---
_id: '61546'
abstract:
- lang: eng
  text: <jats:p>Fuzzing is a powerful software testing technique renowned for its
    effectiveness in identifying software vulnerabilities. Traditional fuzzing evaluations
    typically focus on overall fuzzer performance across a set of target programs,
    yet few benchmarks consider how fine-grained program features influence fuzzing
    effectiveness. To bridge this gap, we introduce FeatureBench, a novel benchmark
    designed to generate programs with configurable, fine-grained program features
    to enhance fuzzing evaluations. We reviewed 25 recent grey-box fuzzing studies,
    extracting 7 program features related to control-flow and data-flow that can impact
    fuzzer performance. Using these features, we generated a benchmark consisting
    of 153 programs controlled by 10 fine-grained configurable parameters. We evaluated
    11 fuzzers using this benchmark, with each fuzzer representing either distinct
    claimed improvements or serving as a widely used baseline in fuzzing evaluations.
    The results indicate that fuzzer performance varies significantly based on the
    program features and their strengths, highlighting the importance of incorporating
    program characteristics into fuzzing evaluations.</jats:p>
author:
- first_name: Miao
  full_name: Miao, Miao
  last_name: Miao
- first_name: Sriteja
  full_name: Kummita, Sriteja
  id: '72582'
  last_name: Kummita
- first_name: Eric
  full_name: Bodden, Eric
  id: '59256'
  last_name: Bodden
  orcid: 0000-0003-3470-3647
- first_name: Shiyi
  full_name: Wei, Shiyi
  last_name: Wei
citation:
  ama: Miao M, Kummita S, Bodden E, Wei S. Program Feature-Based Benchmarking for
    Fuzz Testing. <i>Proceedings of the ACM on Software Engineering</i>. 2025;2(ISSTA):527-549.
    doi:<a href="https://doi.org/10.1145/3728899">10.1145/3728899</a>
  apa: Miao, M., Kummita, S., Bodden, E., &#38; Wei, S. (2025). Program Feature-Based
    Benchmarking for Fuzz Testing. <i>Proceedings of the ACM on Software Engineering</i>,
    <i>2</i>(ISSTA), 527–549. <a href="https://doi.org/10.1145/3728899">https://doi.org/10.1145/3728899</a>
  bibtex: '@article{Miao_Kummita_Bodden_Wei_2025, title={Program Feature-Based Benchmarking
    for Fuzz Testing}, volume={2}, DOI={<a href="https://doi.org/10.1145/3728899">10.1145/3728899</a>},
    number={ISSTA}, journal={Proceedings of the ACM on Software Engineering}, publisher={Association
    for Computing Machinery (ACM)}, author={Miao, Miao and Kummita, Sriteja and Bodden,
    Eric and Wei, Shiyi}, year={2025}, pages={527–549} }'
  chicago: 'Miao, Miao, Sriteja Kummita, Eric Bodden, and Shiyi Wei. “Program Feature-Based
    Benchmarking for Fuzz Testing.” <i>Proceedings of the ACM on Software Engineering</i>
    2, no. ISSTA (2025): 527–49. <a href="https://doi.org/10.1145/3728899">https://doi.org/10.1145/3728899</a>.'
  ieee: 'M. Miao, S. Kummita, E. Bodden, and S. Wei, “Program Feature-Based Benchmarking
    for Fuzz Testing,” <i>Proceedings of the ACM on Software Engineering</i>, vol.
    2, no. ISSTA, pp. 527–549, 2025, doi: <a href="https://doi.org/10.1145/3728899">10.1145/3728899</a>.'
  mla: Miao, Miao, et al. “Program Feature-Based Benchmarking for Fuzz Testing.” <i>Proceedings
    of the ACM on Software Engineering</i>, vol. 2, no. ISSTA, Association for Computing
    Machinery (ACM), 2025, pp. 527–49, doi:<a href="https://doi.org/10.1145/3728899">10.1145/3728899</a>.
  short: M. Miao, S. Kummita, E. Bodden, S. Wei, Proceedings of the ACM on Software
    Engineering 2 (2025) 527–549.
date_created: 2025-10-08T08:29:39Z
date_updated: 2025-10-08T08:32:57Z
department:
- _id: '76'
- _id: '662'
doi: 10.1145/3728899
intvolume: '         2'
issue: ISSTA
language:
- iso: eng
page: 527-549
publication: Proceedings of the ACM on Software Engineering
publication_identifier:
  issn:
  - 2994-970X
publication_status: published
publisher: Association for Computing Machinery (ACM)
status: public
title: Program Feature-Based Benchmarking for Fuzz Testing
type: journal_article
user_id: '15249'
volume: 2
year: '2025'
...