Tentative progress in stats
This commit is contained in:
parent
3cb2c508a0
commit
216e442f5b
4 changed files with 359 additions and 127 deletions
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@ -1,5 +1,6 @@
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#!/usr/bin/env python3
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from stats_accu import StatsAccumulator
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import gather_stats
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import argparse
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@ -15,6 +16,9 @@ class Config:
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if args.feature == 'gather':
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self.output = args.output
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elif args.feature == 'sample':
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self.size = int(args.size)
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elif args.feature == 'analyze':
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self.data_file = args.data_file
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@ -34,6 +38,19 @@ class Config:
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subparsers = parser.add_subparsers(help='Subcommands')
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# Sample stats
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parser_sample = subparsers.add_parser(
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'sample',
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help='Same as gather, but for a random subset of files')
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parser_sample.set_defaults(feature='sample')
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parser_sample.add_argument('--size', '-n',
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default=1000,
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help=('Pick this number of files'))
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parser_sample.add_argument('--output', '-o',
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default='elf_data',
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help=('Output data to this file. Defaults '
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'to "elf_data"'))
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# Gather stats
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parser_gather = subparsers.add_parser(
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'gather',
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@ -70,11 +87,17 @@ def main():
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if config.feature == 'gather':
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stats_accu = gather_stats.gather_system_files(config)
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stats_accu.serialize(config.output)
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stats_accu.dump(config.output)
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elif config.feature == 'sample':
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stats_accu = gather_stats.gather_system_files(
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config,
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sample_size=config.size)
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elif config.feature == 'analyze':
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# TODO
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print("Not implemented", file=sys.stderr)
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stats_accu = StatsAccumulator.load(config.data_file)
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sys.exit(1)
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@ -1,52 +1,119 @@
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from pyelftools_overlay import system_elfs
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import pathos
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from pyelftools_overlay import system_elfs, get_cfi
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from elftools.dwarf import callframe
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import multiprocessing
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import signal
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import itertools
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import random
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from stats_accu import StatsAccumulator
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from stats_accu import \
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StatsAccumulator, SingleFdeData, \
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RegsList, FdeData, DwarfInstr
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class FilesProcessor:
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def __init__(self, cores, stats_accu=None):
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class FilesProcessor(multiprocessing.Process):
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def __init__(self, elf_list, shared_queue):
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super().__init__()
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self.stop_processing = False
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self._processed_counter = itertools.count()
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self.cores = cores
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if stats_accu is None:
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stats_accu = StatsAccumulator()
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self.stats_accu = stats_accu
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self.processed_counter = 0
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self.elf_list = elf_list
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self.shared_queue = shared_queue
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def stop_processing_now(self):
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self.stop_processing = True
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def next_counter(self):
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return self._processed_counter.__next__()
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def run(self):
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pos = 0
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for descr in self.elf_list:
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if self.stop_processing:
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break
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self.process_single_file(descr, pos)
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pos += 1
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def run(self, elf_list):
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self.elf_count = len(elf_list)
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with pathos.multiprocessing.ProcessPool(nodes=self.cores) as pool:
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pool.map(self.process_single_file, elf_list)
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print("=== Finished {} ===".format(self.name))
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return 0
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def process_single_file(self, elf_path):
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def process_single_file(self, elf_descr, pos_in_list):
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if self.stop_processing:
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return
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cur_file_count = self.next_counter()
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print('> [{}/{} {:.0f}%] {}'.format(
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cur_file_count, self.elf_count,
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cur_file_count / self.elf_count * 100, elf_path))
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self.stats_accu.process_file(elf_path)
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elf_path, elf_type = elf_descr
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self.processed_counter += 1
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print('[{}, {}/{}] {}'.format(
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self.shared_queue.qsize(),
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pos_in_list + 1,
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len(self.elf_list),
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elf_path))
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self.process_file(elf_path, elf_type)
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def process_file(self, path, elftype):
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''' Process a single file '''
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cfi = get_cfi(path)
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if not cfi:
