Evolutionary selection for regression test cases based on diversity
发表时间：2021-07-08
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论文类型：
期刊论文
第一作者：
Ma, Baoying
通讯作者：
Wan, Li,姚念民,Fan, Shuping,Zhang, Yan
发表时间：
2021-03-05
发表刊物：
FRONTIERS OF COMPUTER SCIENCE
文献类型：
J
卷号：
15
期号：
2
ISSN号：
2095-2228
摘要：
ConclusionAlthough there are various studies related to selecting test cases, few are available for both path coverage and coverage balance. Our method is to select test cases that both traverse target paths and achieve coverage balance to improve the fault detection rate. We formulate the problem as an evolution selection by applying GA. Experimental results show that our method can effectively improve the fault detection rate of the selected test cases while ensuring the reduction rate. It can select a subset of test cases that meet testing requirements with high efficiency.
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