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| from evaluator.CodeBLEU.parser import DFG_python, DFG_java, DFG_ruby, DFG_go, DFG_php, DFG_javascript, DFG_csharp |
| from evaluator.CodeBLEU.parser import (remove_comments_and_docstrings, |
| tree_to_token_index, |
| index_to_code_token, |
| tree_to_variable_index) |
| from tree_sitter import Language, Parser |
| import os |
|
|
| root_dir = os.path.dirname(__file__) |
|
|
| dfg_function = { |
| 'python': DFG_python, |
| 'java': DFG_java, |
| 'ruby': DFG_ruby, |
| 'go': DFG_go, |
| 'php': DFG_php, |
| 'javascript': DFG_javascript, |
| 'c_sharp': DFG_csharp, |
| } |
|
|
|
|
| def calc_dataflow_match(references, candidate, lang): |
| return corpus_dataflow_match([references], [candidate], lang) |
|
|
|
|
| def corpus_dataflow_match(references, candidates, lang): |
| LANGUAGE = Language(root_dir + '/parser/my-languages.so', lang) |
| parser = Parser() |
| parser.set_language(LANGUAGE) |
| parser = [parser, dfg_function[lang]] |
| match_count = 0 |
| total_count = 0 |
|
|
| for i in range(len(candidates)): |
| references_sample = references[i] |
| candidate = candidates[i] |
| for reference in references_sample: |
| try: |
| candidate = remove_comments_and_docstrings(candidate, 'java') |
| except: |
| pass |
| try: |
| reference = remove_comments_and_docstrings(reference, 'java') |
| except: |
| pass |
|
|
| cand_dfg = get_data_flow(candidate, parser) |
| ref_dfg = get_data_flow(reference, parser) |
|
|
| normalized_cand_dfg = normalize_dataflow(cand_dfg) |
| normalized_ref_dfg = normalize_dataflow(ref_dfg) |
|
|
| if len(normalized_ref_dfg) > 0: |
| total_count += len(normalized_ref_dfg) |
| for dataflow in normalized_ref_dfg: |
| if dataflow in normalized_cand_dfg: |
| match_count += 1 |
| normalized_cand_dfg.remove(dataflow) |
| if total_count == 0: |
| print( |
| "WARNING: There is no reference data-flows extracted from the whole corpus, and the data-flow match score degenerates to 0. Please consider ignoring this score.") |
| return 0 |
| score = match_count / total_count |
| return score |
|
|
|
|
| def get_data_flow(code, parser): |
| try: |
| tree = parser[0].parse(bytes(code, 'utf8')) |
| root_node = tree.root_node |
| tokens_index = tree_to_token_index(root_node) |
| code = code.split('\n') |
| code_tokens = [index_to_code_token(x, code) for x in tokens_index] |
| index_to_code = {} |
| for idx, (index, code) in enumerate(zip(tokens_index, code_tokens)): |
| index_to_code[index] = (idx, code) |
| try: |
| DFG, _ = parser[1](root_node, index_to_code, {}) |
| except: |
| DFG = [] |
| DFG = sorted(DFG, key=lambda x: x[1]) |
| indexs = set() |
| for d in DFG: |
| if len(d[-1]) != 0: |
| indexs.add(d[1]) |
| for x in d[-1]: |
| indexs.add(x) |
| new_DFG = [] |
| for d in DFG: |
| if d[1] in indexs: |
| new_DFG.append(d) |
| codes = code_tokens |
| dfg = new_DFG |
| except: |
| codes = code.split() |
| dfg = [] |
| |
| dic = {} |
| for d in dfg: |
| if d[1] not in dic: |
| dic[d[1]] = d |
| else: |
| dic[d[1]] = (d[0], d[1], d[2], list(set(dic[d[1]][3] + d[3])), list(set(dic[d[1]][4] + d[4]))) |
| DFG = [] |
| for d in dic: |
| DFG.append(dic[d]) |
| dfg = DFG |
| return dfg |
|
|
|
|
| def normalize_dataflow_item(dataflow_item): |
| var_name = dataflow_item[0] |
| var_pos = dataflow_item[1] |
| relationship = dataflow_item[2] |
| par_vars_name_list = dataflow_item[3] |
| par_vars_pos_list = dataflow_item[4] |
|
|
| var_names = list(set(par_vars_name_list + [var_name])) |
| norm_names = {} |
| for i in range(len(var_names)): |
| norm_names[var_names[i]] = 'var_' + str(i) |
|
|
| norm_var_name = norm_names[var_name] |
| relationship = dataflow_item[2] |
| norm_par_vars_name_list = [norm_names[x] for x in par_vars_name_list] |
|
|
| return (norm_var_name, relationship, norm_par_vars_name_list) |
|
|
|
|
| def normalize_dataflow(dataflow): |
| var_dict = {} |
| i = 0 |
| normalized_dataflow = [] |
| for item in dataflow: |
| var_name = item[0] |
| relationship = item[2] |
| par_vars_name_list = item[3] |
| for name in par_vars_name_list: |
| if name not in var_dict: |
| var_dict[name] = 'var_' + str(i) |
| i += 1 |
| if var_name not in var_dict: |
| var_dict[var_name] = 'var_' + str(i) |
| i += 1 |
| normalized_dataflow.append((var_dict[var_name], relationship, [var_dict[x] for x in par_vars_name_list])) |
| return normalized_dataflow |
|
|
