Improving fuzzing assessment methods through the analysis of metrics and experimental conditions Article Swipe
Maialen Eceiza
,
José Luis Flores
,
Mikel Iturbe
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1016/j.cose.2022.102946
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1016/j.cose.2022.102946
Fuzzing is nowadays one of the most widely used bug hunting techniques. By automatically generating malformed inputs, fuzzing aims to trigger unwanted behavior on its target. While fuzzing research has matured considerably in the last years, the evaluation and comparison of different fuzzing proposals remain challenging, as no standard set of metrics, data, or experimental conditions exist to allow such observation. This paper aims to fill that gap by proposing a standard set of features to allow such comparison. For that end, it first reviews the existing evaluation methods in the literature and discusses all existing metrics by evaluating seven fuzzers under identical experimental conditions. After examining the obtained results, it recommends a set of practices –particularly on the metrics to be used–, to allow proper comparison between different fuzzing proposals.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1016/j.cose.2022.102946
- OA Status
- hybrid
- Cited By
- 9
- References
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All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W4304014266Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1016/j.cose.2022.102946Digital Object Identifier
- Title
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Improving fuzzing assessment methods through the analysis of metrics and experimental conditionsWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2022Year of publication
- Publication date
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2022-10-10Full publication date if available
- Authors
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Maialen Eceiza, José Luis Flores, Mikel IturbeList of authors in order
- Landing page
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https://doi.org/10.1016/j.cose.2022.102946Publisher landing page
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YesWhether a free full text is available
- OA status
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hybridOpen access status per OpenAlex
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https://doi.org/10.1016/j.cose.2022.102946Direct OA link when available
- Concepts
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Fuzz testing, Computer science, Set (abstract data type), Data mining, Machine learning, Software, Programming languageTop concepts (fields/topics) attached by OpenAlex
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9Total citation count in OpenAlex
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-
2025: 4, 2024: 4, 2023: 1Per-year citation counts (last 5 years)
- References (count)
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81Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.of | 4, 40, 50, 73, 114 |
| abstract_inverted_index.on | 23, 117 |
| abstract_inverted_index.or | 53 |
| abstract_inverted_index.to | 19, 57, 64, 75, 120, 123 |
| abstract_inverted_index.For | 79 |
| abstract_inverted_index.all | 94 |
| abstract_inverted_index.and | 38, 92 |
| abstract_inverted_index.bug | 9 |
| abstract_inverted_index.gap | 67 |
| abstract_inverted_index.has | 29 |
| abstract_inverted_index.its | 24 |
| abstract_inverted_index.one | 3 |
| abstract_inverted_index.set | 49, 72, 113 |
| abstract_inverted_index.the | 5, 33, 36, 85, 90, 107, 118 |
| abstract_inverted_index.This | 61 |
| abstract_inverted_index.aims | 18, 63 |
| abstract_inverted_index.end, | 81 |
| abstract_inverted_index.fill | 65 |
| abstract_inverted_index.last | 34 |
| abstract_inverted_index.most | 6 |
| abstract_inverted_index.such | 59, 77 |
| abstract_inverted_index.that | 66, 80 |
| abstract_inverted_index.used | 8 |
| abstract_inverted_index.After | 105 |
| abstract_inverted_index.While | 26 |
| abstract_inverted_index.allow | 58, 76, 124 |
| abstract_inverted_index.data, | 52 |
| abstract_inverted_index.exist | 56 |
| abstract_inverted_index.first | 83 |
| abstract_inverted_index.paper | 62 |
| abstract_inverted_index.seven | 99 |
| abstract_inverted_index.under | 101 |
| abstract_inverted_index.proper | 125 |
| abstract_inverted_index.remain | 44 |
| abstract_inverted_index.widely | 7 |
| abstract_inverted_index.years, | 35 |
| abstract_inverted_index.Fuzzing | 0 |
| abstract_inverted_index.between | 127 |
| abstract_inverted_index.fuzzers | 100 |
| abstract_inverted_index.fuzzing | 17, 27, 42, 129 |
| abstract_inverted_index.hunting | 10 |
| abstract_inverted_index.inputs, | 16 |
| abstract_inverted_index.matured | 30 |
| abstract_inverted_index.methods | 88 |
| abstract_inverted_index.metrics | 96, 119 |
| abstract_inverted_index.reviews | 84 |
| abstract_inverted_index.target. | 25 |
| abstract_inverted_index.trigger | 20 |
| abstract_inverted_index.behavior | 22 |
| abstract_inverted_index.existing | 86, 95 |
| abstract_inverted_index.features | 74 |
| abstract_inverted_index.metrics, | 51 |
| abstract_inverted_index.nowadays | 2 |
| abstract_inverted_index.obtained | 108 |
| abstract_inverted_index.research | 28 |
| abstract_inverted_index.results, | 109 |
| abstract_inverted_index.standard | 48, 71 |
| abstract_inverted_index.unwanted | 21 |
| abstract_inverted_index.used–, | 122 |
| abstract_inverted_index.different | 41, 128 |
| abstract_inverted_index.discusses | 93 |
| abstract_inverted_index.examining | 106 |
| abstract_inverted_index.identical | 102 |
| abstract_inverted_index.malformed | 15 |
| abstract_inverted_index.practices | 115 |
| abstract_inverted_index.proposals | 43 |
| abstract_inverted_index.proposing | 69 |
| abstract_inverted_index.comparison | 39, 126 |
| abstract_inverted_index.conditions | 55 |
| abstract_inverted_index.evaluating | 98 |
| abstract_inverted_index.evaluation | 37, 87 |
| abstract_inverted_index.generating | 14 |
| abstract_inverted_index.literature | 91 |
| abstract_inverted_index.proposals. | 130 |
| abstract_inverted_index.recommends | 111 |
| abstract_inverted_index.comparison. | 78 |
| abstract_inverted_index.conditions. | 104 |
| abstract_inverted_index.techniques. | 11 |
| abstract_inverted_index.challenging, | 45 |
| abstract_inverted_index.considerably | 31 |
| abstract_inverted_index.experimental | 54, 103 |
| abstract_inverted_index.observation. | 60 |
| abstract_inverted_index.automatically | 13 |
| abstract_inverted_index.–particularly | 116 |
| cited_by_percentile_year.max | 98 |
| cited_by_percentile_year.min | 89 |
| corresponding_author_ids | https://openalex.org/A5076216328 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 3 |
| corresponding_institution_ids | https://openalex.org/I162361429, https://openalex.org/I4210121514 |
| citation_normalized_percentile.value | 0.89618321 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |