iBiR: bug report driven fault injection

Khanfir, Ahmed and Koyuncu, Anıl and Papadakis, Mike and Cordy, Maxime and Bissyande, Tegawende F. and Klein, Jacques and Le Traon, Yves (2022) iBiR: bug report driven fault injection. ACM Transactions on Software Engineering and Methodology . ISSN 1049-331X (Print) 1557-7392 (Online) Published Online First http://dx.doi.org/10.1145/3542946

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Much research on software engineering relies on experimental studies based on fault injection. Fault injection, however, is not often relevant to emulate real-world software faults since it “blindly” injects large numbers of faults. It remains indeed challenging to inject few but realistic faults that target a particular functionality in a program. In this work, we introduce iBiR, a fault injection tool that addresses this challenge by exploring change patterns associated to user-reported faults. To inject realistic faults, we create mutants by re-targeting a bug report driven automated program repair system, i.e., reversing its code transformation templates. iBiR is further appealing in practice since it requires deep knowledge of neither code nor tests, but just of the program’s relevant bug reports. Thus, our approach focuses the fault injection on the feature targeted by the bug report. We assess iBiR by considering the Defects4J dataset. Experimental results show that our approach outperforms the fault injection performed by traditional mutation testing in terms of semantic similarity with the original bug, when applied at either system or class levels of granularity, and provides better, statistically significant, estimations of test effectiveness (fault detection). Additionally, when injecting 100 faults, iBiR injects faults that couple with the real ones in around 36% of the cases, while mutation testing achieves less than 4%.
Item Type: Article
Divisions: Faculty of Engineering and Natural Sciences > Academic programs > Computer Science & Eng.
Faculty of Engineering and Natural Sciences
Depositing User: Anıl Koyuncu
Date Deposited: 30 Jun 2022 14:33
Last Modified: 04 Sep 2022 21:08
URI: https://research.sabanciuniv.edu/id/eprint/42934

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