You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
538 lines
16 KiB
538 lines
16 KiB
#!/usr/bin/env python2.7
|
|
|
|
# Copyright (c) 2013 - present Facebook, Inc.
|
|
# All rights reserved.
|
|
#
|
|
# This source code is licensed under the BSD style license found in the
|
|
# LICENSE file in the root directory of this source tree. An additional grant
|
|
# of patent rights can be found in the PATENTS file in the same directory.
|
|
|
|
from __future__ import absolute_import
|
|
from __future__ import division
|
|
from __future__ import print_function
|
|
from __future__ import unicode_literals
|
|
|
|
import argparse
|
|
import csv
|
|
import io
|
|
import json
|
|
import logging
|
|
import multiprocessing
|
|
import os
|
|
import platform
|
|
import re
|
|
import shutil
|
|
import stat
|
|
import subprocess
|
|
import sys
|
|
import tempfile
|
|
import time
|
|
import traceback
|
|
import zipfile
|
|
|
|
# Infer imports
|
|
import inferlib
|
|
import utils
|
|
|
|
ANALYSIS_SUMMARY_OUTPUT = 'analysis_summary.txt'
|
|
|
|
BUCK_CONFIG = '.buckconfig.local'
|
|
BUCK_CONFIG_BACKUP = '.buckconfig.local.backup_generated_by_infer'
|
|
DEFAULT_BUCK_OUT = os.path.join(os.getcwd(), 'buck-out')
|
|
DEFAULT_BUCK_OUT_GEN = os.path.join(DEFAULT_BUCK_OUT, 'gen')
|
|
|
|
INFER_REPORT = os.path.join(utils.BUCK_INFER_OUT, utils.CSV_REPORT_FILENAME)
|
|
INFER_STATS = os.path.join(utils.BUCK_INFER_OUT, utils.STATS_FILENAME)
|
|
|
|
INFER_SCRIPT = """\
|
|
#!/usr/bin/env {0}
|
|
import subprocess
|
|
import sys
|
|
|
|
cmd = ['{0}'] + {1} + ['--', 'javac'] + sys.argv[1:]
|
|
subprocess.check_call(cmd)
|
|
"""
|
|
|
|
LOCAL_CONFIG = """\
|
|
[tools]
|
|
javac = %s
|
|
"""
|
|
|
|
|
|
def prepare_build(args):
|
|
"""Creates script that redirects javac calls to inferJ and a local buck
|
|
configuration that tells buck to use that script.
|
|
"""
|
|
|
|
infer_options = [
|
|
'--buck',
|
|
'--incremental',
|
|
'--analyzer', args.analyzer,
|
|
]
|
|
|
|
if args.debug:
|
|
infer_options.append('--debug')
|
|
|
|
if args.no_filtering:
|
|
infer_options.append('--no-filtering')
|
|
|
|
# Create a temporary directory as a cache for jar files.
|
|
infer_cache_dir = os.path.join(args.infer_out, 'cache')
|
|
if not os.path.isdir(infer_cache_dir):
|
|
os.mkdir(infer_cache_dir)
|
|
infer_options.append('--infer_cache')
|
|
infer_options.append(infer_cache_dir)
|
|
temp_files = [infer_cache_dir]
|
|
|
|
try:
|
|
infer = [utils.get_cmd_in_bin_dir('infer')] + infer_options
|
|
except subprocess.CalledProcessError as e:
|
|
logging.error('Could not find infer')
|
|
raise e
|
|
|
|
# Disable the use of buckd as this scripts modifies .buckconfig.local
|
|
logging.info('Disabling buckd: export NO_BUCKD=1')
|
|
os.environ['NO_BUCKD'] = '1'
|
|
|
|
# make sure INFER_ANALYSIS is set when buck is called
|
|
logging.info('Setup Infer analysis mode for Buck: export INFER_ANALYSIS=1')
|
|
os.environ['INFER_ANALYSIS'] = '1'
|
|
|
|
# Create a script to be called by buck
|
