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基于智能优化算法的测试数据生成综述
引用本文:薛 猛,姜淑娟,王荣存.基于智能优化算法的测试数据生成综述[J].计算机工程与应用,2018,54(17):16-23.
作者姓名:薛 猛  姜淑娟  王荣存
作者单位:中国矿业大学 计算机科学与技术学院 矿山数字化教育部工程研究中心,江苏 徐州 221116
摘    要:软件测试是一种极为有效的软件质量保证手段。测试数据生成是软件测试的关键。基于智能优化算法的测试数据生成方法为自动化的测试数据生成提供了解决问题的一个有效手段。首先重点总结归纳了在基于智能优化算法的测试数据生成中使用最为频繁的两种算法:遗传算法和粒子群优化算法的研究成果,分析了研究现状,接着简单介绍了基于智能优化算法的测试数据生成工具:AUSTIN和EvoSuite,最后对存在的问题及未来的研究内容进行了尝试性的探讨。

关 键 词:软件测试  测试数据生成  智能优化算法  遗传算法  粒子群优化  

Systematic review of test data generation based on intelligent optimization algorithm
XUE Meng,JIANG Shujuan,WANG Rongcun.Systematic review of test data generation based on intelligent optimization algorithm[J].Computer Engineering and Applications,2018,54(17):16-23.
Authors:XUE Meng  JIANG Shujuan  WANG Rongcun
Affiliation:Mine Digitization Engineering Research Center of the Ministry of Education, School of Computer Science and Technology, China University of Mining and Technology, Xuzhou, Jiangsu 221116, China
Abstract:Software testing is a very effective means of quality assurance and test data generation plays a key role in it. Test data generation based on intelligent optimization algorithm provides an effective solution to the problem of automated test data generation. And genetic algorithm and particle swarm optimization algorithm are the two most frequently used optimization algorithms in these methods based on intelligent optimization algorithm. Firstly, the current research results are summed up and the research status quo is analyzed in particular. Secondly, test data generation tools:AUSTIN and EvoSuite are introduced simply. Finally, the existing problems and future researches are discussed tentatively.
Keywords:software testing  test data generation  intelligent optimization algorithm  Genetic Algorithm(GA)  Particle Swarm Optimization(PSO)  
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