Boosting fuzzer efficiency: an information theoretic perspective

Author:

Böhme Marcel1,Manès Valentin J. M.2,Cha Sang Kil2

Affiliation:

1. Monash University, Australia

2. KAIST, South Korea

Funder

Australian Research Council

Ministry of Science and ICT, South Korea

Publisher

ACM

Reference45 articles.

1. Abhishek Aarya Oliver Chang Max Moroz Martin Barbella and Jonathan Metzman. 2019. Open sourcing ClusterFuzz. https://security.googleblog.com/ 2019 /02/ open-sourcing-clusterfuzz.html. ( 2019 ). Accessed: 2020-09-30. Abhishek Aarya Oliver Chang Max Moroz Martin Barbella and Jonathan Metzman. 2019. Open sourcing ClusterFuzz. https://security.googleblog.com/ 2019 /02/ open-sourcing-clusterfuzz.html. ( 2019 ). Accessed: 2020-09-30.

2. Coverage and fault detection of the output-uniqueness test selection criteria

3. A practical guide for using statistical tests to assess randomized algorithms in software engineering

4. Ijon: Exploring Deep State Spaces via Fuzzing

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