFromBytesMut;\n\n#[allow(dead_code)]\npub fn test_mutation_borrowed<S, R>(s: &'static S)\nwhere\n    S: ?Sized + StringFromBytesMut + fmt::Debug + PartialEq,\n    R: RefCountedMut<S>,\n{\n    let mut flex_str: FlexStr<S, R> = s.into();\n    assert!(flex_str.is_borrowed());\n\n    let s2 = flex_str.to_mut_type();\n    assert_eq!(s2, s);\n\n    assert!(flex_str.is_inlined());\n    let s2 = flex_str.to_mut_type();\n    assert_eq!(s2, s);\n}\n\n#[allow(dead_code)]\npub fn test_mutation_inlined<S, R>(s: &'static S)\nwhere\n    S: ?Sized + StringFromBytesMut + fmt::Debug + PartialEq,\n    R: RefCountedMut<S>,\n{\n    let mut flex_str: FlexStr<S, R> = s.into();\n    flex_str = flex_str.into_owned();\n    assert!(flex_str.is_inlined());\n\n    let s2 = flex_str.to_mut_type();\n    assert_eq!(s2, s);\n}\n\n#[allow(dead_code)]\npub fn test_mutation_ref_counted<S, R>(s: R)\nwhere\n    S: ?Sized + StringFromBytesMut + fmt::Debug + PartialEq,\n    R: RefCountedMut<S> + for<'a> Into<FlexStr<'a, S, R>>,\n{\n    let mut flex_str: FlexStr<S, R> = s.clone().into();\n    assert!(flex_str.is_ref_counted());\n\n    let s2 = flex_str.to_mut_type();\n    assert_eq!(s2, &*s);\n}\n\n#[allow(dead_code)]\npub fn test_mutation_boxed<S, R>(s: S::Owned)\nwhere\n    S: ?Sized + StringFromBytesMut + fmt::Debug + PartialEq,\n    R: RefCountedMut<S>,\n    S::Owned: for<'a> Into<FlexStr<'a, S, R>> + Clone + AsRef<S>,\n{\n    let mut flex_str: FlexStr<S, R> = s.clone().into();\n    assert!(flex_str.is_boxed());\n\n    let s2 = flex_str.to_mut_type();\n    assert_eq!(s2, s.as_ref());\n}\n"
  },
  {
    "path": "tests/common/mutate_fallback.rs",
    "content": "use core::fmt;\n\nuse flexstr::{FlexStr, ImmutableBytes, RefCountedMut};\n\n#[allow(dead_code)]\npub fn test_mutation_immutable_bytes_borrowed<S, R>(s: &'static S)\nwhere\n    S: ?Sized + ImmutableBytes + fmt::Debug + PartialEq,\n    R: RefCountedMut<S>,\n{\n    let mut flex_str: FlexStr<S, R> = s.into();\n    assert!(flex_str.is_borrowed());\n\n    let s2 = flex_str.to_mut_type_fallback();\n    assert_eq!(s2, s);\n\n    assert!(flex_str.is_ref_counted());\n    let s2 = flex_str.to_mut_type_fallback();\n    assert_eq!(s2, s);\n}\n\n#[allow(dead_code)]\npub fn test_mutation_immutable_bytes_inlined<S, R>(s: &'static S)\nwhere\n    S: ?Sized + ImmutableBytes + fmt::Debug + PartialEq,\n    R: RefCountedMut<S>,\n{\n    let mut flex_str: FlexStr<S, R> = s.into();\n    flex_str = flex_str.into_owned();\n    assert!(flex_str.is_inlined());\n\n    let s2 = flex_str.to_mut_type_fallback();\n    assert_eq!(s2, s);\n\n    assert!(flex_str.is_ref_counted());\n    let s2 = flex_str.to_mut_type_fallback();\n    assert_eq!(s2, s);\n}\n\n#[allow(dead_code)]\npub fn test_mutation_immutable_bytes_ref_counted<S, R>(s: R)\nwhere\n    S: ?Sized + ImmutableBytes + fmt::Debug + PartialEq,\n    R: RefCountedMut<S> + for<'a> Into<FlexStr<'a, S, R>>,\n{\n    let mut flex_str: FlexStr<S, R> = s.clone().into();\n    assert!(flex_str.is_ref_counted());\n\n    let s2 = flex_str.to_mut_type_fallback();\n    assert_eq!(s2, &*s);\n}\n\n#[allow(dead_code)]\npub fn test_mutation_immutable_bytes_boxed<S, R>(s: S::Owned)\nwhere\n    S: ?Sized + ImmutableBytes + fmt::Debug + PartialEq,\n    R: RefCountedMut<S>,\n    S::Owned: for<'a> Into<FlexStr<'a, S, R>> + Clone + AsRef<S>,\n{\n    let mut flex_str: FlexStr<S, R> = s.clone().into();\n    assert!(flex_str.is_boxed());\n\n    let s2 = flex_str.to_mut_type_fallback();\n    assert_eq!(s2, s.as_ref());\n}\n"
  },
  {
    "path": "tests/common/prost.rs",
    "content": "#![allow(dead_code)]\n\nuse core::fmt;\n\nuse prost::Message;\n\n/// Test that encoding and decoding round-trips correctly.\npub fn encode_decode_round_trip<F>(s: &'static str)\nwhere\n    F: Message + Default + TryFrom<&'static str> + PartialEq + fmt::Debug,\n    <F as TryFrom<&'static str>>::Error: fmt::Debug,\n{\n    let original: F = s.try_into().unwrap();\n    let encoded = original.encode_to_vec();\n    let decoded = F::decode(&encoded[..]).unwrap();\n    assert_eq!(original, decoded);\n}\n\n/// Test that length-delimited encoding and decoding round-trips correctly.\npub fn encode_length_delimited_round_trip<F>(s: &'static str)\nwhere\n    F: Message + Default + TryFrom<&'static str> + PartialEq + fmt::Debug,\n    <F as TryFrom<&'static str>>::Error: fmt::Debug,\n{\n    let original: F = s.try_into().unwrap();\n    let encoded = original.encode_length_delimited_to_vec();\n    let decoded = F::decode_length_delimited(&encoded[..]).unwrap();\n    assert_eq!(original, decoded);\n}\n\n/// Test that encoded bytes are just raw UTF-8 (no field tags or wrapping).\npub fn verify_wire_format<F>(s: &'static str)\nwhere\n    F: Message + Default + TryFrom<&'static str> + fmt::Debug,\n    <F as TryFrom<&'static str>>::Error: fmt::Debug,\n{\n    let original: F = s.try_into().unwrap();\n    let encoded = original.encode_to_vec();\n    assert_eq!(encoded, s.as_bytes(), \"encoded bytes should be raw UTF-8\");\n    assert_eq!(\n        original.encoded_len(),\n        s.len(),\n        \"encoded_len should match byte length\"\n    );\n}\n\n/// Test that decoding an empty buffer produces the default (empty string).\npub fn decode_empty<F>()\nwhere\n    F: Message + Default + AsRef<str> + fmt::Debug,\n{\n    let decoded = F::decode(&[][..]).unwrap();\n    assert_eq!(\n        decoded.as_ref(),\n        \"\",\n        \"decoding empty buffer should give empty string\"\n    );\n}\n\n/// Test that clear resets to the default (empty string).\npub fn clear_test<F>(s: &'static str)\nwhere\n    F: Message + Default + TryFrom<&'static str> + AsRef<str> + fmt::Debug,\n    <F as TryFrom<&'static str>>::Error: fmt::Debug,\n{\n    let mut value: F = s.try_into().unwrap();\n    value.clear();\n    assert_eq!(value.as_ref(), \"\", \"clear should reset to empty string\");\n}\n\n/// Verify that `message::encode` (for flex types) and `string::encode` (for String)\n/// produce identical wire format for the same string content. This is the foundation\n/// of cross-type compatibility: if the bytes on the wire are identical, the two types\n/// are interchangeable from a protocol perspective.\npub fn cross_type_wire_compat<F>(s: &'static str)\nwhere\n    F: Message + Default + TryFrom<&'static str> + fmt::Debug,\n    <F as TryFrom<&'static str>>::Error: fmt::Debug,\n{\n    let flex_val: F = s.try_into().unwrap();\n    let string_val = s.to_string();\n    let tag = 1u32;\n\n    // Encode the flex type as a message field\n    let mut flex_buf = Vec::new();\n    prost::encoding::message::encode(tag, &flex_val, &mut flex_buf);\n\n    // Encode the String as a string field\n    let mut string_buf = Vec::new();\n    prost::encoding::string::encode(tag, &string_val, &mut string_buf);\n\n    assert_eq!(\n        flex_buf, string_buf,\n        \"message::encode(flex) and string::encode(String) should produce identical bytes\"\n    );\n\n    // Also verify encoded_len matches\n    let flex_len = prost::encoding::message::encoded_len(tag, &flex_val);\n    let string_len = prost::encoding::string::encoded_len(tag, &string_val);\n    assert_eq!(flex_len, string_len, \"encoded_len should match\");\n}\n\n/// Encode a flex type using `message::encode`, then decode as a String field using\n/// `string::merge`. Simulates: SharedStr/InlineStr server → String client.\npub fn encode_flex_decode_string<F>(s: &'static str)\nwhere\n    F: Message + Default + TryFrom<&'static str> + fmt::Debug,\n    <F as TryFrom<&'static str>>::Error: fmt::Debug,\n{\n    let flex_val: F = s.try_into().unwrap();\n    let tag = 1u32;\n\n    // Encode flex type as a message field\n    let mut buf = Vec::new();\n    prost::encoding::message::encode(tag, &flex_val, &mut buf);\n\n    // Decode the field key, then decode as a String\n    let mut cursor = &buf[..];\n    let (decoded_tag, wire_type) = prost::encoding::decode_key(&mut cursor).unwrap();\n    assert_eq!(decoded_tag, tag);\n\n    let mut decoded = String::new();\n    prost::encoding::string::merge(\n        wire_type,\n        &mut decoded,\n        &mut cursor,\n        prost::encoding::DecodeContext::default(),\n    )\n    .unwrap();\n\n    assert_eq!(\n        decoded, s,\n        \"String decoded from flex-encoded field should match\"\n    );\n}\n\n/// Encode a String using `string::encode`, then decode as a flex type using\n/// `merge_length_delimited`. Simulates: String client → SharedStr/InlineStr server.\npub fn encode_string_decode_flex<F>(s: &'static str)\nwhere\n    F: Message + Default + AsRef<str> + fmt::Debug,\n{\n    let string_val = s.to_string();\n    let tag = 1u32;\n\n    // Encode String as a string field\n    let mut buf = Vec::new();\n    prost::encoding::string::encode(tag, &string_val, &mut buf);\n\n    // Read past the field key, then decode using our merge_length_delimited\n    let mut cursor = &buf[..];\n    let (decoded_tag, wire_type) = prost::encoding::decode_key(&mut cursor).unwrap();\n    assert_eq!(decoded_tag, tag);\n    assert_eq!(wire_type, prost::encoding::WireType::LengthDelimited);\n\n    let mut decoded = F::default();\n    decoded.merge_length_delimited(cursor).unwrap();\n\n    assert_eq!(\n        decoded.as_ref(),\n        s,\n        \"flex type decoded from String-encoded field should match\"\n    );\n}\n"
  },
  {
    "path": "tests/common/serialize.rs",
    "content": "#![allow(dead_code)]\n\nuse core::fmt;\nuse flexstr_support::StringToFromBytes;\nuse serde::{Deserialize, Serialize};\n\npub fn serialize_deserialize_test<'s, F, S>(s: &'static S)\nwhere\n    F: TryFrom<&'s S> + PartialEq + Serialize + for<'de> Deserialize<'de> + fmt::Debug,\n    <F as TryFrom<&'s S>>::Error: fmt::Debug,\n    S: ?Sized + StringToFromBytes + Serialize + fmt::Debug + PartialEq,\n    Box<S>: for<'de> Deserialize<'de>,\n{\n    let expected_str: F = s.try_into().unwrap();\n    let serialized = serde_json::to_value(&expected_str).unwrap();\n    let expected_json = serde_json::to_value(s).unwrap();\n    assert_eq!(expected_json, serialized);\n\n    let deserialized: F = serde_json::from_value(serialized).unwrap();\n    assert_eq!(expected_str, deserialized);\n}\n"
  },
  {
    "path": "tests/common/socket.rs",