|
infer_script = None
|
|
with tempfile.NamedTemporaryFile(delete=False,
|
|
prefix='infer_',
|
|
suffix='.py',
|
|
dir='.') as infer_script:
|
|
logging.info('Creating %s' % infer_script.name)
|
|
infer_script.file.write(
|
|
(INFER_SCRIPT.format(sys.executable, infer)).encode())
|
|
|
|
st = os.stat(infer_script.name)
|
|
os.chmod(infer_script.name, st.st_mode | stat.S_IEXEC)
|
|
|
|
# Backup and patch local buck config
|
|
patched_config = ''
|
|
if os.path.isfile(BUCK_CONFIG):
|
|
logging.info('Backing up %s to %s', BUCK_CONFIG, BUCK_CONFIG_BACKUP)
|
|
shutil.move(BUCK_CONFIG, BUCK_CONFIG_BACKUP)
|
|
with open(BUCK_CONFIG_BACKUP) as buckconfig:
|
|
patched_config = '\n'.join(buckconfig)
|
|
|
|
javac_section = '[tools]\n{0}javac = {1}'.format(
|
|
' ' * 4,
|
|
infer_script.name)
|
|
patched_config += javac_section
|
|
with open(BUCK_CONFIG, 'w') as buckconfig:
|
|
buckconfig.write(patched_config)
|
|
|
|
temp_files += [infer_script.name]
|
|
return temp_files
|
|
|
|
|
|
def java_targets():
|
|
target_types = [
|
|
'android_library',
|
|
'java_library',
|
|
]
|
|
try:
|
|
targets = subprocess.check_output([
|
|
'buck',
|
|
'targets',
|
|
'--type',
|
|
] + target_types).decode().strip().split('\n')
|
|
except subprocess.CalledProcessError as e:
|
|
logging.error('Could not compute java library targets')
|
|
raise e
|
|
return set(targets)
|
|
|
|
|
|
def is_alias(target):
|
|
return ':' not in target
|
|
|
|
|
|
def expand_target(target, java_targets):
|
|
if not is_alias(target):
|
|
return [target]
|
|
else:
|
|
try:
|
|
buck_audit_cmd = ['buck', 'audit', 'classpath', '--dot', target]
|
|
output = subprocess.check_output(buck_audit_cmd)
|
|
dotty = output.decode().split('\n')
|
|
except subprocess.CalledProcessError as e:
|
|
logging.error('Could not expand target {0}'.format(target))
|
|
raise e
|
|
targets = set()
|
|
edge_re = re.compile('.*"(.*)".*"(.*)".*')
|
|
for line in dotty:
|
|
match = re.match(edge_re, line)
|
|
if match:
|
|
for t in match.groups():
|
|
if t in java_targets:
|
|
targets.add(t)
|
|
return targets
|
|
|
|
|
|
def normalize_target(target):
|
|
if is_alias(target) or target.startswith('//'):
|
|
return target
|
|
else:
|
|
return '//' + target
|
|
|
|
|
|
def determine_library_targets(args):
|
|
""" Uses git and buck audit to expand aliases into the list of java or
|
|
android library targets that are parts of these aliases.
|
|
Buck targets directly passed as argument are not expanded """
|
|
|
|
args.targets = [normalize_target(t) for t in args.targets]
|
|
|
|
if any(map(is_alias, args.targets)):
|
|
all_java_targets = java_targets()
|
|
targets = set()
|
|
for t in args.targets:
|
|
targets.update(expand_target(t, all_java_targets))
|
|
args.targets = list(targets)
|
|
|
|
if args.verbose:
|
|
logging.debug('Targets to analyze:')
|
|
for target in args.targets:
|
|
logging.debug(target)
|
|
|
|
|
|
def init_stats(args, start_time):
|
|
"""Returns dictionary with target independent statistics.
