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How to use analyze_all method in ATX

Best Python code snippet using ATX

analyze.py

Source:analyze.py

1#!/usr/bin/python32import sys3import os4import math;5import glob;6import traceback7import matplotlib.pyplot as plt8from matplotlib.collections import PatchCollection9from matplotlib.patches import Rectangle10import numpy as np11import simplejson as json12from optparse import OptionParser13from analyze_debug import parseDebug14from analyze_work import plotWork15from analyze_corpus import plotCorpus16from analyze_signal import plotSignal17from analyze_coverage import plotCoverage18from analyze_programs import plotPrograms19from analyze_triage import plotTriage20from analyze_mab import plotMAB21from analyze_seeds import plotSeeds22from analyze_mutationtree import plotMutationTree23from analyze_crashes import plotCrashes24from plot import plot25if __name__ == "__main__":26    # tests = ["RAMINDEX-0.0", "RAMINDEX-0.2", "RAMINDEX-0.4", "RAMINDEX-0.6", "RAMINDEX-0.8", "RAMINDEX", "KCOV", "NOCOVER", "KCOV-0.0", "NOCOVER-0.0"]27    parser = OptionParser()28    parser.add_option("-B", "--blacklist", dest="blacklist",29                  help="Blacklist", default="")30    parser.add_option("-a", "--all", dest="analyze_all", action="store_true",31                  help="Analyze everything", default=False)32    parser.add_option("-c", "--coverage", dest="analyze_coverage", action="store_true",33                  help="Analyze coverage", default=False)34    parser.add_option("-t", "--triage", dest="analyze_triage", action="store_true",35                  help="Analyze triage", default=False)36    parser.add_option("-w", "--work", dest="analyze_work", action="store_true",37                  help="Analyze work", default=False)38    parser.add_option("-p", "--program", dest="analyze_program", action="store_true",39                  help="Analyze programs", default=False)40    parser.add_option("-m", "--mab", dest="analyze_mab", action="store_true",41                  help="Analyze MAB", default=False)42    parser.add_option("-M", "--mutation-tree", dest="analyze_mutationtree", action="store_true",43                  help="Analyze Mutation Tree", default=False)44    parser.add_option("-s", "--seed", dest="analyze_seed", action="store_true",45                  help="Analyze Seed", default=False)46    parser.add_option("-C", "--crash", dest="analyze_crashes", action="store_true",47                  help="Analyze Crashes", default=False)48    (options, args) = parser.parse_args()49    blacklist = options.blacklist.split(',') if len(options.blacklist) > 0 else []50    tests = [];51    for fn in glob.glob("log_*"):52        skip = False53        for b in blacklist:54            if b in fn:55                skip = True56                break;57        if not skip:58            tests.append(fn.strip("log_"))59    try:60        if options.analyze_coverage or options.analyze_all:61            plotCoverage(tests)62        if options.analyze_triage or options.analyze_all:63            plotTriage(tests)64        if options.analyze_work or options.analyze_all:65            plotWork(tests)66        if options.analyze_mab or options.analyze_all:67            plotMAB(tests)68        if options.analyze_program or options.analyze_all:69            plotPrograms(tests)70        if options.analyze_seed or options.analyze_all:71            plotSeeds(tests)72        if options.analyze_crashes or options.analyze_all:73            plotCrashes(tests)74        if options.analyze_mutationtree or options.analyze_all:75            plotMutationTree(tests)76        #plotSignal(tests)77        #plotCorpus(tests)78        #plotWork(tests)79    except:80        traceback.print_exc()81    """82    data_kcov = parseExp("syzlog_KCOV");83    data_ramindex = parseExp("syzlog_RAMINDEX");84    data_nocover = parseExp("syzlog_NOCOVER");85    # data_random = parseExp("syzlog_RANDOM");86    data = {"Kcov": data_kcov, "Ramindex": data_ramindex, "Nocover": data_nocover};87    plot(data, 1, 2, xlabel="Time elapsed (s)", title="Basic Block Coverage", outfile="execution.png");88    plot(data, 1, 3, xlabel="Time elapsed (s)", title="Hashed Coverage", outfile="execution_hashed.png");...