    "content": "#![allow(dead_code)]\n\nuse flexstr::{FlexStr, RefCounted};\nuse flexstr_support::StringToFromBytes;\nuse std::net::ToSocketAddrs;\n\n/// Test ToSocketAddrs implementation for FlexStr\npub fn test_to_socket_addrs<S, R>(addr: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + ToSocketAddrs,\n    R: RefCounted<S>,\n{\n    let flex_str: FlexStr<'_, S, R> = FlexStr::from_borrowed(addr);\n\n    // Test ToSocketAddrs - this should work if addr is a valid socket address\n    // We'll use a simple test that doesn't require network access\n    let mut iter = flex_str.to_socket_addrs().unwrap();\n    assert!(iter.next().is_some());\n    assert!(iter.next().is_none());\n}\n"
  },
  {
    "path": "tests/common/storage.rs",
    "content": "#![allow(dead_code)]\n\nuse core::fmt;\nuse flexstr::{FlexStr, RefCounted};\nuse flexstr_support::StringToFromBytes;\nuse inline_flexstr::{INLINE_CAPACITY, InlineFlexStr};\n\n/// Test variant query methods\npub fn test_variant_queries<S, R>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n    R: RefCounted<S>,\n    Box<S>: From<S::Owned>,\n    S::Owned: AsRef<S>,\n{\n    // Test borrowed variant\n    let borrowed: FlexStr<'_, S, R> = FlexStr::from_borrowed(s);\n    assert!(borrowed.is_borrowed());\n    assert!(!borrowed.is_inlined());\n    assert!(!borrowed.is_ref_counted());\n    assert!(!borrowed.is_boxed());\n    assert!(borrowed.is_off_heap());\n    assert!(!borrowed.is_on_heap());\n\n    // Test inlined variant (input should be small enough to inline)\n    let inline_str =\n        InlineFlexStr::try_from_type(s).expect(\"test input should be small enough to inline\");\n    let inlined: FlexStr<'_, S, R> = FlexStr::from_inline(inline_str);\n    assert!(!inlined.is_borrowed());\n    assert!(inlined.is_inlined());\n    assert!(!inlined.is_ref_counted());\n    assert!(!inlined.is_boxed());\n    assert!(inlined.is_off_heap());\n    assert!(!inlined.is_on_heap());\n\n    // Test ref_counted variant\n    let rc: R = s.into();\n    let ref_counted: FlexStr<'_, S, R> = FlexStr::from_ref_counted(rc);\n    assert!(!ref_counted.is_borrowed());\n    assert!(!ref_counted.is_inlined());\n    assert!(ref_counted.is_ref_counted());\n    assert!(!ref_counted.is_boxed());\n    assert!(!ref_counted.is_off_heap());\n    assert!(ref_counted.is_on_heap());\n\n    // Test boxed variant\n    let boxed: FlexStr<'_, S, R> = FlexStr::from_boxed(Box::from(s.to_owned()));\n    assert!(!boxed.is_borrowed());\n    assert!(!boxed.is_inlined());\n    assert!(!boxed.is_ref_counted());\n    assert!(boxed.is_boxed());\n    assert!(!boxed.is_off_heap());\n    assert!(boxed.is_on_heap());\n}\n\n/// Test variant transitions: borrowed -> inlined\npub fn test_transition_borrowed_to_inlined<S, R>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n    R: RefCounted<S>,\n{\n    let borrowed: FlexStr<'_, S, R> = FlexStr::from_borrowed(s);\n    let owned = borrowed.to_owned();\n\n    // Input should be small enough to inline\n    assert!(\n        s.self_as_raw_bytes().len() <= INLINE_CAPACITY,\n        \"test input should be small enough to inline\"\n    );\n    assert!(owned.is_inlined() || owned.is_borrowed());\n    assert_eq!(owned.as_ref_type(), s);\n}\n\n/// Test variant transitions: borrowed -> ref_counted\n/// Input must be too large to inline (> INLINE_CAPACITY)\npub fn test_transition_borrowed_to_ref_counted<S, R>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n    R: RefCounted<S>,\n{\n    assert!(\n        s.self_as_raw_bytes().len() > INLINE_CAPACITY,\n        \"test input must be too large to inline\"\n    );\n\n    let borrowed: FlexStr<'_, S, R> = FlexStr::from_borrowed(s);\n    let owned = borrowed.to_owned();\n    assert!(owned.is_ref_counted());\n    assert_eq!(owned.as_ref_type(), s);\n}\n\n/// Test variant transitions: inlined -> ref_counted\n/// Input should be small enough to inline\npub fn test_transition_inlined_to_ref_counted<S, R>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n    R: RefCounted<S>,\n{\n    let inline_str =\n        InlineFlexStr::try_from_type(s).expect(\"test input should be small enough to inline\");\n    let inlined: FlexStr<'_, S, R> = FlexStr::from_inline(inline_str);\n    let cloned = inlined.clone();\n\n    // Cloning inlined should still be inlined\n    assert!(cloned.is_inlined());\n    assert_eq!(cloned.as_ref_type(), s);\n}\n\n/// Test variant transitions: boxed -> inlined/ref_counted\npub fn test_transition_boxed_to_optimized<S, R>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n    R: RefCounted<S>,\n    Box<S>: From<S::Owned>,\n    S::Owned: AsRef<S>,\n{\n    let boxed: FlexStr<'_, S, R> = FlexStr::from_boxed(Box::from(s.to_owned()));\n    let optimized = boxed.optimize();\n\n    // Should be inlined or ref_counted, not boxed\n    assert!(matches!(\n        optimized,\n        FlexStr::Inlined(_) | FlexStr::RefCounted(_)\n    ));\n    assert_eq!(optimized.as_ref_type(), s);\n}\n\n/// Test storage optimization\npub fn test_storage_optimization<S, R>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n    R: RefCounted<S>,\n    Box<S>: From<S::Owned>,\n    S::Owned: AsRef<S>,\n{\n    // Test optimize on boxed (should convert to inlined or ref_counted)\n    let boxed: FlexStr<'_, S, R> = FlexStr::from_boxed(Box::from(s.to_owned()));\n    let optimized = boxed.optimize();\n    assert!(matches!(\n        optimized,\n        FlexStr::Inlined(_) | FlexStr::RefCounted(_)\n    ));\n    assert_eq!(optimized.as_ref_type(), s);\n\n    // Test optimize on borrowed (should stay borrowed)\n    let borrowed: FlexStr<'_, S, R> = FlexStr::from_borrowed(s);\n    let optimized = borrowed.optimize();\n    assert!(optimized.is_borrowed());\n    assert_eq!(optimized.as_ref_type(), s);\n\n    // Test optimize on inlined (should stay inlined)\n    // Input should be small enough to inline\n    let inline_str =\n        InlineFlexStr::try_from_type(s).expect(\"test input should be small enough to inline\");\n    let inlined: FlexStr<'_, S, R> = FlexStr::from_inline(inline_str);\n    let optimized = inlined.optimize();\n    assert!(optimized.is_inlined());\n    assert_eq!(optimized.as_ref_type(), s);\n}\n"
  },
  {
    "path": "tests/common/stringlike.rs",
    "content": "#![allow(dead_code)]\n\nuse core::fmt;\nuse flexstr::{FlexStr, RefCounted, StringLike};\nuse flexstr_support::StringToFromBytes;\n\n/// Test as_str() method for str types\npub fn test_as_str<S, R>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + AsRef<str> + PartialEq,\n    R: RefCounted<S>,\n    FlexStr<'static, S, R>: StringLike<S>,\n{\n    let flex_str: FlexStr<'_, S, R> = FlexStr::from_borrowed(s);\n    let str_ref = StringLike::as_str(&flex_str);\n    assert_eq!(str_ref, s.as_ref());\n}\n\n/// Test as_os_str() method for OsStr types\n#[cfg(all(feature = \"std\", feature = \"osstr\"))]\npub fn test_as_os_str<S, R>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + AsRef<std::ffi::OsStr> + PartialEq,\n    R: RefCounted<S>,\n    FlexStr<'static, S, R>: StringLike<S>,\n{\n    let flex_str: FlexStr<'_, S, R> = FlexStr::from_borrowed(s);\n    let os_str_ref = StringLike::as_os_str(&flex_str);\n    assert_eq!(os_str_ref, s.as_ref());\n}\n\n/// Test as_path() method for Path types\n#[cfg(all(feature = \"std\", feature = \"path\"))]\npub fn test_as_path<S, R>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + AsRef<std::path::Path> + PartialEq,\n    R: RefCounted<S>,\n    FlexStr<'static, S, R>: StringLike<S>,\n{\n    let flex_str: FlexStr<'_, S, R> = FlexStr::from_borrowed(s);\n    let path_ref = StringLike::as_path(&flex_str);\n    assert_eq!(path_ref, s.as_ref());\n}\n\n/// Test as_c_str() method for CStr types\n#[cfg(feature = \"cstr\")]\npub fn test_as_c_str<S, R>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + AsRef<core::ffi::CStr> + PartialEq,\n    R: RefCounted<S>,\n    FlexStr<'static, S, R>: StringLike<S>,\n{\n    let flex_str: FlexStr<'_, S, R> = FlexStr::from_borrowed(s);\n    let c_str_ref = StringLike::as_c_str(&flex_str);\n    assert_eq!(c_str_ref, s.as_ref());\n}\n\n/// Test into_string() method\npub fn test_into_string<S, R>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n    R: RefCounted<S>,\n    S::Owned: Into<String> + From<alloc::boxed::Box<S>> + AsRef<S>,\n    FlexStr<'static, S, R>: StringLike<S>,\n{\n    let flex_str: FlexStr<'_, S, R> = FlexStr::from_borrowed(s);\n    let string = StringLike::into_string(flex_str);\n    assert_eq!(string, s.to_owned().into());\n}\n\n/// Test to_string() method\npub fn test_to_string<S, R>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n    R: RefCounted<S>,\n    S::Owned: Into<String>,\n    FlexStr<'static, S, R>: StringLike<S>,\n{\n    let flex_str: FlexStr<'_, S, R> = FlexStr::from_borrowed(s);\n    let string = StringLike::to_string(&flex_str);\n    assert_eq!(string, s.to_owned().into());\n}\n\n/// Test into_os_string() method\n#[cfg(all(feature = \"std\", feature = \"osstr\"))]\npub fn test_into_os_string<S, R>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n    R: RefCounted<S>,\n    S::Owned: Into<std::ffi::OsString> + From<alloc::boxed::Box<S>> + AsRef<S>,\n    FlexStr<'static, S, R>: StringLike<S>,\n{\n    let flex_str: FlexStr<'_, S, R> = FlexStr::from_borrowed(s);\n    let os_string = StringLike::into_os_string(flex_str);\n    assert_eq!(os_string, s.to_owned().into());\n}\n\n/// Test to_os_string() method\n#[cfg(all(feature = \"std\", feature = \"osstr\"))]\npub fn test_to_os_string<S, R>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n    R: RefCounted<S>,\n    S::Owned: Into<std::ffi::OsString>,\n    FlexStr<'static, S, R>: StringLike<S>,\n{\n    let flex_str: FlexStr<'_, S, R> = FlexStr::from_borrowed(s);\n    let os_string = StringLike::to_os_string(&flex_str);\n    assert_eq!(os_string, s.to_owned().into());\n}\n\n/// Test into_path_buf() method\n#[cfg(all(feature = \"std\", feature = \"path\"))]\npub fn test_into_path_buf<S, R>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n    R: RefCounted<S>,\n    S::Owned: Into<std::path::PathBuf> + From<alloc::boxed::Box<S>> + AsRef<S>,\n    FlexStr<'static, S, R>: StringLike<S>,\n{\n    let flex_str: FlexStr<'_, S, R> = FlexStr::from_borrowed(s);\n    let path_buf = StringLike::into_path_buf(flex_str);\n    assert_eq!(path_buf, s.to_owned().into());\n}\n\n/// Test to_path_buf() method\n#[cfg(all(feature = \"std\", feature = \"path\"))]\npub fn test_to_path_buf<S, R>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n    R: RefCounted<S>,\n    S::Owned: Into<std::path::PathBuf>,\n    FlexStr<'static, S, R>: StringLike<S>,\n{\n    let flex_str: FlexStr<'_, S, R> = FlexStr::from_borrowed(s);\n    let path_buf = StringLike::to_path_buf(&flex_str);\n    assert_eq!