FuzzBench: 2024-05-12-libafl report

experiment summary

We show two different aggregate (cross-benchmark) rankings of fuzzers. The first is based on the average of per-benchmarks scores, where the score represents the percentage of the highest reached median code-coverage on a given benchmark (higher value is better). The second ranking shows the average rank of fuzzers, after we rank them on each benchmark according to their median reached code-covereges (lower value is better).
By avg. score
average normalized score
fuzzer
aflplusplus 98.32
libafl 97.97
honggfuzz 95.19
libafl_saturation 94.84
libfuzzer 93.94
aflsmart 85.54
mopt 85.41
afl 83.95
eclipser 83.70
aflfast 82.82
fairfuzz 79.98
centipede 68.52
By avg. rank
average rank
fuzzer
aflplusplus 1.87
libafl 3.87
libfuzzer 5.04
honggfuzz 5.13
aflsmart 5.83
libafl_saturation 6.22
eclipser 6.74
mopt 7.09
afl 7.22
fairfuzz 9.00
aflfast 9.09
centipede 9.30
  • Critical difference diagram
    The diagram visualizes the average rank of fuzzers (second ranking above) while showing the significance of the differences as well. What is considered a "critical difference" (CD) is based on the Friedman/Nemenyi post-hoc test. See more in the documentation.
    Note: If a fuzzer does not support all benchmarks, its ranking as shown in this diagram can be lower than it should be. So please check the list of supported benchmarks for the fuzzer(s) of your interest. The list could be specified in the fuzzer's README.md like this.
  • 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

      aflplusplus libafl honggfuzz libafl_saturation libfuzzer eclipser aflsmart mopt afl aflfast centipede fairfuzz
    FuzzerMedian 97.00 97.00 97.00 95.00 94.00 94.00 95.00 93.00 94.00 93.00 90.00 87.00
    FuzzerMean 95.00 94.74 92.04 91.70 90.87 88.62 83.17 83.04 81.70 80.65 79.89 77.74
    bloaty_fuzz_target 98.00 98.00 95.00 95.00 89.00 94.00 95.00 97.00 94.00 93.00 nan 80.00
    curl_curl_fuzzer_http 96.00 98.00 97.00 96.00 90.00 93.00 93.00 93.00 93.00 92.00 nan 84.00
    freetype2_ftfuzzer 93.00 92.00 91.00 83.00 79.00 76.00 68.00 68.00 68.00 67.00 58.00 64.00
    harfbuzz_hb-shape-fuzzer 98.00 99.00 96.00 98.00 94.00 96.00 96.00 97.00 96.00 95.00 nan 84.00
    jsoncpp_jsoncpp_fuzzer 99.00 98.00 99.00 98.00 100.00 98.00 98.00 98.00 98.00 98.00 98.00 98.00
    lcms_cms_transform_fuzzer 94.00 95.00 82.00 93.00 87.00 76.00 70.00 72.00 41.00 29.00 38.00 55.00
    libjpeg-turbo_libjpeg_turbo_fuzzer 99.00 82.00 99.00 82.00 99.00 nan 99.00 99.00 99.00 99.00 96.00 99.00
    libpcap_fuzz_both 85.00 83.00 80.00 80.00 75.00 72.00 1.00 1.00 1.00 1.00 81.00 1.00
    libpng_libpng_read_fuzzer 95.00 95.00 96.00 94.00 96.00 95.00 95.00 94.00 95.00 94.00 96.00 94.00
    libxml2_xml 99.00 98.00 98.00 97.00 97.00 97.00 97.00 96.00 96.00 96.00 93.00 88.00
    libxslt_xpath 98.00 97.00 97.00 95.00 92.00 95.00 95.00 93.00 94.00 94.00 94.00 95.00
    mbedtls_fuzz_dtlsclient 71.00 88.00 70.00 70.00 70.00 70.00 70.00 70.00 70.00 68.00 69.00 73.00
    openh264_decoder_fuzzer 99.00 98.00 98.00 97.00 98.00 98.00 99.00 99.00 99.00 99.00 nan 90.00
    openssl_x509 99.00 99.00 99.00 99.00 99.00 99.00 99.00 99.00 99.00 99.00 99.00 99.00
    openthread_ot-ip6-send-fuzzer 90.00 88.00 77.00 86.00 78.00 76.00 73.00 73.00 73.00 73.00 73.00 70.00
    proj4_proj_crs_to_crs_fuzzer 89.00 90.00 97.00 86.00 93.00 60.00 10.00 9.00 9.00 9.00 10.00 10.00
    re2_fuzzer 99.00 99.00 98.00 98.00 99.00 99.00 99.00 98.00 99.00 99.00 95.00 99.00
    sqlite3_ossfuzz 96.00 99.00 68.00 84.00 78.00 90.00 90.00 90.00 91.00 90.00 61.00 57.00
    stb_stbi_read_fuzzer 95.00 96.00 93.00 93.00 88.00 92.00 88.00 87.00 88.00 87.00 86.00 87.00
    systemd_fuzz-link-parser 100.00 97.00 97.00 98.00 95.00 91.00 92.00 91.00 91.00 91.00 98.00 87.00
    vorbis_decode_fuzzer 99.00 98.00 98.00 98.00 99.00 98.00 98.00 98.00 98.00 98.00 90.00 97.00
    woff2_convert_woff2ttf_fuzzer 97.00 98.00 95.00 96.00 96.00 nan 92.00 91.00 91.00 90.00 88.00 81.00
    zlib_zlib_uncompress_fuzzer 97.00 94.00 97.00 93.00 99.00 96.00 96.00 97.00 96.00 94.00 95.00 96.00
    • 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.

bloaty_fuzz_target summary

Ranking by median reached code coverage
Reached code coverage distribution
Mean code coverage growth over time
Mean code coverage growth over time
* The error bands show the 95% confidence interval around the mean code coverage.
error
The following fuzzers do not have enough samples: aflplusplus, aflsmart, mopt, eclipser, libafl.
  • Sample statistics and statistical significance (code coverage)
    Code coverage sample statistics
    count mean std min 25% median 75% max
    fuzzer time
    aflplusplus 82800 15.0 6362.933333 53.783251 6262.0 6318.00 6363.0 6414.50 6437.0
    libafl 82800 11.0 6348.454545 40.497811 6289.0 6318.50 6360.0 6380.00 6400.0
    mopt 82800 14.0 6242.357143 84.158831 6046.0 6225.75 6267.5 6291.00 6350.0
    aflsmart 82800 15.0 6143.400000 156.758139 5816.0 6031.00 6149.0 6241.50 6401.0
    honggfuzz 82800 18.0 6094.111111 174.869662 5884.0 5918.25 6142.0 6248.00 6329.0
    libafl_saturation 82800 20.0 6139.300000 52.680866 6052.0 6088.00 6141.5 6175.00 6220.0
    afl 82800 18.0 6101.944444 119.949240 5889.0 6070.75 6098.5 6141.75 6338.0
    eclipser 82800 11.0 6053.181818 68.930136 5914.0 6022.50 6078.0 6095.50 6135.0
    aflfast 82800 17.0 6028.411765 77.961576 5893.0 5960.00 6035.0 6065.00 6185.0
    libfuzzer 82800 20.0 5795.800000 110.501536 5592.0 5718.75 5781.0 5869.50 5994.0
    fairfuzz 82800 16.0 5189.937500 67.159977 5111.0 5135.25 5170.0 5226.00 5323.0