|
|
"""
|
|
return {
|
|
'float': {},
|
|
'int': {
|
|
'cores': multiprocessing.cpu_count(),
|
|
'time': int(time.time()),
|
|
'start_time': int(round(start_time)),
|
|
},
|
|
'normal': {
|
|
'debug': str(args.debug),
|
|
'analyzer': args.analyzer,
|
|
'machine': platform.machine(),
|
|
'node': platform.node(),
|
|
'project': os.path.basename(os.getcwd()),
|
|
'revision': utils.vcs_revision(),
|
|
'branch': utils.vcs_branch(),
|
|
'system': platform.system(),
|
|
'infer_version': utils.infer_version(),
|
|
'infer_branch': utils.infer_branch(),
|
|
}
|
|
}
|
|
|
|
|
|
def store_performances_csv(infer_out, stats):
|
|
"""Stores the statistics about perfromances into a CSV file to be exported
|
|
to a database"""
|
|
perf_filename = os.path.join(infer_out, utils.CSV_PERF_FILENAME)
|
|
with open(perf_filename, 'w') as csv_file_out:
|
|
csv_writer = csv.writer(csv_file_out)
|
|
keys = ['infer_version', 'project', 'revision', 'files', 'lines',
|
|
'cores', 'system', 'machine', 'node', 'total_time',
|
|
'capture_time', 'analysis_time', 'reporting_time', 'time']
|
|
int_stats = list(stats['int'].items())
|
|
normal_stats = list(stats['normal'].items())
|
|
flat_stats = dict(int_stats + normal_stats)
|
|
values = []
|
|
for key in keys:
|
|
values.append(flat_stats[key])
|
|
csv_writer.writerow(keys)
|
|
csv_writer.writerow(values)
|
|
csv_file_out.flush()
|
|
|
|
|
|
def get_harness_code():
|
|
all_harness_code = '\nGenerated harness code:\n'
|
|
for filename in os.listdir(DEFAULT_BUCK_OUT_GEN):
|
|
if 'InferGeneratedHarness' in filename:
|
|
all_harness_code += '\n' + filename + ':\n'
|
|
with open(os.path.join(DEFAULT_BUCK_OUT_GEN,
|
|
filename), 'r') as file_in:
|
|
all_harness_code += file_in.read()
|
|
return all_harness_code + '\n'
|
|
|
|
|
|
def get_basic_stats(stats):
|
|
files_analyzed = '{0} files ({1} lines) analyzed in {2}s\n\n'.format(
|
|
stats['int']['files'],
|
|
stats['int']['lines'],
|
|
stats['int']['total_time'],
|
|
)
|
|
phase_times = 'Capture time: {0}s\nAnalysis time: {1}s\n\n'.format(
|
|
stats['int']['capture_time'],
|
|
stats['int']['analysis_time'],
|
|
)
|
|
|
|
to_skip = {
|
|
'files',
|
|
'lines',
|
|
'cores',
|
|
'time',
|
|
'start_time',
|
|
'capture_time',
|
|
'analysis_time',
|
|
'reporting_time',
|
|
'total_time',
|
|
}
|
|
bugs_found = 'Errors found:\n\n'
|
|
for key, value in sorted(stats['int'].items()):
|
|
if key not in to_skip:
|
|
bugs_found += ' {0:>8} {1}\n'.format(value, key)
|
|
|
|
basic_stats_message = files_analyzed + phase_times + bugs_found + '\n'
|
|
return basic_stats_message
|
|
|
|
|
|
def get_buck_stats():
|
|
trace_filename = os.path.join(
|
|
DEFAULT_BUCK_OUT,
|
|
'log',
|
|
'traces',
|
|
'build.trace'
|
|
)
|
|
ARGS = 'args'
|
|
SUCCESS_STATUS = 'success_type'
|
|
buck_stats = {}
|
|
try:
|
|
with open(trace_filename, 'r') as file_in:
|
|
trace = json.load(file_in)
|
|
for t in trace:
|
|
if SUCCESS_STATUS in t[ARGS]:
|
|
status = t[ARGS][SUCCESS_STATUS]
|
|
count = buck_stats.get(status, 0)
|
|
buck_stats[status] = count + 1
|
|
|
|
buck_stats_message = 'Buck build statistics:\n\n'
|
|
for key, value in sorted(buck_stats.items()):
|
|
buck_stats_message += ' {0:>8} {1}\n'.format(value, key)
|
|
|
|
return buck_stats_message
|
|
except IOError as e:
|
|
logging.error('Caught %s: %s' % (e.__class__.__name__, str(e)))
|
|
logging.error(traceback.format_exc())
|
|
return ''
|
|
|
|
|
|
class NotFoundInJar(Exception):
|
|
pass
|
|
|
|
|
|
def load_stats(opened_jar):
|
|
try:
|
|
return json.loads(opened_jar.read(INFER_STATS).decode())
|
|
except KeyError as e:
|
|
raise NotFoundInJar
|
|
|
|
|
|
def load_report(opened_jar):
|
|
try:
|
|
sio = io.StringIO(opened_jar.read(INFER_REPORT).decode())
|
|
return list(csv.reader(sio))
|
|
except KeyError as e:
|
|
raise NotFoundInJar
|
|
|
|
|
|
def rows_remove_duplicates(rows):
|
|
seen = {}
|
|
result = []
|
|
for row in rows:
|
|
t = tuple(row)
|
|
if t in seen:
|
|
continue
|
|
seen[t] = 1
|
|
result.append(row)
|
|
return result
|
|
|
|
|
|
def collect_results(args, start_time):
|
|
"""Walks through buck-gen, collects results for the different buck targets
|
|
and stores them in in args.infer_out/results.csv.
