def _run_picire(self, interesting, config, expect, granularity, dd, split,
subset_first, subset_iterator, complement_iterator, cache):
if dd != picire.CombinedParallelDD:
it_kwargs = {
'subset_first': subset_first,
'subset_iterator': subset_iterator,
'complement_iterator': complement_iterator,
}
else:
it_kwargs = {
'config_iterator':
picire.CombinedIterator(subset_first, subset_iterator,
complement_iterator)
}
if dd != picire.LightDD:
cache = picire.shared_cache_decorator(cache)
logging.basicConfig(format='%(message)s')
logging.getLogger('picire').setLevel(logging.DEBUG)
dd_obj = dd(CaseTest(interesting, config),
split=split,
cache=cache(),
**it_kwargs)
output = [
config[x]
for x in dd_obj.ddmin(list(range(len(config))), n=granularity)
]
assert output == expect
def Picire(sut_call,
sut_call_kwargs,
listener,
ident,
issue,
work_dir,
parallel=False,
combine_loops=False,
split_method='zeller',
subset_first=True,
subset_iterator='forward',
complement_iterator='forward',
jobs=os.cpu_count(),
max_utilization=100,
encoding=None,
atom='both',
cache_class='ContentCache',
cleanup=True,
**kwargs):
"""
Test case reducer based on the Picire Parallel Delta Debugging Framework.
**Optional parameters of the reducer:**
- ``parallel``, ``combine_loops``, ``split_method``, ``subset_first``,
``subset_iterator``, ``complement_iterator``, ``jobs``,
``max_utilization``, ``encoding``, ``atom``, ``cache_class``,
``cleanup``
Refer to https://github.com/renatahodovan/picire for configuring Picire.
Note: This reducer is capable of detecting new issues found during the test
reduction (if any).
**Example configuration snippet:**
.. code-block:: ini
[sut.foo]
#call=...
cost=1
reduce=fuzzinator.reduce.Picire
reduce_cost=4
[sut.foo.reduce]
parallel=True
jobs=4
subset_iterator=skip
"""
def eval_arg(arg):
return eval(arg) if isinstance(arg, str) else arg
logging.getLogger('picire').setLevel(logger.level)
src = issue['test']
file_name = issue.get('filename', 'test')
parallel = eval_arg(parallel)
jobs = 1 if not parallel else eval_arg(jobs)
encoding = encoding or chardet.detect(src)['encoding']
cleanup = eval_arg(cleanup)
combine_loops = eval_arg(combine_loops)
subset_first = eval_arg(subset_first)
max_utilization = eval_arg(max_utilization)
split_method = getattr(picire.config_splitters, split_method)
subset_iterator = getattr(picire.config_iterators, subset_iterator)
complement_iterator = getattr(picire.config_iterators, complement_iterator)
cache_class = getattr(picire, cache_class)
if parallel:
cache_class = picire.shared_cache_decorator(cache_class)
# Choose the reducer class that will be used and its configuration.
reduce_config = {'split': split_method}
if not parallel:
reduce_class = picire.LightDD
reduce_config['subset_iterator'] = subset_iterator
reduce_config['complement_iterator'] = complement_iterator
reduce_config['subset_first'] = subset_first
else:
reduce_config['proc_num'] = jobs
reduce_config['max_utilization'] = max_utilization
if combine_loops:
reduce_class = picire.CombinedParallelDD
reduce_config['config_iterator'] = picire.CombinedIterator(
subset_first, subset_iterator, complement_iterator)
else:
reduce_class = picire.ParallelDD
reduce_config['subset_iterator'] = subset_iterator
reduce_config['complement_iterator'] = complement_iterator
reduce_config['subset_first'] = subset_first
issues = dict()
tester_config = dict(sut_call=sut_call,
sut_call_kwargs=sut_call_kwargs,
enc=encoding,
expected=issue['id'],
listener=listener,
ident=ident,
issues=issues)
call_config = dict(reduce_class=reduce_class,
reduce_config=reduce_config,
tester_class=PicireTester,
tester_config=tester_config,
input=file_name,
src=src,
encoding=encoding,
out=work_dir,
atom=atom,
cache_class=cache_class,
cleanup=cleanup)
try:
reduced_file = picire.call(**call_config)
except Exception as e:
logger.warning('Exception in picire', exc_info=e)
return None, list(issues.values())
with open(reduced_file, 'rb') as f:
src = f.read()
return src, list(issues.values())
def Picireny(sut_call,
sut_call_kwargs,
listener,
ident,
issue,
work_dir,
hddmin=None,
parallel=False,
combine_loops=False,
split_method='zeller',
subset_first=True,
subset_iterator='forward',
complement_iterator='forward',
jobs=os.cpu_count(),
max_utilization=100,
encoding=None,
antlr=None,
format=None,
grammar=None,
start=None,
replacements=None,
lang='python',
hdd_star=True,
flatten_recursion=False,
squeeze_tree=True,
skip_unremovable=True,
skip_whitespace=False,
build_hidden_tokens=False,
granularity=2,
cache_class='ContentCache',
cleanup=True,
**kwargs):
"""
Test case reducer based on the Picireny Hierarchical Delta Debugging
Framework.