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return None
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data = FdeData()
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for entry in cfi:
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if isinstance(entry, callframe.CIE): # Is a CIE
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self.process_cie(entry, data)
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elif isinstance(entry, callframe.FDE): # Is a FDE
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self.process_fde(entry, data)
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out = SingleFdeData(path, elftype, data)
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self.shared_queue.put(out)
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def incr_cell(self, table, key):
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''' Increments table[key], or sets it to 1 if unset '''
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if key in table:
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table[key] += 1
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else:
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table[key] = 1
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def process_cie(self, cie, data):
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''' Process a CIE '''
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pass # Nothing needed from a CIE
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def process_fde(self, fde, data):
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''' Process a FDE '''
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data.fde_count += 1
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decoded = fde.get_decoded()
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row_count = len(decoded.table)
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self.incr_cell(data.fde_with_lines, row_count)
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for row in decoded.table:
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self.process_reg(data.regs.cfa, row['cfa'])
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for entry in row:
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if isinstance(entry, int):
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self.process_reg(data.regs.regs[entry], row[entry])
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def process_reg(self, out_reg, reg_def):
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''' Process a register '''
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if isinstance(reg_def, callframe.CFARule):
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if reg_def.reg is not None:
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out_reg.regs[reg_def.reg] += 1
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else:
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pass # TODO exprs
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else:
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self.incr_cell(out_reg.instrs, DwarfInstr.of_pyelf(reg_def.type))
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if reg_def.type == callframe.RegisterRule.REGISTER:
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out_reg.regs[reg_def.arg] += 1
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elif (reg_def.type == callframe.RegisterRule.EXPRESSION) \
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or (reg_def.type == callframe.RegisterRule.VAL_EXPRESSION):
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pass # TODO exprs
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def gather_system_files(config):
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def gather_system_files(config, sample_size=None):
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stats_accu = StatsAccumulator()
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processor = FilesProcessor(config.cores, stats_accu)
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processors = []
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def signal_graceful_exit(sig, frame):
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''' Stop gracefully now '''
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nonlocal processor
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nonlocal processors
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print("Stopping after this ELF…")
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for processor in processors:
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processor.stop_processing_now()
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signal.signal(signal.SIGINT, signal_graceful_exit)
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@ -55,6 +122,50 @@ def gather_system_files(config):
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for elf_path in system_elfs():
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elf_list.append(elf_path)
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processor.run(elf_list)
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if sample_size is not None:
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elf_list_sampled = random.sample(elf_list, sample_size)
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elf_list = elf_list_sampled
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elf_count = len(elf_list)
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elf_per_process = elf_count // config.cores
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elf_list_slices = []
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for i in range(config.cores - 1):
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elf_list_slices.append(
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elf_list[i * elf_per_process : (i+1) * elf_per_process])
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elf_list_slices.append(
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elf_list[(config.cores - 1) * elf_per_process
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: config.cores * elf_per_process])
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shared_queue = multiprocessing.Queue(elf_count)
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for elf_range in elf_list_slices:
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processors.append(FilesProcessor(elf_range, shared_queue))
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if config.cores > 1:
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for processor in processors:
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processor.start()
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while True:
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for processor in processors:
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if processor.is_alive():
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print("== Waiting {} ({} {}) ==".format(
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processor.name, processor.exitcode,
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processor.is_alive()))
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processor.join(timeout=1)
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if processor.exitcode is None:
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break # Loop around
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print("== Joined {} ==".format(processor.name))
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terminated = True
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for processor in processors:
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if processor.exitcode is None:
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terminated = False
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if terminated:
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break
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else:
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processors[0].run() # run(), not start(): in the same thread
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while not shared_queue.empty(): # Reliable because everything is joined
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stats_accu.add_fde(shared_queue.get_nowait())
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return stats_accu
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@ -2,6 +2,7 @@
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from elftools.elf.elffile import ELFFile
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from elftools.common.exceptions import ELFError, DWARFError
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from stats_accu import ElfType
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import os
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@ -44,20 +45,20 @@ def system_elfs():
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os.readlink(path)))
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sysbin_dirs = [
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'/lib',
