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Social Network Analysis in Software Testing to Categorize Unit Test Cases Based on Coverage Information

机译:基于覆盖率信息的软件测试中的社交网络分析,以对单元测试用例进行分类

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Software testing is the most visible and cost-consuming activity in assuring the quality of software systems. In today's large-scale software systems, test (suite) maintenance is an inseparable part of software maintenance. Clarity of the purpose of each test case in the suite can be improved by proper naming and appropriate packaging, which decreases the cost of test maintenance. As a software system evolves its test suites need to be updated (maintained) to verify new or modified functionality of the software, and thus test cases may need to be categorized in a different way. In this work, we are proposing a technique to categorize the test cases automatically based on their coverage information. The proposed process can be performed dynamically over the life cycle of the system to improve the quality of test packaging. We build a social network of test cases and use coverage information to define links between them. This network is used to identify higher groups of test cases such as test package. To the best of our knowledge, this is the first trial in this direction. To evaluate our technique, we applied it on three open source systems with available JUnit test suits to identify test packages. We measured the quality of the discovered packages in terms of cohesion and coupling and compared them with the original packaging from test developers of these projects. The result sh.ows that our technique can be used to categorize test cases automatically by even improving the quality of the packages
机译:在确保软件系统质量方面,软件测试是最可见,最消耗成本的活动。在当今的大型软件系统中,测试(套件)维护是软件维护不可分割的一部分。通过适当的命名和适当的包装,可以提高套件中每个测试用例的用途的清晰度,从而降低测试维护的成本。随着软件系统的发展,需要更新(维护)其测试套件以验证软件的新功能或修改后的功能,因此可能需要以不同的方式对测试用例进行分类。在这项工作中,我们提出了一种根据测试用例的覆盖范围信息自动对其进行分类的技术。可以在系统的整个生命周期中动态执行建议的过程,以提高测试包装的质量。我们建立了一个测试用例的社交网络,并使用覆盖率信息来定义它们之间的链接。该网络用于识别更高级别的测试用例,例如测试包。据我们所知,这是朝这个方向进行的第一次试验。为了评估我们的技术,我们将其应用于具有可用JUnit测试套件的三个开源系统上,以识别测试包。我们从内聚力和耦合度方面衡量了发现的程序包的质量,并将其与这些项目的测试开发人员提供的原始程序包进行了比较。结果表明,我们的技术甚至可以提高软件包的质量,从而可以用于对测试用例进行自动分类

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