|
|
"""
|
|
buck_stats = get_buck_stats()
|
|
logging.info(buck_stats)
|
|
with open(os.path.join(args.infer_out, ANALYSIS_SUMMARY_OUTPUT), 'w') as f:
|
|
f.write(buck_stats)
|
|
|
|
all_rows = []
|
|
headers = []
|
|
stats = init_stats(args, start_time)
|
|
|
|
accumulation_whitelist = list(map(re.compile, [
|
|
'^cores$',
|
|
'^time$',
|
|
'^start_time$',
|
|
'.*_pc',
|
|
]))
|
|
|
|
expected_analyzer = stats['normal']['analyzer']
|
|
expected_version = stats['normal']['infer_version']
|
|
|
|
for root, _, files in os.walk(DEFAULT_BUCK_OUT_GEN):
|
|
for f in [f for f in files if f.endswith('.jar')]:
|
|
path = os.path.join(root, f)
|
|
try:
|
|
with zipfile.ZipFile(path) as jar:
|
|
# Accumulate integers and float values
|
|
target_stats = load_stats(jar)
|
|
|
|
found_analyzer = target_stats['normal']['analyzer']
|
|
found_version = target_stats['normal']['infer_version']
|
|
|
|
if (found_analyzer != expected_analyzer
|
|
or found_version != expected_version):
|
|
continue
|
|
else:
|
|
for type_k in ['int', 'float']:
|
|
items = target_stats.get(type_k, {}).items()
|
|
for key, value in items:
|
|
if not any(map(lambda r: r.match(key),
|
|
accumulation_whitelist)):
|
|
old_value = stats[type_k].get(key, 0)
|
|
stats[type_k][key] = old_value + value
|
|
|
|
rows = load_report(jar)
|
|
if len(rows) > 0:
|
|
headers.append(rows[0])
|
|
all_rows.extend(rows[1:])
|
|
|
|
# Override normals
|
|
stats['normal'].update(target_stats.get('normal', {}))
|
|
except NotFoundInJar:
|
|
pass
|
|
except zipfile.BadZipfile:
|
|
logging.warn('Bad zip file %s', path)
|
|
|
|
csv_report = os.path.join(args.infer_out, utils.CSV_REPORT_FILENAME)
|
|
bugs_out = os.path.join(args.infer_out, utils.BUGS_FILENAME)
|
|
|
|
if len(headers) == 0:
|
|
with open(csv_report, 'w'):
|
|
pass
|
|
logging.info('No reports found')
|
|
return
|
|
elif len(headers) > 1:
|
|
if any(map(lambda x: x != headers[0], headers)):
|
|
raise Exception('Inconsistent reports found')
|
|
|
|
# Convert all float values to integer values
|
|
for key, value in stats.get('float', {}).items():
|
|
stats['int'][key] = int(round(value))
|
|
|
|
# Delete the float entries before exporting the results
|
|
del(stats['float'])
|
|
|
|
with open(csv_report, 'w') as report:
|
|
writer = csv.writer(report)
|
|
writer.writerows([headers[0]] + rows_remove_duplicates(all_rows))
|
|
report.flush()
|
|
|
|
# export the CSV rows to JSON
|
|
utils.create_json_report(args.infer_out)
|
|
|
|
print('\n')
|
|
inferlib.print_errors(csv_report, bugs_out)
|
|
|
|
stats['int']['total_time'] = int(round(utils.elapsed_time(start_time)))
|
|
|
|
store_performances_csv(args.infer_out, stats)
|
|
|
|
stats_filename = os.path.join(args.infer_out, utils.STATS_FILENAME)
|
|
with open(stats_filename, 'w') as stats_out:
|
|
json.dump(stats, stats_out, indent=2)
|
|
|
|
basic_stats = get_basic_stats(stats)
|
|
|
|
if args.print_harness:
|
|
harness_code = get_harness_code()
|
|
basic_stats += harness_code
|
|
|
|
logging.info(basic_stats)
|
|
|
|
with open(os.path.join(args.infer_out, ANALYSIS_SUMMARY_OUTPUT), 'a') as f:
|
|
f.write(basic_stats)
|
|
|
|
|
|
def cleanup(temp_files):
|
|
"""Removes the generated .buckconfig.local and the temporary infer script.