**Mandatory parameters of the reducer:**
- Either ``format`` or ``grammar`` and ``start`` must be defined.
**Optional parameters of the reducer:**
- ``hddmin``, ``parallel``, ``combine_loops``, ``split_method``, ``subset_first``,
``subset_iterator``, ``complement_iterator``, ``jobs``, ``max_utilization``, ``encoding``,
``antlr``, ``format``, ``grammar``, ``start``, ``replacements``, ``lang``,
``hdd_star``, ``flatten_recursion``, ``squeeze_tree``, ``skip_unremovable``, ``skip_whitespace``,
``build_hidden_tokens``, ``granularity``, ``cache_class``, ``cleanup``
Refer to https://github.com/renatahodovan/picireny for configuring Picireny.
Note: This reducer is capable of detecting new issues found during the test
reduction (if any).
**Example configuration snippet:**
.. code-block:: ini
[sut.foo]
#call=...
cost=1
reduce=fuzzinator.reduce.Picireny
reduce_cost=4
[sut.foo.reduce]
hddmin=full
grammar=/home/alice/grammars-v4/HTMLParser.g4 /home/alice/grammars-v4/HTMLLexer.g4
start=htmlDocument
parallel=True
jobs=4
subset_iterator=skip
"""
def eval_arg(arg):
return eval(arg) if isinstance(arg, str) else arg
logging.getLogger('picireny').setLevel(logger.level)
antlr = picireny.process_antlr4_path(antlr)
if antlr is None:
return None, []
input_format, start = picireny.process_antlr4_format(
format=format,
grammar=json.loads(grammar),
start=start,
replacements=replacements)
if not (input_format and start):
logger.warning('Processing the arguments of picireny failed.')
return None, []
src = issue['test']
file_name = issue.get('filename', 'test')
hddmin = picireny.cli.args_hdd_choices[hddmin if hddmin else 'full']
parallel = eval_arg(parallel)
combine_loops = eval_arg(combine_loops)
split_method = getattr(picire.config_splitters, split_method)
subset_first = eval_arg(subset_first)
subset_iterator = getattr(picire.config_iterators, subset_iterator)
complement_iterator = getattr(picire.config_iterators, complement_iterator)
jobs = 1 if not parallel else eval_arg(jobs)
max_utilization = eval_arg(max_utilization)
encoding = encoding or chardet.detect(src)['encoding'] or 'utf-8'
hdd_star = eval_arg(hdd_star)
flatten_recursion = eval_arg(flatten_recursion)
squeeze_tree = eval_arg(squeeze_tree)
skip_unremovable = eval_arg(skip_unremovable)
skip_whitespace = eval_arg(skip_whitespace)
build_hidden_tokens = eval_arg(build_hidden_tokens)
granularity = eval_arg(granularity) if granularity != 'inf' else float(
'inf')
cleanup = eval_arg(cleanup)
cache_class = getattr(picire, cache_class)
if parallel:
cache_class = picire.shared_cache_decorator(cache_class)
