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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Arnau Gàmez-Montolio (City, University of London; Activision Research), Enric Florit (Universitat de Barcelona), Martin Brain (City, University of London), Jacob M. Howe (City, University of London)

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Performance, Correctness, Exceptions: Pick Three

Andrea Gussoni (Politecnico di Milano), Alessandro Di Federico (Politecnico di Milano), Pietro Fezzardi (Politecnico di Milano), Giovanni Agosta (Politecnico di Milano)

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Blaze: A Framework for Interprocedural Binary Analysis

Matthew Revelle, Matt Parker, Kevin Orr (Kudu Dynamics)

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REDsec: Running Encrypted Discretized Neural Networks in Seconds

Lars Wolfgang Folkerts (University of Delaware), Charles Gouert (University of Delaware), Nektarios Georgios Tsoutsos (University of Delaware)

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