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为了提升软件测试的效率,加快软件研发的进度,提出了一种基于多种群进化的测试用例排序算法。该算法首先针对单种群遗传算法容易产生早熟收敛的问题,提出了一种多种群并行进化模型,以增强算法的全局寻优能力;然后根据该模型,结合软件需求覆盖和软件缺陷检测率,综合考虑代码覆盖率、测试用例设计信息和历史执行信息三个方面的因素,提出了一种动态调整测试用例优先级的计算方法。实验结果表明:与传统的面向单一目标覆盖的测试用例优先级排序算法相比,该算法的测试速率和软件缺陷检测能力得到一定的提升。
In order to improve the efficiency of software testing and speed up the progress of software development, a multi-population evolutionary test case sequencing algorithm is proposed. Firstly, aiming at the problem of premature convergence in single-population genetic algorithm, a multi-population parallel evolutionary model is proposed to enhance the global optimization ability of the algorithm. Then according to the model, combined with the software coverage and software defect detection rate, Considering the three factors of code coverage, test case design information and historical execution information, a method to dynamically adjust the priority of test cases is proposed. The experimental results show that compared with the traditional prioritization algorithm for single-target coverage, the testing speed and software defect detection ability of the algorithm are improved to a certain extent.