CmpRuns.py
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#!/usr/bin/env python
"""
CmpRuns - A simple tool for comparing two static analyzer runs to determine
which reports have been added, removed, or changed.
This is designed to support automated testing using the static analyzer, from
two perspectives:
1. To monitor changes in the static analyzer's reports on real code bases,
for regression testing.
2. For use by end users who want to integrate regular static analyzer testing
into a buildbot like environment.
Usage:
# Load the results of both runs, to obtain lists of the corresponding
# AnalysisDiagnostic objects.
#
resultsA = loadResultsFromSingleRun(singleRunInfoA, deleteEmpty)
resultsB = loadResultsFromSingleRun(singleRunInfoB, deleteEmpty)
# Generate a relation from diagnostics in run A to diagnostics in run B
# to obtain a list of triples (a, b, confidence).
diff = compareResults(resultsA, resultsB)
"""
from __future__ import division, print_function
from collections import defaultdict
from math import log
from optparse import OptionParser
import json
import os
import plistlib
import re
import sys
STATS_REGEXP = re.compile(r"Statistics: (\{.+\})", re.MULTILINE | re.DOTALL)
class Colors(object):
"""
Color for terminal highlight.
"""
RED = '\x1b[2;30;41m'
GREEN = '\x1b[6;30;42m'
CLEAR = '\x1b[0m'
# Information about analysis run:
# path - the analysis output directory
# root - the name of the root directory, which will be disregarded when
# determining the source file name
class SingleRunInfo(object):
def __init__(self, path, root="", verboseLog=None):
self.path = path
self.root = root.rstrip("/\\")
self.verboseLog = verboseLog
class AnalysisDiagnostic(object):
def __init__(self, data, report, htmlReport):
self._data = data
self._loc = self._data['location']
self._report = report
self._htmlReport = htmlReport
self._reportSize = len(self._data['path'])
def getFileName(self):
root = self._report.run.root
fileName = self._report.files[self._loc['file']]
if fileName.startswith(root) and len(root) > 0:
return fileName[len(root) + 1:]
return fileName
def getRootFileName(self):
path = self._data['path']
if not path:
return self.getFileName()
p = path[0]
if 'location' in p:
fIdx = p['location']['file']
else: # control edge
fIdx = path[0]['edges'][0]['start'][0]['file']
out = self._report.files[fIdx]
root = self._report.run.root
if out.startswith(root):
return out[len(root):]
return out
def getLine(self):
return self._loc['line']
def getColumn(self):
return self._loc['col']
def getPathLength(self):
return self._reportSize
def getCategory(self):
return self._data['category']
def getDescription(self):
return self._data['description']
def getIssueIdentifier(self):
id = self.getFileName() + "+"
if 'issue_context' in self._data:
id += self._data['issue_context'] + "+"
if 'issue_hash_content_of_line_in_context' in self._data:
id += str(self._data['issue_hash_content_of_line_in_context'])
return id
def getReport(self):
if self._htmlReport is None:
return " "
return os.path.join(self._report.run.path, self._htmlReport)
def getReadableName(self):
if 'issue_context' in self._data:
funcnamePostfix = "#" + self._data['issue_context']
else:
funcnamePostfix = ""
rootFilename = self.getRootFileName()
fileName = self.getFileName()
if rootFilename != fileName:
filePrefix = "[%s] %s" % (rootFilename, fileName)
else:
filePrefix = rootFilename
return '%s%s:%d:%d, %s: %s' % (filePrefix,
funcnamePostfix,
self.getLine(),
self.getColumn(), self.getCategory(),
self.getDescription())
# Note, the data format is not an API and may change from one analyzer
# version to another.
def getRawData(self):
return self._data
class AnalysisReport(object):
def __init__(self, run, files):
self.run = run
self.files = files
self.diagnostics = []
class AnalysisRun(object):
def __init__(self, info):
self.path = info.path
self.root = info.root
self.info = info
self.reports = []
# Cumulative list of all diagnostics from all the reports.
self.diagnostics = []
self.clang_version = None
self.stats = []
def getClangVersion(self):
return self.clang_version
def readSingleFile(self, p, deleteEmpty):
data = plistlib.readPlist(p)
if 'statistics' in data:
self.stats.append(json.loads(data['statistics']))
data.pop('statistics')
