Keisuke Nishimura, Yuichi Sugiyama, Yuki Koike, Masaya Motoda, Tomoya Kitagawa, Toshiki Takatera, Yuma Kurogome (Ricerca Security, Inc.)

Fuzzing has contributed to automatically identifying bugs and vulnerabilities in the software testing field. Although it can efficiently generate crashing inputs, these inputs are usually analyzed manually. Several root cause analysis (RCA) techniques have been proposed to automatically analyze the root causes of crashes to mitigate this cost. However, outstanding challenges for realizing more elaborate RCA techniques remain unknown owing to the lack of extensive evaluation methods over existing techniques. With this problem in mind, we developed an end-to-end benchmarking platform, RCABench, that can evaluate RCA techniques for various targeted programs in a detailed and comprehensive manner. Our experiments with RCABench indicated that the evaluations in previous studies were not enough to fully support their claims. Moreover, this platform can be leveraged to evaluate emerging RCA techniques by comparing them with existing techniques.

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Xiaochuan Zhang (Artificial Intelligence Research Center, National Innovation Institute of Defense Technology), Wenjie Sun (State Key Laboratory of Mathematical Engineering and Advanced Computing), Jianmin Pang (State Key Laboratory of Mathematical Engineering and Advanced Computing), Fudong Liu (State Key Laboratory of Mathematical Engineering and Advanced Computing), Zhen Ma (State Key Laboratory of Mathematical Engineering and Advanced…

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Tianxi Ji (Texas Tech University), Erman Ayday (Case Western Reserve University), Emre Yilmaz (University of Houston-Downtown), Ming Li (CSE Department The University of Texas at Arlington), Pan Li (Case Western Reserve University)

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Dr. Zhiqiang Lin (Distinguished Professor of Engineering at The Ohio State University)

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