llvm-project/llvm/utils/llvm-locstats/llvm-locstats.py

341 lines
13 KiB
Python
Executable File

#!/usr/bin/env python
#
# This is a tool that works like debug location coverage calculator.
# It parses the llvm-dwarfdump --statistics output by reporting it
# in a more human readable way.
#
from __future__ import print_function
import argparse
import os
import sys
from json import loads
from math import ceil
from collections import OrderedDict
from subprocess import Popen, PIPE
# Initialize the plot.
def init_plot(plt):
plt.title('Debug Location Statistics', fontweight='bold')
plt.xlabel('location buckets')
plt.ylabel('number of variables in the location buckets')
plt.xticks(rotation=45, fontsize='x-small')
plt.yticks()
# Finalize the plot.
def finish_plot(plt):
plt.legend()
plt.grid(color='grey', which='major', axis='y', linestyle='-', linewidth=0.3)
plt.savefig('locstats.png')
print('The plot was saved within "locstats.png".')
# Holds the debug location statistics.
class LocationStats:
def __init__(self, file_name, variables_total, variables_total_locstats,
variables_with_loc, variables_scope_bytes_covered, variables_scope_bytes,
variables_coverage_map):
self.file_name = file_name
self.variables_total = variables_total
self.variables_total_locstats = variables_total_locstats
self.variables_with_loc = variables_with_loc
self.scope_bytes_covered = variables_scope_bytes_covered
self.scope_bytes = variables_scope_bytes
self.variables_coverage_map = variables_coverage_map
# Get the PC ranges coverage.
def get_pc_coverage(self):
pc_ranges_covered = int(ceil(self.scope_bytes_covered * 100.0) \
/ self.scope_bytes)
return pc_ranges_covered
# Pretty print the debug location buckets.
def pretty_print(self):
if self.scope_bytes == 0:
print ('No scope bytes found.')
return -1
pc_ranges_covered = self.get_pc_coverage()
variables_coverage_per_map = {}
for cov_bucket in coverage_buckets():
variables_coverage_per_map[cov_bucket] = \
int(ceil(self.variables_coverage_map[cov_bucket] * 100.0) \
/ self.variables_total_locstats)
print (' =================================================')
print (' Debug Location Statistics ')
print (' =================================================')
print (' cov% samples percentage(~) ')
print (' -------------------------------------------------')
for cov_bucket in coverage_buckets():
print (' {0:10} {1:8d} {2:3d}%'. \
format(cov_bucket, self.variables_coverage_map[cov_bucket], \
variables_coverage_per_map[cov_bucket]))
print (' =================================================')
print (' -the number of debug variables processed: ' \
+ str(self.variables_total_locstats))
print (' -PC ranges covered: ' + str(pc_ranges_covered) + '%')
# Only if we are processing all the variables output the total
# availability.
if self.variables_total and self.variables_with_loc:
total_availability = int(ceil(self.variables_with_loc * 100.0) \
/ self.variables_total)
print (' -------------------------------------------------')
print (' -total availability: ' + str(total_availability) + '%')
print (' =================================================')
return 0
# Draw a plot representing the location buckets.
def draw_plot(self):
from matplotlib import pyplot as plt
buckets = range(len(self.variables_coverage_map))
plt.figure(figsize=(12, 8))
init_plot(plt)
plt.bar(buckets, self.variables_coverage_map.values(), align='center',
tick_label=self.variables_coverage_map.keys(),
label='variables of {}'.format(self.file_name))
# Place the text box with the coverage info.
pc_ranges_covered = self.get_pc_coverage()
props = dict(boxstyle='round', facecolor='wheat', alpha=0.5)
plt.text(0.02, 0.90, 'PC ranges covered: {}%'.format(pc_ranges_covered),
transform=plt.gca().transAxes, fontsize=12,
verticalalignment='top', bbox=props)
finish_plot(plt)
