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Generation of automatic test cases with mutation analysis and hybrid genetic algorithm

机译:利用变异分析和混合遗传算法生成自动测试用例

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Software testing is one of the most important and expensive (in term of time and cost) phase of software development life cycle. Over the past few decades a lot of research has been done on automatic software testing process but due to dynamic memory allocation, software is very much unpredictable in behavior. Different Meta heuristic algorithms are applied for improving the efficiency of software testing process. Mutation testing is a one kind of the software testing in which some mutants are injected intently in the program/software and tester finds these mutants during testing process [4]. In this paper a Hybrid Genetic Algorithm is proposed for generating test data automatically using data flow testing approach for mutation testing.
机译:软件测试是软件开发生命周期中最重要且最昂贵(在时间和成本方面)的阶段之一。在过去的几十年中,已经对自动软件测试过程进行了大量研究,但是由于动态内存分配,软件的行为非常难以预测。应用不同的元启发式算法来提高软件测试过程的效率。突变测试是一种软件测试,其中有意将一些突变体注入程序/软件中,测试人员在测试过程中发现了这些突变体[4]。本文提出了一种混合遗传算法,可以使用数据流测试方法自动生成测试数据,以进行突变测试。

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