Abstract
By optimizing the execution order of test cases, test case prioritization techniques can effectively improve the efficiency of software testing. Test case prioritization is becoming a hot topic in software testing research. Combining genetic algorithm with test-points coverage, this paper obtains some meaningful research results in test case prioritization, especially for the functional testing. Firstly, presents two new test case prioritization evaluations APTC and its improvement APRC_C. As focused on test-points coverage, these evaluations are more suitable for black-box testing. Then, proposes a test case prioritization method based on genetic algorithm, whose representation, selection, crossover and mutation are designed for black-box testing. Finally, verifies the proposed method by experiments data. The experimental results show that the proposed method can achieve desired effect.
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Zhang, W., Wei, B., Du, H. (2014). Test Case Prioritization Based on Genetic Algorithm and Test-Points Coverage. In: Sun, Xh., et al. Algorithms and Architectures for Parallel Processing. ICA3PP 2014. Lecture Notes in Computer Science, vol 8630. Springer, Cham. https://doi.org/10.1007/978-3-319-11197-1_50
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DOI: https://doi.org/10.1007/978-3-319-11197-1_50
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