FuzzBench: 2024-05-16-aflpp 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 97.69
libafl 97.28
honggfuzz 94.53
libfuzzer 93.67
lfuzz 92.90
afl 82.56
mopt 81.15
aflsmart 80.14
aflfast 79.80
fairfuzz 79.08
eclipser 75.57
centipede 69.10
By avg. rank
average rank
fuzzer
aflplusplus 2.45
lfuzz 4.00
libafl 4.36
libfuzzer 4.36
honggfuzz 6.00
aflsmart 6.64
afl 7.18
eclipser 7.18
mopt 7.18
fairfuzz 8.82
aflfast 9.00
centipede 9.09
  • 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 libfuzzer lfuzz eclipser centipede afl mopt aflsmart aflfast fairfuzz
    FuzzerMedian 97.00 95.00 95.00 94.00 95.00 95.00 89.00 94.00 94.00 94.00 93.00 84.00
    FuzzerMean 94.73 94.27 91.45 90.91 90.09 89.44 81.67 80.45 79.18 78.09 77.82 77.18
    bloaty_fuzz_target 98.00 98.00 92.00 91.00 86.00 94.00 nan 94.00 96.00 94.00 93.00 80.00
    freetype2_ftfuzzer 91.00 90.00 91.00 77.00 85.00 74.00 58.00 66.00 66.00 67.00 65.00 63.00
    harfbuzz_hb-shape-fuzzer 98.00 99.00 96.00 94.00 97.00 97.00 nan 96.00 97.00 96.00 96.00 84.00
    lcms_cms_transform_fuzzer 92.00 94.00 73.00 86.00 70.00 75.00 37.00 67.00 51.00 40.00 29.00 55.00
    libjpeg-turbo_libjpeg_turbo_fuzzer 82.00 82.00 82.00 82.00 82.00 nan 82.00 82.00 82.00 82.00 99.00 99.00
    libpcap_fuzz_both 94.00 91.00 89.00 82.00 83.00 79.00 91.00 1.00 1.00 1.00 1.00 1.00
    libpng_libpng_read_fuzzer 95.00 95.00 95.00 96.00 95.00 95.00 96.00 94.00 94.00 94.00 93.00 94.00
    openssl_x509 99.00 99.00 98.00 99.00 99.00 99.00 99.00 99.00 99.00 99.00 98.00 99.00
    vorbis_decode_fuzzer 98.00 97.00 96.00 98.00 99.00 96.00 88.00 97.00 97.00 97.00 97.00 96.00
    woff2_convert_woff2ttf_fuzzer 98.00 98.00 97.00 96.00 96.00 nan 89.00 93.00 92.00 93.00 91.00 82.00
    zlib_zlib_uncompress_fuzzer 97.00 94.00 97.00 99.00 99.00 96.00 95.00 96.00 96.00 96.00 94.00 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: eclipser.
  • 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 6343.000000 41.929766 6252.0 6324.25 6352.0 6367.00 6402.0
    aflplusplus 82800 20.0 6328.300000 69.291224 6149.0 6327.50 6340.0 6368.00 6429.0
    mopt 82800 20.0 6189.050000 93.155487 6019.0 6121.00 6188.0 6260.50 6323.0
    aflsmart 82800 20.0 6146.000000 146.262561 5784.0 6070.75 6104.0 6271.00 6381.0
    eclipser 82800 11.0 6053.181818 68.930136 5914.0 6022.50 6078.0 6095.50 6135.0
    afl 82800 20.0 6040.550000 112.988809 5838.0 5956.50 6062.5 6098.75 6233.0
    aflfast 82800 17.0 6028.411765 77.961576 5893.0 5960.00 6035.0 6065.00 6185.0
    honggfuzz 82800 20.0 6044.800000 190.055560 5739.0 5920.75 5971.0 6222.50 6334.0
    libfuzzer 82800 20.0 5899.050000 118.185614 5708.0 5797.75 5905.0 5980.25 6141.0
    lfuzz 82800 19.0 5493.736842 113.566350 5232.0 5410.00 5536.0 5576.50 5662.0
    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