    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.
  • Unique code coverage plots
    Ranking by unique code branches covered
    Each bar shows the total number of code branches found by a given fuzzer. The colored area shows the number of unique code branches (i.e., branches that were not covered by any other fuzzers).
    Pairwise unique code coverage
    Each cell represents the number of code branches covered by the fuzzer of the column but not by the fuzzer of the row

curl_curl_fuzzer_http summary

Ranking by median reached code coverage
Reached code coverage distribution
Mean code coverage growth over time
Mean code coverage growth over time
* The error bands show the 95% confidence interval around the mean code coverage.
error
The following fuzzers do not have enough samples: libafl, mopt, honggfuzz.
  • Sample statistics and statistical significance (code coverage)
    Code coverage sample statistics
    count mean std min 25% median 75% max
    fuzzer time
    libafl 82800 15.0 10874.666667 79.035857 10747.0 10842.50 10871.0 10903.00 11092.0
    honggfuzz 82800 12.0 10852.333333 75.781184 10735.0 10803.75 10842.0 10911.75 10967.0
    aflplusplus 82800 17.0 10784.764706 88.029490 10636.0 10737.00 10750.0 10845.00 10952.0
    libafl_saturation 82800 19.0 10720.052632 70.138334 10599.0 10670.00 10713.0 10778.00 10859.0
    aflsmart 82800 17.0 10390.764706 113.590014 10102.0 10374.00 10412.0 10455.00 10512.0
    eclipser 82800 17.0 10351.470588 163.547057 9942.0 10353.00 10381.0 10436.00 10545.0
    afl 82800 17.0 10349.000000 110.809521 10104.0 10303.00 10355.0 10449.00 10493.0
    mopt 82800 14.0 10343.285714 52.470400 10244.0 10310.75 10353.0 10377.00 10441.0
    aflfast 82800 17.0 10254.352941 107.364997 9962.0 10228.00 10291.0 10314.00 10399.0
    libfuzzer 82800 20.0 9910.950000 396.324890 9220.0 9475.75 10035.5 10211.50 10516.0
    fairfuzz 82800 19.0 9222.578947 391.462545 8215.0 8926.50 9379.0 9512.00 9714.0

    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.
  • Unique code coverage plots
    Ranking by unique code branches covered
    Each bar shows the total number of code branches found by a given fuzzer. The colored area shows the number of unique code branches (i.e., branches that were not covered by any other fuzzers).
    Pairwise unique code coverage
    Each cell represents the number of code branches covered by the fuzzer of the column but not by the fuzzer of the row

freetype2_ftfuzzer summary

Ranking by median reached code coverage
Reached code coverage distribution
Mean code coverage growth over time
Mean code coverage growth over time
* The error bands show the 95% confidence interval around the mean code coverage.
error
The following fuzzers do not have enough samples: honggfuzz, mopt, aflfast, libafl.
  • Sample statistics and statistical significance (code coverage)
    Code coverage sample statistics
    count mean std min 25% median 75% max
    fuzzer time
    aflplusplus 82800 16.0 11317.312500 469.680135 10099.0 11260.25 11429.5 11614.50 11875.0
    libafl 82800 8.0 11233.125000 573.448326 10421.0 10942.25 11301.5 11468.00 12222.0
    honggfuzz 82800 15.0 11146.933333 587.165767 9966.0 10638.00 11211.0 11643.50 11874.0
    libafl_saturation 82800 20.0 10286.750000 411.102353 9688.0 10050.00 10180.5 10496.25 11014.0
    libfuzzer 82800 20.0 9686.850000 575.195187 8786.0 9311.25 9719.5 10053.50 11076.0
    eclipser 82800 18.0 9312.222222 98.567717 9066.0 9283.00 9317.0 9355.50 9516.0
    aflsmart 82800 17.0 8323.647059 218.891794 7882.0 8183.00 8427.0 8489.00 8603.0
    mopt 82800 14.0 8386.428571 93.355989 8142.0 8352.25 8394.0 8459.00 8499.0
    afl 82800 17.0 8258.117647 210.946345 7860.0 8255.00 8313.0 8393.00 8532.0
    aflfast 82800 13.0 8162.615385 203.476673 7780.0 8005.00 8204.0 8329.00 8411.0
    fairfuzz 82800 17.0 7936.117647 236.373349 7764.0 7809.00 7863.0 7895.00 8582.0
    centipede 82800 19.0 7235.526316 211.190374 6852.0 7110.50 7190.0 7354.00 7653.0

    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.
  • Unique code coverage plots
    Ranking by unique code branches covered
    Each bar shows the total number of code branches found by a given fuzzer. The colored area shows the number of unique code branches (i.e., branches that were not covered by any other fuzzers).
    Pairwise unique code coverage
    Each cell represents the number of code branches covered by the fuzzer of the column but not by the fuzzer of the row

harfbuzz_hb-shape-fuzzer summary

Ranking by median reached code coverage
Reached code coverage distribution
Mean code coverage growth over time
Mean code coverage growth over time
* The error bands show the 95% confidence interval around the mean code coverage.
error
The following fuzzers do not have enough samples: mopt, fairfuzz, libafl, honggfuzz.
  • Sample statistics and statistical significance (code coverage)
    Code coverage sample statistics
    count mean std min 25% median 75% max
    fuzzer time
    libafl 82800 11.0 11004.454545 134.697709 10716.0 11019.00 11049.0 11079.00 11133.0
    aflplusplus 82800 17.0 10913.411765 154.392786 10415.0 10928.00 10958.0 10990.00 11038.0
    libafl_saturation 82800 20.0 10915.450000 34.345727 10866.0 10887.50 10913.5 10930.25 10990.0
    mopt 82800 15.0 10787.266667 79.410747 10535.0 10768.50 10803.0 10831.50 10876.0
    eclipser 82800 20.0 10769.400000 51.530676 10623.0 10744.25 10777.0 10789.50 10868.0
    afl 82800 18.0 10766.222222 44.163540 10669.0 10737.25 10773.5 10791.25 10845.0
    aflsmart 82800 18.0 10772.000000 45.695926 10703.0 10737.50 10763.5 10805.75 10859.0
    honggfuzz 82800 8.0 10715.750000 14.992855 10696.0 10704.25 10716.0 10726.25 10736.0
    aflfast 82800 18.0 10653.000000 67.534741 10498.0 10637.75 10667.5 10692.00 10756.0
    libfuzzer 82800 20.0 10556.700000 73.370079 10375.0 10509.25 10564.5 10605.00 10679.0
    fairfuzz 82800 14.0 9509.571429 347.646530 9071.0 9259.50 9399.0 9715.75 10155.0