(path_buf, s.to_owned().into());\n}\n\n/// Test into_c_string() method\n#[cfg(feature = \"cstr\")]\npub fn test_into_c_string<S, R>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n    R: RefCounted<S> + fmt::Debug,\n    S::Owned: Into<alloc::ffi::CString> + From<alloc::boxed::Box<S>> + AsRef<S>,\n    FlexStr<'static, S, R>: StringLike<S>,\n{\n    let flex_str: FlexStr<'_, S, R> = FlexStr::from_borrowed(s);\n    let c_string = StringLike::into_c_string(flex_str);\n    assert_eq!(\n        c_string.as_bytes_with_nul(),\n        s.to_owned().into().as_bytes_with_nul()\n    );\n}\n\n/// Test to_c_string() method\n#[cfg(feature = \"cstr\")]\npub fn test_to_c_string<S, R>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n    R: RefCounted<S> + fmt::Debug,\n    S::Owned: Into<alloc::ffi::CString>,\n    FlexStr<'static, S, R>: StringLike<S>,\n{\n    let flex_str: FlexStr<'_, S, R> = FlexStr::from_borrowed(s);\n    let c_string = StringLike::to_c_string(&flex_str);\n    let expected: alloc::ffi::CString = s.to_owned().into();\n    assert_eq!(c_string.as_bytes_with_nul(), expected.as_bytes_with_nul());\n}\n\n/// Test into_vec_bytes() method\n#[cfg(feature = \"bytes\")]\npub fn test_into_vec_bytes<S, R>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n    R: RefCounted<S>,\n    S::Owned: Into<alloc::vec::Vec<u8>> + From<alloc::boxed::Box<S>> + AsRef<S>,\n    FlexStr<'static, S, R>: StringLike<S>,\n{\n    let flex_str: FlexStr<'_, S, R> = FlexStr::from_borrowed(s);\n    let vec_bytes = StringLike::into_vec_bytes(flex_str);\n    assert_eq!(vec_bytes, s.to_owned().into());\n}\n\n/// Test to_vec_bytes() method\n#[cfg(feature = \"bytes\")]\npub fn test_to_vec_bytes<S, R>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n    R: RefCounted<S>,\n    S::Owned: Into<alloc::vec::Vec<u8>>,\n    FlexStr<'static, S, R>: StringLike<S>,\n{\n    let flex_str: FlexStr<'_, S, R> = FlexStr::from_borrowed(s);\n    let vec_bytes = StringLike::to_vec_bytes(&flex_str);\n    assert_eq!(vec_bytes, s.to_owned().into());\n}\n"
  },
  {
    "path": "tests/common/try_from.rs",
    "content": "#![allow(dead_code)]\n\nuse core::fmt;\nuse flexstr::{FlexStr, RefCounted};\nuse flexstr_support::StringToFromBytes;\n\n/// Test TryFrom success path for FlexStr\npub fn test_try_from_flex_str_success<'s, T, S, R>(value: T)\nwhere\n    T: core::convert::TryInto<FlexStr<'s, S, R>>,\n    T::Error: fmt::Debug,\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n    R: RefCounted<S> + fmt::Debug,\n{\n    let flex_str: FlexStr<'s, S, R> = value.try_into().unwrap();\n    assert_eq!(flex_str.as_ref_type(), flex_str.as_ref_type()); // Basic sanity check\n}\n\n/// Test TryFrom error path for FlexStr\npub fn test_try_from_flex_str_error<'s, T, S, R>(value: T)\nwhere\n    T: core::convert::TryInto<FlexStr<'s, S, R>>,\n    T::Error: fmt::Debug + fmt::Display,\n    S: ?Sized + StringToFromBytes + fmt::Debug,\n    R: RefCounted<S> + fmt::Debug,\n{\n    let result: Result<FlexStr<'s, S, R>, T::Error> = value.try_into();\n    let err = result.unwrap_err();\n    // Test that error can be displayed\n    let _ = format!(\"{}\", err);\n}\n\n/// Test TryFrom<&[u8]> for FlexStr<str, R> with invalid UTF-8\n#[cfg(feature = \"str\")]\npub fn test_try_from_bytes_invalid_utf8<R>()\nwhere\n    R: RefCounted<str> + core::fmt::Debug,\n{\n    use core::str::Utf8Error;\n\n    // Invalid UTF-8 sequence\n    let invalid_utf8: &[u8] = &[0xFF, 0xFF, 0xFF];\n    let result: Result<FlexStr<'_, str, R>, Utf8Error> = invalid_utf8.try_into();\n    let _err = result.unwrap_err(); // Test that error can be unwrapped\n}\n\n/// Test TryFrom<Vec<u8>> for FlexStr<str, R> with invalid UTF-8\n#[cfg(feature = \"str\")]\npub fn test_try_from_vec_bytes_invalid_utf8<R>()\nwhere\n    R: RefCounted<str> + fmt::Debug,\n{\n    use alloc::string::FromUtf8Error;\n\n    // Invalid UTF-8 sequence\n    let invalid_utf8 = alloc::vec![0xFF, 0xFF, 0xFF];\n    let result: Result<FlexStr<'static, str, R>, FromUtf8Error> = invalid_utf8.try_into();\n    let _err = result.unwrap_err();\n}\n\n/// Test TryFrom<CString> for FlexStr<str, R> with invalid UTF-8\n#[cfg(all(feature = \"str\", feature = \"cstr\"))]\npub fn test_try_from_cstring_invalid_utf8<R>()\nwhere\n    R: RefCounted<str>,\n{\n    use alloc::ffi::{CString, IntoStringError};\n\n    // Create a CString with invalid UTF-8 (this is tricky, but we can try)\n    // Note: CString::new will fail if there's a NUL byte, so we need a different approach\n    // For now, we'll test with a valid CString that contains non-UTF-8 bytes\n    // This test may need adjustment based on actual CString behavior\n    let cstring = CString::new(b\"test\\0\").unwrap();\n    // This should succeed since \"test\" is valid UTF-8\n    let result: Result<FlexStr<'static, str, R>, IntoStringError> = cstring.try_into();\n    let _flex_str = result.unwrap();\n}\n\n/// Test TryFrom<&str> for FlexStr<CStr, R>\n#[cfg(feature = \"cstr\")]\npub fn test_try_from_str_cstr<R>()\nwhere\n    R: RefCounted<core::ffi::CStr> + fmt::Debug,\n{\n    use flexstr::{FlexStr, InteriorNulError};\n\n    // Valid CStr (no interior NUL)\n    let s: &str = \"test\";\n    let result: Result<FlexStr<'_, core::ffi::CStr, R>, InteriorNulError> = s.try_into();\n    let flex_str = result.unwrap();\n    assert_eq!(flex_str.as_ref_type().to_bytes(), b\"test\");\n\n    // Invalid CStr (interior NUL)\n    let s_with_nul: &str = \"test\\0middle\";\n    let result: Result<FlexStr<'_, core::ffi::CStr, R>, InteriorNulError> = s_with_nul.try_into();\n    result.unwrap_err();\n}\n\n/// Test TryFrom<&[u8]> for FlexStr<CStr, R>\n#[cfg(feature = \"cstr\")]\npub fn test_try_from_bytes_cstr<R>()\nwhere\n    R: RefCounted<core::ffi::CStr> + fmt::Debug,\n{\n    use flexstr::{FlexStr, InteriorNulError};\n\n    // Valid CStr (no interior NUL)\n    let bytes: &[u8] = b\"test\";\n    let result: Result<FlexStr<'_, core::ffi::CStr, R>, InteriorNulError> = bytes.try_into();\n    let flex_str = result.unwrap();\n    assert_eq!(flex_str.as_ref_type().to_bytes(), b\"test\");\n\n    // Invalid CStr (interior NUL)\n    let bytes_with_nul: &[u8] = b\"test\\0middle\";\n    let result: Result<FlexStr<'_, core::ffi::CStr, R>, InteriorNulError> =\n        bytes_with_nul.try_into();\n    result.unwrap_err();\n}\n\n/// Test TryFrom<&OsStr> for FlexStr<str, R>\n#[cfg(all(feature = \"str\", feature = \"std\"))]\npub fn test_try_from_osstr_str<R>()\nwhere\n    R: RefCounted<str> + fmt::Debug,\n{\n    use flexstr::FlexStr;\n    use std::ffi::OsStr;\n\n    // Valid UTF-8 OsStr\n    let os_str = OsStr::new(\"test\");\n    let result: Result<FlexStr<'_, str, R>, core::str::Utf8Error> = os_str.try_into();\n    let flex_str = result.unwrap();\n    assert_eq!(flex_str.as_ref_type(), \"test\");\n}\n\n/// Test TryFrom<&Path> for FlexStr<str, R>\n#[cfg(all(feature = \"str\", feature = \"std\"))]\npub fn test_try_from_path_str<R>()\nwhere\n    R: RefCounted<str> + fmt::Debug,\n{\n    use flexstr::FlexStr;\n    use std::path::Path;\n\n    // Valid UTF-8 Path\n    let path = Path::new(\"test\");\n    let result: Result<FlexStr<'_, str, R>, core::str::Utf8Error> = path.try_into();\n    let flex_str = result.unwrap();\n    assert_eq!(flex_str.as_ref_type(), \"test\");\n}\n\n/// Test TryFrom<Vec<u8>> for FlexStr<str, R>\n#[cfg(feature = \"str\")]\npub fn test_try_from_vec_u8_str<R>()\nwhere\n    R: RefCounted<str> + fmt::Debug,\n{\n    use alloc::string::FromUtf8Error;\n    use flexstr::FlexStr;\n\n    // Valid UTF-8 Vec<u8>\n    let vec = b\"test\".to_vec();\n    let result: Result<FlexStr<'static, str, R>, FromUtf8Error> = vec.try_into();\n    let flex_str = result.unwrap();\n    assert_eq!(flex_str.as_ref_type(), \"test\");\n\n    // Invalid UTF-8 Vec<u8>\n    let invalid_vec = vec![0xFF, 0xFF, 0xFF];\n    let result: Result<FlexStr<'static, str, R>, FromUtf8Error> = invalid_vec.try_into();\n    result.unwrap_err();\n}\n\n/// Test TryFrom<CString> for FlexStr<str, R>\n#[cfg(all(feature = \"str\", feature = \"cstr\"))]\npub fn test_try_from_cstring_str<R>()\nwhere\n    R: RefCounted<str> + fmt::Debug,\n{\n    use alloc::ffi::{CString, IntoStringError};\n    use flexstr::FlexStr;\n\n    // Valid UTF-8 CString\n    let cstring = CString::new(\"test\").unwrap();\n    let result: Result<FlexStr<'static, str, R>, IntoStringError> = cstring.try_into();\n    let flex_str = result.unwrap();\n    assert_eq!(flex_str.as_ref_type(), \"test\");\n}\n"
  },
  {
    "path": "tests/common/utoipa.rs",
    "content": "#![allow(dead_code)]\n\nuse utoipa::openapi::RefOr;\nuse utoipa::openapi::schema::Schema;\nuse utoipa::{PartialSchema, ToSchema};\n\n/// Verify that the schema is `{\"type\": \"string\"}` — identical to String's OpenAPI representation.\npub fn schema_is_string<F>()\nwhere\n    F: PartialSchema,\n{\n    let schema = F::schema();\n    let RefOr::T(Schema::Object(obj)) = &schema else {\n        panic!(\"expected Object schema, got a Ref\");\n    };\n    let json = serde_json::to_value(obj).unwrap();\n    assert_eq!(json, serde_json::json!({\"type\": \"string\"}));\n}\n\n/// Verify that name() returns \"String\" so it's indistinguishable from String in OpenAPI output.\npub fn name_is_string<F>()\nwhere\n    F: ToSchema,\n{\n    assert_eq!(F::name(), \"String\");\n}\n"
  },
  {
    "path": "tests/common/zeroize.rs",
