Grammar-based Fuzzing

Grammar-Based Fuzzing is a fuzz testing technique that generates inputs by systematically applying mutations and derivations based on a formal grammar, distinguishing it from other fuzzing methods through its structured, syntax-aware approach to test case generation.

40

Publications

3.6K

Citations

124

Authors

57

Institutions

Publications per year

2017–2026

29

Variants

Grammar-based Fuzz Testing

Authors

124

  1. PG
    Patrice Godefroid

    Microsoft (United States), United States

    5 publications · 970 citations

    5

    h-index

  2. RP
    Rohan Padhye

    University of California, Berkeley, United States

    2 publications · 37 citations

    2

    h-index

  3. LW
    Lei Wei

    Nanyang Technological University, Singapore

    2 publications · 555 citations

    2

    h-index

  4. JW
    Junjie Wang

    Institute of Software, China

    2 publications · 555 citations

    2

    h-index

  5. OB
    Osbert Bastani

    California University of Pennsylvania, United States

    2 publications · 180 citations

    2

    h-index

1–5 of 124

Venues

  1. arXiv (Cornell University)

    Repository · 2 publications · 65 citations

    2

    h-index

  2. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 2 publications · 107 citations

    2

    h-index

  3. ACM SIGPLAN Notices

    2 publications · 179 citations

    2

    h-index

  4. Information and Software Technology

    1 publications · 57 citations

    1

    h-index

  5. Nutrition Today

    1 publications · 21 citations

    1

    h-index

1–5