    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.
  • Unique code coverage plots
    Ranking by unique code branches covered
    Each bar shows the total number of code branches found by a given fuzzer. The colored area shows the number of unique code branches (i.e., branches that were not covered by any other fuzzers).
    Pairwise unique code coverage
    Each cell represents the number of code branches covered by the fuzzer of the column but not by the fuzzer of the row

jsoncpp_jsoncpp_fuzzer summary

Ranking by median reached code coverage
Reached code coverage distribution
Mean code coverage growth over time
Mean code coverage growth over time
* The error bands show the 95% confidence interval around the mean code coverage.
error
The following fuzzers do not have enough samples: aflsmart, libafl, aflfast.
  • Sample statistics and statistical significance (code coverage)
    Code coverage sample statistics
    count mean std min 25% median 75% max
    fuzzer time
    libfuzzer 82800 20.0 524.900000 0.307794 524.0 525.00 525.0 525.00 525.0
    honggfuzz 82800 16.0 522.500000 1.154701 521.0 522.00 522.0 524.00 524.0
    aflplusplus 82800 17.0 519.941176 0.242536 519.0 520.00 520.0 520.00 520.0
    centipede 82800 16.0 520.250000 1.949359 518.0 519.00 519.0 522.00 523.0
    eclipser 82800 20.0 516.200000 5.176872 505.0 516.50 518.0 520.00 520.0
    mopt 82800 16.0 518.250000 1.183216 516.0 517.75 518.0 519.00 520.0
    afl 82800 17.0 514.588235 6.195349 502.0 516.00 517.0 519.00 520.0
    aflfast 82800 12.0 514.916667 6.126816 501.0 516.75 517.0 517.50 519.0
    aflsmart 82800 14.0 516.428571 3.715131 504.0 517.00 517.0 517.75 519.0
    fairfuzz 82800 16.0 516.437500 2.988171 509.0 516.75 517.0 518.25 520.0
    libafl 82800 13.0 517.461538 1.050031 516.0 517.00 517.0 518.00 520.0
    libafl_saturation 82800 20.0 517.450000 1.099043 515.0 517.00 517.0 518.25 519.0

    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.
  • Unique code coverage plots
    Ranking by unique code branches covered
    Each bar shows the total number of code branches found by a given fuzzer. The colored area shows the number of unique code branches (i.e., branches that were not covered by any other fuzzers).
    Pairwise unique code coverage
    Each cell represents the number of code branches covered by the fuzzer of the column but not by the fuzzer of the row

lcms_cms_transform_fuzzer summary

Ranking by median reached code coverage
Reached code coverage distribution
Mean code coverage growth over time
Mean code coverage growth over time
* The error bands show the 95% confidence interval around the mean code coverage.
error
The following fuzzers do not have enough samples: honggfuzz, libafl.
  • Sample statistics and statistical significance (code coverage)
    Code coverage sample statistics
    count mean std min 25% median 75% max
    fuzzer time
    libafl 82800 9.0 2085.777778 80.161989 1934.0 2038.00 2087.0 2134.00 2186.0
    aflplusplus 82800 17.0 2008.411765 174.692250 1536.0 2024.00 2056.0 2101.00 2125.0
    libafl_saturation 82800 20.0 1954.100000 194.347464 1491.0 1922.00 2034.5 2069.50 2169.0
    libfuzzer 82800 18.0 1937.333333 107.209525 1788.0 1860.00 1905.0 2018.00 2135.0
    honggfuzz 82800 11.0 1578.818182 434.253110 741.0 1542.00 1807.0 1848.00 1923.0
    eclipser 82800 17.0 1656.823529 137.802955 1398.0 1537.00 1671.0 1753.00 1893.0
    mopt 82800 18.0 1334.222222 446.061399 586.0 873.25 1574.0 1668.50 1795.0
    aflsmart 82800 17.0 1318.294118 462.454696 642.0 859.00 1546.0 1667.00 1762.0
    fairfuzz 82800 18.0 1274.277778 397.407600 800.0 901.00 1221.0 1636.25 1940.0
    afl 82800 17.0 1135.764706 470.692247 583.0 651.00 906.0 1631.00 1728.0
    centipede 82800 18.0 949.388889 231.815378 756.0 782.50 846.5 1025.75 1362.0
    aflfast 82800 19.0 663.947368 178.273969 519.0 619.00 643.0 645.50 1383.0

    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.
  • Unique code coverage plots
    Ranking by unique code branches covered
    Each bar shows the total number of code branches found by a given fuzzer. The colored area shows the number of unique code branches (i.e., branches that were not covered by any other fuzzers).
    Pairwise unique code coverage
    Each cell represents the number of code branches covered by the fuzzer of the column but not by the fuzzer of the row

libjpeg-turbo_libjpeg_turbo_fuzzer summary

Ranking by median reached code coverage
Reached code coverage distribution
Mean code coverage growth over time
Mean code coverage growth over time
* The error bands show the 95% confidence interval around the mean code coverage.
error
The following fuzzers do not have enough samples: aflplusplus, fairfuzz, libafl.
  • Sample statistics and statistical significance (code coverage)
    Code coverage sample statistics
    count mean std min 25% median 75% max
    fuzzer time
    libfuzzer 82800 19.0 3087.157895 1.772104 3082.0 3086.00 3087.0 3088.50 3089.0
    aflplusplus 82800 15.0 3082.800000 2.274078 3078.0 3081.50 3082.0 3084.50 3086.0
    aflsmart 82800 17.0 3080.352941 5.024206 3069.0 3080.00 3082.0 3084.00 3086.0
    fairfuzz 82800 13.0 3072.615385 17.399897 3017.0 3072.00 3079.0 3080.00 3084.0
    afl 82800 18.0 3078.611111 5.203380 3070.0 3075.25 3078.5 3083.00 3086.0
    mopt 82800 17.0 3070.882353 21.109484 3014.0 3072.00 3078.0 3081.00 3086.0
    honggfuzz 82800 17.0 3063.411765 9.454224 3040.0 3060.00 3066.0 3068.00 3075.0
    aflfast 82800 17.0 3050.470588 30.820281 3007.0 3014.00 3065.0 3077.00 3084.0
    centipede 82800 19.0 2971.631579 31.225365 2915.0 2945.50 2986.0 2999.50 3008.0
    libafl 82800 10.0 2545.500000 1.779513 2543.0 2545.00 2545.0 2545.75 2550.0
    libafl_saturation 82800 20.0 2543.400000 0.502625 2543.0 2543.00 2543.0 2544.00 2544.0