    "content": "#![allow(dead_code)]\n\nuse core::fmt;\nuse flexstr::{FlexStr, RefCountedMut, StringLike};\nuse flexstr_support::StringToFromBytes;\nuse inline_flexstr::InlineFlexStr;\nuse zeroize::{TryZeroize, Zeroize};\n\n/// Test try_zeroize on an Inlined variant — should succeed\npub fn test_zeroize_inlined<S, R>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n    R: RefCountedMut<S>,\n{\n    let inline = InlineFlexStr::try_from_type(s).expect(\"test input should be small enough\");\n    let mut flex: FlexStr<'_, S, R> = FlexStr::from_inline(inline);\n    assert!(flex.is_inlined());\n\n    assert!(flex.try_zeroize());\n\n    assert!(flex.is_inlined());\n    assert!(StringLike::is_empty(&flex));\n}\n\n/// Test try_zeroize on a Borrowed variant — should fail (we don't own the data)\npub fn test_zeroize_borrowed<S, R>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n    R: RefCountedMut<S>,\n{\n    let mut flex: FlexStr<'_, S, R> = FlexStr::from_borrowed(s);\n    assert!(flex.is_borrowed());\n\n    assert!(!flex.try_zeroize());\n\n    // Value should be unchanged\n    assert!(flex.is_borrowed());\n    assert_eq!(flex.as_ref_type(), s);\n}\n\n/// Test try_zeroize on a unique RefCounted variant (last reference) — should succeed\npub fn test_zeroize_ref_counted<S, R>(rc: R)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n    R: RefCountedMut<S>,\n{\n    let mut flex: FlexStr<'_, S, R> = FlexStr::from_ref_counted(rc);\n    assert!(flex.is_ref_counted());\n\n    assert!(flex.try_zeroize());\n\n    assert!(flex.is_inlined());\n    assert!(StringLike::is_empty(&flex));\n}\n\n/// Test try_zeroize on a Boxed variant — should succeed\npub fn test_zeroize_boxed<S, R>(s: &'static S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n    R: RefCountedMut<S>,\n    Box<S>: From<S::Owned>,\n    S::Owned: AsRef<S>,\n{\n    let boxed = Box::from(s.to_owned());\n    let mut flex: FlexStr<'_, S, R> = FlexStr::from_boxed(boxed);\n    assert!(flex.is_boxed());\n\n    assert!(flex.try_zeroize());\n\n    assert!(flex.is_inlined());\n    assert!(StringLike::is_empty(&flex));\n}\n\n/// Test try_zeroize on a shared RefCounted variant — should fail (other references exist)\npub fn test_zeroize_ref_counted_shared<S, R>(rc: R)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n    R: RefCountedMut<S> + Clone,\n{\n    let mut flex: FlexStr<'_, S, R> = FlexStr::from_ref_counted(rc);\n    assert!(flex.is_ref_counted());\n\n    // Create a second reference so try_zeroize cannot get exclusive access\n    let flex2 = flex.clone();\n    assert!(flex2.is_ref_counted());\n\n    assert!(!flex.try_zeroize());\n\n    // Value should be unchanged — still ref counted and pointing to the same data\n    assert!(flex.is_ref_counted());\n    assert_eq!(flex.as_ref_type(), flex2.as_ref_type());\n}\n\n/// Test that InlineFlexStr raw bytes are actually zeroed after zeroize\npub fn test_zeroize_inline_bytes_cleared<S>(s: &S)\nwhere\n    S: ?Sized + StringToFromBytes + fmt::Debug + PartialEq,\n{\n    let mut inline = InlineFlexStr::try_from_type(s).expect(\"test input should be small enough\");\n\n    // Verify we have non-zero data\n    assert!(\n        !S::self_as_raw_bytes(s).is_empty(),\n        \"test input must be non-empty\"\n    );\n\n    // Get a raw pointer to the struct's memory (struct is on the stack, still alive after zeroize)\n    let ptr = &inline as *const InlineFlexStr<S> as *const u8;\n    let size = core::mem::size_of::<InlineFlexStr<S>>();\n\n    inline.zeroize();\n\n    // Read the raw bytes of the struct — it's still alive on the stack\n    let bytes = unsafe { core::slice::from_raw_parts(ptr, size) };\n    assert!(\n        bytes.iter().all(|&b| b == 0),\n        \"all bytes of InlineFlexStr should be zero after zeroize, got: {bytes:?}\"\n    );\n}\n"
  },
  {
    "path": "tests/test_bytes.rs",
    "content": "#![cfg(feature = \"bytes\")]\n\nextern crate alloc;\n\nuse alloc::sync::Arc;\n\n#[cfg(feature = \"serde\")]\nuse flexstr::{LocalBytes, SharedBytes};\nuse inline_flexstr::INLINE_CAPACITY;\n\nmod common;\n\n// *** Serialize/Deserialize Tests ***\n\n#[cfg(feature = \"serde\")]\n#[test]\nfn serialize_deserialize_test_local_bytes() {\n    common::serialize::serialize_deserialize_test::<LocalBytes, [u8]>(b\"test\");\n}\n\n#[cfg(feature = \"serde\")]\n#[test]\nfn serialize_deserialize_test_shared_bytes() {\n    common::serialize::serialize_deserialize_test::<SharedBytes, [u8]>(b\"test\");\n}\n\n// *** Basic Tests ***\n\n#[test]\nfn test_creation_from_borrowed_bytes() {\n    common::basic::test_creation_from_borrowed::<[u8], Arc<[u8]>>(b\"test\");\n}\n\n#[test]\nfn test_creation_from_inline_bytes() {\n    common::basic::test_creation_from_inline::<[u8], Arc<[u8]>>(b\"test\");\n}\n\n#[test]\nfn test_creation_from_ref_counted_bytes() {\n    common::basic::test_creation_from_ref_counted::<[u8], Arc<[u8]>>((*b\"test\").into());\n}\n\n#[test]\nfn test_empty_bytes() {\n    common::basic::test_empty::<[u8], Arc<[u8]>>(b\"\");\n}\n\n#[test]\nfn test_accessors_bytes() {\n    common::basic::test_accessors::<[u8], Arc<[u8]>>(b\"test\");\n}\n\n#[test]\nfn test_clone_all_variants_bytes() {\n    common::basic::test_clone_all_variants::<[u8], Arc<[u8]>>(b\"test\");\n}\n\n#[test]\nfn test_default_bytes() {\n    common::basic::test_default::<[u8], Arc<[u8]>>();\n}\n\n// *** Conversion Tests ***\n\n#[test]\nfn test_to_owned_bytes() {\n    common::conversion::test_to_owned::<[u8], Arc<[u8]>>(b\"test\");\n}\n\n#[test]\nfn test_into_owned_bytes() {\n    common::conversion::test_into_owned::<[u8], Arc<[u8]>>(b\"test\");\n}\n\n#[test]\nfn test_to_owned_type_bytes() {\n    common::conversion::test_to_owned_type::<[u8], Arc<[u8]>>(b\"test\");\n}\n\n#[test]\nfn test_optimize_bytes() {\n    common::conversion::test_optimize::<[u8], Arc<[u8]>>(b\"test\");\n}\n\n#[test]\nfn test_from_borrowed_ref_bytes() {\n    common::conversion::test_from_borrowed_ref::<[u8], Arc<[u8]>>(b\"test\");\n}\n\n#[test]\nfn test_from_inline_flex_str_bytes() {\n    common::conversion::test_from_inline_flex_str::<[u8], Arc<[u8]>>(b\"test\");\n}\n\n// *** Comparison Tests ***\n\n#[test]\nfn test_partial_eq_bytes() {\n    common::comparison::test_partial_eq::<[u8], Arc<[u8]>>(b\"test\", b\"test\");\n    common::comparison::test_partial_eq::<[u8], Arc<[u8]>>(b\"test\", b\"other\");\n}\n\n#[test]\nfn test_eq_bytes() {\n    common::comparison::test_eq::<[u8], Arc<[u8]>>(b\"test\");\n}\n\n#[test]\nfn test_partial_ord_bytes() {\n    common::comparison::test_partial_ord::<[u8], Arc<[u8]>>(b\"a\", b\"b\");\n}\n\n#[test]\nfn test_ord_bytes() {\n    common::comparison::test_ord::<[u8], Arc<[u8]>>(b\"a\", b\"b\");\n}\n\n#[test]\nfn test_hash_bytes() {\n    common::comparison::test_hash::<[u8], Arc<[u8]>>(b\"test\");\n}\n\n#[test]\nfn test_comparison_with_ref_bytes() {\n    common::comparison::test_comparison_with_ref::<[u8], Arc<[u8]>>(b\"test\");\n}\n\n// *** Storage Tests ***\n\n#[test]\nfn test_variant_queries_bytes() {\n    common::storage::test_variant_queries::<[u8], Arc<[u8]>>(b\"test\");\n}\n\n#[test]\nfn test_transition_borrowed_to_inlined_bytes() {\n    common::storage::test_transition_borrowed_to_inlined::<[u8], Arc<[u8]>>(b\"test\");\n}\n\n#[test]\nfn test_storage_optimization_bytes() {\n    common::storage::test_storage_optimization::<[u8], Arc<[u8]>>(b\"test\");\n}\n\n// *** Edge Case Tests ***\n\n#[test]\nfn test_empty_string_bytes() {\n    common::edge_cases::test_empty_string::<[u8], Arc<[u8]>>(b\"\");\n}\n\n#[test]\nfn test_various_lengths_bytes() {\n    common::edge_cases::test_various_lengths::<[u8], Arc<[u8]>>(b\"test\");\n    common::edge_cases::test_various_lengths::<[u8], Arc<[u8]>>(b\"\");\n    common::edge_cases::test_various_lengths::<[u8], Arc<[u8]>>(b\"a\");\n}\n\n#[test]\nfn test_special_content_bytes() {\n    common::edge_cases::test_special_content::<[u8], Arc<[u8]>>(b\"test\");\n}\n\n#[test]\nfn test_clone_variants_bytes() {\n    common::edge_cases::test_clone_variants::<[u8], Arc<[u8]>>(b\"test\");\n}\n\n// *** StringLike Tests ***\n\n#[test]\nfn test_into_vec_bytes() {\n    common::stringlike::test_into_vec_bytes::<[u8], Arc<[u8]>>(b\"test\");\n}\n\n#[test]\nfn test_to_vec_bytes() {\n    common::stringlike::test_to_vec_bytes::<[u8], Arc<[u8]>>(b\"test\");\n}\n\n// *** TryFrom Tests ***\n\n// *** From Tests ***\n\n#[test]\nfn test_from_vec_bytes() {\n    common::from::test_from_vec_bytes::<Arc<[u8]>>();\n}\n\n#[test]\nfn test_from_str_bytes() {\n    common::from::test_from_str_bytes::<Arc<[u8]>>();\n}\n\n// *** FromStr Tests ***\n\n#[test]\nfn test_from_str_bytes_success() {\n    common::from_str::test_from_str_bytes_success::<Arc<[u8]>>();\n}\n\n// *** AsRef Tests ***\n\n#[test]\nfn test_as_ref_bytes_flex_str() {\n    common::as_ref::test_as_ref_bytes_flex_str::<Arc<[u8]>>(b\"test\");\n}\n\n// *** FlexStr Edge Cases ***\n\n#[test]\nfn test_optimize_ref_counted_to_inlined_bytes() {\n    common::inline_edge_cases::test_optimize_ref_counted_to_inlined::<[u8], Arc<[u8]>>(b\"test\");\n}\n\n#[test]\nfn test_optimize_ref_counted_stays_ref_counted_bytes() {\n    let long_bytes: &'static [u8] = Box::leak(Box::new([0u8; INLINE_CAPACITY + 1]));\n    common::inline_edge_cases::test_optimize_ref_counted_stays_ref_counted::<[u8], Arc<[u8]>>(\n        long_bytes,\n    );\n}\n\n// *** Mutation Tests ***\n\n#[test]\nfn test_mutation_borrowed_bytes() {\n    common::mutate::test_mutation_borrowed::<[u8], Arc<[u8]>>(b\"test\");\n}\n\n#[test]\nfn test_mutation_inlined_bytes() {\n    common::mutate::test_mutation_inlined::<[u8], Arc<[u8]>>(b\"test\");\n}\n\n#[test]\nfn test_mutation_ref_counted_bytes() {\n    common::mutate::test_mutation_ref_counted::<[u8], Arc<[u8]>>((*b\"test\").into());\n}\n\n#[test]\nfn test_mutation_boxed_bytes() {\n    common::mutate::test_mutation_boxed::<[u8], Arc<[u8]>>(b\"test\".into());\n}\n\n// *** Zeroize Tests ***\n\n#[cfg(feature = \"zeroize\")]\n#[test]\nfn test_zeroize_inlined_bytes() {\n    common::zeroize::test_zeroize_inlined::<[u8], Arc<[u8]>>(b\"test\");\n}\n\n#[cfg(feature = \"zeroize\")]\n#[test]\nfn test_zeroize_borrowed_bytes() {\n    common::zeroize::test_zeroize_borrowed::<[u8], Arc<[u8]>>(b\"test\");\n}\n\n#[cfg(feature = \"zeroize\")]\n#[test]\nfn test_zeroize_ref_counted_bytes() {\n    common::zeroize::test_zeroize_ref_counted::<[u8], Arc<[u8]>>(Arc::from(&b\"test\"[..]));\n}\n\n#[cfg(feature = \"zeroize\")]\n#[test]\nfn test_zeroize_ref_counted_shared_bytes() {\n    common::zeroize::test_zeroize_ref_counted_shared::<[u8], Arc<[u8]>>(Arc::from(&b\"test\"[..]));\n}\n\n#[cfg(feature = \"zeroize\")]\n#[test]\nfn test_zeroize_boxed_bytes() {\n    common::zeroize::test_zeroize_boxed::<[u8], Arc<[u8]>>(b\"test\");\n}\n\n#[cfg(feature = \"zeroize\")]\n#[test]\nfn test_zeroize_inline_bytes_cleared_bytes() {\n    common::zeroize::test_zeroize_inline_bytes_cleared::<[u8]>(b\"test\");\n}\n"
  },
  {
    "path": "tests/test_cstr.rs",
