ShadowBug: Enhanced Synthetic Fuzzing Benchmark Generation

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Zhou, Zhengxiang, and Cong Wang. “ShadowBug: Enhanced Synthetic Fuzzing Benchmark Generation”. IEEE Open Journal of the Computer Society, vol. 5, 2024, pp. 95-106, https://doi.org/10.1109/ojcs.2024.3378384.
Zhou, Z., & Wang, C. (2024). ShadowBug: Enhanced Synthetic Fuzzing Benchmark Generation. IEEE Open Journal of the Computer Society, 5, 95-106. https://doi.org/10.1109/ojcs.2024.3378384
Zhou Z, Wang C. ShadowBug: Enhanced Synthetic Fuzzing Benchmark Generation. IEEE Open Journal of the Computer Society. 2024;5:95-106.
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Refrences
Title Journal Journal Categories Citations Publication Date
FIXREVERTER: A realistic bug injection methodology for benchmarking fuzz testing 2022
UNIFUZZ: A holistic and pragmatic metrics-driven platform for evaluating fuzzers 2021
AFL++: Combining incremental steps of fuzzing research 2020
FuzzGuard: Filtering out unreachable inputs in directed grey-box fuzzing through deep learning 2020
ParmeSan: Sanitizer-guided greybox fuzzing 2020