    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.
  • Unique code coverage plots
    Ranking by unique code branches covered
    Each bar shows the total number of code branches found by a given fuzzer. The colored area shows the number of unique code branches (i.e., branches that were not covered by any other fuzzers).
    Pairwise unique code coverage
    Each cell represents the number of code branches covered by the fuzzer of the column but not by the fuzzer of the row

libpcap_fuzz_both summary

Ranking by median reached code coverage
Reached code coverage distribution
Mean code coverage growth over time
Mean code coverage growth over time
* The error bands show the 95% confidence interval around the mean code coverage.
error
The following fuzzers do not have enough samples: aflfast, aflsmart, centipede, honggfuzz, mopt, libafl_saturation, libafl.
  • Sample statistics and statistical significance (code coverage)
    Code coverage sample statistics
    count mean std min 25% median 75% max
    fuzzer time
    aflplusplus 82800 16.0 2901.187500 118.532257 2721.0 2794.25 2897.5 2994.5 3129.0
    libafl 82800 3.0 2807.000000 64.210591 2736.0 2780.00 2824.0 2842.5 2861.0
    centipede 82800 15.0 1788.666667 1437.918022 100.0 104.50 2773.0 2910.5 3390.0
    honggfuzz 82800 15.0 2772.733333 147.428175 2564.0 2679.00 2738.0 2854.0 3129.0
    libafl_saturation 82800 9.0 2716.444444 56.389518 2628.0 2676.00 2728.0 2771.0 2775.0
    libfuzzer 82800 20.0 2574.000000 93.538621 2460.0 2525.75 2544.0 2590.0 2877.0
    eclipser 82800 19.0 2461.052632 196.678947 1977.0 2403.00 2446.0 2609.0 2706.0
    aflfast 82800 15.0 39.066667 4.463609 34.0 34.00 43.0 43.0 43.0
    afl 82800 18.0 38.777778 4.492550 34.0 34.00 41.0 43.0 43.0
    aflsmart 82800 15.0 34.600000 2.323790 34.0 34.00 34.0 34.0 43.0
    fairfuzz 82800 16.0 37.375000 4.500000 34.0 34.00 34.0 43.0 43.0
    mopt 82800 15.0 144.866667 416.958180 34.0 34.00 34.0 43.0 1652.0

    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.
  • Unique code coverage plots
    Ranking by unique code branches covered
    Each bar shows the total number of code branches found by a given fuzzer. The colored area shows the number of unique code branches (i.e., branches that were not covered by any other fuzzers).
    Pairwise unique code coverage
    Each cell represents the number of code branches covered by the fuzzer of the column but not by the fuzzer of the row

libpng_libpng_read_fuzzer summary

Ranking by median reached code coverage
Reached code coverage distribution
Mean code coverage growth over time
Mean code coverage growth over time
* The error bands show the 95% confidence interval around the mean code coverage.
error
The following fuzzers do not have enough samples: afl, aflsmart, aflfast, libafl.
  • Sample statistics and statistical significance (code coverage)
    Code coverage sample statistics
    count mean std min 25% median 75% max
    fuzzer time
    libfuzzer 82800 20.0 2017.750000 0.966546 2015.0 2018.00 2018.0 2018.00 2019.0
    centipede 82800 18.0 2014.000000 3.613699 2006.0 2013.00 2015.0 2016.75 2018.0
    honggfuzz 82800 18.0 2011.777778 2.860595 2007.0 2010.00 2011.5 2013.50 2018.0
    aflplusplus 82800 16.0 2008.437500 21.734669 1993.0 2002.00 2004.0 2005.00 2089.0
    libafl 82800 6.0 1996.666667 8.640988 1980.0 1996.50 1999.0 2001.50 2004.0
    eclipser 82800 18.0 1983.000000 27.563830 1900.0 1988.25 1993.5 1996.25 1999.0
    aflsmart 82800 15.0 1968.066667 37.151171 1909.0 1926.00 1992.0 1996.00 1997.0
    afl 82800 15.0 1973.733333 35.293599 1902.0 1978.00 1991.0 1993.00 2004.0
    fairfuzz 82800 18.0 1972.166667 30.020091 1889.0 1955.75 1981.0 1996.00 1999.0
    libafl_saturation 82800 19.0 1985.052632 9.483750 1975.0 1978.50 1981.0 1995.00 2001.0
    mopt 82800 16.0 1970.500000 28.768038 1912.0 1949.00 1980.5 1994.25 2001.0
    aflfast 82800 13.0 1951.153846 47.435651 1822.0 1945.00 1969.0 1975.00 1991.0

    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.
  • Unique code coverage plots
    Ranking by unique code branches covered
    Each bar shows the total number of code branches found by a given fuzzer. The colored area shows the number of unique code branches (i.e., branches that were not covered by any other fuzzers).
    Pairwise unique code coverage
    Each cell represents the number of code branches covered by the fuzzer of the column but not by the fuzzer of the row

libxml2_xml summary

Ranking by median reached code coverage
Reached code coverage distribution
Mean code coverage growth over time
Mean code coverage growth over time
* The error bands show the 95% confidence interval around the mean code coverage.
error
The following fuzzers do not have enough samples: afl, aflsmart, libafl.
  • Sample statistics and statistical significance (code coverage)
    Code coverage sample statistics
    count mean std min 25% median 75% max
    fuzzer time
    aflplusplus 82800 16.0 15727.187500 50.646775 15620.0 15693.50 15744.0 15761.25 15807.0
    libafl 82800 13.0 15591.615385 107.294407 15251.0 15590.00 15625.0 15645.00 15661.0
    honggfuzz 82800 17.0 15606.294118 40.253516 15536.0 15585.00 15602.0 15627.00 15693.0
    libafl_saturation 82800 20.0 15472.100000 31.141274 15400.0 15459.75 15474.0 15497.50 15511.0
    libfuzzer 82800 20.0 15406.700000 75.891266 15281.0 15367.25 15395.0 15451.75 15559.0
    eclipser 82800 17.0 15366.176471 70.190130 15247.0 15310.00 15373.0 15407.00 15477.0
    aflsmart 82800 14.0 15337.785714 63.447348 15209.0 15310.50 15340.0 15380.25 15431.0
    mopt 82800 18.0 15322.888889 58.018140 15184.0 15302.25 15330.0 15346.75 15425.0
    afl 82800 15.0 15335.066667 49.574571 15270.0 15311.50 15328.0 15357.50 15439.0
    aflfast 82800 20.0 15313.550000 68.346235 15189.0 15271.50 15322.0 15363.75 15441.0
    centipede 82800 17.0 14686.235294 163.148525 14302.0 14555.00 14751.0 14794.00 14881.0
    fairfuzz 82800 19.0 14034.842105 437.228934 12545.0 13923.00 14065.0 14210.00 14843.0