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: aflfast.
  • 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 11363.350000 626.091239 10087.0 11149.50 11475.5 11834.25 12138.0
    aflplusplus 82800 20.0 11381.750000 411.452098 10657.0 11001.25 11431.5 11707.75 12014.0
    libafl 82800 20.0 11388.900000 686.837443 10085.0 10910.25 11281.5 11976.25 12475.0
    lfuzz 82800 19.0 10658.052632 397.274950 9896.0 10415.00 10699.0 10878.00 11360.0
    libfuzzer 82800 20.0 9691.850000 478.040989 8979.0 9503.25 9650.5 9810.25 10769.0
    eclipser 82800 18.0 9312.222222 98.567717 9066.0 9283.00 9317.0 9355.50 9516.0
    aflsmart 82800 20.0 8342.750000 174.588501 7870.0 8314.75 8393.0 8435.50 8535.0
    mopt 82800 20.0 8321.650000 153.060454 7821.0 8324.75 8357.5 8392.00 8480.0
    afl 82800 20.0 8262.200000 189.522558 7862.0 8164.50 8342.5 8407.25 8475.0
    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 20.0 7264.350000 173.182069 6852.0 7190.50 7299.0 7378.00 7565.0

    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: fairfuzz, honggfuzz.
  • 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 11039.650000 37.033804 10965.0 11029.50 11045.0 11058.00 11106.0
    aflplusplus 82800 20.0 10860.700000 236.201988 9917.0 10891.50 10922.0 10958.75 11010.0
    lfuzz 82800 20.0 10832.600000 136.223655 10329.0 10793.75 10859.5 10899.25 11015.0
    mopt 82800 20.0 10778.950000 52.249880 10651.0 10757.50 10789.5 10796.25 10863.0
    eclipser 82800 20.0 10769.400000 51.530676 10623.0 10744.25 10777.0 10789.50 10868.0
    aflsmart 82800 20.0 10763.700000 42.521945 10652.0 10753.00 10764.5 10791.00 10839.0
    afl 82800 20.0 10745.000000 44.143307 10636.0 10734.00 10757.0 10771.75 10812.0
    honggfuzz 82800 14.0 10686.000000 25.495098 10629.0 10672.50 10689.5 10703.50 10719.0
    aflfast 82800 18.0 10653.000000 67.534741 10498.0 10637.75 10667.5 10692.00 10756.0
    libfuzzer 82800 20.0 10537.350000 68.395348 10421.0 10484.00 10522.0 10600.25 10656.0
    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

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.
  • 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 2087.400000 78.542245 1869.0 2055.50 2100.0 2118.00 2212.0
    aflplusplus 82800 17.0 2008.411765 174.692250 1536.0 2024.00 2056.0 2101.00 2125.0
    libfuzzer 82800 20.0 1895.950000 59.130965 1788.0 1846.25 1903.5 1946.50 1992.0
    eclipser 82800 17.0 1656.823529 137.802955 1398.0 1537.00 1671.0 1753.00 1893.0
    honggfuzz 82800 20.0 1438.100000 500.925974 694.0 778.00 1631.5 1838.25 1918.0
    lfuzz 82800 20.0 1475.450000 366.521124 754.0 1306.00 1553.5 1757.75 1920.0
    afl 82800 20.0 1311.250000 440.908736 648.0 876.00 1498.0 1675.50 1776.0
    fairfuzz 82800 18.0 1274.277778 397.407600 800.0 901.00 1221.0 1636.25 1940.0
    mopt 82800 20.0 1154.600000 428.242602 650.0 697.50 1133.0 1559.00 1736.0
    aflsmart 82800 20.0 1074.750000 469.254714 650.0 652.00 900.0 1561.00 1791.0
    centipede 82800 20.0 988.700000 247.792167 753.0 811.25 834.0 1228.25 1496.0
    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: fairfuzz.
  • Sample statistics and statistical significance (code coverage)
    Code coverage sample statistics
    count mean std min 25% median 75% max
    fuzzer time
    fairfuzz 82800 13.0 3072.615385 17.399897 3017.0 3072.00 3079.0 3080.00 3084.0
    aflfast 82800 17.0 3050.470588 30.820281 3007.0 3014.00 3065.0 3077.00 3084.0
    lfuzz 82800 19.0 2550.105263 0.936586 2549.0 2549.00 2550.0 2551.00 2552.0
    libfuzzer 82800 20.0 2549.600000 1.846761 2546.0 2549.75 2550.0 2550.00 2553.0
    aflplusplus 82800 20.0 2548.950000 2.187885 2546.0 2547.00 2548.5 2551.00 2552.0
    centipede 82800 20.0 2546.000000 1.555973 2542.0 2545.00 2546.0 2547.00 2550.0
    aflsmart 82800 20.0 2544.750000 1.773341 2543.0 2543.00 2545.0 2546.00 2549.0
    libafl 82800 20.0 2544.700000 1.031095 2543.0 2544.00 2545.0 2545.25 2546.0
    afl 82800 20.0 2544.600000 1.759186 2541.0 2543.75 2544.0 2545.25 2548.0
    honggfuzz 82800 20.0 2543.800000 1.765160 2538.0 2543.00 2544.0 2544.00 2548.0
    mopt 82800 20.0 2544.200000 1.542384 2540.0 2543.75 2544.0 2545.00 2547.0