# Compare the two LocationStats objects and draw a plot showing
# the difference.
def draw_location_diff(self, locstats_to_compare):
from matplotlib import pyplot as plt
pc_ranges_covered = self.get_pc_coverage()
pc_ranges_covered_to_compare = locstats_to_compare.get_pc_coverage()
buckets = range(len(self.variables_coverage_map))
buckets_to_compare = range(len(locstats_to_compare.variables_coverage_map))
fig = plt.figure(figsize=(12, 8))
ax = fig.add_subplot(111)
init_plot(plt)
ax.bar(buckets, self.variables_coverage_map.values(), align='edge',
tick_label=self.variables_coverage_map.keys(), width=0.4,
label='variables of {}'.format(self.file_name))
ax.bar(buckets_to_compare,
locstats_to_compare.variables_coverage_map.values(),
color='r', align='edge', width=-0.4,
tick_label=locstats_to_compare.variables_coverage_map.keys(),
label='variables of {}'.format(locstats_to_compare.file_name))
props = dict(boxstyle='round', facecolor='wheat', alpha=0.5)
plt.text(0.02, 0.88,
'{} PC ranges covered: {}%'. \
format(self.file_name, pc_ranges_covered),
transform=plt.gca().transAxes, fontsize=12,
verticalalignment='top', bbox=props)
plt.text(0.02, 0.83,
'{} PC ranges covered: {}%'. \
format(locstats_to_compare.file_name,
pc_ranges_covered_to_compare),
transform=plt.gca().transAxes, fontsize=12,
verticalalignment='top', bbox=props)
finish_plot(plt)
# Define the location buckets.
def coverage_buckets():
yield '0%'
yield '(0%,10%)'
for start in range(10, 91, 10):
yield '[{0}%,{1}%)'.format(start, start + 10)
yield '100%'
# Parse the JSON representing the debug statistics, and create a
# LocationStats object.
def parse_locstats(opts, binary):
# These will be different due to different options enabled.
variables_total = None
variables_total_locstats = None
variables_with_loc = None
variables_scope_bytes_covered = None
variables_scope_bytes = None
variables_scope_bytes_entry_values = None
variables_coverage_map = OrderedDict()
# Get the directory of the LLVM tools.
llvm_dwarfdump_cmd = os.path.join(os.path.dirname(__file__), \
"llvm-dwarfdump")
# The statistics llvm-dwarfdump option.
llvm_dwarfdump_stats_opt = "--statistics"
# Generate the stats with the llvm-dwarfdump.
subproc = Popen([llvm_dwarfdump_cmd, llvm_dwarfdump_stats_opt, binary], \
stdin=PIPE, stdout=PIPE, stderr=PIPE, \
universal_newlines = True)
cmd_stdout, cmd_stderr = subproc.communicate()
# Get the JSON and parse it.
json_parsed = None
try:
json_parsed = loads(cmd_stdout)
except:
print ('error: No valid llvm-dwarfdump statistics found.')
sys.exit(1)
if opts.only_variables:
# Read the JSON only for local variables.
variables_total_locstats = \
json_parsed['total vars procesed by location statistics']
variables_scope_bytes_covered = \
json_parsed['vars scope bytes covered']
variables_scope_bytes = \
json_parsed['vars scope bytes total']
if not opts.ignore_debug_entry_values:
for cov_bucket in coverage_buckets():
cov_category = "vars with {} of its scope covered".format(cov_bucket)
variables_coverage_map[cov_bucket] = json_parsed[cov_category]
else:
variables_scope_bytes_entry_values = \
json_parsed['vars entry value scope bytes covered']
variables_scope_bytes_covered = variables_scope_bytes_covered \
- variables_scope_bytes_entry_values
for cov_bucket in coverage_buckets():
cov_category = \
"vars (excluding the debug entry values) " \
"with {} of its scope covered".format(cov_bucket)
variables_coverage_map[cov_bucket] = json_parsed[cov_category]
elif opts.only_formal_parameters:
