FuzzBench: 2024-07-08-dgfuzz-1 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
libafl	97.69
libfuzzer	93.66
afl	84.87
aflfast	82.37
aflplusplus	79.76
honggfuzz	78.25
eclipser	74.87
centipede	72.21
mopt	67.35
aflsmart	67.01
fairfuzz	64.78
dgfuzz	29.59

By avg. rank

	average rank
fuzzer
aflplusplus	2.83
libafl	3.43
libfuzzer	4.43
honggfuzz	5.57
afl	5.61
eclipser	5.78
aflsmart	6.26
mopt	6.87
aflfast	7.78
dgfuzz	7.96
centipede	8.00
fairfuzz	8.43

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

	libafl	aflplusplus	dgfuzz	honggfuzz	libfuzzer	eclipser	afl	centipede	aflfast	mopt	aflsmart	fairfuzz
FuzzerMedian	97.00	97.00	97.00	95.00	94.00	93.00	93.00	91.00	92.00	93.00	94.00	86.00
FuzzerMean	94.48	93.05	92.14	91.32	90.61	87.37	82.57	80.25	80.22	79.00	78.58	76.05
bloaty_fuzz_target	97.00	95.00	nan	91.00	87.00	92.00	92.00	nan	92.00	94.00	93.00	79.00
curl_curl_fuzzer_http	98.00	98.00	nan	98.00	89.00	93.00	93.00	nan	93.00	93.00	94.00	84.00
freetype2_ftfuzzer	87.00	90.00	nan	90.00	76.00	73.00	65.00	56.00	63.00	65.00	65.00	61.00
harfbuzz_hb-shape-fuzzer	98.00	97.00	98.00	95.00	94.00	96.00	96.00	nan	95.00	96.00	96.00	84.00
jsoncpp_jsoncpp_fuzzer	98.00	99.00	nan	99.00	100.00	98.00	98.00	98.00	98.00	98.00	98.00	98.00
lcms_cms_transform_fuzzer	95.00	91.00	95.00	73.00	89.00	75.00	69.00	36.00	29.00	51.00	40.00	55.00
libjpeg-turbo_libjpeg_turbo_fuzzer	99.00	nan	nan	nan	99.00	nan	99.00	98.00	99.00	nan	nan	nan
libpcap_fuzz_both	76.00	88.00	86.00	79.00	73.00	71.00	0.00	81.00	1.00	0.00	0.00	0.00
libpng_libpng_read_fuzzer	95.00	95.00	nan	95.00	96.00	94.00	94.00	95.00	92.00	94.00	94.00	94.00
libxml2_xml	98.00	99.00	nan	98.00	97.00	97.00	97.00	93.00	96.00	97.00	97.00	89.00
libxslt_xpath	96.00	99.00	nan	97.00	93.00	95.00	95.00	94.00	94.00	93.00	95.00	95.00
mbedtls_fuzz_dtlsclient	86.00	70.00	97.00	69.00	69.00	69.00	69.00	68.00	67.00	69.00	69.00	72.00
openh264_decoder_fuzzer	98.00	99.00	nan	98.00	98.00	98.00	98.00	95.00	99.00	99.00	98.00	90.00
openssl_x509	99.00	99.00	nan	99.00	99.00	99.00	99.00	99.00	99.00	99.00	99.00	99.00
openthread_ot-ip6-send-fuzzer	87.00	75.00	74.00	75.00	75.00	73.00	71.00	70.00	71.00	71.00	71.00	68.00
proj4_proj_crs_to_crs_fuzzer	87.00	81.00	nan	95.00	91.00	59.00	9.00	9.00	8.00	9.00	9.00	9.00
re2_fuzzer	98.00	99.00	nan	98.00	99.00	99.00	99.00	95.00	99.00	98.00	99.00	99.00
sqlite3_ossfuzz	99.00	nan	nan	nan	81.00	nan	93.00	64.00	92.00	nan	nan	nan
stb_stbi_read_fuzzer	94.00	96.00	97.00	92.00	88.00	91.00	87.00	85.00	86.00	86.00	87.00	86.00
systemd_fuzz-link-parser	98.00	99.00	nan	97.00	97.00	91.00	91.00	97.00	91.00	91.00	91.00	86.00
vorbis_decode_fuzzer	98.00	99.00	98.00	97.00	99.00	97.00	98.00	89.00	98.00	98.00	98.00	97.00
woff2_convert_woff2ttf_fuzzer	97.00	nan	nan	nan	96.00	nan	91.00	88.00	89.00	nan	nan	nan
zlib_zlib_uncompress_fuzzer	95.00	nan	nan	nan	99.00	nan	96.00	95.00	94.00	nan	nan	nan

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: eclipser, aflplusplus.

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	6359.900000	57.601078	6257.0	6317.50	6364.0	6391.75	6458.0
aflplusplus	82800	10.0	6271.900000	29.091618	6240.0	6249.00	6271.0	6284.50	6334.0
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
afl	82800	20.0	6091.050000	75.644233	5902.0	6066.00	6079.5	6132.25	6300.0
eclipser	82800	11.0	6053.181818	68.930136	5914.0	6022.50	6078.0	6095.50	6135.0
aflfast	82800	20.0	6077.150000	116.111233	5846.0	6016.00	6076.0	6140.25	6335.0
honggfuzz	82800	20.0	6044.800000	190.055560	5739.0	5920.75	5971.0	6222.50	6334.0
libfuzzer	82800	20.0	5759.850000	158.541469	5522.0	5657.50	5742.0	5840.25	6038.0
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 honggfuzz libafl libfuzzer mopt