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