    "content": "#![cfg(feature = \"cstr\")]\n\nextern crate alloc;\n\nuse alloc::{rc::Rc, sync::Arc};\n\n#[cfg(feature = \"serde\")]\nuse flexstr::{LocalCStr, SharedCStr};\n\nuse core::ffi::CStr;\n\nmod common;\n\n// *** Serialize/Deserialize Tests ***\n\n#[cfg(feature = \"serde\")]\n#[test]\nfn serialize_deserialize_test_local_cstr() {\n    common::serialize::serialize_deserialize_test::<LocalCStr, CStr>(c\"test\");\n}\n\n#[cfg(feature = \"serde\")]\n#[test]\nfn serialize_deserialize_test_shared_cstr() {\n    common::serialize::serialize_deserialize_test::<SharedCStr, CStr>(c\"test\");\n}\n\n// *** Basic Tests ***\n\n#[test]\nfn test_creation_from_borrowed_cstr() {\n    common::basic::test_creation_from_borrowed::<CStr, Arc<CStr>>(c\"test\");\n}\n\n#[test]\nfn test_creation_from_inline_cstr() {\n    common::basic::test_creation_from_inline::<CStr, Arc<CStr>>(c\"test\");\n}\n\n#[test]\nfn test_creation_from_ref_counted_cstr() {\n    common::basic::test_creation_from_ref_counted::<CStr, Arc<CStr>>(c\"test\".into());\n}\n\n#[test]\nfn test_empty_cstr() {\n    common::basic::test_empty::<CStr, Arc<CStr>>(c\"\");\n}\n\n#[test]\nfn test_accessors_cstr() {\n    common::basic::test_accessors::<CStr, Arc<CStr>>(c\"test\");\n}\n\n#[test]\nfn test_clone_all_variants_cstr() {\n    common::basic::test_clone_all_variants::<CStr, Arc<CStr>>(c\"test\");\n}\n\n#[test]\nfn test_default_cstr() {\n    common::basic::test_default::<CStr, Arc<CStr>>();\n}\n\n// *** Conversion Tests ***\n\n#[test]\nfn test_to_owned_cstr() {\n    common::conversion::test_to_owned::<CStr, Arc<CStr>>(c\"test\");\n}\n\n#[test]\nfn test_into_owned_cstr() {\n    common::conversion::test_into_owned::<CStr, Arc<CStr>>(c\"test\");\n}\n\n#[test]\nfn test_to_owned_type_cstr() {\n    common::conversion::test_to_owned_type::<CStr, Arc<CStr>>(c\"test\");\n}\n\n#[test]\nfn test_optimize_cstr() {\n    common::conversion::test_optimize::<CStr, Arc<CStr>>(c\"test\");\n}\n\n#[test]\nfn test_from_borrowed_ref_cstr() {\n    common::conversion::test_from_borrowed_ref::<CStr, Arc<CStr>>(c\"test\");\n}\n\n#[test]\nfn test_from_inline_flex_str_cstr() {\n    common::conversion::test_from_inline_flex_str::<CStr, Arc<CStr>>(c\"test\");\n}\n\n// *** Comparison Tests ***\n\n#[test]\nfn test_partial_eq_cstr() {\n    common::comparison::test_partial_eq::<CStr, Arc<CStr>>(c\"test\", c\"test\");\n    common::comparison::test_partial_eq::<CStr, Arc<CStr>>(c\"test\", c\"other\");\n}\n\n#[test]\nfn test_eq_cstr() {\n    common::comparison::test_eq::<CStr, Arc<CStr>>(c\"test\");\n}\n\n#[test]\nfn test_hash_cstr() {\n    common::comparison::test_hash::<CStr, Arc<CStr>>(c\"test\");\n}\n\n#[test]\nfn test_comparison_with_ref_cstr() {\n    common::comparison::test_comparison_with_ref::<CStr, Arc<CStr>>(c\"test\");\n}\n\n// *** Storage Tests ***\n\n#[test]\nfn test_variant_queries_cstr() {\n    common::storage::test_variant_queries::<CStr, Arc<CStr>>(c\"test\");\n}\n\n#[test]\nfn test_transition_borrowed_to_inlined_cstr() {\n    common::storage::test_transition_borrowed_to_inlined::<CStr, Arc<CStr>>(c\"test\");\n}\n\n#[test]\nfn test_storage_optimization_cstr() {\n    common::storage::test_storage_optimization::<CStr, Arc<CStr>>(c\"test\");\n}\n\n// *** Edge Case Tests ***\n\n#[test]\nfn test_empty_string_cstr() {\n    common::edge_cases::test_empty_string::<CStr, Arc<CStr>>(c\"\");\n}\n\n#[test]\nfn test_various_lengths_cstr() {\n    common::edge_cases::test_various_lengths::<CStr, Arc<CStr>>(c\"test\");\n    common::edge_cases::test_various_lengths::<CStr, Arc<CStr>>(c\"\");\n}\n\n#[test]\nfn test_special_content_cstr() {\n    common::edge_cases::test_special_content::<CStr, Arc<CStr>>(c\"test\");\n}\n\n#[test]\nfn test_clone_variants_cstr() {\n    common::edge_cases::test_clone_variants::<CStr, Arc<CStr>>(c\"test\");\n}\n\n// *** Error Tests ***\n\n#[test]\nfn test_interior_nul_error() {\n    common::errors::test_interior_nul_error();\n}\n\n#[test]\nfn test_too_long_or_nul_error_too_long() {\n    common::errors::test_too_long_or_nul_error_too_long();\n}\n\n#[test]\nfn test_too_long_or_nul_error_nul() {\n    common::errors::test_too_long_or_nul_error_nul();\n}\n\n// *** StringLike Tests ***\n\n#[test]\nfn test_as_c_str() {\n    common::stringlike::test_as_c_str::<CStr, Arc<CStr>>(c\"test\");\n}\n\n#[test]\nfn test_into_c_string() {\n    common::stringlike::test_into_c_string::<CStr, Arc<CStr>>(c\"test\");\n}\n\n#[test]\nfn test_to_c_string() {\n    common::stringlike::test_to_c_string::<CStr, Arc<CStr>>(c\"test\");\n}\n\n// *** CStr-Specific Tests ***\n\n#[test]\nfn test_try_from_bytes_with_nul() {\n    common::cstr_specific::test_try_from_bytes_with_nul::<Arc<CStr>>();\n}\n\n#[test]\nfn test_try_from_bytes_without_nul() {\n    common::cstr_specific::test_try_from_bytes_without_nul::<Arc<CStr>>();\n}\n\n#[test]\nfn test_try_from_bytes_interior_nul() {\n    common::cstr_specific::test_try_from_bytes_interior_nul::<Arc<CStr>>();\n}\n\n#[test]\nfn test_as_bytes_with_nul() {\n    common::cstr_specific::test_as_bytes_with_nul::<Arc<CStr>>(c\"test\");\n}\n\n// *** Mutation Tests ***\n\n#[test]\nfn test_mutation_borrowed_shared_cstr() {\n    common::mutate_fallback::test_mutation_immutable_bytes_borrowed::<CStr, Arc<CStr>>(c\"test\");\n}\n\n#[test]\nfn test_mutation_borrowed_local_cstr() {\n    common::mutate_fallback::test_mutation_immutable_bytes_borrowed::<CStr, Rc<CStr>>(c\"test\");\n}\n\n#[test]\nfn test_mutation_inlined_shared_cstr() {\n    common::mutate_fallback::test_mutation_immutable_bytes_inlined::<CStr, Arc<CStr>>(c\"test\");\n}\n\n#[test]\nfn test_mutation_inlined_local_cstr() {\n    common::mutate_fallback::test_mutation_immutable_bytes_inlined::<CStr, Rc<CStr>>(c\"test\");\n}\n\n#[test]\nfn test_mutation_shared_ref_counted_cstr() {\n    common::mutate_fallback::test_mutation_immutable_bytes_ref_counted::<CStr, Arc<CStr>>(\n        c\"test\".into(),\n    );\n}\n\n#[test]\nfn test_mutation_local_ref_counted_cstr() {\n    common::mutate_fallback::test_mutation_immutable_bytes_ref_counted::<CStr, Rc<CStr>>(\n        c\"test\".into(),\n    );\n}\n\n// NOTE: Boxed strings don't use Rc/Arc, so we don't need to test both\n#[test]\nfn test_mutation_boxed_cstr() {\n    common::mutate_fallback::test_mutation_immutable_bytes_boxed::<CStr, Arc<CStr>>(c\"test\".into());\n}\n\n// *** PartialEq with Owned Types Tests ***\n\n#[test]\nfn test_partial_eq_with_owned_types_cstr() {\n    common::comparison::test_partial_eq_with_owned_types::<CStr, Arc<CStr>>(c\"test\");\n}\n\n// *** TryFrom Tests ***\n\n#[test]\nfn test_try_from_str_cstr() {\n    common::try_from::test_try_from_str_cstr::<Arc<CStr>>();\n}\n\n#[test]\nfn test_try_from_bytes_cstr() {\n    common::try_from::test_try_from_bytes_cstr::<Arc<CStr>>();\n}\n\n// *** FromStr Tests ***\n\n#[test]\nfn test_from_str_cstr_success() {\n    common::from_str::test_from_str_cstr_success::<Arc<CStr>>();\n}\n\n#[test]\nfn test_from_str_cstr_error() {\n    common::from_str::test_from_str_cstr_error::<Arc<CStr>>();\n}\n\n// *** AsRef Tests ***\n\n#[test]\nfn test_as_ref_cstr_flex_str() {\n    common::as_ref::test_as_ref_cstr_flex_str::<Arc<CStr>>(c\"test\");\n}\n\n// *** Zeroize Tests ***\n\n#[cfg(feature = \"zeroize\")]\n#[test]\nfn test_zeroize_inlined_cstr() {\n    common::zeroize::test_zeroize_inlined::<CStr, Arc<CStr>>(c\"test\");\n}\n\n#[cfg(feature = \"zeroize\")]\n#[test]\nfn test_zeroize_borrowed_cstr() {\n    common::zeroize::test_zeroize_borrowed::<CStr, Arc<CStr>>(c\"test\");\n}\n\n#[cfg(feature = \"zeroize\")]\n#[test]\nfn test_zeroize_ref_counted_cstr() {\n    common::zeroize::test_zeroize_ref_counted::<CStr, Arc<CStr>>(Arc::from(c\"test\"));\n}\n\n#[cfg(feature = \"zeroize\")]\n#[test]\nfn test_zeroize_ref_counted_shared_cstr() {\n    common::zeroize::test_zeroize_ref_counted_shared::<CStr, Arc<CStr>>(Arc::from(c\"test\"));\n}\n\n#[cfg(feature = \"zeroize\")]\n#[test]\nfn test_zeroize_boxed_cstr() {\n    common::zeroize::test_zeroize_boxed::<CStr, Arc<CStr>>(c\"test\");\n}\n\n#[cfg(feature = \"zeroize\")]\n#[test]\nfn test_zeroize_inline_bytes_cleared_cstr() {\n    common::zeroize::test_zeroize_inline_bytes_cleared::<CStr>(c\"test\");\n}\n"
  },
  {
    "path": "tests/test_osstr.rs",
    "content": "#![cfg(all(feature = \"std\", feature = \"osstr\"))]\n\nextern crate alloc;\n\nuse alloc::{rc::Rc, sync::Arc};\nuse std::ffi::OsStr;\n\n#[cfg(feature = \"serde\")]\nuse flexstr::{LocalOsStr, SharedOsStr};\nuse inline_flexstr::INLINE_CAPACITY;\n\nmod common;\n\n// *** Serialize/Deserialize Tests ***\n\n#[cfg(feature = \"serde\")]\n#[test]\nfn serialize_deserialize_test_local_osstr() {\n    common::serialize::serialize_deserialize_test::<LocalOsStr, OsStr>(OsStr::new(\"test\"));\n}\n\n#[cfg(feature = \"serde\")]\n#[test]\nfn serialize_deserialize_test_shared_osstr() {\n    common::serialize::serialize_deserialize_test::<SharedOsStr, OsStr>(OsStr::new(\"test\"));\n}\n\n// *** Basic Tests ***\n\n#[test]\nfn test_creation_from_borrowed_osstr() {\n    common::basic::test_creation_from_borrowed::<OsStr, Arc<OsStr>>(OsStr::new(\"test\"));\n}\n\n#[test]\nfn test_creation_from_inline_osstr() {\n    common::basic::test_creation_from_inline::<OsStr, Arc<OsStr>>(OsStr::new(\"test\"));\n}\n\n#[test]\nfn test_creation_from_ref_counted_osstr() {\n    common::basic::test_creation_from_ref_counted::<OsStr, Arc<OsStr>>(OsStr::new(\"test\").into());\n}\n\n#[test]\nfn test_empty_osstr() {\n    common::basic::test_empty::<OsStr, Arc<OsStr>>(OsStr::new(\"\"));\n}\n\n#[test]\nfn test_accessors_osstr() {\n    common::basic::test_accessors::<OsStr, Arc<OsStr>>(OsStr::new(\"test\"));\n}\n\n#[test]\nfn test_clone_all_variants_osstr() {\n    common::basic::test_clone_all_variants::<OsStr, Arc<OsStr>>(OsStr::new(\"test\"));\n}\n\n#[test]\nfn test_default_osstr() {\n    common::basic::test_default::<OsStr, Arc<OsStr>>();\n}\n\n// *** Conversion Tests ***\n\n#[test]\nfn test_to_owned_osstr() {\n    common::conversion::test_to_owned::<OsStr, Arc<OsStr>>(OsStr::new(\"test\"));\n}\n\n#[test]\nfn test_into_owned_osstr() {\n    common::conversion::test_into_owned::<OsStr, Arc<OsStr>>(OsStr::new(\"test\"));\n}\n\n#[test]\nfn test_to_owned_type_osstr() {\n    common::conversion::test_to_owned_type::<OsStr, Arc<OsStr>>(OsStr::new(\"test\"));\n}\n\n#[test]\nfn test_optimize_osstr() {\n    common::conversion::test_optimize::<OsStr, Arc<OsStr>>(OsStr::new(\"test\"));\n}\n\n#[test]\nfn test_from_borrowed_ref_osstr() {\n    common::conversion::test_from_borrowed_ref::<OsStr, Arc<OsStr>>(OsStr::new(\"test\"));\n}\n\n#[test]\nfn test_from_inline_flex_str_osstr() {\n    common::conversion::test_from_inline_flex_str::<OsStr, Arc<OsStr>>(OsStr::new(\"test\"));\n}\n\n// *** Comparison Tests ***\n\n#[test]\nfn test_partial_eq_osstr() {\n    common::comparison::test_partial_eq::<OsStr, Arc<OsStr>>(\n        OsStr::new(\"test\"),\n        OsStr::new(\"test\"),\n    );\n    common::comparison::test_partial_eq::<OsStr, Arc<OsStr>>(\n        OsStr::new(\"test\"),\n        OsStr::new(\"other\"),\n    );\n}\n\n#[test]\nfn test_eq_osstr() {\n    common::comparison::test_eq::<OsStr, Arc<OsStr>>(OsStr::new(\"test\"));\n}\n\n#[test]\nfn test_hash_osstr() {\n    common::comparison::test_hash::<OsStr, Arc<OsStr>>(OsStr::new(\"test\"));\n}\n\n#[test]\nfn