Empirical evaluation of Pareto efficient multi-objective regression test case prioritisation

Epitropakis, Michael G. and Yoo, Shin and Harman, Mark and Burke, Edmund K. (2015) Empirical evaluation of Pareto efficient multi-objective regression test case prioritisation. In: ISSTA 2015 Proceedings of the 2015 International Symposium on Software Testing and Analysis. ACM, USA, pp. 234-245. ISBN 9781450336208

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Abstract

The aim of test case prioritisation is to determine an ordering of test cases that maximises the likelihood of early fault revelation. Previous prioritisation techniques have tended to be single objective, for which the additional greedy algorithm is the current state-of-the-art. Unlike test suite minimisation, multi objective test case prioritisation has not been thoroughly evaluated. This paper presents an extensive empirical study of the effectiveness of multi objective test case prioritisation, evaluating it on multiple versions of five widely-used benchmark programs and a much larger real world system of over 1 million lines of code. The paper also presents a lossless coverage compaction algorithm that dramatically scales the performance of all algorithms studied by between 2 and 4 orders of magnitude, making prioritisation practical for even very demanding problems. Copyright is held by the owner/author(s).

Item Type:
Contribution in Book/Report/Proceedings
Additional Information:
© Authors, 2015. 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 2015 Proceedings of the 2015 International Symposium on Software Testing and Analysis http://dx.doi.org/10.1145/2771783.2771788
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/1700/1712
Subjects:
?? ADDITIONAL GREEDY ALGORITHMCOVERAGE COMPACTIONMULTI-OBJECTIVE EVOLUTIONARY ALGORITHMTEST CASE PRIORITIZATIONSOFTWARE ??
ID Code:
85018
Deposited By:
Deposited On:
02 Mar 2017 16:16
Refereed?:
Yes
Published?:
Published
Last Modified:
16 Sep 2023 03:10