Seed Corpus Generation

Seed Corpus Generation is the systematic process of creating an initial collection of input data specifically designed to serve as a foundational basis for fuzz testing, distinguished by its role in enhancing the effectiveness and efficiency of test case exploration through the provision of semantically and syntactically relevant starting inputs.

16

Publications

834

Citations

60

Authors

22

Institutions

Publications per year

2017–2026

10

Authors

60

  1. SM
    Simon Mille

    Universitat Pompeu Fabra, Spain

    1 publications · 10 citations

    1

    h-index

  2. NM
    Nikolay Matyunin

    Honda (Japan), Japan

    1 publications · 19 citations

    1

    h-index

  3. FP
    Fernando Pereira

    Instituto de Telecomunicações, Portugal

    1 publications · 32 citations

    1

    h-index

  4. YZ
    Yaowen Zheng

    Institute of Information Engineering, China

    1 publications · 16 citations

    1

    h-index

  5. SF
    Susanne Fertmann

    Saarland University, Germany

    1 publications · 14 citations

    1

    h-index

1–5 of 60

Venues

  1. IEEE Access

    1 publications · 18 citations

    2

    h-index

  2. Computers & Security

    1 publications · 16 citations

    1

    h-index

  3. 1

    h-index

  4. 1

    h-index

  5. Institutional Repositories DataBase (IRDB)

    Repository · 1 publications · 28 citations

    1

    h-index

1–5