# Choose the reducer class that will be used and its configuration.
reduce_config = {'split': split_method}
if not parallel:
reduce_class = picire.LightDD
reduce_config['subset_iterator'] = subset_iterator
reduce_config['complement_iterator'] = complement_iterator
reduce_config['subset_first'] = subset_first
else:
reduce_config['proc_num'] = jobs
reduce_config['max_utilization'] = max_utilization
if combine_loops:
reduce_class = picire.CombinedParallelDD
reduce_config['config_iterator'] = picire.CombinedIterator(
subset_first, subset_iterator, complement_iterator)
else:
reduce_class = picire.ParallelDD
reduce_config['subset_iterator'] = subset_iterator
reduce_config['complement_iterator'] = complement_iterator
reduce_config['subset_first'] = subset_first
issues = dict()
tester_config = dict(sut_call=sut_call,
sut_call_kwargs=sut_call_kwargs,
enc=encoding,
expected=issue['id'],
listener=listener,
ident=ident,
issues=issues)
try:
hdd_tree = picireny.build_with_antlr4(
input=file_name,
src=src,
encoding=encoding,
out=work_dir,
input_format=input_format,
start=start,
antlr=antlr,
lang=lang,
build_hidden_tokens=build_hidden_tokens,
cleanup=cleanup)
reduced_file = picireny.reduce(
hdd_tree=hdd_tree,
reduce_class=reduce_class,
reduce_config=reduce_config,
tester_class=PicireTester,
tester_config=tester_config,
input=file_name,
encoding=encoding,
out=work_dir,
hddmin=hddmin,
hdd_star=hdd_star,
flatten_recursion=flatten_recursion,
squeeze_tree=squeeze_tree,
skip_unremovable=skip_unremovable,
skip_whitespace=skip_whitespace,
unparse_with_whitespace=not build_hidden_tokens,
granularity=granularity,
cache_class=cache_class,
cleanup=cleanup)
except Exception as e:
logger.warning('Exception in picireny', exc_info=e)
return None, list(issues.values())
with open(reduced_file, 'rb') as f:
src = f.read()
return src, list(issues.values())
def Picireny(sut_call,
sut_call_kwargs,
listener,
ident,
issue,
work_dir,
grammar,
start_rule,
replacements=None,
islands=None,
parallel=False,
combine_loops=False,
split_method='zeller',
subset_first=True,
subset_iterator='forward',
complement_iterator='forward',
jobs=os.cpu_count(),
max_utilization=100,
encoding=None,
disable_cache=False,
cleanup=True,
**kwargs):
"""
Test case reducer based on the Picireny Hierarchical Delta Debugging
Framework.
**Mandatory parameters of the reducer:**
- ``grammar``, ``start_rule``
**Optional parameters of the reducer:**
- ``replacements``, ``islands``, ``parallel``, ``combine_loops``,
``split_method``, ``subset_first``, ``subset_iterator``,
``complement_iterator``, ``jobs``, ``max_utilization``, ``encoding``,
``disable_cache``, ``cleanup``
Refer to https://github.com/renatahodovan/picireny for configuring Picireny.
Note: This reducer is capable of detecting new issues found during the test
reduction (if any).
**Example configuration snippet:**
.. code-block:: ini
[sut.foo]
#call=...
cost=1
reduce=fuzzinator.reduce.Picireny
reduce_cost=4
[sut.foo.reduce]
grammar=/home/alice/grammars-v4/HTMLParser.g4 /home/alice/grammars-v4/HTMLLexer.g4
start_rule=htmlDocument
parallel=True
jobs=4
subset_iterator=skip
"""
# TODO: may be moved to start of file once picireny is available from pypi
import picireny
def eval_arg(arg):
return eval(arg) if isinstance(arg, str) else arg
logging.getLogger('picireny').setLevel(logger.level)
src = issue['test']
file_name = issue.get('filename', 'test')
parallel = eval_arg(parallel)
jobs = 1 if not parallel else eval_arg(jobs)
disable_cache = eval_arg(disable_cache)
encoding = encoding or chardet.detect(src)['encoding']
cleanup = eval_arg(cleanup)
combine_loops = eval_arg(combine_loops)
subset_first = eval_arg(subset_first)
max_utilization = eval_arg(max_utilization)
split_method = getattr(picire.config_splitters, split_method)
subset_iterator = getattr(picire.config_iterators, subset_iterator)
complement_iterator = getattr(picire.config_iterators, complement_iterator)
if islands:
with open(islands, 'rb') as f:
islands_src = f.read()
try:
islands = eval(islands_src)
except Exception as err:
listener.warning(msg='Exception in island descriptor: ' % err)
