Feedback-driven Fuzzing

Feedback-Driven Fuzzing is a fuzz testing method that iteratively generates test inputs by leveraging runtime feedback from prior executions to guide the exploration of program paths, thereby distinguishing itself from non-guided fuzzing techniques through its adaptive, feedback-informed input mutation strategy.

28

Publications

2.5K

Citations

120

Authors

45

Institutions

Publications per year

2017–2026

27

Authors

120

  1. YL
    Yang Liu

    Nanyang Technological University, Singapore

    4 publications · 518 citations

    4

    h-index

  2. YJ
    Yu Jiang

    Tsinghua University, China

    4 publications · 79 citations

    4

    h-index

  3. JL
    Jie Liang

    Tsinghua University, China

    3 publications · 68 citations

    3

    h-index

  4. TH
    Thorsten Holz

    Ruhr University Bochum, Germany

    3 publications · 672 citations

    3

    h-index

  5. XX
    Xiaofei Xie

    Nanyang Technological University, Singapore

    3 publications · 500 citations

    3

    h-index

1–5 of 120

Venues

  1. arXiv (Cornell University)

    Repository · 4 publications · 86 citations

    4

    h-index

  2. USENIX Security Symposium

    Conference · 2 publications · 191 citations

    2

    h-index

  3. Proceedings of the ACM on Programming Languages

    PACMPL · 1 publications · 67 citations

    1

    h-index

  4. ACM Transactions on Software Engineering and Methodology

    TOSEM · 1 publications · 40 citations

    1

    h-index

  5. IEEE INFOCOM 2022 - IEEE Conference on Computer Communications

    Conference · 1 publications · 15 citations

    1

    h-index

1–5