FuzzBench: 2024-04-24-full-muttfuzz 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	97.61
libafl	97.48
honggfuzz	94.46
libfuzzer	93.27
honggfuzz_muttfuzz	91.00
aflsmart	85.00
mopt	84.88
afl	83.40
eclipser	83.06
aflfast	82.28
fairfuzz	79.40
aflsmart_muttfuzz	71.06
centipede	67.90
libfuzzer_muttfuzz	64.24
libafl_muttfuzz	63.42
aflplusplus_muttfuzz	32.77

By avg. rank

	average rank
fuzzer
aflplusplus	2.65
libafl	5.00
libfuzzer	5.61
honggfuzz_muttfuzz	5.74
honggfuzz	6.30
aflsmart	7.00
eclipser	8.04
mopt	8.30
afl	8.43
libafl_muttfuzz	8.48
aflfast	10.52
fairfuzz	11.04
aflplusplus_muttfuzz	11.09
centipede	11.13
libfuzzer_muttfuzz	11.17
aflsmart_muttfuzz	12.17

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	libafl_muttfuzz	honggfuzz_muttfuzz	honggfuzz	aflplusplus_muttfuzz	libfuzzer	eclipser	libfuzzer_muttfuzz	aflsmart_muttfuzz	aflsmart	mopt	afl	aflfast	centipede	fairfuzz
FuzzerMedian	97.00	96.00	96.00	96.00	96.00	96.00	94.00	94.00	88.00	89.00	94.00	93.00	94.00	93.00	88.00	86.00
FuzzerMean	94.22	94.17	93.67	91.95	91.30	91.12	90.22	87.90	84.41	83.84	82.61	82.48	81.04	80.04	79.16	77.17
bloaty_fuzz_target	98.00	99.00	nan	95.00	95.00	95.00	89.00	94.00	80.00	nan	95.00	97.00	94.00	93.00	nan	80.00
curl_curl_fuzzer_http	98.00	97.00	96.00	99.00	98.00	nan	91.00	94.00	84.00	90.00	94.00	94.00	94.00	93.00	nan	85.00
freetype2_ftfuzzer	88.00	88.00	75.00	95.00	87.00	nan	75.00	72.00	61.00	62.00	65.00	65.00	64.00	63.00	55.00	61.00
harfbuzz_hb-shape-fuzzer	98.00	99.00	nan	94.00	96.00	nan	95.00	96.00	88.00	88.00	96.00	97.00	96.00	95.00	nan	84.00
jsoncpp_jsoncpp_fuzzer	99.00	98.00	nan	99.00	99.00	99.00	100.00	98.00	100.00	98.00	98.00	98.00	98.00	98.00	98.00	98.00
lcms_cms_transform_fuzzer	90.00	91.00	90.00	84.00	79.00	nan	84.00	73.00	nan	43.00	68.00	69.00	40.00	28.00	37.00	53.00
libjpeg-turbo_libjpeg_turbo_fuzzer	99.00	99.00	99.00	99.00	99.00	nan	99.00	nan	96.00	95.00	99.00	99.00	99.00	99.00	96.00	99.00
libpcap_fuzz_both	85.00	82.00	nan	87.00	80.00	nan	75.00	72.00	70.00	nan	1.00	1.00	1.00	1.00	81.00	1.00
libpng_libpng_read_fuzzer	95.00	95.00	94.00	96.00	95.00	95.00	96.00	95.00	nan	91.00	94.00	94.00	94.00	93.00	96.00	94.00
libxml2_xml	99.00	98.00	nan	98.00	98.00	nan	97.00	97.00	89.00	90.00	97.00	96.00	96.00	96.00	93.00	88.00
libxslt_xpath	98.00	96.00	97.00	96.00	97.00	nan	92.00	95.00	76.00	85.00	95.00	93.00	94.00	94.00	94.00	95.00
mbedtls_fuzz_dtlsclient	71.00	86.00	96.00	66.00	70.00	73.00	70.00	70.00	66.00	66.00	70.00	70.00	70.00	68.00	69.00	73.00
openh264_decoder_fuzzer	99.00	98.00	nan	98.00	98.00	nan	98.00	98.00	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	99.00	99.00	99.00	99.00
openthread_ot-ip6-send-fuzzer	85.00	85.00	82.00	73.00	73.00	74.00	73.00	72.00	73.00	68.00	69.00	70.00	69.00	69.00	69.00	66.00
proj4_proj_crs_to_crs_fuzzer	89.00	90.00	nan	nan	97.00	nan	93.00	60.00	nan	nan	10.00	9.00	9.00	9.00	10.00	10.00
re2_fuzzer	99.00	98.00	99.00	99.00	98.00	nan	99.00	99.00	nan	99.00	99.00	98.00	99.00	99.00	95.00	99.00
sqlite3_ossfuzz	97.00	90.00	nan	66.00	69.00	nan	79.00	91.00	65.00	62.00	91.00	91.00	92.00	91.00	62.00	58.00
stb_stbi_read_fuzzer	93.00	95.00	95.00	95.00	91.00	nan	87.00	91.00	nan	nan	87.00	86.00	86.00	86.00	84.00	86.00
systemd_fuzz-link-parser	100.00	99.00	97.00	96.00	97.00	nan	95.00	91.00	94.00	86.00	92.00	91.00	91.00	91.00	98.00	87.00
vorbis_decode_fuzzer	94.00	93.00	93.00	94.00	93.00	nan	94.00	93.00	97.00	89.00	94.00	93.00	93.00	93.00	85.00	92.00
woff2_convert_woff2ttf_fuzzer	97.00	96.00	98.00	98.00	95.00	97.00	96.00	nan	nan	87.00	92.00	91.00	91.00	90.00	88.00	81.00
zlib_zlib_uncompress_fuzzer	97.00	95.00	95.00	97.00	97.00	97.00	99.00	96.00	99.00	97.00	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

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, honggfuzz_muttfuzz, libfuzzer_muttfuzz, aflplusplus_muttfuzz.

Sample statistics and statistical significance (code coverage)

Code coverage sample statistics

		count	mean	std	min	25%	median	75%	max
fuzzer	time
libafl	82800	19.0	6373.315789	64.294507	6225.0	6334.00	6392.0	6418.00	6451.0
aflplusplus	82800	15.0	6362.933333	53.783251	6262.0	6318.00	6363.0	6414.50	6437.0
mopt	82800	14.0	6242.357143	84.158831	6046.0	6225.75	6267.5	6291.00	6350.0
honggfuzz_muttfuzz	82800	10.0	6131.200000	165.609178	5808.0	6094.75	6160.5	6241.75	6302.0
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
aflplusplus_muttfuzz	82800	3.0	6062.333333	291.496712	5742.0	5937.50	6133.0	6222.50	6312.0
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
libfuzzer_muttfuzz	82800	4.0	5230.500000	271.985906	4936.0	5044.75	5224.5	5410.25	5537.0
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 aflplusplus_muttfuzz aflsmart aflsmart_muttfuzz centipede eclipser fairfuzz honggfuzz honggfuzz_muttfuzz libafl libafl_muttfuzz libfuzzer libfuzzer_muttfuzz mopt