    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.
  • Unique code coverage plots
    Ranking by unique code branches covered
    Each bar shows the total number of code branches found by a given fuzzer. The colored area shows the number of unique code branches (i.e., branches that were not covered by any other fuzzers).
    Pairwise unique code coverage
    Each cell represents the number of code branches covered by the fuzzer of the column but not by the fuzzer of the row

libxslt_xpath summary

Ranking by median reached code coverage
Reached code coverage distribution
Mean code coverage growth over time
Mean code coverage growth over time
* The error bands show the 95% confidence interval around the mean code coverage.
error
The following fuzzers do not have enough samples: libafl.
  • Sample statistics and statistical significance (code coverage)
    Code coverage sample statistics
    count mean std min 25% median 75% max
    fuzzer time
    aflplusplus 82800 19.0 11188.052632 70.243603 11078.0 11132.00 11168.0 11224.50 11313.0
    honggfuzz 82800 16.0 11040.375000 89.626540 10864.0 10994.50 11076.0 11107.00 11137.0
    libafl 82800 9.0 10986.000000 87.728274 10837.0 10938.00 11001.0 11021.00 11147.0
    fairfuzz 82800 17.0 10804.470588 200.035346 10162.0 10772.00 10855.0 10906.00 11044.0
    aflsmart 82800 16.0 10830.500000 104.788676 10507.0 10812.00 10842.0 10886.00 10968.0
    libafl_saturation 82800 20.0 10827.000000 76.076831 10703.0 10776.00 10837.0 10890.25 10936.0
    eclipser 82800 18.0 10767.611111 123.770252 10424.0 10773.25 10801.5 10834.00 10888.0
    afl 82800 16.0 10714.937500 122.364193 10433.0 10665.50 10741.5 10794.25 10846.0
    centipede 82800 16.0 10682.000000 104.691929 10510.0 10624.75 10670.5 10746.25 10908.0
    aflfast 82800 17.0 10648.647059 90.347898 10408.0 10638.00 10666.0 10700.00 10732.0
    mopt 82800 16.0 10562.250000 164.019308 10134.0 10474.75 10608.0 10641.50 10781.0
    libfuzzer 82800 20.0 10411.500000 338.820633 9128.0 10379.25 10448.5 10556.50 10772.0

    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.
  • Unique code coverage plots
    Ranking by unique code branches covered
    Each bar shows the total number of code branches found by a given fuzzer. The colored area shows the number of unique code branches (i.e., branches that were not covered by any other fuzzers).
    Pairwise unique code coverage
    Each cell represents the number of code branches covered by the fuzzer of the column but not by the fuzzer of the row

mbedtls_fuzz_dtlsclient summary

Ranking by median reached code coverage
Reached code coverage distribution
Mean code coverage growth over time
Mean code coverage growth over time
* The error bands show the 95% confidence interval around the mean code coverage.
error
The following fuzzers do not have enough samples: fairfuzz, mopt, libafl.
  • Sample statistics and statistical significance (code coverage)
    Code coverage sample statistics
    count mean std min 25% median 75% max
    fuzzer time
    libafl 82800 11.0 3230.909091 372.432398 2705.0 2921.50 3370.0 3524.50 3674.0
    fairfuzz 82800 15.0 2849.466667 159.218119 2754.0 2779.00 2801.0 2807.50 3296.0
    aflplusplus 82800 16.0 2753.687500 26.469401 2713.0 2730.75 2754.5 2774.75 2803.0
    honggfuzz 82800 17.0 2701.235294 23.236634 2664.0 2687.00 2704.0 2713.00 2757.0
    libafl_saturation 82800 20.0 2878.000000 312.837944 2680.0 2693.75 2703.0 3074.75 3659.0
    aflsmart 82800 19.0 2657.421053 87.858039 2506.0 2568.00 2699.0 2723.00 2773.0
    eclipser 82800 16.0 2726.562500 280.074030 2496.0 2674.00 2692.5 2715.00 3730.0
    mopt 82800 14.0 2665.428571 65.113764 2510.0 2673.75 2688.5 2702.50 2721.0
    libfuzzer 82800 20.0 2684.650000 27.583891 2636.0 2663.25 2684.5 2701.00 2746.0
    afl 82800 16.0 2733.937500 299.446037 2502.0 2664.00 2682.0 2698.00 3827.0
    centipede 82800 17.0 2710.117647 263.068167 2619.0 2630.00 2650.0 2666.00 3728.0
    aflfast 82800 17.0 2557.411765 121.454754 2309.0 2599.00 2611.0 2624.00 2667.0

    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.
  • Unique code coverage plots
    Ranking by unique code branches covered
    Each bar shows the total number of code branches found by a given fuzzer. The colored area shows the number of unique code branches (i.e., branches that were not covered by any other fuzzers).
    Pairwise unique code coverage
    Each cell represents the number of code branches covered by the fuzzer of the column but not by the fuzzer of the row

openh264_decoder_fuzzer summary

Ranking by median reached code coverage
Reached code coverage distribution
Mean code coverage growth over time
Mean code coverage growth over time
* The error bands show the 95% confidence interval around the mean code coverage.
error
The following fuzzers do not have enough samples: aflplusplus, libafl.
  • Sample statistics and statistical significance (code coverage)
    Code coverage sample statistics
    count mean std min 25% median 75% max
    fuzzer time
    aflplusplus 82800 15.0 9547.466667 28.547871 9476.0 9536.00 9553.0 9560.50 9601.0
    aflfast 82800 20.0 9541.450000 56.935305 9355.0 9537.75 9547.5 9561.50 9623.0
    aflsmart 82800 20.0 9540.600000 34.399204 9491.0 9514.75 9539.5 9573.75 9593.0
    afl 82800 20.0 9442.900000 414.768661 7682.0 9526.50 9533.0 9544.25 9570.0
    mopt 82800 20.0 9506.350000 98.190618 9153.0 9509.50 9530.0 9545.25 9616.0
    eclipser 82800 20.0 9521.850000 39.701882 9415.0 9501.25 9526.0 9541.00 9616.0
    libfuzzer 82800 20.0 9497.650000 33.784573 9395.0 9490.75 9507.0 9520.25 9529.0
    honggfuzz 82800 20.0 9443.400000 88.478008 9197.0 9403.50 9487.5 9504.50 9530.0
    libafl 82800 11.0 9442.181818 33.459881 9380.0 9416.00 9453.0 9460.00 9503.0
    libafl_saturation 82800 20.0 9426.950000 38.845815 9355.0 9401.00 9422.5 9463.00 9480.0
    fairfuzz 82800 20.0 8690.750000 181.798001 8400.0 8579.25 8713.0 8780.50 9055.0

