FuzzBench: 2024-05-10-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	99.44
libafl	97.41
honggfuzz	96.79
libfuzzer	95.38
mopt	84.95
aflsmart	84.71
gfuzz	84.15
afl	81.65
aflfast	79.84
fairfuzz	79.14
eclipser	75.72
centipede	70.19

By avg. rank

	average rank
fuzzer
aflplusplus	1.82
libfuzzer	3.82
libafl	4.64
honggfuzz	5.82
aflsmart	5.91
gfuzz	6.00
mopt	6.09
afl	7.27
eclipser	7.55
centipede	9.09
fairfuzz	9.27
aflfast	9.45

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	eclipser	gfuzz	mopt	aflsmart	centipede	afl	aflfast	fairfuzz
FuzzerMedian	97.00	95.00	96.00	96.00	95.00	90.00	97.00	95.00	90.00	95.00	94.00	84.00
FuzzerMean	95.82	93.91	93.45	92.00	89.11	88.90	83.00	82.64	82.33	79.82	78.09	77.27
bloaty_fuzz_target	98.00	98.00	95.00	89.00	94.00	85.00	97.00	95.00	nan	94.00	93.00	80.00
freetype2_ftfuzzer	93.00	92.00	91.00	79.00	76.00	83.00	68.00	68.00	58.00	68.00	67.00	64.00
harfbuzz_hb-shape-fuzzer	98.00	99.00	96.00	94.00	96.00	nan	97.00	96.00	nan	96.00	95.00	84.00
lcms_cms_transform_fuzzer	94.00	95.00	82.00	87.00	76.00	75.00	72.00	70.00	38.00	41.00	29.00	55.00
libjpeg-turbo_libjpeg_turbo_fuzzer	99.00	82.00	99.00	99.00	nan	82.00	99.00	99.00	96.00	99.00	99.00	99.00
libpcap_fuzz_both	85.00	83.00	80.00	75.00	72.00	78.00	1.00	1.00	81.00	1.00	1.00	1.00
libpng_libpng_read_fuzzer	95.00	95.00	96.00	96.00	95.00	95.00	94.00	95.00	96.00	95.00	94.00	94.00
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
vorbis_decode_fuzzer	99.00	98.00	98.00	99.00	98.00	99.00	98.00	98.00	90.00	98.00	98.00	97.00
woff2_convert_woff2ttf_fuzzer	97.00	98.00	95.00	96.00	nan	96.00	91.00	92.00	88.00	91.00	90.00	81.00
zlib_zlib_uncompress_fuzzer	97.00	94.00	97.00	99.00	96.00	97.00	97.00	96.00	95.00	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

Mean code coverage growth over time

* The error bands show the 95% confidence interval around the mean code coverage.

The following fuzzers do not have enough samples: aflplusplus, aflsmart, mopt, eclipser, libafl, gfuzz.

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
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
gfuzz	82800	2.0	5480.500000	120.915260	5395.0	5437.75	5480.5	5523.25	5566.0
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

Code coverage reports for each fuzzer on this benchmark

afl aflfast aflplusplus aflsmart centipede eclipser fairfuzz gfuzz honggfuzz libafl libfuzzer mopt