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'/usr/lib',
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'/usr/local/lib',
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'/bin',
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'/usr/bin',
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'/usr/local/bin',
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'/sbin',
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('/lib', ElfType.ELF_LIB),
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('/usr/lib', ElfType.ELF_LIB),
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('/usr/local/lib', ElfType.ELF_LIB),
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('/bin', ElfType.ELF_BINARY),
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('/usr/bin', ElfType.ELF_BINARY),
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('/usr/local/bin', ElfType.ELF_BINARY),
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('/sbin', ElfType.ELF_BINARY),
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]
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to_explore = sysbin_dirs
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seen_elfs = set()
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while to_explore:
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bindir = to_explore.pop()
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bindir, elftype = to_explore.pop()
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if not os.path.isdir(bindir):
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continue
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@ -65,12 +66,23 @@ def system_elfs():
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for direntry in os.scandir(bindir):
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if not direntry.is_file():
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if direntry.is_dir():
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to_explore.append(direntry.path)
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to_explore.append((direntry.path, elftype))
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continue
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canonical_name = readlink_rec(direntry.path)
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if canonical_name in seen_elfs:
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continue
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valid_elf = True
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try:
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with open(canonical_name, 'rb') as handle:
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magic_bytes = handle.read(4)
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if magic_bytes != b'\x7fELF':
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valid_elf = False
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except Exception:
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continue
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if not valid_elf:
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continue
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seen_elfs.add(canonical_name)
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yield canonical_name
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yield (canonical_name, elftype)
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@ -1,9 +1,9 @@
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from elftools.dwarf import callframe
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from pyelftools_overlay import get_cfi
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from enum import Enum
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import json
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import enum
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import subprocess
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import re
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import json
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import collections
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from math import ceil
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@ -69,109 +69,195 @@ def elf_so_deps(path):
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"{}.").format(path, exn.returncode))
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class ElfType(Enum):
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ELF_LIB = auto()
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ELF_BINARY = auto()
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class ElfType(enum.Enum):
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ELF_LIB = enum.auto()
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ELF_BINARY = enum.auto()
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class DwarfInstr(enum.Enum):
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@staticmethod
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def of_pyelf(val):
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_table = {
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callframe.RegisterRule.UNDEFINED: DwarfInstr.INSTR_UNDEF,
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callframe.RegisterRule.SAME_VALUE: DwarfInstr.INSTR_SAME_VALUE,
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callframe.RegisterRule.OFFSET: DwarfInstr.INSTR_OFFSET,
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callframe.RegisterRule.VAL_OFFSET: DwarfInstr.INSTR_VAL_OFFSET,
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callframe.RegisterRule.REGISTER: DwarfInstr.INSTR_REGISTER,
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callframe.RegisterRule.EXPRESSION: DwarfInstr.INSTR_EXPRESSION,
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callframe.RegisterRule.VAL_EXPRESSION:
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DwarfInstr.INSTR_VAL_EXPRESSION,
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callframe.RegisterRule.ARCHITECTURAL:
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DwarfInstr.INSTR_ARCHITECTURAL,
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}
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return _table[val]
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INSTR_UNDEF = enum.auto()
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INSTR_SAME_VALUE = enum.auto()
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INSTR_OFFSET = enum.auto()
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INSTR_VAL_OFFSET = enum.auto()
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INSTR_REGISTER = enum.auto()
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INSTR_EXPRESSION = enum.auto()
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INSTR_VAL_EXPRESSION = enum.auto()
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INSTR_ARCHITECTURAL = enum.auto()
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def intify_dict(d):
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out = {}
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for key in d:
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try:
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nKey = int(key)
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except Exception:
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nKey = key
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try:
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out[nKey] = int(d[key])
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except ValueError:
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out[nKey] = d[key]
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return out
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class RegData:
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def __init__(self, instrs=None, regs=None, exprs=None):
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if instrs is None:
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instrs = {}
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if regs is None:
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regs = [0]*17
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if exprs is None:
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exprs = {}
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self.instrs = intify_dict(instrs)
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self.regs = regs
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self.exprs = intify_dict(exprs)
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@staticmethod
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def map_dict_keys(fnc, dic):
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out = {}
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for key in dic:
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out[fnc(key)] = dic[key]
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return out
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def dump(self):
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return {
