Coverage-guided Fuzzing
Coverage-Guided Fuzzing is a fuzz testing method that systematically generates test inputs by iteratively mutating existing inputs and prioritizing those that increase code coverage, thereby enhancing the discovery of software vulnerabilities through directed exploration of program execution paths.
178
Publications
13.6K
Citations
593
Authors
198
Institutions
Publications per year
2017–2026
161
178
Automated Whitebox Fuzz Testing.
Patrice Godefroid, Michael Y. Levin, David A. Molnar · 2008 · 1.1K citations
Coverage-based Greybox Fuzzing as Markov Chain
Marcel Böhme, Van-Thuan Pham, Abhik Roychoudhury · 2016 · 619 citations
VUzzer: Application-aware Evolutionary Fuzzing
Sanjay Rawat, Vivek Jain, Ashish Kumar et al. · 2017 · 589 citations · Full text
Angora: Efficient Fuzzing by Principled Search
Sapienz: multi-objective automated testing for Android applications
Ke Mao, Mark Harman, Yue Jia · 2016 · 531 citations · Full text
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198
Tsinghua University
Beijing, China
16 h-index
66 publications
4.8K citations
University of California, Berkeley
Berkeley, United States
9 h-index
23 publications
3.3K citations

National University of Defense Technology
Changsha, China
9 h-index
42 publications
940 citations
National University of Singapore
Singapore, Singapore
8 h-index
14 publications
3.2K citations
Nanyang Technological University
Singapore, Singapore
7 h-index
32 publications
4.8K citations
University of Illinois Urbana-Champaign
Urbana, United States
6 h-index
9 publications
710 citations
Kyushu University
Fukuoka, Japan
5 h-index
8 publications
1.2K citations
Ruhr University Bochum
Bochum, Germany
5 h-index
13 publications
1K citations
1–8 of 198
Repository · 12 publications · 474 citations
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Conference · 7 publications · 296 citations
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TOSEM · 4 publications · 134 citations
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PACMPL · 4 publications · 175 citations
4
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Conference · 4 publications · 238 citations
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