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Comparison of Unit-Level Automated Test Generation Tools

机译:单元级自动测试生成工具的比较

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Data from projects worldwide show that many software projects fail and most are completed late or over budget. Unit testing is a simple but effective technique to improve software in terms of quality, flexibility, and time-to-market. A key idea of unit testing is that each piece of code needs its own tests and the best person to design those tests is the developer who wrote the software. However, generating tests for each unit by hand is very expensive, possibly prohibitively so. Automatic test data generation is essential to support unit testing and as unit testing is achieving more attention, developers have a greater need for automated unit test data generation tools. However, developers have very little information about which tools are effective. This experiment compared three well-known public-accessible unit test data generation tools, JCrasher, TestGen4j, and JUB. We applied them to Java classes and evaluated them based on their mutation scores. As a comparison, we created two additional sets of tests for each class. One test set contained random values and the other contained values to satisfy edge coverage. Results showed that the automatic test data generation tools generated tests with almost the same mutation scores as the random tests.
机译:来自全球项目的数据表明,许多软件项目失败,并且大多数项目延迟完成或超出预算。单元测试是一种简单但有效的技术,可以从质量,灵活性和上市时间方面改进软件。单元测试的关键思想是每段代码都需要自己的测试,而设计这些测试的最佳人选是编写软件的开发人员。但是,手动为每个单元生成测试非常昂贵,可能过于昂贵。自动测试数据生成对于支持单元测试至关重要,并且随着单元测试越来越受到关注,开发人员对自动单元测试数据生成工具的需求也越来越大。但是,开发人员几乎没有关于哪些工具有效的信息。该实验比较了三个著名的公共可访问单元测试数据生成工具JCrasher,TestGen4j和JUB。我们将它们应用于Java类,并根据其变异分数对其进行了评估。作为比较,我们为每个类另外创建了两组测试。一个测试集包含随机值,另一个包含满足边缘覆盖率的值。结果表明,自动测试数据生成工具所生成的测试的突变得分与随机测试几乎相同。

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