SYMBOL INDEX (125 symbols across 22 files)

FILE: asm_embedding/DocumentManipulation.py
  function list_to_str (line 5) | def list_to_str(li):
  function document_append (line 12) | def document_append(strin):

FILE: asm_embedding/FunctionAnalyzerRadare.py
  class RadareFunctionAnalyzer (line 8) | class RadareFunctionAnalyzer:
    method __init__ (line 10) | def __init__(self, filename, use_symbol, depth):
    method __enter__ (line 17) | def __enter__(self):
    method filter_reg (line 21) | def filter_reg(op):
    method filter_imm (line 25) | def filter_imm(op):
    method filter_mem (line 34) | def filter_mem(op):
    method filter_memory_references (line 48) | def filter_memory_references(i):
    method get_callref (line 68) | def get_callref(my_function, depth):
    method get_instruction (line 76) | def get_instruction(self):
    method function_to_inst (line 92) | def function_to_inst(self, functions_dict, my_function, depth):
    method get_arch (line 130) | def get_arch(self):
    method find_functions (line 142) | def find_functions(self):
    method find_functions_by_symbols (line 150) | def find_functions_by_symbols(self):
    method analyze (line 159) | def analyze(self):
    method close (line 188) | def close(self):
    method __exit__ (line 191) | def __exit__(self, exc_type, exc_value, traceback):

FILE: asm_embedding/FunctionNormalizer.py
  class FunctionNormalizer (line 7) | class FunctionNormalizer:
    method __init__ (line 9) | def __init__(self, max_instruction):
    method normalize (line 12) | def normalize(self, f):
    method normalize_function_pairs (line 19) | def normalize_function_pairs(self, pairs):
    method normalize_functions (line 29) | def normalize_functions(self, functions):

FILE: asm_embedding/InstructionsConverter.py
  class InstructionsConverter (line 7) | class InstructionsConverter:
    method __init__ (line 9) | def __init__(self, json_i2id):
    method convert_to_ids (line 14) | def convert_to_ids(self, instructions_list):

FILE: dataset_creation/DataSplitter.py
  class DataSplitter (line 10) | class DataSplitter:
    method __init__ (line 12) | def __init__(self, db_name):
    method create_pair_table (line 15) | def create_pair_table(self, table_name):
    method get_ids (line 23) | def get_ids(self, set_type):
    method select_similar_cfg (line 32) | def select_similar_cfg(id, provenance, ids, cursor):
    method select_dissimilar_cfg (line 41) | def select_dissimilar_cfg(ids, provenance, cursor):
    method create_epoch_pairs (line 50) | def create_epoch_pairs(self, epoch_number, pairs_table,id_table):
    method create_pairs (line 76) | def create_pairs(self, total_epochs):
    method prepare_set (line 94) | def prepare_set(data_to_include, table_name, file_list, cur):
    method split_data (line 105) | def split_data(self, validation_dim, test_dim):

FILE: dataset_creation/DatabaseFactory.py
  class DatabaseFactory (line 17) | class DatabaseFactory:
    method __init__ (line 19) | def __init__(self, db_name, root_path):
    method worker (line 24) | def worker(item):
    method extract_function (line 29) | def extract_function(graph_analyzer):
    method insert_in_db (line 34) | def insert_in_db(db_name, pool_sem, func, filename, function_name, ins...
    method analyze_file (line 62) | def analyze_file(item):
    method create_db (line 94) | def create_db(self):
    method scan_for_file (line 114) | def scan_for_file(self, start):
    method remove_override (line 128) | def remove_override(self, file_list):
    method build_db (line 146) | def build_db(self, use_symbol, depth):

FILE: dataset_creation/ExperimentUtil.py
  function debug_msg (line 9) | def debug_msg():
  function build_configuration (line 27) | def build_configuration(db_name, root_dir, use_symbols, callee_depth):
  function split_configuration (line 36) | def split_configuration(db_name, val_split, test_split, epochs):
  function embedd_configuration (line 45) | def embedd_configuration(db_name, model, batch_size, max_instruction, em...

FILE: dataset_creation/FunctionsEmbedder.py
  class FunctionsEmbedder (line 12) | class FunctionsEmbedder:
    method __init__ (line 14) | def __init__(self,  model, batch_size, max_instruction):
    method compute_embeddings (line 21) | def compute_embeddings(self, functions):
    method create_table (line 27) | def create_table(db_name, table_name):
    method compute_and_save_embeddings_from_db (line 34) | def compute_and_save_embeddings_from_db(self, db_name, table_name):

FILE: dataset_creation/convertDB.py
  function create_db (line 13) | def create_db(db_name):
  function reverse_graph (line 32) | def reverse_graph(cfg, lstm_cfg):
  function copy_split (line 47) | def copy_split(old_cur, new_cur, table):
  function copy_table (line 55) | def copy_table(old_cur, new_cur, table_old, table_new):