    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: afl, aflfast, 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 5.0 2895.600000 137.583793 2698.0 2849.0 2891.0 2978.0 3062.0
    libafl 82800 3.0 2812.666667 232.508781 2579.0 2697.0 2815.0 2929.5 3044.0
    centipede 82800 20.0 2423.700000 1007.383641 101.0 2647.5 2811.5 2901.0 3035.0
    honggfuzz 82800 20.0 2722.850000 143.003230 2288.0 2701.5 2751.5 2809.0 2950.0
    lfuzz 82800 19.0 2611.210526 134.448494 2410.0 2526.5 2571.0 2672.0 2872.0
    libfuzzer 82800 19.0 2549.631579 72.861521 2460.0 2503.0 2525.0 2577.0 2706.0
    eclipser 82800 19.0 2461.052632 196.678947 1977.0 2403.0 2446.0 2609.0 2706.0
    aflfast 82800 15.0 39.066667 4.463609 34.0 34.0 43.0 43.0 43.0
    afl 82800 15.0 38.200000 4.647580 34.0 34.0 34.0 43.0 43.0
    aflsmart 82800 20.0 34.000000 0.000000 34.0 34.0 34.0 34.0 34.0
    fairfuzz 82800 16.0 37.375000 4.500000 34.0 34.0 34.0 43.0 43.0
    mopt 82800 14.0 36.214286 3.826599 34.0 34.0 34.0 37.0 43.0

    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: 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 2017.850000 0.875094 2015.0 2018.00 2018.0 2018.00 2019.0
    centipede 82800 20.0 2015.350000 2.207046 2009.0 2014.00 2016.0 2017.00 2018.0
    honggfuzz 82800 20.0 2030.000000 33.450671 2003.0 2009.75 2011.5 2039.75 2098.0
    lfuzz 82800 20.0 2006.900000 19.306121 1986.0 2003.00 2004.5 2007.00 2085.0
    aflplusplus 82800 20.0 2007.450000 19.701656 1984.0 2003.75 2004.0 2006.25 2088.0
    libafl 82800 20.0 1994.100000 10.808866 1971.0 1989.75 1998.0 2001.25 2005.0
    eclipser 82800 18.0 1983.000000 27.563830 1900.0 1988.25 1993.5 1996.25 1999.0
    aflsmart 82800 20.0 1964.400000 41.639303 1888.0 1926.50 1992.5 1995.25 1998.0
    afl 82800 20.0 1975.300000 32.509270 1873.0 1974.75 1985.5 1995.25 2001.0
    fairfuzz 82800 18.0 1972.166667 30.020091 1889.0 1955.75 1981.0 1996.00 1999.0
    mopt 82800 20.0 1969.650000 25.915399 1915.0 1945.50 1976.5 1990.75 1999.0
    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

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: eclipser, aflfast.
  • Sample statistics and statistical significance (code coverage)
    Code coverage sample statistics
    count mean std min 25% median 75% max
    fuzzer time
    aflplusplus 82800 20.0 5832.900000 3.024462 5821.0 5833.00 5833.5 5834.00 5835.0
    lfuzz 82800 19.0 5831.842105 2.929982 5822.0 5831.00 5832.0 5832.50 5838.0
    libfuzzer 82800 20.0 5830.150000 11.699190 5818.0 5825.50 5830.0 5832.00 5875.0
    aflsmart 82800 20.0 5826.300000 5.582869 5808.0 5827.00 5828.0 5829.00 5831.0
    afl 82800 20.0 5825.950000 4.236123 5815.0 5824.00 5827.0 5829.00 5830.0
    eclipser 82800 15.0 5825.266667 4.096456 5817.0 5823.50 5827.0 5828.00 5831.0
    mopt 82800 20.0 5823.350000 6.507283 5813.0 5815.75 5826.0 5829.00 5830.0
    libafl 82800 20.0 5824.000000 5.525063 5808.0 5820.00 5824.0 5829.25 5830.0
    fairfuzz 82800 16.0 5821.125000 2.753785 5816.0 5819.50 5822.0 5823.00 5825.0
    centipede 82800 20.0 5820.500000 6.893933 5808.0 5814.00 5820.5 5826.00 5831.0
    aflfast 82800 14.0 5817.000000 8.009610 5807.0 5810.25 5816.0 5824.00 5829.0
    honggfuzz 82800 20.0 5813.450000 7.126489 5801.0 5808.75 5811.0 5820.25 5822.0