# Read the JSON only for formal parameters.
variables_total_locstats = \
json_parsed['total params procesed by location statistics']
variables_scope_bytes_covered = \
json_parsed['formal params scope bytes covered']
variables_scope_bytes = \
json_parsed['formal params scope bytes total']
if not opts.ignore_debug_entry_values:
for cov_bucket in coverage_buckets():
cov_category = "params with {} of its scope covered".format(cov_bucket)
variables_coverage_map[cov_bucket] = json_parsed[cov_category]
else:
variables_scope_bytes_entry_values = \
json_parsed['formal params entry value scope bytes covered']
variables_scope_bytes_covered = variables_scope_bytes_covered \
- variables_scope_bytes_entry_values
for cov_bucket in coverage_buckets():
cov_category = \
"params (excluding the debug entry values) " \
"with {} of its scope covered".format(cov_bucket)
variables_coverage_map[cov_bucket] = json_parsed[cov_category]
else:
# Read the JSON for both local variables and formal parameters.
variables_total = \
json_parsed['source variables']
variables_with_loc = json_parsed['variables with location']
variables_total_locstats = \
json_parsed['total variables procesed by location statistics']
variables_scope_bytes_covered = \
json_parsed['scope bytes covered']
variables_scope_bytes = \
json_parsed['scope bytes total']
if not opts.ignore_debug_entry_values:
for cov_bucket in coverage_buckets():
cov_category = "variables with {} of its scope covered". \
format(cov_bucket)
variables_coverage_map[cov_bucket] = json_parsed[cov_category]
else:
variables_scope_bytes_entry_values = \
json_parsed['entry value scope bytes covered']
variables_scope_bytes_covered = variables_scope_bytes_covered \
- variables_scope_bytes_entry_values
for cov_bucket in coverage_buckets():
cov_category = "variables (excluding the debug entry values) " \
"with {} of its scope covered". format(cov_bucket)
variables_coverage_map[cov_bucket] = json_parsed[cov_category]
return LocationStats(binary, variables_total, variables_total_locstats,
variables_with_loc, variables_scope_bytes_covered,
variables_scope_bytes, variables_coverage_map)
# Parse the program arguments.
def parse_program_args(parser):
parser.add_argument('--only-variables', action='store_true', default=False,
help='calculate the location statistics only for local variables')
parser.add_argument('--only-formal-parameters', action='store_true',
default=False,
help='calculate the location statistics only for formal parameters')
parser.add_argument('--ignore-debug-entry-values', action='store_true',
default=False,
help='ignore the location statistics on locations with '
'entry values')
parser.add_argument('--draw-plot', action='store_true', default=False,
help='show histogram of location buckets generated (requires '
'matplotlib)')
parser.add_argument('--compare', action='store_true', default=False,
help='compare the debug location coverage on two files provided, '
'and draw a plot showing the difference (requires '
'matplotlib)')
parser.add_argument('file_names', nargs='+', type=str, help='file to process')
return parser.parse_args()
# Verify that the program inputs meet the requirements.
def verify_program_inputs(opts):
if len(sys.argv) < 2:
print ('error: Too few arguments.')
return False
if opts.only_variables and opts.only_formal_parameters:
print ('error: Please use just one --only* option.')
return False
if not opts.compare and len(opts.file_names) != 1:
print ('error: Please specify only one file to process.')
return False
if opts.compare and len(opts.file_names) != 2:
print ('error: Please specify two files to process.')
return False
if opts.draw_plot or opts.compare:
try:
import matplotlib
except ImportError:
print('error: matplotlib not found.')
return False
return True
def Main():
parser = argparse.ArgumentParser()
opts = parse_program_args(parser)
if not verify_program_inputs(opts):
parser.print_help()
sys.exit(1)
binary_file = opts.file_names[0]
locstats = parse_locstats(opts, binary_file)
if not opts.compare:
if opts.draw_plot:
# Draw a histogram representing the location buckets.
locstats.draw_plot()
else:
# Pretty print collected info on the standard output.
if locstats.pretty_print() == -1:
sys.exit(0)
else:
binary_file_to_compare = opts.file_names[1]
locstats_to_compare = parse_locstats(opts, binary_file_to_compare)
# Draw a plot showing the difference in debug location coverage between
# two files.
locstats.draw_location_diff(locstats_to_compare)
if __name__ == '__main__':
Main()
sys.exit(0)