analysis.py

Source:analysis.py

1import pandas as pd2import matplotlib.pyplot as plt3import numpy as np4import seaborn as sns5def analyze_all(agent_name, data_file):6    analyze("{}_parametrized".format(agent_name), "data/{}_parametrized_total_results.csv".format(data_file), [0, 6, 7, 8])7    #analyze("{}_decay".format(agent_name), "data/{}_decaying_learning_parametrized_total_results.csv".format(data_file), [0, 6, 7])8    #analyze("{}_slow_decay".format(agent_name), "data/{}_slow_decaying_learning_parametrized_total_results.csv".format(data_file), [0, 6, 7])9    analyze_groups("{}_parametrized".format(agent_name), "data/{}_parametrized_total_results.csv".format(data_file))10def analyze_groups(agent_name, data_file):11    print agent_name12    print "-------------"13    # Read agent runs data14    agent_data = pd.read_csv(data_file)15    grouped = agent_data.groupby(['alpha', 'gamma', 'epsilon'])16    f = {'n_dest_reached':['mean','std'], 'last_dest_fail':['mean','std'], 'last_penalty':['mean','std'], 'len_qvals':['mean','std']}17    aggregated_result = grouped.agg(f).reset_index()18    19    sorted_results = aggregated_result.sort([('last_penalty', 'mean'), ('last_penalty', 'std')], ascending=[1, 0]).head(n=10)20    print sorted_results21    print "-------------"22    sorted_q = aggregated_result.sort([('n_dest_reached', 'mean'), ('n_dest_reached', 'std')], ascending=[0, 1]).head(n=10)23    print sorted_q24    print "====================================="25def analyze(agent_name, data_file, drop_columns):26    # Read agent runs data27    agent_data = pd.read_csv(data_file)28    29    # Remove parameter columns30    metrics_only = agent_data.drop(agent_data.columns[drop_columns], axis=1)31    print "Agent global Metrics"32    print metrics_only.describe()33    # Rewards will be plotted somewhere wlse34    metrics_only.drop("reward_sum", axis=1, inplace=True)35    sns.boxplot(data=metrics_only)36    plt.savefig("charts/{}_global_results_boxplot.png".format(agent_name))37    plt.close()38    filtered = agent_data.sort(['last_penalty', 'last_dest_fail', 'n_dest_reached'], ascending=[1, 1, 0]).head(n=10)39    40    print "-------------"41    print "Best 10"42    print filtered.describe()43    print "------------"44    print filtered45    to_plot = filtered.drop(agent_data.columns[drop_columns], axis=1)46    to_plot.drop("reward_sum", axis=1, inplace=True)47    sns.boxplot(data=to_plot)48    plt.savefig("charts/{}_filtered_results_boxplot.png".format(agent_name))49    plt.close()50    print "====================================="51        52if __name__ == '__main__':53     # Read agent runs data54    agent_data = pd.read_csv("data/LearningAgent_results.csv")55    drop_columns = [0, 1]56    # Remove parameter columns57    metrics_only = agent_data.drop(agent_data.columns[drop_columns], axis=1)58    print "Agent global Metrics"59    print metrics_only.describe()60    sns.boxplot(data=metrics_only)61    plt.savefig("charts/final_agent_boxplot.png")62    plt.close()63    #pd.set_option('display.max_columns', None)64    #pd.set_option('display.width', 1000)65    #analyze_all("only_input_without_waypoint","OnlyInputWithoutWaypointStateAgent")66    #analyze_all("input_with_waypoint","InputWithWaypointStateAgent")67    #analyze_all("input_with_waypoint_and_deadline","InputWithWaypointAndDeadlineStateAgent")68    #analyze_all("input_with_waypoint_without_right","WithoutRightStateAgent")69    #analyze_all("input_with_waypoint_without_right_and_reduced_left","LearningAgent")...

test.py

Source:test.py

...8        existed_before = os.path.isfile(filename)9        b = Backend("test.sonare")10        if not existed_before:11            load_elf(b, "test.so")12            analyze_all(b)13    else:14        b = Backend()15        load_elf(b, "test.so")16        analyze_all(b)17    print(f"found {len(b.names)} aliases")18    print(f"found {len(b.functions)} functions")19    for sec in b.sections.iter_by_addr():...

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