    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.
  • Unique code coverage plots
    Ranking by unique code branches covered
    Each bar shows the total number of code branches found by a given fuzzer. The colored area shows the number of unique code branches (i.e., branches that were not covered by any other fuzzers).
    Pairwise unique code coverage
    Each cell represents the number of code branches covered by the fuzzer of the column but not by the fuzzer of the row

openssl_x509 summary

Ranking by median reached code coverage
Reached code coverage distribution
Mean code coverage growth over time
Mean code coverage growth over time
* The error bands show the 95% confidence interval around the mean code coverage.
error
The following fuzzers do not have enough samples: afl, aflsmart, centipede, eclipser, aflfast, aflplusplus, honggfuzz, libafl.
  • Sample statistics and statistical significance (code coverage)
    Code coverage sample statistics
    count mean std min 25% median 75% max
    fuzzer time
    aflplusplus 82800 14.0 5830.142857 4.258153 5821.0 5830.25 5831.5 5833.00 5834.0
    libfuzzer 82800 20.0 5826.550000 6.202504 5817.0 5820.00 5830.0 5832.00 5834.0
    aflsmart 82800 15.0 5827.066667 4.847189 5817.0 5825.50 5829.0 5830.50 5833.0
    afl 82800 15.0 5826.600000 3.960519 5820.0 5824.00 5828.0 5829.50 5832.0
    mopt 82800 18.0 5824.555556 6.536974 5811.0 5823.25 5828.0 5828.75 5831.0
    eclipser 82800 15.0 5825.266667 4.096456 5817.0 5823.50 5827.0 5828.00 5831.0
    libafl 82800 9.0 5826.222222 4.352522 5821.0 5823.00 5825.0 5830.00 5833.0
    centipede 82800 15.0 5822.200000 6.689010 5812.0 5818.00 5824.0 5826.50 5834.0
    fairfuzz 82800 16.0 5821.125000 2.753785 5816.0 5819.50 5822.0 5823.00 5825.0
    libafl_saturation 82800 20.0 5819.100000 4.951342 5808.0 5818.00 5820.0 5822.00 5826.0
    aflfast 82800 14.0 5817.000000 8.009610 5807.0 5810.25 5816.0 5824.00 5829.0
    honggfuzz 82800 14.0 5814.000000 6.480741 5802.0 5808.50 5814.5 5820.00 5821.0

    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.
  • Unique code coverage plots
    Ranking by unique code branches covered
    Each bar shows the total number of code branches found by a given fuzzer. The colored area shows the number of unique code branches (i.e., branches that were not covered by any other fuzzers).
    Pairwise unique code coverage
    Each cell represents the number of code branches covered by the fuzzer of the column but not by the fuzzer of the row

openthread_ot-ip6-send-fuzzer summary

Ranking by median reached code coverage
Reached code coverage distribution
Mean code coverage growth over time
Mean code coverage growth over time
* The error bands show the 95% confidence interval around the mean code coverage.
error
The following fuzzers do not have enough samples: afl, aflsmart, mopt, aflplusplus, libafl.
  • Sample statistics and statistical significance (code coverage)
    Code coverage sample statistics
    count mean std min 25% median 75% max
    fuzzer time
    aflplusplus 82800 13.0 3418.846154 249.915601 3048.0 3065.00 3568.0 3577.00 3622.0
    libafl 82800 8.0 3428.500000 348.288058 3043.0 3071.25 3468.5 3611.00 3941.0
    libafl_saturation 82800 20.0 3329.500000 207.859138 3010.0 3043.75 3427.5 3484.00 3546.0
    libfuzzer 82800 20.0 3100.350000 66.718793 3066.0 3076.00 3080.0 3093.25 3371.0
    honggfuzz 82800 18.0 3070.388889 168.342836 2900.0 2954.00 3045.0 3068.75 3537.0
    eclipser 82800 16.0 2984.937500 66.946216 2895.0 2918.25 2999.5 3036.75 3073.0
    mopt 82800 15.0 2930.933333 69.999456 2824.0 2908.50 2916.0 2925.00 3065.0
    aflsmart 82800 15.0 2906.333333 69.832112 2795.0 2869.00 2915.0 2917.00 3052.0
    afl 82800 15.0 2911.333333 60.366342 2817.0 2904.50 2910.0 2917.00 3035.0
    aflfast 82800 17.0 2896.294118 42.210432 2808.0 2902.00 2907.0 2912.00 2980.0
    centipede 82800 17.0 2856.352941 57.396582 2763.0 2790.00 2884.0 2900.00 2917.0
    fairfuzz 82800 19.0 2779.105263 65.278799 2676.0 2745.50 2764.0 2801.50 2912.0

    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.
  • Unique code coverage plots
    Ranking by unique code branches covered
    Each bar shows the total number of code branches found by a given fuzzer. The colored area shows the number of unique code branches (i.e., branches that were not covered by any other fuzzers).
    Pairwise unique code coverage
    Each cell represents the number of code branches covered by the fuzzer of the column but not by the fuzzer of the row

proj4_proj_crs_to_crs_fuzzer summary

Ranking by median reached code coverage
Reached code coverage distribution
Mean code coverage growth over time
Mean code coverage growth over time
* The error bands show the 95% confidence interval around the mean code coverage.
error
The following fuzzers do not have enough samples: libafl.
  • Sample statistics and statistical significance (code coverage)
    Code coverage sample statistics
    count mean std min 25% median 75% max
    fuzzer time
    honggfuzz 82800 20.0 7876.50 187.114235 7418.0 7806.25 7899.0 8012.50 8095.0
    libfuzzer 82800 20.0 7539.35 112.017045 7396.0 7453.00 7529.5 7595.50 7798.0
    libafl 82800 10.0 7345.40 84.850457 7232.0 7288.25 7328.0 7413.50 7489.0
    aflplusplus 82800 20.0 7283.95 142.745071 7069.0 7159.25 7262.5 7383.00 7572.0
    libafl_saturation 82800 20.0 6971.55 214.567245 6471.0 6865.50 6968.0 7134.00 7314.0
    eclipser 82800 20.0 4850.35 238.740175 4471.0 4688.75 4879.5 4962.25 5520.0
    centipede 82800 20.0 819.80 3.819617 814.0 817.00 820.0 822.00 828.0
    fairfuzz 82800 20.0 779.35 98.588606 494.0 810.00 816.0 819.00 821.0
    aflsmart 82800 20.0 788.70 74.788192 487.0 804.25 813.0 818.25 820.0
    afl 82800 20.0 788.80 70.480755 497.0 803.00 806.0 810.50 819.0
    mopt 82800 20.0 788.85 33.590843 728.0 786.00 805.0 808.00 818.0
    aflfast 82800 20.0 715.30 120.099126 480.0 729.50 739.5 804.00 819.0