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'instrs': RegData.map_dict_keys(lambda x: x.value, self.instrs),
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'regs': self.regs,
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'exprs': self.exprs,
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}
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@staticmethod
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def load(data):
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return RegData(
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instrs=RegData.map_dict_keys(
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lambda x: DwarfInstr(int(x)),
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data['instrs']),
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regs=data['regs'],
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exprs=data['exprs'],
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)
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class RegsList:
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def __init__(self, cfa=None, regs=None):
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if cfa is None:
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cfa = RegsList.fresh_reg()
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if regs is None:
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regs = [RegsList.fresh_reg() for _ in range(17)]
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self.cfa = cfa
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self.regs = regs
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@staticmethod
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def fresh_reg():
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return RegData()
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def dump(self):
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return {
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'cfa': RegData.dump(self.cfa),
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'regs': [RegData.dump(r) for r in self.regs],
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}
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@staticmethod
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def load(data):
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return RegsList(
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cfa=RegData.load(data['cfa']),
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regs=[RegData.load(r) for r in data['regs']],
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)
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class FdeData:
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def __init__(self, fde_count=0, fde_with_lines=None, regs=None):
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if fde_with_lines is None:
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fde_with_lines = {}
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if regs is None:
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regs = RegsList()
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self.fde_count = fde_count
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self.fde_with_lines = intify_dict(fde_with_lines)
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self.regs = regs
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def dump(self):
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return {
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'fde_count': self.fde_count,
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'fde_with_lines': self.fde_with_lines,
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'regs': self.regs.dump(),
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}
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@staticmethod
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def load(data):
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return FdeData(
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fde_count=int(data['fde_count']),
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fde_with_lines=data['fde_with_lines'],
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regs=RegsList.load(data['regs']))
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class SingleFdeData:
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def __init__(self, path, elf_type, data):
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self.path = path
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self.elf_type = elf_type
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self.data = data
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self.data = data # < of type FdeData
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self.gather_deps()
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def gather_deps(self):
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""" Collect ldd data on the binary """
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self.deps = elf_so_deps(self.path)
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# self.deps = elf_so_deps(self.path)
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self.deps = []
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def dump(self):
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return {
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'path': self.path,
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'elf_type': self.elf_type.value,
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'data': self.data.dump()
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}
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@staticmethod
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def load(data):
|
||||
return SingleFdeData(
|
||||
data['path'],
|
||||
ElfType(int(data['elf_type'])),
|
||||
FdeData.load(data['data']))
|
||||
|
||||
|
||||
class StatsAccumulator:
|
||||
def __init__(self):
|
||||
self.elf_count = 0
|
||||
self.fde_count = 0
|
||||
self.fde_row_count = 0
|
||||
self.fde_with_n_rows = {}
|
||||
self.fdes = []
|
||||
|
||||
def serialize(self, path):
|
||||
''' Save the gathered data to `stream` '''
|
||||
def add_fde(self, fde_data):
|
||||
self.fdes.append(fde_data)
|
||||
|
||||
notable_fields = [
|
||||
'elf_count',
|
||||
'fde_count',
|
||||
'fde_row_count',
|
||||
'fde_with_n_rows',
|
||||
]
|
||||
out = {}
|
||||
for field in notable_fields:
|
||||
out[field] = self.__dict__[field]
|
||||
def get_fdes(self):
|
||||
return self.fdes
|
||||
|
||||
with open(path, 'wb') as stream:
|
||||
json.dump(out, stream)
|
||||
def add_stats_accu(self, stats_accu):
|
||||
for fde in stats_accu.get_fdes():
|
||||
self.add_fde(fde)
|
||||
|
||||
def dump(self, path):
|
||||
dict_form = [fde.dump() for fde in self.fdes]
|
||||
print(dict_form)
|
||||
with open(path, 'w') as handle:
|
||||
handle.write(json.dumps(dict_form))
|
||||
|
||||
@staticmethod
|
||||
def unserialize(path):
|
||||
def load(path):
|
||||
with open(path, 'r') as handle:
|
||||
text = handle.read()
|
||||
out = StatsAccumulator()
|
||||
with open(path, 'wb') as stream:
|
||||
data = json.load(stream)
|
||||
for field in data:
|
||||
out.field = data[field]
|
||||
out.fdes = [SingleFdeData.load(data) for data in json.loads(text)]
|
||||
return out
|
||||
|
||||
def report(self):
|
||||
''' Report on the statistics gathered '''
|
||||
|
||||
self.fde_rows_proportion = ProportionFinder(
|
||||
self.fde_with_n_rows)
|
||||
|
||||
rows = [
|
||||
("ELFs analyzed", self.elf_count),
|
||||
("FDEs analyzed", self.fde_count),
|
||||
("FDE rows analyzed", self.fde_row_count),
|
||||
("Avg. rows per FDE", self.fde_row_count / self.fde_count),
|
||||
("Median rows per FDE",
|
||||
self.fde_rows_proportion.find_at_proportion(0.5)),
|
||||
("Max rows per FDE", max(self.fde_with_n_rows.keys())),
|
||||
]
|
||||
|
||||
title_size = max(map(lambda x: len(x[0]), rows))
|
||||
line_format = "{:<" + str(title_size + 1) + "} {}"
|
||||
|
||||
for row in rows:
|
||||
print(line_format.format(row[0], row[1]))
|
||||
|
||||
def process_file(self, path):
|
||||
''' Process a single file '''
|
||||
|
||||
cfi = get_cfi(path)
|
||||
if not cfi:
|
||||
return
|
||||
|
||||
self.elf_count += 1
|
||||
|
||||
for entry in cfi:
|
||||
if isinstance(entry, callframe.CIE): # Is a CIE
|
||||
self.process_cie(entry)
|
||||
elif isinstance(entry, callframe.FDE): # Is a FDE
|
||||
self.process_fde(entry)
|
||||
|
||||
def incr_cell(self, table, key):
|
||||
''' Increments table[key], or sets it to 1 if unset '''
|
||||
if key in table:
|
||||
table[key] += 1
|
||||
else:
|
||||
table[key] = 1
|
||||
|
||||
def process_cie(self, cie):
|
||||
''' Process a CIE '''
|
||||
pass # Nothing needed from a CIE
|
||||
|
||||
def process_fde(self, fde):
|
||||
''' Process a FDE '''
|
||||
self.fde_count += 1
|
||||
|
||||
decoded = fde.get_decoded()
|
||||
row_count = len(decoded.table)
|
||||
self.fde_row_count += row_count
|
||||
self.incr_cell(self.fde_with_n_rows, row_count)
|
||||
|
|
|
|||
Loading…
Reference in a new issue