FuzzBench: 2023-04-20-symcts 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	86.70
honggfuzz	83.99
aflplusplus	82.06
mopt	74.71
aflsmart	73.73
eclipser	73.52
afl	73.15
libfuzzer	72.38
aflfast	72.17
fairfuzz	69.37
symcts_afl	65.68
symcts_symqemu_afl	54.07
centipede	46.06
symcc_aflplusplus	28.75
symcts	27.40
symcts_symqemu	24.54
symsan	7.95

By avg. rank

	average rank
fuzzer
libafl	4.48
honggfuzz	5.19
aflplusplus	5.76
aflsmart	5.81
eclipser	6.24
afl	6.57
mopt	6.95
symcts_afl	8.19
libfuzzer	8.52
aflfast	8.86
symcts_symqemu_afl	9.33
fairfuzz	9.67
centipede	10.48
symcc_aflplusplus	11.14
symcts	12.81
symcts_symqemu	13.00
symsan	13.76

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	honggfuzz	aflplusplus	eclipser	symsan	symcts_afl	libfuzzer	symcts_symqemu_afl	mopt	aflsmart	afl	aflfast	fairfuzz	symcc_aflplusplus	centipede	symcts	symcts_symqemu
FuzzerMedian	91.00	93.00	91.00	81.00	77.00	84.00	81.00	83.00	87.00	88.00	88.00	87.00	80.00	69.00	62.00	73.50	59.00
FuzzerMean	84.29	81.67	79.67	78.89	77.00	74.11	73.95	73.20	72.95	72.10	71.62	70.48	67.71	59.60	55.12	55.10	44.73
bloaty_fuzz_target	98.00	95.00	76.00	95.00	nan	57.00	85.00	66.00	97.00	97.00	95.00	94.00	81.00	8.00	nan	nan	66.00
curl_curl_fuzzer_http	60.00	60.00	60.00	58.00	nan	49.00	48.00	52.00	58.00	58.00	58.00	57.00	52.00	99.00	nan	nan	8.00
freetype2_ftfuzzer	90.00	93.00	97.00	76.00	nan	90.00	72.00	91.00	69.00	68.00	69.00	65.00	64.00	32.00	12.00	nan	nan
harfbuzz_hb-shape-fuzzer	99.00	97.00	99.00	97.00	nan	nan	86.00	nan	97.00	97.00	97.00	96.00	87.00	40.00	45.00	nan	nan
jsoncpp_jsoncpp_fuzzer	81.00	81.00	81.00	81.00	nan	81.00	82.00	81.00	81.00	80.00	81.00	80.00	80.00	100.00	81.00	nan	59.00
lcms_cms_transform_fuzzer	91.00	79.00	91.00	79.00	nan	91.00	79.00	90.00	64.00	41.00	34.00	28.00	51.00	nan	1.00	90.00	83.00
libjpeg-turbo_libjpeg_turbo_fuzzer	99.00	99.00	98.00	nan	nan	98.00	73.00	84.00	99.00	99.00	99.00	99.00	99.00	20.00	99.00	38.00	nan
libpcap_fuzz_both	86.00	86.00	92.00	78.00	87.00	83.00	80.00	84.00	1.00	1.00	1.00	1.00	1.00	nan	87.00	nan	nan
libpng_libpng_read_fuzzer	95.00	96.00	94.00	95.00	nan	95.00	95.00	94.00	95.00	95.00	95.00	94.00	95.00	0.00	0.00	80.00	nan
libxml2_xml	99.00	99.00	78.00	98.00	nan	nan	93.00	72.00	97.00	98.00	97.00	97.00	90.00	nan	93.00	nan	nan
libxslt_xpath	56.00	57.00	35.00	56.00	nan	33.00	32.00	nan	55.00	56.00	56.00	55.00	56.00	98.00	55.00	nan	nan
openh264_decoder_fuzzer	99.00	99.00	98.00	99.00	nan	99.00	95.00	99.00	99.00	99.00	99.00	99.00	90.00	nan	nan	9.00	9.00
openssl_x509	42.00	42.00	13.00	42.00	nan	13.00	42.00	13.00	42.00	42.00	42.00	42.00	42.00	99.00	13.00	13.00	12.00
openthread_ot-ip6-send-fuzzer	78.00	66.00	67.00	67.00	67.00	93.00	68.00	79.00	64.00	64.00	64.00	63.00	60.00	nan	62.00	84.00	77.00
proj4_proj_crs_to_crs_fuzzer	86.00	98.00	85.00	59.00	nan	84.00	nan	83.00	9.00	9.00	9.00	9.00	9.00	nan	nan	nan	nan
re2_fuzzer	98.00	99.00	99.00	99.00	nan	99.00	99.00	99.00	99.00	99.00	99.00	99.00	99.00	nan	96.00	nan	nan
sqlite3_ossfuzz	90.00	76.00	91.00	96.00	nan	11.00	61.00	11.00	95.00	96.00	95.00	93.00	67.00	nan	66.00	10.00	10.00
stb_stbi_read_fuzzer	92.00	63.00	97.00	92.00	nan	84.00	86.00	nan	87.00	88.00	88.00	87.00	87.00	nan	86.00	70.00	75.00
systemd_fuzz-link-parser	37.00	36.00	37.00	34.00	nan	nan	18.00	nan	34.00	34.00	34.00	34.00	32.00	100.00	36.00	nan	nan
vorbis_decode_fuzzer	98.00	98.00	87.00	98.00	nan	91.00	99.00	nan	98.00	99.00	99.00	98.00	98.00	nan	16.00	80.00	17.00
woff2_convert_woff2ttf_fuzzer	96.00	96.00	98.00	nan	nan	83.00	86.00	nan	92.00	94.00	93.00	90.00	82.00	nan	89.00	77.00	76.00

