Automated crash fault localization
S. Popping (TU Delft - Electrical Engineering, Mathematics and Computer Science)
Arie van van Deursen – Mentor (TU Delft - Software Technology)
Xavier Devroey – Mentor (TU Delft - Software Engineering)
Annibale Panichella – Graduation committee member (TU Delft - Software Engineering)
MM de Weerdt – Graduation committee member (TU Delft - Algorithmics)
P. Derakhshanfar – Graduation committee member (TU Delft - Software Engineering)
More Info
expand_more
Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.
Abstract
Debugging application crashes is an expensive and time-taking process, relying on the developer’s expertise, and requiring knowledge about the system. Over the years, the research community has developed several automated approaches to ease debugging. Among those approaches, search-based crash reproduction, which tries to generate a test case capable of reproducing a given crash to make it observable to the developers, solely based on the stack trace included in the crash report. We believe that this makes crash reproduction the perfect candidate to achieve end-to-end crash fault localization. In this thesis, we explore and empirically evaluate the usage of search-based crash reproduction combined with spectrum-based fault localization on 50 real-world crashes. Starting from a crash report, we generate crash-reproducing test cases and use them in conjunction with the existing or an automatically generated unit test suite as input for spectrum-based fault localization. Our results show that, although, hand-written test cases remain the most efficient in the general scenario, automatically generated crash-reproducing test cases still reduce the number of statements to be investigated by developers. Additionally, when considering the best-case scenario where only crash-reproducing test cases covering the fault are evaluated, we observe no statistically significant difference between the accuracy of fault localization when using hand-written or automatically generated test cases. Our results confirm the feasibility of end-to-end automated crash fault localization. The results also identify new challenges for both automated test case generation and fault localization, as well as when they are combined.