|
|
"""
|
|
for file in [BUCK_CONFIG] + temp_files:
|
|
try:
|
|
logging.info('Removing %s' % file)
|
|
if os.path.isdir(file):
|
|
shutil.rmtree(file)
|
|
else:
|
|
os.unlink(file)
|
|
except IOError:
|
|
logging.error('Could not remove %s' % file)
|
|
|
|
if os.path.isfile(BUCK_CONFIG_BACKUP):
|
|
logging.info('Restoring %s', BUCK_CONFIG)
|
|
shutil.move(BUCK_CONFIG_BACKUP, BUCK_CONFIG)
|
|
|
|
|
|
if __name__ == '__main__':
|
|
parser = argparse.ArgumentParser(parents=[inferlib.base_parser])
|
|
parser.add_argument('--verbose', action='store_true',
|
|
help='Print buck compilation steps')
|
|
parser.add_argument('--no-cache', action='store_true',
|
|
help='Do not use buck distributed cache')
|
|
parser.add_argument('--print-harness', action='store_true',
|
|
help='Print generated harness code (Android only)')
|
|
parser.add_argument('targets', nargs='*', metavar='target',
|
|
help='Build targets to analyze')
|
|
args = parser.parse_args()
|
|
|
|
utils.configure_logging(args.verbose)
|
|
timer = utils.Timer(logging.info)
|
|
temp_files = []
|
|
|
|
try:
|
|
start_time = time.time()
|
|
logging.info('Starting the analysis')
|
|
subprocess.check_call(
|
|
[utils.get_cmd_in_bin_dir('InferAnalyze'), '-version'])
|
|
|
|
if not os.path.isdir(args.infer_out):
|
|
os.mkdir(args.infer_out)
|
|
|
|
timer.start('Preparing build...')
|
|
temp_files += prepare_build(args)
|
|
timer.stop('Build prepared')
|
|
|
|
# TODO(t3786463) Start buckd.
|
|
|
|
timer.start('Computing library targets')
|
|
determine_library_targets(args)
|
|
timer.stop('%d targets computed', len(args.targets))
|
|
|
|
timer.start('Running buck...')
|
|
buck_cmd = ['buck', 'build']
|
|
if args.no_cache:
|
|
buck_cmd += ['--no-cache']
|
|
if args.verbose:
|
|
buck_cmd += ['-v', '2']
|
|
subprocess.check_call(buck_cmd + args.targets)
|
|
timer.stop('Buck finished')
|
|
|
|
timer.start('Collecting results...')
|
|
collect_results(args, start_time)
|
|
timer.stop('Done')
|
|
|
|
except KeyboardInterrupt as e:
|
|
timer.stop('Exiting')
|
|
sys.exit(0)
|
|
except Exception as e:
|
|
timer.stop('Failed')
|
|
logging.error('Caught %s: %s' % (e.__class__.__name__, str(e)))
|
|
logging.error(traceback.format_exc())
|
|
sys.exit(1)
|
|
finally:
|
|
cleanup(temp_files)
|
|
|
|
|
|
# vim: set sw=4 ts=4 et:
|