    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, eclipser.
  • Sample statistics and statistical significance (code coverage)
    Code coverage sample statistics
    count mean std min 25% median 75% max
    fuzzer time
    lfuzz 82800 20.0 1281.850000 2.560325 1278.0 1280.00 1281.0 1284.00 1287.0
    libfuzzer 82800 20.0 1266.750000 2.221308 1263.0 1265.75 1267.0 1268.00 1274.0
    aflplusplus 82800 20.0 1264.550000 2.211810 1261.0 1263.00 1264.0 1265.25 1269.0
    afl 82800 20.0 1251.350000 12.482725 1201.0 1250.75 1253.5 1257.00 1261.0
    mopt 82800 20.0 1250.400000 9.626717 1218.0 1252.00 1253.0 1254.00 1256.0
    aflsmart 82800 20.0 1244.100000 19.558011 1199.0 1247.00 1251.5 1254.00 1259.0
    libafl 82800 20.0 1251.450000 3.103055 1247.0 1248.75 1250.5 1254.25 1257.0
    aflfast 82800 15.0 1246.400000 14.695966 1195.0 1246.00 1250.0 1252.50 1256.0
    eclipser 82800 15.0 1248.133333 5.514483 1236.0 1245.00 1248.0 1252.50 1255.0
    honggfuzz 82800 20.0 1243.700000 8.742516 1230.0 1236.25 1246.0 1250.50 1255.0
    fairfuzz 82800 18.0 1228.111111 28.060625 1175.0 1208.25 1238.0 1250.75 1257.0
    centipede 82800 20.0 1144.800000 17.644441 1118.0 1132.25 1142.5 1162.00 1179.0

    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: aflsmart.
  • Sample statistics and statistical significance (code coverage)
    Code coverage sample statistics
    count mean std min 25% median 75% max
    fuzzer time
    aflplusplus 82800 20.0 1179.250000 12.636101 1157.0 1168.00 1181.0 1189.25 1198.0
    libafl 82800 20.0 1176.850000 15.587698 1138.0 1168.25 1181.0 1186.25 1201.0
    honggfuzz 82800 20.0 1169.200000 20.995238 1114.0 1168.75 1171.0 1181.00 1195.0
    libfuzzer 82800 20.0 1146.050000 50.539693 1071.0 1101.00 1165.0 1188.00 1204.0
    lfuzz 82800 19.0 1164.315789 12.301999 1149.0 1154.50 1160.0 1172.50 1189.0
    aflsmart 82800 13.0 1105.461538 29.809438 1047.0 1090.00 1123.0 1127.00 1129.0
    afl 82800 20.0 1111.650000 22.697728 1060.0 1103.00 1120.5 1127.00 1136.0
    mopt 82800 20.0 1115.450000 18.259749 1068.0 1106.25 1119.5 1128.75 1140.0
    aflfast 82800 17.0 1090.352941 24.882075 1043.0 1071.00 1099.0 1108.00 1118.0
    centipede 82800 20.0 1074.500000 18.303005 1032.0 1061.00 1082.5 1087.00 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: aflsmart.
  • Sample statistics and statistical significance (code coverage)
    Code coverage sample statistics
    count mean std min 25% median 75% max
    fuzzer time
    lfuzz 82800 20.0 470.550000 0.686333 469.0 470.00 471.0 471.00 472.0
    libfuzzer 82800 20.0 467.500000 4.872047 461.0 462.75 470.5 472.00 473.0
    honggfuzz 82800 20.0 461.900000 4.610058 456.0 458.75 461.0 467.00 470.0
    aflplusplus 82800 20.0 460.800000 4.916139 456.0 457.00 460.0 462.25 472.0
    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
    mopt 82800 20.0 456.100000 4.024922 449.0 455.00 455.5 458.50 464.0
    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 20.0 453.300000 3.435113 445.0 451.00 454.0 455.25 462.0
    libafl 82800 20.0 449.350000 5.264329 439.0 447.50 449.0 451.00 461.0
    aflfast 82800 17.0 428.352941 37.729202 345.0 401.00 448.0 454.00 458.0

    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,)