Search-Based Crash Reproduction and Its Impact on Debugging

Title

Search-Based Crash Reproduction and Its Impact on Debugging

 Author

Soltani, M. (TU Delft Software Engineering) ORCID 0000-0003-2788-796X
Panichella, A. (TU Delft Software Engineering) ORCID 0000-0002-7395-3588
van Deursen, A. (TU Delft Software Technology) ORCID 0000-0003-4850-3312

 Department

Software Technology

 Date

2020

 Abstract

Software systems fail. These failures are often reported to issue tracking systems, where they are prioritized and assigned to responsible developers to be investigated. When developers debug software, they need to reproduce the reported failure in order to verify whether their fix actually prevents the failure from happening again. Since manually reproducing each failure could be a complex task, several automated techniques have been proposed to tackle this problem. Despite showing advancements in this area, the proposed techniques showed various types of limitations. In this paper, we present EvoCrash, a new approach to automated crash reproduction based on a novel evolutionary algorithm, called Guided Genetic Algorithm (GGA). We report on our empirical study on using EvoCrash to reproduce 54 real-world crashes, as well as the results of a controlled experiment, involving human participants, to assess the impact of EvoCrash tests in debugging. Based on our results, EvoCrash outperforms state-of-the-art techniques in crash reproduction and uncovers failures that are undetected by classical coverage-based unit test generation tools. In addition, we observed that using EvoCrash helps developers provide fixes more often and take less time when debugging, compared to developers debugging and fixing code without using EvoCrash tests.


 Subject

Search-Based Software Testing
Genetic Algorithms
Automated Crash Reproduction
Empirical Software Engineering
empirical software engineering
Search-based software testing
genetic algorithms
automated crash reproduction

 To reference this document use:

http://resolver.tudelft.nl/uuid:1281ce36-7afc-43d9-ad83-b69c60fbd49a

 DOI

https://doi.org/10.1109/TSE.2018.2877664

 ISSN

0098-5589

 Source

IEEE Transactions on Software Engineering, 46 (12), 1294-1317

 Part of collection

Institutional Repository

 Document type

journal article

 Rights

© 2020 M. Soltani, A. Panichella, A. van Deursen
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