# We want to retrieve the clang version even if there are no
# reports. Assume that all reports were created using the same
# clang version (this is always true and is more efficient).
if 'clang_version' in data:
if self.clang_version is None:
self.clang_version = data.pop('clang_version')
else:
data.pop('clang_version')
# Ignore/delete empty reports.
if not data['files']:
if deleteEmpty:
os.remove(p)
return
# Extract the HTML reports, if they exists.
if 'HTMLDiagnostics_files' in data['diagnostics'][0]:
htmlFiles = []
for d in data['diagnostics']:
# FIXME: Why is this named files, when does it have multiple
# files?
assert len(d['HTMLDiagnostics_files']) == 1
htmlFiles.append(d.pop('HTMLDiagnostics_files')[0])
else:
htmlFiles = [None] * len(data['diagnostics'])
report = AnalysisReport(self, data.pop('files'))
diagnostics = [AnalysisDiagnostic(d, report, h)
for d, h in zip(data.pop('diagnostics'), htmlFiles)]
assert not data
report.diagnostics.extend(diagnostics)
self.reports.append(report)
self.diagnostics.extend(diagnostics)
def loadResults(path, opts, root="", deleteEmpty=True):
"""
Backwards compatibility API.
"""
return loadResultsFromSingleRun(SingleRunInfo(path, root, opts.verboseLog),
deleteEmpty)
def loadResultsFromSingleRun(info, deleteEmpty=True):
"""
# Load results of the analyzes from a given output folder.
# - info is the SingleRunInfo object
# - deleteEmpty specifies if the empty plist files should be deleted
"""
path = info.path
run = AnalysisRun(info)
if os.path.isfile(path):
run.readSingleFile(path, deleteEmpty)
else:
for (dirpath, dirnames, filenames) in os.walk(path):
for f in filenames:
if (not f.endswith('plist')):
continue
p = os.path.join(dirpath, f)
run.readSingleFile(p, deleteEmpty)
return run
def cmpAnalysisDiagnostic(d):
return d.getIssueIdentifier()
def compareResults(A, B, opts):
"""
compareResults - Generate a relation from diagnostics in run A to
diagnostics in run B.
The result is the relation as a list of triples (a, b) where
each element {a,b} is None or a matching element from the respective run
"""
res = []
# Map size_before -> size_after
path_difference_data = []
# Quickly eliminate equal elements.
neqA = []
neqB = []
eltsA = list(A.diagnostics)
eltsB = list(B.diagnostics)
eltsA.sort(key=cmpAnalysisDiagnostic)
eltsB.sort(key=cmpAnalysisDiagnostic)
while eltsA and eltsB:
a = eltsA.pop()
b = eltsB.pop()
if (a.getIssueIdentifier() == b.getIssueIdentifier()):
if a.getPathLength() != b.getPathLength():
if opts.relative_path_histogram:
path_difference_data.append(
float(a.getPathLength()) / b.getPathLength())
elif opts.relative_log_path_histogram:
path_difference_data.append(
log(float(a.getPathLength()) / b.getPathLength()))
elif opts.absolute_path_histogram:
path_difference_data.append(
a.getPathLength() - b.getPathLength())
res.append((a, b))
elif a.getIssueIdentifier() > b.getIssueIdentifier():
eltsB.append(b)
neqA.append(a)
else:
eltsA.append(a)
neqB.append(b)
neqA.extend(eltsA)
neqB.extend(eltsB)
# FIXME: Add fuzzy matching. One simple and possible effective idea would
# be to bin the diagnostics, print them in a normalized form (based solely
# on the structure of the diagnostic), compute the diff, then use that as
# the basis for matching. This has the nice property that we don't depend
# in any way on the diagnostic format.
for a in neqA:
res.append((a, None))
for b in neqB:
res.append((None, b))
if opts.relative_log_path_histogram or opts.relative_path_histogram or \
opts.absolute_path_histogram:
from matplotlib import pyplot
pyplot.hist(path_difference_data, bins=100)
pyplot.show()
return res
def computePercentile(l, percentile):
"""
Return computed percentile.
