Test Suite Reduction via Evolutionary Clustering
Test suite reduction is an effective way to reduce the cost of regression testing by identifying and removing redundant test cases from the original test suite. In this paper, we propose a novel cluster test suite reduction using an evolutionary multi-objective optimization algorithm. Specifically,...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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IEEE
2021-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9350625/ |
| _version_ | 1818734492464971776 |
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| author | Chunyan Xia Yan Zhang Zhanwei Hui |
| author_facet | Chunyan Xia Yan Zhang Zhanwei Hui |
| author_sort | Chunyan Xia |
| collection | DOAJ |
| description | Test suite reduction is an effective way to reduce the cost of regression testing by identifying and removing redundant test cases from the original test suite. In this paper, we propose a novel cluster test suite reduction using an evolutionary multi-objective optimization algorithm. Specifically, we use a K-means algorithm to group similar test cases to the same cluster. Then the evolutionary algorithm is used to remove redundant test cases based on the clustering results, and optimization objects are represented as the coverage-related criteria, fault-related criteria and cost-related criteria. The experimental results involving eight subject programs show that the proposed method can outperform the other three state-of-the-arts with respect to both fault detection (4.61% -9.44%) and reduction ratio (4.10% -10.64%). Meanwhile, the experiments also prove that our method has a better performance of missing failure rate (0.049% -0.132%) and code coverage rate (3.34% -6.10%). Besides, the proposed method costs are found to be comparable to the other techniques. |
| first_indexed | 2024-12-18T00:06:11Z |
| format | Article |
| id | doaj.art-4c4348b977924c3ca3f2509f08bfb6e3 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-18T00:06:11Z |
| publishDate | 2021-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-4c4348b977924c3ca3f2509f08bfb6e32022-12-21T21:27:48ZengIEEEIEEE Access2169-35362021-01-019281112812110.1109/ACCESS.2021.30583019350625Test Suite Reduction via Evolutionary ClusteringChunyan Xia0https://orcid.org/0000-0003-4515-7573Yan Zhang1https://orcid.org/0000-0002-5594-4792Zhanwei Hui2https://orcid.org/0000-0003-2709-6834School of Computer and Information Technology, Mudanjiang Normal University, Mudanjiang, ChinaSchool of Computer and Information Technology, Mudanjiang Normal University, Mudanjiang, ChinaInstitute of Evaluation and Assessment Research, Academy of Military Science, Beijing, ChinaTest suite reduction is an effective way to reduce the cost of regression testing by identifying and removing redundant test cases from the original test suite. In this paper, we propose a novel cluster test suite reduction using an evolutionary multi-objective optimization algorithm. Specifically, we use a K-means algorithm to group similar test cases to the same cluster. Then the evolutionary algorithm is used to remove redundant test cases based on the clustering results, and optimization objects are represented as the coverage-related criteria, fault-related criteria and cost-related criteria. The experimental results involving eight subject programs show that the proposed method can outperform the other three state-of-the-arts with respect to both fault detection (4.61% -9.44%) and reduction ratio (4.10% -10.64%). Meanwhile, the experiments also prove that our method has a better performance of missing failure rate (0.049% -0.132%) and code coverage rate (3.34% -6.10%). Besides, the proposed method costs are found to be comparable to the other techniques.https://ieeexplore.ieee.org/document/9350625/Regression testingcluster analysisgenetic algorithmtest suite reduction |
| spellingShingle | Chunyan Xia Yan Zhang Zhanwei Hui Test Suite Reduction via Evolutionary Clustering IEEE Access Regression testing cluster analysis genetic algorithm test suite reduction |
| title | Test Suite Reduction via Evolutionary Clustering |
| title_full | Test Suite Reduction via Evolutionary Clustering |
| title_fullStr | Test Suite Reduction via Evolutionary Clustering |
| title_full_unstemmed | Test Suite Reduction via Evolutionary Clustering |
| title_short | Test Suite Reduction via Evolutionary Clustering |
| title_sort | test suite reduction via evolutionary clustering |
| topic | Regression testing cluster analysis genetic algorithm test suite reduction |
| url | https://ieeexplore.ieee.org/document/9350625/ |
| work_keys_str_mv | AT chunyanxia testsuitereductionviaevolutionaryclustering AT yanzhang testsuitereductionviaevolutionaryclustering AT zhanweihui testsuitereductionviaevolutionaryclustering |