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smartBugs.py
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#!/usr/bin/env python3
import yaml
import argparse
import os
import sys
from datetime import timedelta
from multiprocessing import Pool, Value
from time import time, localtime, strftime
from src.interface.cli import create_parser, getRemoteDataset, \
isRemoteDataset, DATASET_CHOICES, TOOLS_CHOICES
from src.docker_api.docker_api import analyse_files
import git
cfg_dataset_path = os.path.abspath('config/dataset/dataset.yaml')
with open(cfg_dataset_path, 'r') as ymlfile:
try:
cfg_dataset = yaml.safe_load(ymlfile)
except yaml.YAMLError as exc:
print(exc)
output_folder = strftime("%Y%d%m_%H%M", localtime())
logs = open('results/logs/SmartBugs_' + output_folder + '.log', 'w')
start_time = time()
nb_task_done = Value('i', 0)
total_execution = Value('f', 0)
nb_task = 0
def analyse(args):
global logs, output_folder, nb_task, nb_task_done, total_execution
(tool, file) = args
try:
start = time()
sys.stdout.write('\x1b[1;37m' + 'Analysing file [%d/%d]: ' % (nb_task_done.value, nb_task) + '\x1b[0m')
sys.stdout.write('\x1b[1;34m' + file + '\x1b[0m')
sys.stdout.write('\x1b[1;37m' + ' [' + tool + ']' + '\x1b[0m' + '\n')
analyse_files(tool, file, logs, output_folder)
with nb_task_done.get_lock():
nb_task_done.value += 1
with total_execution.get_lock():
total_execution.value += time() - start
duration = str(timedelta(seconds=round(time() - start)))
task_sec = nb_task_done.value/(time() - start_time)
remaining_time = str(timedelta(seconds=round((nb_task - nb_task_done.value) / task_sec)))
sys.stdout.write('\x1b[1;37m' + 'Done [%d/%d, %s]: ' % (nb_task_done.value, nb_task, remaining_time) + '\x1b[0m')
sys.stdout.write('\x1b[1;34m' + file + '\x1b[0m')
sys.stdout.write('\x1b[1;37m' + ' [' + tool + '] in ' + duration + ' ' + '\x1b[0m' + '\n')
logs.write('[%d/%d] ' % (nb_task_done.value, nb_task) + file + ' [' + tool + '] in ' + duration + ' \n')
except Exception as e:
print(e)
raise e
def exec_cmd(args: argparse.Namespace):
global logs, output_folder, nb_task
logs.write('Arguments passed: ' + str(sys.argv) + '\n')
files_to_analyze = []
if args.dataset:
if args.dataset == ['all']:
DATASET_CHOICES.remove('all')
args.dataset = DATASET_CHOICES
for dataset in args.dataset:
# Directory search is recursive (see below), so
# if a remote D is used, we don't need to specify
# the subsets of D
base_name = dataset.split('/')[0]
if isRemoteDataset(cfg_dataset, base_name):
remote_info = getRemoteDataset(cfg_dataset, base_name)
base_path = remote_info['local_dir']
if not os.path.isdir(base_path):
# local copy does not exist; we need to clone it
print('\x1b[1;37m' + "%s is a remote dataset. Do you want to create a local copy? [Y/n] " % base_name + '\x1b[0m')
answer = input()
if answer.lower() in ['yes', 'y', '']:
sys.stdout.write('\x1b[1;37m' + 'Cloning remote dataset [%s <- %s]... ' % (base_path, remote_info['url']) + '\x1b[0m')
sys.stdout.flush()
git.Repo.clone_from(remote_info['url'], base_path)
sys.stdout.write('\x1b[1;37m\n' + 'Done.' + '\x1b[0m\n')
else:
print('\x1b[1;33m' + 'ABORTING: cannot proceed without local copy of remote dataset %s' % base_name + '\x1b[0m')
quit()
else:
sys.stdout.write('\x1b[1;37m' + 'Using remote dataset [%s <- %s] ' % (base_path, remote_info['url']) + '\x1b[0m\n')
if dataset == base_name: # basename included
dataset_path = base_path
args.file.append(dataset_path)
if dataset != base_name and base_name not in args.dataset:
sbset_name = dataset.split('/')[1]
dataset_path = os.path.join(base_path, remote_info['subsets'][sbset_name])
args.file.append(dataset_path)
else:
dataset_path = cfg_dataset[dataset]
args.file.append(dataset_path)
for file in args.file:
# analyse files
if os.path.basename(file).endswith('.sol'):
files_to_analyze.append(file)
# analyse dirs recursively
elif os.path.isdir(file):
for root, dirs, files in os.walk(file):
for name in files:
if name.endswith('.sol'):
files_to_analyze.append(os.path.join(root, name))
else:
print('%s is not a directory or a solidity file' % file)
if args.tool == ['all']:
TOOLS_CHOICES.remove('all')
args.tool = TOOLS_CHOICES
tasks = []
for file in files_to_analyze:
for tool in args.tool:
results_folder = 'results/' + tool + '/' + output_folder
if not os.path.exists(results_folder):
os.makedirs(results_folder)
if args.skip_existing:
file_name = os.path.splitext(os.path.basename(file))[0]
folder = os.path.join(results_folder, file_name, 'result.json')
if os.path.exists(folder):
continue
tasks.append((tool, file))
nb_task = len(tasks)
with Pool(processes=args.processes) as pool:
pool.map(analyse, tasks)
return logs
if __name__ == '__main__':
args = create_parser()
logs = exec_cmd(args)
elapsed_time = round(time() - start_time)
if elapsed_time > 60:
elapsed_time_sec = round(elapsed_time % 60)
elapsed_time = round(elapsed_time // 60)
print('Analysis completed. \nIt took %sm %ss to analyse all files.' % (elapsed_time, elapsed_time_sec))
logs.write('Analysis completed. \nIt took %sm %ss to analyse all files.' % (elapsed_time, elapsed_time_sec))
else:
print('Analysis completed. \nIt took %ss to analyse all files.' % elapsed_time)
logs.write('Analysis completed. \nIt took %ss to analyse all files.' % elapsed_time)