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Fault coverage-based test suite optimization method for regression testing: learning from mistakes-based approach

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Abstract

This paper presents a novel method referred as fault coverage-based test suite optimization (FCBTSO) for regression test suite optimization. FCBTSO is proposed based on Harrolds–Gupta–Soffa (HGS) test suite reduction method, and it follows the phenomenon: “learning from mistakes”. We conducted computational experiments on 12 versions of benchmarked programs retrieved from software artefact infrastructure repository and dummy fault matrix test. The performance of the proposed FCBTSO is measured against the traditional test suite reduction methods (Greedy method, Additional Greedy, HGS, and Enhanced HGS) by following the performance measures: fault coverage, execution time and reduced optimized test suite size. Rigorous statistical tests are conducted to determine the performance significance, which indicates that FCBTSO outperforms other approaches implemented with respect to the execution time that includes the execution time of the proposed approach to find the optimized test suite and the execution time of test cases in the optimized test suite.

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Agrawal, A. P., Choudhary, A., Kaur, A., & Pandey, H. M. (2020). Fault coverage-based test suite optimization method for regression testing: learning from mistakes-based approach. Neural Computing and Applications, 32(12), 7769–7784. https://doi.org/10.1007/s00521-019-04098-9

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