摘要
基于智能优化算法的测试用例生成是自动化测试领域的研究热点,在目前的群体智能优化算法中遗传算法应用最为广泛。从四个方面总结了遗传算法在用例数据生成中的应用:改进遗传算子、改善适应度函数、融合其他算法以及并行遗传算法。在此基础上,提出了遗传算法在用例生成应用中面临的三个关键问题,为其他智能优化算法的改进提供参考,并对基于遗传算法的测试用例生成问题的未来研究方向做出展望。
The generation of test cases based on intelligent optimization algorithms is a research hotspot in the field of automated testing,and genetic algorithms are the most widely used among the current crowd intelligent optimization algorithms.This article summarizes the application of genetic algorithms in the generation of use case data from four aspects:improved genetic operators,improved fitness functions,fusion of other algorithms,and parallel genetic algorithms.On this basis,three key issues that genetic algorithm faces in the application of use case generation are proposed,which provide reference for the improvement of other intelligent optimization algorithms,and prospect the future research direction of test case generation based on genetic algorithms.
作者
赫彦文
刘紫阳
李建义
彭新宇
He Yanwen;Liu Ziyang;Li Jianyi;Peng Xinyu(North China Institute of Aerospace Engineering,Langfang 065000,China;Aerospace Software Joint Innovation Center,North China Institute of Aerospace Engineering,Langfang 065000,China)
出处
《廊坊师范学院学报(自然科学版)》
2020年第4期16-20,共5页
Journal of Langfang Normal University(Natural Science Edition)
基金
北华航天工业学院硕士研究生创新资助项目(YKY-2020-01)。
关键词
软件测试
自动生成用例
遗传算法
遗传算子
适应度函数
software testing
automatic use case generation
genetic algorithm
genetic operator
fitness function