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Comparison study of optimized test suite generation using Genetic and Memetic algorithm

机译:遗传算法优化试验套件的比较研究

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Testing is one of the important phase of software engineering field, which checks the correctness of software. A common part in software testing is that test data are generated. For this test data, tester manually adds different test cases. But adding test cases manually is very difficult task. So we generate set of test cases called as test suite. Test case is nothing but a condition which we want to check. Code coverage is important factor in test suite. While generating a test suite, consider a inheritance tree a of class and generate test cases by considering all branches of that tree. Test case may have more than one goal, check feasibility for this particular goal. For generating optimized test suite, apply Genetic and Memetic algorithm. The aim of this test suite generation is covering all branches for maximum code coverage while keeping the minimum size. Applying both algorithms for code coverage. Code coverage of Memetic algorithm is maximum than code coverage of Genetic algorithm. We have implemented this system and for checking result use open source project such as Roops and net.
机译:测试是软件工程领域的重要阶段之一,可以检查软件的正确性。软件测试中的一个共同部分是生成测试数据。对于此测试数据,测试仪手动添加了不同的测试用例。但是手动添加测试用例是非常困难的任务。因此,我们生成一组称为测试套件的测试用例。测试案例只不过是我们想要检查的条件。代码覆盖是测试套件的重要因素。在生成测试套件时,请考虑类中的继承树,并通过考虑该树的所有分支来生成测试用例。测试案例可能有多个目标,检查这种特定目标的可行性。用于产生优化的测试套件,应用遗传和膜算法。该测试套件生成的目的正在覆盖所有分支机构,以获得最大代码覆盖率,同时保持最小尺寸。应用两个算法进行代码覆盖。 Memetic算法的代码覆盖率比遗传算法的代码覆盖率最大。我们已经实现了该系统,并检查结果使用罗波和网络等开源项目。

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