test_comparison_with_ref_osstr() {\n    common::comparison::test_comparison_with_ref::<OsStr, Arc<OsStr>>(OsStr::new(\"test\"));\n}\n\n// *** Storage Tests ***\n\n#[test]\nfn test_variant_queries_osstr() {\n    common::storage::test_variant_queries::<OsStr, Arc<OsStr>>(OsStr::new(\"test\"));\n}\n\n#[test]\nfn test_transition_borrowed_to_inlined_osstr() {\n    common::storage::test_transition_borrowed_to_inlined::<OsStr, Arc<OsStr>>(OsStr::new(\"test\"));\n}\n\n#[test]\nfn test_storage_optimization_osstr() {\n    common::storage::test_storage_optimization::<OsStr, Arc<OsStr>>(OsStr::new(\"test\"));\n}\n\n// *** Edge Case Tests ***\n\n#[test]\nfn test_empty_string_osstr() {\n    common::edge_cases::test_empty_string::<OsStr, Arc<OsStr>>(OsStr::new(\"\"));\n}\n\n#[test]\nfn test_various_lengths_osstr() {\n    common::edge_cases::test_various_lengths::<OsStr, Arc<OsStr>>(OsStr::new(\"test\"));\n    common::edge_cases::test_various_lengths::<OsStr, Arc<OsStr>>(OsStr::new(\"\"));\n}\n\n#[test]\nfn test_special_content_osstr() {\n    common::edge_cases::test_special_content::<OsStr, Arc<OsStr>>(OsStr::new(\"test\"));\n}\n\n#[test]\nfn test_clone_variants_osstr() {\n    common::edge_cases::test_clone_variants::<OsStr, Arc<OsStr>>(OsStr::new(\"test\"));\n}\n\n// *** StringLike Tests ***\n\n#[test]\nfn test_as_os_str() {\n    common::stringlike::test_as_os_str::<OsStr, Arc<OsStr>>(OsStr::new(\"test\"));\n}\n\n#[test]\nfn test_into_os_string() {\n    common::stringlike::test_into_os_string::<OsStr, Arc<OsStr>>(OsStr::new(\"test\"));\n}\n\n#[test]\nfn test_to_os_string() {\n    common::stringlike::test_to_os_string::<OsStr, Arc<OsStr>>(OsStr::new(\"test\"));\n}\n\n// *** TryFrom Tests ***\n\n// *** From Tests ***\n\n#[test]\nfn test_from_os_string() {\n    common::from::test_from_os_string::<Arc<OsStr>>();\n}\n\n#[test]\nfn test_from_string_osstr() {\n    common::from::test_from_string_osstr::<Arc<OsStr>>();\n}\n\n#[test]\nfn test_from_path_buf_osstr() {\n    common::from::test_from_path_buf_osstr::<Arc<OsStr>>();\n}\n\n#[test]\nfn test_from_str_ref_osstr() {\n    common::from::test_from_str_ref_osstr::<Arc<OsStr>>();\n}\n\n#[test]\nfn test_from_path_ref_osstr() {\n    common::from::test_from_path_ref_osstr::<Arc<OsStr>>();\n}\n\n// *** FromStr Tests ***\n\n#[test]\nfn test_from_str_osstr_success() {\n    common::from_str::test_from_str_osstr_success::<Arc<OsStr>>();\n}\n\n// *** AsRef Tests ***\n\n#[test]\nfn test_as_ref_osstr_flex_str() {\n    common::as_ref::test_as_ref_osstr_flex_str::<Arc<OsStr>>(OsStr::new(\"test\"));\n}\n\n// *** FlexStr Edge Cases ***\n\n#[test]\nfn test_optimize_ref_counted_to_inlined_osstr() {\n    common::inline_edge_cases::test_optimize_ref_counted_to_inlined::<OsStr, Arc<OsStr>>(\n        OsStr::new(\"test\"),\n    );\n}\n\n#[test]\nfn test_optimize_ref_counted_stays_ref_counted_osstr() {\n    let long_str: &'static str = Box::leak(Box::new(\"x\".repeat(INLINE_CAPACITY + 1)));\n    common::inline_edge_cases::test_optimize_ref_counted_stays_ref_counted::<OsStr, Arc<OsStr>>(\n        OsStr::new(long_str),\n    );\n}\n\n// *** Mutation Tests ***\n\n#[test]\nfn test_mutation_shared_borrowed_osstr() {\n    common::mutate_fallback::test_mutation_immutable_bytes_borrowed::<OsStr, Arc<OsStr>>(\n        OsStr::new(\"test\"),\n    );\n}\n\n#[test]\nfn test_mutation_local_borrowed_osstr() {\n    common::mutate_fallback::test_mutation_immutable_bytes_borrowed::<OsStr, Rc<OsStr>>(\n        OsStr::new(\"test\"),\n    );\n}\n\n#[test]\nfn test_mutation_shared_inlined_osstr() {\n    common::mutate_fallback::test_mutation_immutable_bytes_inlined::<OsStr, Arc<OsStr>>(\n        OsStr::new(\"test\"),\n    );\n}\n\n#[test]\nfn test_mutation_local_inlined_osstr() {\n    common::mutate_fallback::test_mutation_immutable_bytes_inlined::<OsStr, Rc<OsStr>>(OsStr::new(\n        \"test\",\n    ));\n}\n\n#[test]\nfn test_mutation_shared_ref_counted_osstr() {\n    common::mutate_fallback::test_mutation_immutable_bytes_ref_counted::<OsStr, Arc<OsStr>>(\n        OsStr::new(\"test\").into(),\n    );\n}\n\n#[test]\nfn test_mutation_local_ref_counted_osstr() {\n    common::mutate_fallback::test_mutation_immutable_bytes_ref_counted::<OsStr, Rc<OsStr>>(\n        OsStr::new(\"test\").into(),\n    );\n}\n\n// NOTE: Boxed strings don't use Rc/Arc, so we don't need to test both\n#[test]\nfn test_mutation_boxed_osstr() {\n    common::mutate_fallback::test_mutation_immutable_bytes_boxed::<OsStr, Arc<OsStr>>(\n        OsStr::new(\"test\").into(),\n    );\n}\n\n// *** Zeroize Tests ***\n\n#[cfg(feature = \"zeroize\")]\n#[test]\nfn test_zeroize_inlined_osstr() {\n    common::zeroize::test_zeroize_inlined::<OsStr, Arc<OsStr>>(OsStr::new(\"test\"));\n}\n\n#[cfg(feature = \"zeroize\")]\n#[test]\nfn test_zeroize_borrowed_osstr() {\n    common::zeroize::test_zeroize_borrowed::<OsStr, Arc<OsStr>>(OsStr::new(\"test\"));\n}\n\n#[cfg(feature = \"zeroize\")]\n#[test]\nfn test_zeroize_ref_counted_osstr() {\n    common::zeroize::test_zeroize_ref_counted::<OsStr, Arc<OsStr>>(Arc::from(OsStr::new(\"test\")));\n}\n\n#[cfg(feature = \"zeroize\")]\n#[test]\nfn test_zeroize_ref_counted_shared_osstr() {\n    common::zeroize::test_zeroize_ref_counted_shared::<OsStr, Arc<OsStr>>(Arc::from(OsStr::new(\n        \"test\",\n    )));\n}\n\n#[cfg(feature = \"zeroize\")]\n#[test]\nfn test_zeroize_boxed_osstr() {\n    common::zeroize::test_zeroize_boxed::<OsStr, Arc<OsStr>>(OsStr::new(\"test\"));\n}\n\n#[cfg(feature = \"zeroize\")]\n#[test]\nfn test_zeroize_inline_bytes_cleared_osstr() {\n    common::zeroize::test_zeroize_inline_bytes_cleared::<OsStr>(OsStr::new(\"test\"));\n}\n"
  },
  {
    "path": "tests/test_path.rs",
    "content": "#![cfg(all(feature = \"std\", feature = \"path\"))]\n\nextern crate alloc;\n\nuse alloc::{rc::Rc, sync::Arc};\n\n#[cfg(feature = \"serde\")]\nuse flexstr::{LocalPath, SharedPath};\nuse inline_flexstr::INLINE_CAPACITY;\n\nuse std::path::Path;\n\nmod common;\n\n// *** Serialize/Deserialize Tests ***\n\n#[cfg(feature = \"serde\")]\n#[test]\nfn serialize_deserialize_test_local_path() {\n    common::serialize::serialize_deserialize_test::<LocalPath, Path>(Path::new(\"test\"));\n}\n\n#[cfg(feature = \"serde\")]\n#[test]\nfn serialize_deserialize_test_shared_path() {\n    common::serialize::serialize_deserialize_test::<SharedPath, Path>(Path::new(\"test\"));\n}\n\n// *** Basic Tests ***\n\n#[test]\nfn test_creation_from_borrowed_path() {\n    common::basic::test_creation_from_borrowed::<Path, Arc<Path>>(Path::new(\"test\"));\n}\n\n#[test]\nfn test_creation_from_inline_path() {\n    common::basic::test_creation_from_inline::<Path, Arc<Path>>(Path::new(\"test\"));\n}\n\n#[test]\nfn test_creation_from_ref_counted_path() {\n    common::basic::test_creation_from_ref_counted::<Path, Arc<Path>>(Path::new(\"test\").into());\n}\n\n#[test]\nfn test_empty_path() {\n    common::basic::test_empty::<Path, Arc<Path>>(Path::new(\"\"));\n}\n\n#[test]\nfn test_accessors_path() {\n    common::basic::test_accessors::<Path, Arc<Path>>(Path::new(\"test\"));\n}\n\n#[test]\nfn test_clone_all_variants_path() {\n    common::basic::test_clone_all_variants::<Path, Arc<Path>>(Path::new(\"test\"));\n}\n\n// Path doesn't implement Default, so skip this test\n// #[test]\n// fn test_default_path() {\n//     common::basic::test_default::<Path, Arc<Path>>();\n// }\n\n// *** Conversion Tests ***\n\n#[test]\nfn test_to_owned_path() {\n    common::conversion::test_to_owned::<Path, Arc<Path>>(Path::new(\"test\"));\n}\n\n#[test]\nfn test_into_owned_path() {\n    common::conversion::test_into_owned::<Path, Arc<Path>>(Path::new(\"test\"));\n}\n\n#[test]\nfn test_to_owned_type_path() {\n    common::conversion::test_to_owned_type::<Path, Arc<Path>>(Path::new(\"test\"));\n}\n\n#[test]\nfn test_optimize_path() {\n    common::conversion::test_optimize::<Path, Arc<Path>>(Path::new(\"test\"));\n}\n\n#[test]\nfn test_from_borrowed_ref_path() {\n    common::conversion::test_from_borrowed_ref::<Path, Arc<Path>>(Path::new(\"test\"));\n}\n\n#[test]\nfn test_from_inline_flex_str_path() {\n    common::conversion::test_from_inline_flex_str::<Path, Arc<Path>>(Path::new(\"test\"));\n}\n\n// *** Comparison Tests ***\n\n#[test]\nfn test_partial_eq_path() {\n    common::comparison::test_partial_eq::<Path, Arc<Path>>(Path::new(\"test\"), Path::new(\"test\"));\n    common::comparison::test_partial_eq::<Path, Arc<Path>>(Path::new(\"test\"), Path::new(\"other\"));\n}\n\n#[test]\nfn test_eq_path() {\n    common::comparison::test_eq::<Path, Arc<Path>>(Path::new(\"test\"));\n}\n\n#[test]\nfn test_hash_path() {\n    common::comparison::test_hash::<Path, Arc<Path>>(Path::new(\"test\"));\n}\n\n#[test]\nfn test_comparison_with_ref_path() {\n    common::comparison::test_comparison_with_ref::<Path, Arc<Path>>(Path::new(\"test\"));\n}\n\n// *** Storage Tests ***\n\n#[test]\nfn test_variant_queries_path() {\n    common::storage::test_variant_queries::<Path, Arc<Path>>(Path::new(\"test\"));\n}\n\n#[test]\nfn test_transition_borrowed_to_inlined_path() {\n    common::storage::test_transition_borrowed_to_inlined::<Path, Arc<Path>>(Path::new(\"test\"));\n}\n\n#[test]\nfn test_storage_optimization_path() {\n    common::storage::test_storage_optimization::<Path, Arc<Path>>(Path::new(\"test\"));\n}\n\n// *** Edge Case Tests ***\n\n#[test]\nfn test_empty_string_path() {\n    common::edge_cases::test_empty_string::<Path, Arc<Path>>(Path::new(\"\"));\n}\n\n#[test]\nfn test_various_lengths_path() {\n    common::edge_cases::test_various_lengths::<Path, Arc<Path>>(Path::new(\"test\"));\n    common::edge_cases::test_various_lengths::<Path, Arc<Path>>(Path::new(\"\"));\n}\n\n#[test]\nfn test_special_content_path() {\n    common::edge_cases::test_special_content::<Path, Arc<Path>>(Path::new(\"test\"));\n}\n\n#[test]\nfn test_clone_variants_path() {\n    common::edge_cases::test_clone_variants::<Path, Arc<Path>>(Path::new(\"test\"));\n}\n\n// *** StringLike Tests ***\n\n#[test]\nfn test_as_path() {\n    common::stringlike::test_as_path::<Path, Arc<Path>>(Path::new(\"test\"));\n}\n\n#[test]\nfn test_into_path_buf() {\n    common::stringlike::test_into_path_buf::<Path, Arc<Path>>(Path::new(\"test\"));\n}\n\n#[test]\nfn test_to_path_buf() {\n    common::stringlike::test_to_path_buf::<Path, Arc<Path>>(Path::new(\"test\"));\n}\n\n// *** TryFrom Tests ***\n\n// *** From Tests ***\n\n#[test]\nfn test_from_path_buf() {\n    common::from::test_from_path_buf::<Arc<Path>>();\n}\n\n#[test]\nfn test_from_string_path() {\n    