    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.
  • Unique code coverage plots
    Ranking by unique code branches covered
    Each bar shows the total number of code branches found by a given fuzzer. The colored area shows the number of unique code branches (i.e., branches that were not covered by any other fuzzers).
    Pairwise unique code coverage
    Each cell represents the number of code branches covered by the fuzzer of the column but not by the fuzzer of the row

re2_fuzzer summary

Ranking by median reached code coverage
Reached code coverage distribution
Mean code coverage growth over time
Mean code coverage growth over time
* The error bands show the 95% confidence interval around the mean code coverage.
error
The following fuzzers do not have enough samples: libafl.
  • Sample statistics and statistical significance (code coverage)
    Code coverage sample statistics
    count mean std min 25% median 75% max
    fuzzer time
    libfuzzer 82800 20.0 2883.800000 2.764436 2879.0 2881.75 2883.5 2886.00 2888.0
    aflplusplus 82800 17.0 2876.882353 6.772023 2856.0 2876.00 2878.0 2881.00 2883.0
    aflsmart 82800 17.0 2862.705882 22.769949 2776.0 2865.00 2868.0 2870.00 2876.0
    afl 82800 17.0 2854.352941 30.250912 2784.0 2863.00 2867.0 2871.00 2872.0
    eclipser 82800 17.0 2849.176471 37.480387 2746.0 2854.00 2867.0 2872.00 2877.0
    fairfuzz 82800 16.0 2849.875000 34.960692 2757.0 2858.75 2864.0 2866.00 2872.0
    aflfast 82800 16.0 2849.187500 32.711300 2761.0 2853.00 2862.0 2866.00 2869.0
    libafl 82800 9.0 2860.333333 4.123106 2852.0 2858.00 2862.0 2863.00 2864.0
    honggfuzz 82800 18.0 2854.055556 6.347507 2839.0 2849.75 2853.0 2859.50 2862.0
    mopt 82800 17.0 2832.235294 42.418347 2741.0 2795.00 2851.0 2863.00 2871.0
    libafl_saturation 82800 20.0 2844.350000 9.852998 2816.0 2840.25 2847.0 2848.25 2859.0
    centipede 82800 16.0 2767.187500 18.999013 2740.0 2753.75 2768.0 2780.25 2801.0

    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.
  • Unique code coverage plots
    Ranking by unique code branches covered
    Each bar shows the total number of code branches found by a given fuzzer. The colored area shows the number of unique code branches (i.e., branches that were not covered by any other fuzzers).
    Pairwise unique code coverage
    Each cell represents the number of code branches covered by the fuzzer of the column but not by the fuzzer of the row

sqlite3_ossfuzz summary

Ranking by median reached code coverage
Reached code coverage distribution
Mean code coverage growth over time
Mean code coverage growth over time
* The error bands show the 95% confidence interval around the mean code coverage.
error
The following fuzzers do not have enough samples: centipede, fairfuzz, libafl.
  • Sample statistics and statistical significance (code coverage)
    Code coverage sample statistics
    count mean std min 25% median 75% max
    fuzzer time
    libafl 82800 11.0 20788.636364 80.304760 20662.0 20732.00 20771.0 20855.50 20919.0
    aflplusplus 82800 16.0 19945.687500 835.681097 17914.0 20010.25 20239.0 20431.25 20666.0
    afl 82800 19.0 19120.631579 271.473185 18750.0 18964.50 19069.0 19300.00 19764.0
    aflsmart 82800 16.0 18967.187500 332.880002 18405.0 18748.75 19007.0 19215.75 19455.0
    mopt 82800 18.0 18989.611111 257.525359 18358.0 18874.00 18944.0 19173.00 19401.0
    eclipser 82800 16.0 18884.375000 348.908751 17767.0 18835.25 18909.5 19083.75 19306.0
    aflfast 82800 17.0 18843.058824 250.648526 18143.0 18773.00 18861.0 18991.00 19214.0
    libafl_saturation 82800 19.0 17175.578947 1276.056047 13901.0 17527.00 17761.0 17789.00 17885.0
    libfuzzer 82800 20.0 16488.200000 438.534713 15855.0 16168.25 16443.5 16695.00 17571.0
    honggfuzz 82800 16.0 14378.875000 498.141329 13529.0 14138.50 14347.0 14592.00 15289.0
    centipede 82800 14.0 13009.714286 460.146537 12336.0 12762.25 12918.5 13128.25 13853.0
    fairfuzz 82800 12.0 12516.333333 1555.113169 10873.0 11305.75 12095.0 13230.75 15546.0

    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.
  • Unique code coverage plots
    Ranking by unique code branches covered
    Each bar shows the total number of code branches found by a given fuzzer. The colored area shows the number of unique code branches (i.e., branches that were not covered by any other fuzzers).
    Pairwise unique code coverage
    Each cell represents the number of code branches covered by the fuzzer of the column but not by the fuzzer of the row

stb_stbi_read_fuzzer summary

Ranking by median reached code coverage
Reached code coverage distribution
Mean code coverage growth over time
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
    libafl 82800 20.0 2183.650000 50.927477 2107.0 2136.75 2191.5 2206.50 2270.0
    aflplusplus 82800 18.0 2161.722222 47.721996 2113.0 2115.00 2159.0 2207.25 2222.0
    libafl_saturation 82800 20.0 2135.450000 38.725043 2098.0 2101.75 2119.5 2180.25 2203.0
    honggfuzz 82800 16.0 2118.062500 21.971098 2108.0 2111.00 2113.0 2115.00 2200.0
    eclipser 82800 19.0 2102.210526 10.141110 2081.0 2099.50 2106.0 2108.00 2115.0
    libfuzzer 82800 20.0 2035.650000 42.067959 1982.0 2009.00 2014.5 2062.25 2123.0
    aflsmart 82800 16.0 2028.937500 45.036976 1979.0 2001.75 2005.5 2087.25 2109.0
    afl 82800 16.0 2009.000000 49.946638 1936.0 1985.00 2003.5 2007.25 2108.0
    fairfuzz 82800 16.0 1999.312500 43.870596 1942.0 1976.50 1993.5 1999.00 2084.0
    aflfast 82800 17.0 1998.058824 34.450092 1963.0 1982.00 1987.0 1997.00 2087.0
    mopt 82800 18.0 1988.333333 28.033593 1952.0 1976.25 1984.0 2000.00 2080.0
    centipede 82800 17.0 1957.647059 5.049024 1952.0 1954.00 1957.0 1959.00 1973.0