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: symcts_symqemu_afl, symcts_symqemu, symcc_aflplusplus, symcts_afl.

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	6296.300000	44.018058	6161.0	6283.25	6307.0	6328.25	6338.0
mopt	82800	20.0	6236.050000	71.516266	6071.0	6226.50	6243.5	6268.50	6354.0
aflsmart	82800	20.0	6198.450000	127.984981	5937.0	6102.25	6205.0	6295.25	6394.0
honggfuzz	82800	20.0	6109.350000	211.677330	5795.0	5892.50	6113.5	6333.00	6374.0
eclipser	82800	20.0	6110.200000	114.487232	5900.0	6066.75	6107.0	6144.50	6360.0
afl	82800	20.0	6085.700000	136.253286	5875.0	6048.75	6078.0	6130.50	6384.0
aflfast	82800	20.0	6080.100000	119.230824	5858.0	6033.50	6059.0	6136.50	6350.0
libfuzzer	82800	20.0	5513.950000	135.178040	5307.0	5419.50	5466.5	5582.25	5874.0
fairfuzz	82800	20.0	5217.750000	121.813868	5060.0	5145.00	5194.5	5272.75	5570.0
aflplusplus	82800	20.0	4902.900000	89.010880	4755.0	4834.50	4888.0	4972.50	5040.0
symcts_symqemu_afl	82800	4.0	4297.750000	91.565550	4226.0	4243.25	4267.5	4322.00	4430.0
symcts_symqemu	82800	3.0	4251.333333	11.150486	4243.0	4245.00	4247.0	4255.50	4264.0
symcts_afl	82800	1.0	3648.000000	NaN	3648.0	3648.00	3648.0	3648.00	3648.0
symcc_aflplusplus	82800	1.0	551.000000	NaN	551.0	551.00	551.0	551.00	551.0

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 symcc_aflplusplus symcts symcts_afl symcts_symqemu symcts_symqemu_afl symsan