common::from::test_from_string_path::<Arc<Path>>();\n}\n\n#[test]\nfn test_from_os_string_path() {\n    common::from::test_from_os_string_path::<Arc<Path>>();\n}\n\n#[test]\nfn test_from_str_ref_path() {\n    common::from::test_from_str_ref_path::<Arc<Path>>();\n}\n\n#[test]\nfn test_from_osstr_ref_path() {\n    common::from::test_from_osstr_ref_path::<Arc<Path>>();\n}\n\n// *** FromStr Tests ***\n\n#[test]\nfn test_from_str_path_success() {\n    common::from_str::test_from_str_path_success::<Arc<Path>>();\n}\n\n// *** AsRef Tests ***\n\n#[test]\nfn test_as_ref_path_flex_str() {\n    common::as_ref::test_as_ref_path_flex_str::<Arc<Path>>(Path::new(\"test\"));\n}\n\n// *** FlexStr Edge Cases ***\n\n#[test]\nfn test_optimize_ref_counted_to_inlined_path() {\n    common::inline_edge_cases::test_optimize_ref_counted_to_inlined::<Path, Arc<Path>>(Path::new(\n        \"test\",\n    ));\n}\n\n#[test]\nfn test_optimize_ref_counted_stays_ref_counted_path() {\n    let long_str: &'static str = Box::leak(Box::new(\"x\".repeat(INLINE_CAPACITY + 1)));\n    common::inline_edge_cases::test_optimize_ref_counted_stays_ref_counted::<Path, Arc<Path>>(\n        Path::new(long_str),\n    );\n}\n\n// *** Mutation Tests ***\n\n#[test]\nfn test_mutation_borrowed_shared_path() {\n    common::mutate_fallback::test_mutation_immutable_bytes_borrowed::<Path, Arc<Path>>(Path::new(\n        \"test\",\n    ));\n}\n\n#[test]\nfn test_mutation_borrowed_local_path() {\n    common::mutate_fallback::test_mutation_immutable_bytes_borrowed::<Path, Rc<Path>>(Path::new(\n        \"test\",\n    ));\n}\n\n#[test]\nfn test_mutation_inlined_shared_path() {\n    common::mutate_fallback::test_mutation_immutable_bytes_inlined::<Path, Arc<Path>>(Path::new(\n        \"test\",\n    ));\n}\n\n#[test]\nfn test_mutation_inlined_local_path() {\n    common::mutate_fallback::test_mutation_immutable_bytes_inlined::<Path, Rc<Path>>(Path::new(\n        \"test\",\n    ));\n}\n\n#[test]\nfn test_mutation_shared_ref_counted_path() {\n    common::mutate_fallback::test_mutation_immutable_bytes_ref_counted::<Path, Arc<Path>>(\n        Path::new(\"test\").into(),\n    );\n}\n\n#[test]\nfn test_mutation_local_ref_counted_path() {\n    common::mutate_fallback::test_mutation_immutable_bytes_ref_counted::<Path, Rc<Path>>(\n        Path::new(\"test\").into(),\n    );\n}\n\n// NOTE: Boxed strings don't use Rc/Arc, so we don't need to test both\n#[test]\nfn test_mutation_boxed_path() {\n    common::mutate_fallback::test_mutation_immutable_bytes_boxed::<Path, Arc<Path>>(\n        Path::new(\"test\").into(),\n    );\n}\n\n// *** Zeroize Tests ***\n\n#[cfg(feature = \"zeroize\")]\n#[test]\nfn test_zeroize_inlined_path() {\n    common::zeroize::test_zeroize_inlined::<Path, Arc<Path>>(Path::new(\"test\"));\n}\n\n#[cfg(feature = \"zeroize\")]\n#[test]\nfn test_zeroize_borrowed_path() {\n    common::zeroize::test_zeroize_borrowed::<Path, Arc<Path>>(Path::new(\"test\"));\n}\n\n#[cfg(feature = \"zeroize\")]\n#[test]\nfn test_zeroize_ref_counted_path() {\n    common::zeroize::test_zeroize_ref_counted::<Path, Arc<Path>>(Arc::from(Path::new(\"test\")));\n}\n\n#[cfg(feature = \"zeroize\")]\n#[test]\nfn test_zeroize_ref_counted_shared_path() {\n    common::zeroize::test_zeroize_ref_counted_shared::<Path, Arc<Path>>(Arc::from(Path::new(\n        \"test\",\n    )));\n}\n\n#[cfg(feature = \"zeroize\")]\n#[test]\nfn test_zeroize_boxed_path() {\n    common::zeroize::test_zeroize_boxed::<Path, Arc<Path>>(Path::new(\"test\"));\n}\n\n#[cfg(feature = \"zeroize\")]\n#[test]\nfn test_zeroize_inline_bytes_cleared_path() {\n    common::zeroize::test_zeroize_inline_bytes_cleared::<Path>(Path::new(\"test\"));\n}\n"
  },
  {
    "path": "tests/test_str.rs",
    "content": "#![cfg(feature = \"str\")]\n\nextern crate alloc;\n\nuse alloc::sync::Arc;\n\n#[cfg(feature = \"serde\")]\nuse flexstr::LocalStr;\n#[cfg(any(feature = \"prost\", feature = \"serde\", feature = \"utoipa\"))]\nuse flexstr::SharedStr;\nuse inline_flexstr::INLINE_CAPACITY;\n\nmod common;\n\n// *** Serialize/Deserialize Tests ***\n\n#[cfg(feature = \"serde\")]\n#[test]\nfn serialize_deserialize_test_local_str() {\n    common::serialize::serialize_deserialize_test::<LocalStr, str>(\"test\");\n}\n\n#[cfg(feature = \"serde\")]\n#[test]\nfn serialize_deserialize_test_shared_str() {\n    common::serialize::serialize_deserialize_test::<SharedStr, str>(\"test\");\n}\n\n// *** Basic Tests ***\n\n#[test]\nfn test_creation_from_borrowed_str() {\n    common::basic::test_creation_from_borrowed::<str, Arc<str>>(\"test\");\n}\n\n#[test]\nfn test_creation_from_owned_str() {\n    common::basic::test_creation_from_owned::<str, Arc<str>>(\"test\".to_string());\n}\n\n#[test]\nfn test_creation_from_inline_str() {\n    common::basic::test_creation_from_inline::<str, Arc<str>>(\"test\");\n}\n\n#[test]\nfn test_creation_from_ref_counted_str() {\n    common::basic::test_creation_from_ref_counted::<str, Arc<str>>(\"test\".into());\n}\n\n#[test]\nfn test_creation_from_boxed_str() {\n    common::basic::test_creation_from_boxed::<str, Arc<str>>(\"test\");\n}\n\n#[test]\nfn test_empty_str() {\n    common::basic::test_empty::<str, Arc<str>>(\"\");\n}\n\n#[test]\nfn test_accessors_str() {\n    common::basic::test_accessors::<str, Arc<str>>(\"test\");\n}\n\n#[test]\nfn test_clone_all_variants_str() {\n    common::basic::test_clone_all_variants::<str, Arc<str>>(\"test\");\n}\n\n#[test]\nfn test_default_str() {\n    common::basic::test_default::<str, Arc<str>>();\n}\n\n// *** Conversion Tests ***\n\n#[test]\nfn test_to_owned_str() {\n    common::conversion::test_to_owned::<str, Arc<str>>(\"test\");\n}\n\n#[test]\nfn test_into_owned_str() {\n    common::conversion::test_into_owned::<str, Arc<str>>(\"test\");\n}\n\n#[test]\nfn test_to_owned_type_str() {\n    common::conversion::test_to_owned_type::<str, Arc<str>>(\"test\");\n}\n\n#[test]\nfn test_into_owned_type_str() {\n    common::conversion::test_into_owned_type::<str, Arc<str>>(\"test\");\n}\n\n#[test]\nfn test_to_local_str() {\n    common::conversion::test_to_local::<str>(\"test\");\n}\n\n#[test]\nfn test_into_local_str() {\n    common::conversion::test_into_local::<str>(\"test\");\n}\n\n#[test]\nfn test_to_shared_str() {\n    common::conversion::test_to_shared::<str>(\"test\");\n}\n\n#[test]\nfn test_into_shared_str() {\n    common::conversion::test_into_shared::<str>(\"test\");\n}\n\n#[test]\nfn test_optimize_str() {\n    common::conversion::test_optimize::<str, Arc<str>>(\"test\");\n}\n\n#[test]\nfn test_from_borrowed_ref_str() {\n    common::conversion::test_from_borrowed_ref::<str, Arc<str>>(\"test\");\n}\n\n#[test]\nfn test_from_box_str() {\n    common::conversion::test_from_box::<str, Arc<str>>(\"test\");\n}\n\n#[test]\nfn test_from_inline_flex_str_str() {\n    common::conversion::test_from_inline_flex_str::<str, Arc<str>>(\"test\");\n}\n\n#[test]\nfn test_from_cow_str() {\n    common::conversion::test_from_cow::<str, Arc<str>>(\"test\");\n}\n\n// *** Comparison Tests ***\n\n#[test]\nfn test_partial_eq_str() {\n    common::comparison::test_partial_eq::<str, Arc<str>>(\"test\", \"test\");\n    common::comparison::test_partial_eq::<str, Arc<str>>(\"test\", \"other\");\n}\n\n#[test]\nfn test_eq_str() {\n    common::comparison::test_eq::<str, Arc<str>>(\"test\");\n}\n\n#[test]\nfn test_partial_ord_str() {\n    common::comparison::test_partial_ord::<str, Arc<str>>(\"a\", \"b\");\n}\n\n#[test]\nfn test_ord_str() {\n    common::comparison::test_ord::<str, Arc<str>>(\"a\", \"b\");\n}\n\n#[test]\nfn test_hash_str() {\n    common::comparison::test_hash::<str, Arc<str>>(\"test\");\n}\n\n#[test]\nfn test_comparison_with_ref_str() {\n    common::comparison::test_comparison_with_ref::<str, Arc<str>>(\"test\");\n}\n\n#[test]\nfn test_comparison_with_owned_str() {\n    common::comparison::test_comparison_with_owned::<str, Arc<str>>(\"test\");\n}\n\n#[test]\nfn test_comparison_with_inline_str() {\n    common::comparison::test_comparison_with_inline::<str, Arc<str>>(\"test\");\n}\n\n#[test]\nfn test_partial_eq_with_owned_types_str() {\n    common::comparison::test_partial_eq_with_owned_types::<str, Arc<str>>(\"test\");\n}\n\n// *** Storage Tests ***\n\n#[test]\nfn test_variant_queries_str() {\n    common::storage::test_variant_queries::<str, Arc<str>>(\"test\");\n}\n\n#[test]\nfn test_transition_borrowed_to_inlined_str() {\n    common::storage::test_transition_borrowed_to_inlined::<str, Arc<str>>(\"test\");\n}\n\n#[test]\nfn test_transition_borrowed_to_ref_counted_str() {\n    common::storage::test_transition_borrowed_to_ref_counted::<str, Arc<str>>(\n        \"this is a very long string that definitely won't fit inline\",\n    );\n}\n\n#[test]\nfn test_transition_inlined_to_ref_counted_str() {\n    common::storage::test_transition_inlined_to_ref_counted::<str, Arc<str>>(\"test\");\n}\n\n#[test]\nfn test_transition_boxed_to_optimized_str() {\n    common::storage::test_transition_boxed_to_optimized::<str, Arc<str>>(\"test\");\n}\n\n#[test]\nfn test_storage_optimization_str() {\n    common::storage::test_storage_optimization::<str, Arc<str>>(\"test\");\n}\n\n// *** Edge Case Tests ***\n\n#[test]\nfn test_empty_string_str() {\n    common::edge_cases::test_empty_string::<str, Arc<str>>(\"\");\n}\n\n#[test]\nfn test_capacity_boundary_exact_str() {\n    // Create a string exactly at capacity\n    let s = \"a\".repeat(INLINE_CAPACITY);\n    let s_static: &'static str = Box::leak(s.into_boxed_str());\n    common::edge_cases::test_capacity_boundary_exact::<str, Arc<str>>(s_static);\n}\n\n#[test]\nfn test_capacity_boundary_overflow_str() {\n    common::edge_cases::test_capacity_boundary_overflow::<str>(\"test\");\n}\n\n#[test]\nfn test_try_from_too_long_str() {\n    common::edge_cases::test_try_from_too_long();\n}\n\n#[test]\nfn test_various_lengths_str() {\n    common::edge_cases::test_various_lengths::<str, Arc<str>>(\"test\");\n    common::edge_cases::test_various_lengths::<str, Arc<str>>(\"\");\n    common::edge_cases::test_various_lengths::<str, Arc<str>>(\"a\");\n}\n\n#[test]\nfn test_special_content_str() {\n    common::edge_cases::test_special_content::<str, Arc<str>>(\"test\");\n    common::edge_cases::test_special_content::<str, Arc<str>>(\"hello\\nworld\");\n    common::edge_cases::test_special_content::<str, Arc<str>>(\"🚀\");\n}\n\n#[test]\nfn test_clone_variants_str() {\n    common::edge_cases::test_clone_variants::<str, Arc<str>>(\"test\");\n}\n\n// *** Error Tests ***\n\n#[test]\nfn test_too_long_for_inlining() {\n    