    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.
  • Unique code coverage plots
    Ranking by unique code branches covered
    Each bar shows the total number of code branches found by a given fuzzer. The colored area shows the number of unique code branches (i.e., branches that were not covered by any other fuzzers).
    Pairwise unique code coverage
    Each cell represents the number of code branches covered by the fuzzer of the column but not by the fuzzer of the row

vorbis_decode_fuzzer summary

Ranking by median reached code coverage
Reached code coverage distribution
Mean code coverage growth over time
Mean code coverage growth over time
* The error bands show the 95% confidence interval around the mean code coverage.
error
The following fuzzers do not have enough samples: aflfast, centipede, eclipser, libafl.
  • Sample statistics and statistical significance (code coverage)
    Code coverage sample statistics
    count mean std min 25% median 75% max
    fuzzer time
    aflplusplus 82800 19.0 1265.842105 2.455451 1262.0 1264.00 1267.0 1268.00 1269.0
    libfuzzer 82800 20.0 1255.700000 54.323689 1025.0 1267.00 1267.0 1269.00 1271.0
    aflsmart 82800 17.0 1252.117647 15.591995 1194.0 1252.00 1255.0 1258.00 1262.0
    mopt 82800 16.0 1250.000000 19.572089 1178.0 1250.75 1254.0 1257.25 1261.0
    libafl 82800 11.0 1254.090909 2.981763 1251.0 1252.00 1253.0 1254.50 1261.0
    afl 82800 17.0 1245.941176 15.666328 1201.0 1247.00 1252.0 1254.00 1258.0
    aflfast 82800 15.0 1246.400000 14.695966 1195.0 1246.00 1250.0 1252.50 1256.0
    honggfuzz 82800 16.0 1248.500000 6.673330 1235.0 1245.75 1248.5 1254.00 1259.0
    eclipser 82800 15.0 1248.133333 5.514483 1236.0 1245.00 1248.0 1252.50 1255.0
    libafl_saturation 82800 20.0 1247.300000 3.373270 1242.0 1244.75 1248.0 1249.25 1253.0
    fairfuzz 82800 18.0 1228.111111 28.060625 1175.0 1208.25 1238.0 1250.75 1257.0
    centipede 82800 15.0 1143.733333 9.917277 1127.0 1136.50 1146.0 1150.00 1162.0

    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.
  • Unique code coverage plots
    Ranking by unique code branches covered
    Each bar shows the total number of code branches found by a given fuzzer. The colored area shows the number of unique code branches (i.e., branches that were not covered by any other fuzzers).
    Pairwise unique code coverage
    Each cell represents the number of code branches covered by the fuzzer of the column but not by the fuzzer of the row

woff2_convert_woff2ttf_fuzzer summary

Ranking by median reached code coverage
Reached code coverage distribution
Mean code coverage growth over time
Mean code coverage growth over time
* The error bands show the 95% confidence interval around the mean code coverage.
error
The following fuzzers do not have enough samples: mopt, libafl, aflsmart.
  • Sample statistics and statistical significance (code coverage)
    Code coverage sample statistics
    count mean std min 25% median 75% max
    fuzzer time
    libafl 82800 14.0 1183.357143 14.323768 1155.0 1170.25 1190.5 1192.00 1208.0
    aflplusplus 82800 17.0 1179.882353 11.362671 1154.0 1172.00 1180.0 1189.00 1197.0
    libfuzzer 82800 20.0 1156.150000 46.898855 1058.0 1129.50 1174.5 1194.25 1214.0
    libafl_saturation 82800 20.0 1168.100000 12.535843 1148.0 1159.25 1168.5 1177.00 1197.0
    honggfuzz 82800 17.0 1155.882353 27.126745 1113.0 1130.00 1158.0 1177.00 1198.0
    aflsmart 82800 13.0 1105.461538 29.809438 1047.0 1090.00 1123.0 1127.00 1129.0
    mopt 82800 15.0 1109.600000 21.503488 1071.0 1095.00 1116.0 1127.00 1136.0
    afl 82800 16.0 1106.125000 21.171915 1066.0 1098.25 1113.0 1121.75 1133.0
    aflfast 82800 17.0 1090.352941 24.882075 1043.0 1071.00 1099.0 1108.00 1118.0
    centipede 82800 18.0 1075.166667 13.057565 1060.0 1064.25 1072.0 1088.75 1099.0
    fairfuzz 82800 17.0 994.941176 30.150602 959.0 982.00 991.0 1001.00 1098.0

    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.
  • Unique code coverage plots
    Ranking by unique code branches covered
    Each bar shows the total number of code branches found by a given fuzzer. The colored area shows the number of unique code branches (i.e., branches that were not covered by any other fuzzers).
    Pairwise unique code coverage
    Each cell represents the number of code branches covered by the fuzzer of the column but not by the fuzzer of the row

zlib_zlib_uncompress_fuzzer summary

Ranking by median reached code coverage
Reached code coverage distribution
Mean code coverage growth over time
Mean code coverage growth over time
* The error bands show the 95% confidence interval around the mean code coverage.
error
The following fuzzers do not have enough samples: aflplusplus, mopt, aflsmart, libafl.
  • Sample statistics and statistical significance (code coverage)
    Code coverage sample statistics
    count mean std min 25% median 75% max
    fuzzer time
    libfuzzer 82800 20.0 469.650000 3.897030 462.0 469.50 471.5 472.00 473.0
    aflplusplus 82800 15.0 461.666667 4.685337 456.0 458.00 461.0 462.50 471.0
    mopt 82800 15.0 455.066667 12.290918 423.0 455.00 460.0 461.00 469.0
    honggfuzz 82800 18.0 458.777778 3.858612 452.0 458.00 459.0 460.75 468.0
    fairfuzz 82800 16.0 457.875000 3.685557 455.0 455.75 457.0 459.00 470.0
    aflsmart 82800 12.0 455.750000 13.948770 416.0 455.75 456.0 462.00 470.0
    afl 82800 16.0 449.625000 17.450406 406.0 454.75 455.0 459.25 466.0
    eclipser 82800 16.0 451.687500 13.189484 423.0 450.25 455.0 458.00 471.0
    centipede 82800 18.0 453.166667 2.935583 451.0 451.00 452.0 455.00 462.0
    aflfast 82800 17.0 428.352941 37.729202 345.0 401.00 448.0 454.00 458.0
    libafl 82800 7.0 448.714286 6.156684 442.0 444.50 447.0 451.50 460.0
    libafl_saturation 82800 20.0 441.200000 7.171581 425.0 437.00 441.5 446.25 455.0

    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.
  • Unique code coverage plots
    Ranking by unique code branches covered
    Each bar shows the total number of code branches found by a given fuzzer. The colored area shows the number of unique code branches (i.e., branches that were not covered by any other fuzzers).
    Pairwise unique code coverage
    Each cell represents the number of code branches covered by the fuzzer of the column but not by the fuzzer of the row

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.

Experiment Description:

(None,)