Although 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.

中文翻译：

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基于多样性的回归测试用例的进化选择

尽管有许多与选择测试用例相关的研究，但很少有关于路径覆盖和覆盖平衡的信息。我们的方法是选择既要遍历目标路径又要达到覆盖范围平衡的测试用例，以提高故障检测率。我们通过应用遗传算法将问题表述为进化选择。实验结果表明，该方法可以有效地提高所选测试案例的故障检测率，同时又能保证故障率的降低。它可以高效地选择满足测试要求的测试用例的子集。