common::errors::test_too_long_for_inlining();\n}\n\n#[test]\nfn test_too_long_or_utf8_error_too_long() {\n    common::errors::test_too_long_or_utf8_error_too_long();\n}\n\n#[test]\nfn test_too_long_or_utf8_error_utf8() {\n    common::errors::test_too_long_or_utf8_error_utf8();\n}\n\n// *** StringLike Tests ***\n\n#[test]\nfn test_as_str() {\n    common::stringlike::test_as_str::<str, Arc<str>>(\"test\");\n}\n\n#[test]\nfn test_into_string() {\n    common::stringlike::test_into_string::<str, Arc<str>>(\"test\");\n}\n\n#[test]\nfn test_to_string() {\n    common::stringlike::test_to_string::<str, Arc<str>>(\"test\");\n}\n\n// *** TryFrom Tests ***\n\n#[test]\nfn test_try_from_bytes_invalid_utf8() {\n    common::try_from::test_try_from_bytes_invalid_utf8::<Arc<str>>();\n}\n\n#[test]\nfn test_try_from_vec_bytes_invalid_utf8() {\n    common::try_from::test_try_from_vec_bytes_invalid_utf8::<Arc<str>>();\n}\n\n// *** From Tests ***\n\n#[test]\nfn test_from_string() {\n    common::from::test_from_string_str::<Arc<str>>();\n}\n\n// *** FromStr Tests ***\n\n#[test]\nfn test_from_str_flex_str_success() {\n    common::from_str::test_from_str_flex_str_success::<str, Arc<str>>(\"test\");\n}\n\n// *** FlexStr Edge Cases ***\n\n#[test]\nfn test_optimize_ref_counted_to_inlined() {\n    common::inline_edge_cases::test_optimize_ref_counted_to_inlined::<str, Arc<str>>(\"test\");\n}\n\n#[test]\nfn test_optimize_ref_counted_stays_ref_counted() {\n    let long_str: &'static str = Box::leak(Box::new(\"x\".repeat(INLINE_CAPACITY + 1)));\n    common::inline_edge_cases::test_optimize_ref_counted_stays_ref_counted::<str, Arc<str>>(\n        long_str,\n    );\n}\n\n// *** Mutation Tests ***\n\n#[test]\nfn test_mutation_borrowed_str() {\n    common::mutate::test_mutation_borrowed::<str, Arc<str>>(\"test\");\n}\n\n#[test]\nfn test_mutation_inlined_str() {\n    common::mutate::test_mutation_inlined::<str, Arc<str>>(\"test\");\n}\n\n#[test]\nfn test_mutation_ref_counted_str() {\n    common::mutate::test_mutation_ref_counted::<str, Arc<str>>(\"test\".into());\n}\n\n#[test]\nfn test_mutation_boxed_str() {\n    common::mutate::test_mutation_boxed::<str, Arc<str>>(\"test\".into());\n}\n\n// *** Display Tests ***\n\n#[test]\nfn test_display_str() {\n    common::display::test_display::<str, Arc<str>>(\"test\");\n}\n\n// *** Borrow Tests ***\n\n#[test]\nfn test_borrow_str() {\n    common::borrow::test_borrow::<str, Arc<str>>(\"test\");\n}\n\n// *** Index Tests ***\n\n#[test]\nfn test_index_str() {\n    common::index::test_index::<str, Arc<str>>(\"test\");\n}\n\n// *** ToSocketAddrs Tests ***\n\n#[cfg(feature = \"std\")]\n#[test]\nfn test_to_socket_addrs_str() {\n    common::socket::test_to_socket_addrs::<str, Arc<str>>(\"127.0.0.1:8080\");\n}\n\n// *** TryFrom Tests ***\n\n#[cfg(feature = \"std\")]\n#[test]\nfn test_try_from_osstr_str() {\n    common::try_from::test_try_from_osstr_str::<Arc<str>>();\n}\n\n#[cfg(feature = \"std\")]\n#[test]\nfn test_try_from_path_str() {\n    common::try_from::test_try_from_path_str::<Arc<str>>();\n}\n\n#[test]\nfn test_try_from_vec_u8_str() {\n    common::try_from::test_try_from_vec_u8_str::<Arc<str>>();\n}\n\n#[cfg(feature = \"cstr\")]\n#[test]\nfn test_try_from_cstring_str() {\n    common::try_from::test_try_from_cstring_str::<Arc<str>>();\n}\n\n// *** FromStr Tests ***\n\n#[cfg(feature = \"cstr\")]\n#[test]\nfn test_from_str_cstr_success() {\n    common::from_str::test_from_str_cstr_success::<Arc<core::ffi::CStr>>();\n}\n\n#[cfg(feature = \"cstr\")]\n#[test]\nfn test_from_str_cstr_error() {\n    common::from_str::test_from_str_cstr_error::<Arc<core::ffi::CStr>>();\n}\n\n// *** AsRef Tests ***\n\n#[test]\nfn test_as_ref_str_flex_str() {\n    common::as_ref::test_as_ref_str_flex_str::<Arc<str>>(\"test\");\n}\n\n// *** Prost Tests ***\n\n#[cfg(feature = \"prost\")]\n#[test]\nfn prost_encode_decode_shared_str() {\n    common::prost::encode_decode_round_trip::<SharedStr>(\"test\");\n}\n\n#[cfg(feature = \"prost\")]\n#[test]\nfn prost_encode_decode_shared_str_long() {\n    common::prost::encode_decode_round_trip::<SharedStr>(\n        \"this is a very long string that definitely won't fit inline\",\n    );\n}\n\n#[cfg(feature = \"prost\")]\n#[test]\nfn prost_encode_decode_shared_str_empty() {\n    common::prost::encode_decode_round_trip::<SharedStr>(\"\");\n}\n\n#[cfg(feature = \"prost\")]\n#[test]\nfn prost_encode_decode_shared_str_unicode() {\n    common::prost::encode_decode_round_trip::<SharedStr>(\"hello 🌍🚀\");\n}\n\n#[cfg(feature = \"prost\")]\n#[test]\nfn prost_length_delimited_shared_str() {\n    common::prost::encode_length_delimited_round_trip::<SharedStr>(\"test\");\n}\n\n#[cfg(feature = \"prost\")]\n#[test]\nfn prost_wire_format_shared_str() {\n    common::prost::verify_wire_format::<SharedStr>(\"test\");\n    common::prost::verify_wire_format::<SharedStr>(\"\");\n    common::prost::verify_wire_format::<SharedStr>(\"hello 🌍🚀\");\n}\n\n#[cfg(feature = \"prost\")]\n#[test]\nfn prost_decode_empty_shared_str() {\n    common::prost::decode_empty::<SharedStr>();\n}\n\n#[cfg(feature = \"prost\")]\n#[test]\nfn prost_clear_shared_str() {\n    common::prost::clear_test::<SharedStr>(\"test\");\n}\n\n#[cfg(feature = \"prost\")]\n#[test]\nfn prost_encode_decode_inline_str() {\n    use inline_flexstr::InlineStr;\n    common::prost::encode_decode_round_trip::<InlineStr>(\"test\");\n}\n\n#[cfg(feature = \"prost\")]\n#[test]\nfn prost_encode_decode_inline_str_empty() {\n    use inline_flexstr::InlineStr;\n    common::prost::encode_decode_round_trip::<InlineStr>(\"\");\n}\n\n#[cfg(feature = \"prost\")]\n#[test]\nfn prost_wire_format_inline_str() {\n    use inline_flexstr::InlineStr;\n    common::prost::verify_wire_format::<InlineStr>(\"test\");\n    common::prost::verify_wire_format::<InlineStr>(\"\");\n}\n\n#[cfg(feature = \"prost\")]\n#[test]\nfn prost_decode_empty_inline_str() {\n    use inline_flexstr::InlineStr;\n    common::prost::decode_empty::<InlineStr>();\n}\n\n#[cfg(feature = \"prost\")]\n#[test]\nfn prost_clear_inline_str() {\n    use inline_flexstr::InlineStr;\n    common::prost::clear_test::<InlineStr>(\"test\");\n}\n\n#[cfg(feature = \"prost\")]\n#[test]\nfn prost_inline_str_too_long() {\n    use inline_flexstr::InlineStr;\n    use prost::Message;\n\n    // Encode a string that's too long for inline storage\n    let long: SharedStr = \"this is a very long string that definitely won't fit inline\".into();\n    let encoded = long.encode_to_vec();\n\n    // Decoding into InlineStr should fail\n    let result = InlineStr::decode(&encoded[..]);\n    assert!(\n        result.is_err(),\n        \"should fail for string too long for inline storage\"\n    );\n}\n\n// *** Prost Cross-Type Interoperability Tests ***\n\n#[cfg(feature = \"prost\")]\n#[test]\nfn prost_cross_type_wire_compat_shared_str() {\n    common::prost::cross_type_wire_compat::<SharedStr>(\"test\");\n    common::prost::cross_type_wire_compat::<SharedStr>(\"hello 🌍🚀\");\n    common::prost::cross_type_wire_compat::<SharedStr>(\"\");\n    common::prost::cross_type_wire_compat::<SharedStr>(\n        \"this is a very long string that definitely won't fit inline\",\n    );\n}\n\n#[cfg(feature = \"prost\")]\n#[test]\nfn prost_cross_type_wire_compat_inline_str() {\n    use inline_flexstr::InlineStr;\n    common::prost::cross_type_wire_compat::<InlineStr>(\"test\");\n    common::prost::cross_type_wire_compat::<InlineStr>(\"\");\n}\n\n#[cfg(feature = \"prost\")]\n#[test]\nfn prost_encode_shared_str_decode_string() {\n    common::prost::encode_flex_decode_string::<SharedStr>(\"test\");\n    common::prost::encode_flex_decode_string::<SharedStr>(\"hello 🌍🚀\");\n    common::prost::encode_flex_decode_string::<SharedStr>(\"\");\n    common::prost::encode_flex_decode_string::<SharedStr>(\n        \"this is a very long string that definitely won't fit inline\",\n    );\n}\n\n#[cfg(feature = \"prost\")]\n#[test]\nfn prost_encode_inline_str_decode_string() {\n    use inline_flexstr::InlineStr;\n    common::prost::encode_flex_decode_string::<InlineStr>(\"test\");\n    common::prost::encode_flex_decode_string::<InlineStr>(\"\");\n}\n\n#[cfg(feature = \"prost\")]\n#[test]\nfn prost_encode_string_decode_shared_str() {\n    common::prost::encode_string_decode_flex::<SharedStr>(\"test\");\n    common::prost::encode_string_decode_flex::<SharedStr>(\"hello 🌍🚀\");\n    common::prost::encode_string_decode_flex::<SharedStr>(\"\");\n    common::prost::encode_string_decode_flex::<SharedStr>(\n        \"this is a very long string that definitely won't fit inline\",\n    );\n}\n\n#[cfg(feature = \"prost\")]\n#[test]\nfn prost_encode_string_decode_inline_str() {\n    use inline_flexstr::InlineStr;\n    common::prost::encode_string_decode_flex::<InlineStr>(\"test\");\n    common::prost::encode_string_decode_flex::<InlineStr>(\"\");\n}\n\n// *** Utoipa Tests ***\n\n#[cfg(feature = \"utoipa\")]\n#[test]\nfn utoipa_schema_is_string_shared_str() {\n    common::utoipa::schema_is_string::<SharedStr>();\n}\n\n#[cfg(feature = \"utoipa\")]\n#[test]\nfn utoipa_name_is_string_shared_str() {\n    common::utoipa::name_is_string::<SharedStr>();\n}\n\n#[cfg(feature = \"utoipa\")]\n#[test]\nfn utoipa_schema_is_string_inline_str() {\n    use inline_flexstr::InlineStr;\n    common::utoipa::schema_is_string::<InlineStr>();\n}\n\n#[cfg(feature = \"utoipa\")]\n#[test]\nfn utoipa_name_is_string_inline_str() {\n    use inline_flexstr::InlineStr;\n    common::utoipa::name_is_string::<InlineStr>();\n}\n\n// *** Zeroize Tests ***\n\n#[cfg(feature = \"zeroize\")]\n#[test]\nfn test_zeroize_inlined_str() {\n    common::zeroize::test_zeroize_inlined::<str, Arc<str>>(\"test\");\n}\n\n#[cfg(feature = \"zeroize\")]\n#[test]\nfn test_zeroize_borrowed_str() {\n    common::zeroize::test_zeroize_borrowed::<str, Arc<str>>(\"test\");\n}\n\n#[cfg(feature = \"zeroize\")]\n#[test]\nfn test_zeroize_ref_counted_str() {\n    common::zeroize::test_zeroize_ref_counted::<str, Arc<str>>(\"test\".into());\n}\n\n#[cfg(feature = \"zeroize\")]\n#[test]\nfn test_zeroize_ref_counted_shared_str() {\n    common::zeroize::test_zeroize_ref_counted_shared::<str, Arc<str>>(\"test\".into());\n}\n\n#[cfg(feature = \"zeroize\")]\n#[test]\nfn test_zeroize_boxed_str() {\n    common::zeroize::test_zeroize_boxed::<str, Arc<str>>(\"test\");\n}\n\n#[cfg(feature = \"zeroize\")]\n#[test]\nfn test_zeroize_inline_bytes_cleared_str() {\n    common::zeroize::test_zeroize_inline_bytes_cleared::<str>(\"test\");\n}\n\n// *** Serialize Tests ***\n"
  }
]