FuzzBench: pinky14 report

(experiment incomplete/still running...)
warning
Please consider this as a preliminary report to demonstrate the capabilities of FuzzBench. While we have tried our best, we have not confirmed that we configured everything correctly. We are hoping to work together with the community to validate results and improve the set of fuzzers, benchmarks, and their configurations in the future. See FAQ for more details.

experiment summary

No aggregate ranking as the data contains a single benchmark.
  • Median relative code-coverages on each benchmark

    Note: The relative coverage summary table shows the median relative performance of each fuzzer to the experiment maximum. Thus the highest relative performance may not be 100%.
    trial_relative_coverage = trial_coverage / experiment_max_coverage

    app_wrs_rf_new app_stable app_wrs_rf_old
    FuzzerMedian 97.98 96.09 87.20
    FuzzerMean 97.98 96.09 87.20
    freetype2-2017 97.98 96.09 87.20
    • Fuzzers are sorted by "FuzzerMean" (average median relative coverage), highest on the left.
    • Green background = highest relative median coverage.
    • Blue gradient background = greater than 95% relative median coverage.

freetype2-2017 summary

Ranking by median reached code coverage
Reached code coverage distribution
Mean code coverage growth over time
* The error bands show the 95% confidence interval around the mean code coverage.
  • Sample statistics and statistical significance (code coverage)
    Code coverage sample statistics
    count mean std min 25% median 75% max
    fuzzer time
    app_wrs_rf_new 86400 8.0 24405.125 304.431760 24066.0 24159.75 24298.5 24715.5 24799.0
    app_stable 86400 8.0 23940.625 578.188535 23048.0 23605.25 23829.0 24435.0 24732.0
    app_wrs_rf_old 86400 8.0 21762.500 493.803026 21277.0 21398.25 21624.5 21959.0 22537.0

    Vargha-Delaney A12 measure
    The table summarizes the A12 values from the pairwise Vargha-Delaney A measure of effect size. Green cells indicate the probability the fuzzer in the row will outperform the fuzzer in the column.
    Mann-Whitney U test
    The table summarizes the p values of pairwise Mann-Whitney U tests. Green cells indicate that the reached coverage distribution of a given fuzzer pair is significantly different.

experiment data

You can download the raw data for this report here.

Check out the documentation on how to create customized reports using this data. Also see some example Colab notebooks for doing custom analysis on the data here.

The experiment was conducted using this FuzzBench commit: da8e7b127d295d436fdb53eda46710f70b361c8f

To reproduce this experiment run the following commands in your FuzzBench repo:
# Check out the right commit.
git checkout da8e7b127d295d436fdb53eda46710f70b361c8f
# Download the internal config file.
curl https://storage.googleapis.com/pinky14/config/experiment.yaml > /tmp/experiment-config.yaml
make install-dependencies
# Launch the experiment using paramters from the internal config file.
PYTHONPATH=. python experiment/reproduce_experiment.py -c /tmp/experiment-config.yaml -e <new_experiment_name>

Experiment Description:

(None,)