基于I-MOEA/D的多目标测试用例优先级排序
Multi-objective test case prioritization based on I-MOEA/D
袁光辉 1许华1
作者信息
- 1. 安徽大学江淮学院 理工部,安徽 合肥 230031;合肥理工学院,安徽 合肥 230031
- 折叠
摘要
多目标测试用例优先级排序(MOTCP)是回归测试领域中的热门问题,其目的是获得测试用例的执行顺序,最大限度地提高发现缺陷的能力和效率.文章提出一种基于改进MOEA/D算法的多目标测试用例优先级排序方法(I-MOEA/D):首先将多目标测试用例优先级排序问题建模为一个多目标优化问题,然后通过改进MOEA/D算法来解决该优化问题.具体而言:通过引入权重向量自适应策略,以保持子问题之间的多样性;通过位置交叉法对交叉算子进行改进,以加快算法的收敛速度,抵消权重向量计算时间开销;对邻域动态更新,以促进测试用例之间的信息交流和共享.实验结果表明:所提算法在MOTCP方面取得了较好的效果,与其他方法相比,该方法能提高测试用例的发现缺陷能力和效率.
Abstract
Multi objective test case prioritization(MOTCP)is a popular issue in the field of regression testing,the purpose of which is to obtain the order in which test cases are executed to maximize the ability and efficiency to find defects.In this paper,a multi-objective test case prioritization method(I-MOEA/D)based on the improved MOEA/D algo-rithm is proposed.The multi-objective test case prioritization problem is modeled as a multi-objective optimization prob-lem,and then the optimization problem is solved by improving the MOEA/D algorithm.Specifically,on the one hand,the weight vector adaptive strategy is introduced to maintain the diversity among subproblems.On the other hand,the cross-over operator is improved by the positional crossover method to accelerate the convergence speed of the algorithm and off-set the time overhead of weight vector calculation.Furthermore,information exchange and sharing are facilitated between test cases by dynamically updating the neighborhood.Experimental results show that the proposed algorithm has achieved good results in MOTCP.Compared with other methods,this method can improve the defect detection ability and efficien-cy of test cases.
关键词
多目标/测试用例优先级排序/MOEA/D/权重向量自适应Key words
multi-objective/test case prioritization/MOEA/D/weight vector adaptive引用本文复制引用
基金项目
安徽省高等学校自然科学研究重点项目(KJ2021A1217)
出版年
2024
NETL
NSTL
万方数据