# Choose the reducer class that will be used and its configuration.
reduce_config = {'split': split_method}
if not parallel:
reduce_class = picire.LightDD
reduce_config['subset_iterator'] = subset_iterator
reduce_config['complement_iterator'] = complement_iterator
reduce_config['subset_first'] = subset_first
else:
reduce_config['proc_num'] = jobs
reduce_config['max_utilization'] = max_utilization
if combine_loops:
reduce_class = picire.CombinedParallelDD
reduce_config['config_iterator'] = picire.CombinedIterator(
subset_first, subset_iterator, complement_iterator)
else:
reduce_class = picire.ParallelDD
reduce_config['subset_iterator'] = subset_iterator
reduce_config['complement_iterator'] = complement_iterator
reduce_config['subset_first'] = subset_first
replacements = replacements or dict()
issues = dict()
tester_config = dict(sut_call=sut_call,
sut_call_kwargs=sut_call_kwargs,
enc=encoding,
expected=issue['id'],
listener=listener,
ident=ident,
issues=issues)
call_config = dict(reduce_class=reduce_class,
reduce_config=reduce_config,
tester_class=PicireTester,
tester_config=tester_config,
input=file_name,
src=src,
encoding=encoding,
out=work_dir,
antlr=os.path.join(os.path.expanduser('~'), '.picireny',
'antlr.jar'),
grammar=json.loads(grammar),
islands=islands,
start_rule=start_rule,
replacements=replacements,
parallel=parallel,
disable_cache=disable_cache,
cleanup=cleanup)
try:
reduced_file = picireny.call(**call_config)
except:
return None, list(issues.values())
with open(reduced_file, 'rb') as f:
src = f.read()
return src, list(issues.values())
def Picireny(sut_call,
sut_call_kwargs,
listener,
ident,
issue,
work_dir,
grammar,
start_rule,
hddmin=None,
parallel=False,
combine_loops=False,
split_method='zeller',
subset_first=True,
subset_iterator='forward',
complement_iterator='forward',
jobs=os.cpu_count(),
max_utilization=100,
encoding=None,
antlr=None,
replacements=None,
islands=None,
lang='python',
hdd_star=True,
squeeze_tree=True,
skip_unremovable_tokens=True,
cache_class='ContentCache',
cleanup=True,
**kwargs):
"""
Test case reducer based on the Picireny Hierarchical Delta Debugging
Framework.
**Mandatory parameters of the reducer:**
- ``grammar``, ``start_rule``
**Optional parameters of the reducer:**
- ``hddmin``, ``parallel``, ``combine_loops``, ``split_method``, ``subset_first``,
``subset_iterator``, ``complement_iterator``, ``jobs``, ``max_utilization``, ``encoding``,
``antlr``, ``replacements``, ``islands``, ``lang``, ``hdd_star``,
``squeeze_tree``, ``skip_unremovable_tokens``, ``cache_class``, ``cleanup``
Refer to https://github.com/renatahodovan/picireny for configuring Picireny.
Note: This reducer is capable of detecting new issues found during the test
reduction (if any).
**Example configuration snippet:**
.. code-block:: ini
[sut.foo]
#call=...
cost=1
reduce=fuzzinator.reduce.Picireny
reduce_cost=4
[sut.foo.reduce]
hddmin=full
grammar=/home/alice/grammars-v4/HTMLParser.g4 /home/alice/grammars-v4/HTMLLexer.g4
start_rule=htmlDocument
parallel=True
jobs=4
subset_iterator=skip
"""
def eval_arg(arg):
return eval(arg) if isinstance(arg, str) else arg
logging.getLogger('picireny').setLevel(logger.level)
src = issue['test']
file_name = issue.get('filename', 'test')
hddmin = picireny.cli.args_hdd_choices[hddmin if hddmin else 'full']
parallel = eval_arg(parallel)
jobs = 1 if not parallel else eval_arg(jobs)
encoding = encoding or chardet.detect(src)['encoding']
cleanup = eval_arg(cleanup)
combine_loops = eval_arg(combine_loops)
subset_first = eval_arg(subset_first)
max_utilization = eval_arg(max_utilization)
split_method = getattr(picire.config_splitters, split_method)
subset_iterator = getattr(picire.config_iterators, subset_iterator)
complement_iterator = getattr(picire.config_iterators, complement_iterator)
cache_class = getattr(picire, cache_class)
if parallel:
cache_class = picire.shared_cache_decorator(cache_class)
if islands:
with open(islands, 'rb') as f:
islands_src = f.read()
try:
islands = json.loads(islands_src.decode(),
object_hook=picireny.antlr4.IslandDescriptor.
json_load_object_hook)
except Exception as err:
listener.warning(msg='Exception in island descriptor: ' % err)
