在单元测试用例中自动识别测试中的焦点方法

Mohammad Ghafari, C. Ghezzi, K. Rubinov
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引用次数: 32

摘要

现代迭代和增量软件开发依赖于持续的测试。测试到代码的可追溯性链接的知识促进了测试驱动的开发,并改进了软件的发展。先前的研究确定了测试用例和被测试类之间的可追溯性链接。虽然这些信息很有帮助,但是更细粒度的技术可以提供更多有用的信息,而不仅仅是被测类的知识。在本文中,我们将重点放在实例化有状态对象的Java类上,并提出一种自动化技术,用于在单元测试用例中精确检测被测试的重点方法。焦点方法表示单元测试用例中测试场景的核心。它们的主要目的是影响对象的状态,然后由其他检查器方法检查,这些检查器方法的目的是辅助的,需要被识别出来。将焦点与其他(非焦点)方法区分开来很难手动完成。提出了一种自动检测被测焦点方法的方法。对真实世界软件的实验评估表明,我们的方法在超过85%的情况下识别了测试中的焦点方法,为测试到代码的可追溯性链接的精确自动恢复提供了基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automatically identifying focal methods under test in unit test cases
Modern iterative and incremental software development relies on continuous testing. The knowledge of test-to-code traceability links facilitates test-driven development and improves software evolution. Previous research identified traceability links between test cases and classes under test. Though this information is helpful, a finer granularity technique can provide more useful information beyond the knowledge of the class under test. In this paper, we focus on Java classes that instantiate stateful objects and propose an automated technique for precise detection of the focal methods under test in unit test cases. Focal methods represent the core of a test scenario inside a unit test case. Their main purpose is to affect an object's state that is then checked by other inspector methods whose purpose is ancillary and needs to be identified as such. Distinguishing focal from other (non-focal) methods is hard to accomplish manually. We propose an approach to detect focal methods under test automatically. An experimental assessment with real-world software shows that our approach identifies focal methods under test in more than 85% of cases, providing a ground for precise automatic recovery of test-to-code traceability links.
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