Rights statement: © 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
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Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
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TY - GEN
T1 - Empirical evaluation of Pareto efficient multi-objective regression test case prioritisation
AU - Epitropakis, Michael G.
AU - Yoo, Shin
AU - Harman, Mark
AU - Burke, Edmund K.
N1 - © 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
PY - 2015/7/13
Y1 - 2015/7/13
N2 - 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).
AB - 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).
KW - Additional greedy algorithm
KW - Coverage compaction
KW - Multi-objective evolutionary algorithm
KW - Test case prioritization
U2 - 10.1145/2771783.2771788
DO - 10.1145/2771783.2771788
M3 - Conference contribution/Paper
AN - SCOPUS:84975760228
SP - 234
EP - 245
BT - ISSTA 2015 Proceedings of the 2015 International Symposium on Software Testing and Analysis
PB - ACM
CY - New York
T2 - 24th International Symposium on Software Testing and Analysis, ISSTA 2015
Y2 - 13 July 2015 through 17 July 2015
ER -