"""
return sorted(l)[int(round(percentile * len(l) + 0.5)) - 1]
def deriveStats(results):
# Assume all keys are the same in each statistics bucket.
combined_data = defaultdict(list)
# Collect data on paths length.
for report in results.reports:
for diagnostic in report.diagnostics:
combined_data['PathsLength'].append(diagnostic.getPathLength())
for stat in results.stats:
for key, value in stat.items():
combined_data[key].append(value)
combined_stats = {}
for key, values in combined_data.items():
combined_stats[str(key)] = {
"max": max(values),
"min": min(values),
"mean": sum(values) / len(values),
"90th %tile": computePercentile(values, 0.9),
"95th %tile": computePercentile(values, 0.95),
"median": sorted(values)[len(values) // 2],
"total": sum(values)
}
return combined_stats
def compareStats(resultsA, resultsB):
statsA = deriveStats(resultsA)
statsB = deriveStats(resultsB)
keys = sorted(statsA.keys())
for key in keys:
print(key)
for kkey in statsA[key]:
valA = float(statsA[key][kkey])
valB = float(statsB[key][kkey])
report = "%.3f -> %.3f" % (valA, valB)
# Only apply highlighting when writing to TTY and it's not Windows
if sys.stdout.isatty() and os.name != 'nt':
if valB != 0:
ratio = (valB - valA) / valB
if ratio < -0.2:
report = Colors.GREEN + report + Colors.CLEAR
elif ratio > 0.2:
report = Colors.RED + report + Colors.CLEAR
print("\t %s %s" % (kkey, report))
def dumpScanBuildResultsDiff(dirA, dirB, opts, deleteEmpty=True,
Stdout=sys.stdout):
# Load the run results.
resultsA = loadResults(dirA, opts, opts.rootA, deleteEmpty)
resultsB = loadResults(dirB, opts, opts.rootB, deleteEmpty)
if opts.show_stats:
compareStats(resultsA, resultsB)
if opts.stats_only:
return
# Open the verbose log, if given.
if opts.verboseLog:
auxLog = open(opts.verboseLog, "wb")
else:
auxLog = None
diff = compareResults(resultsA, resultsB, opts)
foundDiffs = 0
totalAdded = 0
totalRemoved = 0
for res in diff:
a, b = res
if a is None:
Stdout.write("ADDED: %r\n" % b.getReadableName())
foundDiffs += 1
totalAdded += 1
if auxLog:
auxLog.write("('ADDED', %r, %r)\n" % (b.getReadableName(),
b.getReport()))
elif b is None:
Stdout.write("REMOVED: %r\n" % a.getReadableName())
foundDiffs += 1
totalRemoved += 1
if auxLog:
auxLog.write("('REMOVED', %r, %r)\n" % (a.getReadableName(),
a.getReport()))
else:
pass
TotalReports = len(resultsB.diagnostics)
Stdout.write("TOTAL REPORTS: %r\n" % TotalReports)
Stdout.write("TOTAL ADDED: %r\n" % totalAdded)
Stdout.write("TOTAL REMOVED: %r\n" % totalRemoved)
if auxLog:
auxLog.write("('TOTAL NEW REPORTS', %r)\n" % TotalReports)
auxLog.write("('TOTAL DIFFERENCES', %r)\n" % foundDiffs)
auxLog.close()
return foundDiffs, len(resultsA.diagnostics), len(resultsB.diagnostics)
def generate_option_parser():
parser = OptionParser("usage: %prog [options] [dir A] [dir B]")
parser.add_option("", "--rootA", dest="rootA",
help="Prefix to ignore on source files for directory A",
action="store", type=str, default="")
parser.add_option("", "--rootB", dest="rootB",
help="Prefix to ignore on source files for directory B",
action="store", type=str, default="")
parser.add_option("", "--verbose-log", dest="verboseLog",
help="Write additional information to LOG \
[default=None]",
action="store", type=str, default=None,
metavar="LOG")
parser.add_option("--relative-path-differences-histogram",
action="store_true", dest="relative_path_histogram",
default=False,
help="Show histogram of relative paths differences. \
Requires matplotlib")
parser.add_option("--relative-log-path-differences-histogram",
action="store_true", dest="relative_log_path_histogram",
default=False,
help="Show histogram of log relative paths differences. \
Requires matplotlib")
parser.add_option("--absolute-path-differences-histogram",
action="store_true", dest="absolute_path_histogram",
default=False,
help="Show histogram of absolute paths differences. \
Requires matplotlib")
parser.add_option("--stats-only", action="store_true", dest="stats_only",
default=False, help="Only show statistics on reports")
parser.add_option("--show-stats", action="store_true", dest="show_stats",
default=False, help="Show change in statistics")
return parser
def main():
parser = generate_option_parser()
(opts, args) = parser.parse_args()
if len(args) != 2:
parser.error("invalid number of arguments")
dirA, dirB = args
dumpScanBuildResultsDiff(dirA, dirB, opts)
if __name__ == '__main__':
main()