Mutation-aware fault prediction

Bowes, David and Hall, Tracy and Harman, Mark and Jia, Yue and Sarro, Federica and Wu, Fan (2016) Mutation-aware fault prediction. In: ISSTA 2016 Proceedings of the 25th International Symposium on Software Testing and Analysis. Association for Computing Machinery, Inc, DEU, pp. 330-341. ISBN 9781450343909

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Abstract

We introduce mutation-aware fault prediction, which leverages additional guidance from metrics constructed in terms of mutants and the test cases that cover and detect them. We report the results of 12 sets of experiments, applying 4 Different predictive modelling techniques to 3 large real-world systems (both open and closed source). The results show that our proposal can significantly (p ≤ 0:05) improve fault prediction performance. Moreover, mutation-based metrics lie in the top 5% most frequently relied upon fault predictors in 10 of the 12 sets of experiments, and provide the majority of the top ten fault predictors in 9 of the 12 sets of experiments.

Item Type: Contribution in Book/Report/Proceedings
Additional Information: © ACM, 2016. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in ISSTA 2016 Proceedings of the 25th International Symposium on Software Testing and Analysis http://dx.doi.org/10.1145/2931037.2931039
Uncontrolled Keywords: /dk/atira/pure/subjectarea/asjc/1700/1712
Subjects:
Departments: Faculty of Science and Technology > School of Computing & Communications
ID Code: 127422
Deposited By: ep_importer_pure
Deposited On: 11 Sep 2018 13:48
Refereed?: Yes
Published?: Published
Last Modified: 22 Feb 2020 05:57
URI: https://eprints.lancs.ac.uk/id/eprint/127422

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