FILE: downloader.py
  class Downloader (line 10) | class Downloader:
    method __init__ (line 12) | def __init__(self):
    method download_file (line 55) | def download_file(id,path):
    method decompress_file (line 64) | def decompress_file(file_src,file_path):
    method download (line 72) | def download(self):

FILE: function_search/EvaluateSearchEngine.py
  class SearchEngineEvaluator (line 16) | class SearchEngineEvaluator:
    method __init__ (line 18) | def __init__(self, db_name, table, limit=None,k=None):
    method do_search (line 25) | def do_search(self, target_db_name, target_fcn_ids):
    method calc_auc (line 29) | def calc_auc(self, target_db_name, target_fcn_ids):
    method find_target_fcn (line 38) | def find_target_fcn(self, compiler, opt, num):
    method functions_ground_truth (line 66) | def functions_ground_truth(labels, indices, values, true_label):
    method evaluate_precision_on_all_functions (line 88) | def evaluate_precision_on_all_functions(self, compiler, opt):
  function test (line 110) | def test(dbName, table, opt,x,k):

FILE: function_search/FunctionSearchEngine.py
  class TopK (line 21) | class TopK:
    method __init__ (line 26) | def __init__(self):
    method loads_embeddings_SE (line 30) | def loads_embeddings_SE(self, lista_embeddings):
    method topK (line 42) | def topK(self, k, target):
  class FunctionSearchEngine (line 47) | class FunctionSearchEngine:
    method __init__ (line 49) | def __init__(self, db_name, table_name, limit=None):
    method load_target (line 91) | def load_target(self, target_db_name, target_fcn_ids, calc_mean=False):
    method embeddingToNp (line 117) | def embeddingToNp(self, e):
    method top_k (line 124) | def top_k(self, target, k=None):
    method pp_search (line 131) | def pp_search(self, k):
    method search (line 138) | def search(self, k):

FILE: function_search/fromJsonSearchToPlot.py
  function find_dcg (line 11) | def find_dcg(element_list):
  function count_ones (line 18) | def count_ones(element_list):
  function extract_info (line 22) | def extract_info(file_1):
  function print_graph (line 62) | def print_graph(info1, file_name, label_y, title_1, p):
  function compare_and_print (line 73) | def compare_and_print(file):

FILE: helloworld.c
  function main (line 4) | int main(){

FILE: neural_network/PairFactory.py
  class PairFactory (line 20) | class PairFactory:
    method __init__ (line 22) | def __init__(self, db_name, dataset_type, batch_size, max_instructions...
    method split (line 40) | def split( a, n):
    method truncate_and_compute_lengths (line 44) | def truncate_and_compute_lengths(pairs, max_instructions):
    method async_chunker (line 59) | def async_chunker(self, epoch):
    method get_pair_fromdb (line 89) | def get_pair_fromdb(self, id_1, id_2):
    method get_couple_from_db (line 100) | def get_couple_from_db(self, epoch_number, chunk):
    method async_create_couple (line 166) | def async_create_couple(self, epoch,n_chunk,q):
    method async_get_dataset (line 171) | def async_get_dataset(self, q):

FILE: neural_network/SAFEEmbedder.py
  class SAFEEmbedder (line 5) | class SAFEEmbedder:
    method __init__ (line 7) | def __init__(self, model_file):
    method loadmodel (line 15) | def loadmodel(self):
    method get_tensor (line 28) | def get_tensor(self):
    method embedd (line 33) | def embedd(self, nodi_input, lengths_input):

FILE: neural_network/SAFE_model.py
  class modelSAFE (line 18) | class modelSAFE:
    method __init__ (line 20) | def __init__(self, flags, embedding_matrix):
    method load_model (line 49) | def load_model(path):
    method create_network (line 71) | def create_network(self):
    method train (line 86) | def train(self):

FILE: neural_network/SiameseSAFE.py
  class SiameseSelfAttentive (line 16) | class SiameseSelfAttentive:
    method __init__ (line 18) | def __init__(self,
    method restore_model (line 47) | def restore_model(self, old_session):
    method self_attentive_network (line 61) | def self_attentive_network(self, input_x, lengths):
    method generate_new_safe (line 89) | def generate_new_safe(self):

FILE: neural_network/parameters.py
  function getLogger (line 16) | def getLogger(logfile):
  class Flags (line 26) | class Flags:
    method __init__ (line 28) | def __init__(self):
    method reset_logdir (line 85) | def reset_logdir(self):
    method close_log (line 106) | def close_log(self):
    method __str__ (line 114) | def __str__(self):

FILE: neural_network/train.py
  function load_embedding_matrix (line 10) | def load_embedding_matrix(embedder_folder):
  function run_test (line 29) | def run_test():

FILE: safe.py
  class SAFE (line 12) | class SAFE:
    method __init__ (line 14) | def __init__(self, model):
    method embedd_function (line 21) | def embedd_function(self, filename, address):

FILE: utils/utils.py
  function print_safe (line 4) | def print_safe():