# Choose the reducer class that will be used and its configuration.
reduce_config = {'split': split_method}
if not parallel:
reduce_class = picire.LightDD
reduce_config['subset_iterator'] = subset_iterator
reduce_config['complement_iterator'] = complement_iterator
reduce_config['subset_first'] = subset_first
else:
reduce_config['proc_num'] = jobs
reduce_config['max_utilization'] = max_utilization
if combine_loops:
reduce_class = picire.CombinedParallelDD
reduce_config['config_iterator'] = picire.CombinedIterator(
subset_first, subset_iterator, complement_iterator)
else:
reduce_class = picire.ParallelDD
reduce_config['subset_iterator'] = subset_iterator
reduce_config['complement_iterator'] = complement_iterator
reduce_config['subset_first'] = subset_first
replacements = replacements or dict()
issues = dict()
tester_config = dict(sut_call=sut_call,
sut_call_kwargs=sut_call_kwargs,
enc=encoding,
expected=issue['id'],
listener=listener,
ident=ident,
issues=issues)
call_config = dict(reduce_class=reduce_class,
reduce_config=reduce_config,
tester_class=PicireTester,
tester_config=tester_config,
input=file_name,
src=src,
encoding=encoding,
out=work_dir,
hddmin=hddmin,
antlr=antlr or picireny.cli.antlr_default_path,
grammar=json.loads(grammar),
start_rule=start_rule,
replacements=replacements,
islands=islands,
lang=lang,
hdd_star=hdd_star,
squeeze_tree=squeeze_tree,
skip_unremovable_tokens=skip_unremovable_tokens,
cache_class=cache_class,
cleanup=cleanup)
try:
reduced_file = picireny.call(**call_config)
except Exception as e:
logger.warning('Exception in picireny', exc_info=e)
return None, list(issues.values())
with open(reduced_file, 'rb') as f:
src = f.read()
return src, list(issues.values())
def Picire(sut_call,
sut_call_kwargs,
listener,
ident,
issue,
work_dir,
parallel=False,
combine_loops=False,
split_method='zeller',
subset_first=True,
subset_iterator='forward',
complement_iterator='forward',
jobs=os.cpu_count(),
max_utilization=100,
encoding=None,
atom='line',
disable_cache=False,
cleanup=True,
**kwargs):
"""
Test case reducer based on the Picire Parallel Delta Debugging Framework.
Optional parameters of the reducer:
- 'parallel', 'combine_loops', 'split_method', 'subset_first',
'subset_iterator', 'complement_iterator', 'jobs', 'max_utilization',
'encoding', 'atom', 'disable_cache', 'cleanup'
Refer to https://github.com/renatahodovan/picire for configuring Picire.
Note: This reducer is capable of detecting new issues found during the test
reduction (if any).
Example configuration snippet:
[sut.foo]
#call=...
cost=1
reduce=fuzzinator.reduce.Picire
reduce_cost=4
[sut.foo.reduce]
parallel=True
jobs=4
subset_iterator=skip
"""
def eval_arg(arg):
return eval(arg) if isinstance(arg, str) else arg
logging.getLogger('picire').setLevel(logger.level)
src = issue['test']
file_name = issue.get('filename', 'test')
parallel = eval_arg(parallel)
jobs = 1 if not parallel else eval_arg(jobs)
disable_cache = eval_arg(disable_cache)
encoding = encoding or chardet.detect(src)['encoding']
cleanup = eval_arg(cleanup)
combine_loops = eval_arg(combine_loops)
subset_first = eval_arg(subset_first)
max_utilization = eval_arg(max_utilization)
split_method = getattr(picire.config_splitters, split_method)
subset_iterator = getattr(picire.config_iterators, subset_iterator)
complement_iterator = getattr(picire.config_iterators, complement_iterator)
# Choose the reducer class that will be used and its configuration.
reduce_config = {'split': split_method}
if not parallel:
reduce_class = picire.LightDD
reduce_config['subset_iterator'] = subset_iterator
reduce_config['complement_iterator'] = complement_iterator
reduce_config['subset_first'] = subset_first
else:
reduce_config['proc_num'] = jobs
reduce_config['max_utilization'] = max_utilization
if combine_loops:
reduce_class = picire.CombinedParallelDD
reduce_config['config_iterator'] = picire.CombinedIterator(
subset_first, subset_iterator, complement_iterator)
else:
reduce_class = picire.ParallelDD
reduce_config['subset_iterator'] = subset_iterator
reduce_config['complement_iterator'] = complement_iterator
reduce_config['subset_first'] = subset_first
issues = dict()
tester_config = dict(sut_call=sut_call,
sut_call_kwargs=sut_call_kwargs,
enc=encoding,
expected=issue['id'],
listener=listener,
ident=ident,
issues=issues)
call_config = dict(reduce_class=reduce_class,
reduce_config=reduce_config,
tester_class=PicireTester,
tester_config=tester_config,
input=file_name,
src=src,
encoding=encoding,
out=work_dir,
atom=atom,
parallel=parallel,
disable_cache=disable_cache,
cleanup=cleanup)
try:
reduced_file = picire.call(**call_config)
except:
return None, list(issues.values())
# Reduce by char if we used line based reduce earlier.
if atom == 'line':
with open(reduced_file, 'rb') as f:
src = f.read()
call_config.update(dict(atom='char', src=src))
try:
reduced_file = picire.call(**call_config)
except:
return None, list(issues.values())
with open(reduced_file, 'rb') as f:
src = f.read()
return src, list(issues.values())