Evolutionary selection for regression test cases based on diversity

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.

Automated summary

This research proposes a method to improve fault detection rate by selecting test cases using genetic algorithm to achieve both path coverage and coverage balance. Experimental results demonstrate that this method can efficiently select test cases that meet testing requirements.