Software testing and retesting occurs continuously during the software development lifecycle to detect errors as early as possible and to ensure that changes to existing software do not break the software. Test suites once developed are reused and updated frequently as the software evolves. As a result, some test cases in the test suite may become redundant as the software is modified over time since the requirements covered by them are also covered by other test cases. Due to the resource and time constraints for re-executing large test suites, it is important to develop techniques to minimize available test suites by removing redundant test cases. In general, the test suite minimization problem is NP complete. In this paper, we present a new greedy heuristic algorithm for selecting a minimal subset of a test suite T that covers all the requirements covered by T. We show how our algorithm was inspired by the concept analysis framework. We conducted experiments to measure the extentof test suite reduction obtained by our algorithm and prior heuristics for test suite minimization. In our experiments, our algorithm always selected same size or smaller size test suite than that selected by prior heuristics and had comparable time performance.
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机译：在软件开发生命周期期间，在软件开发生命周期中持续发生软件测试和重新静验，以便尽早检测错误，并确保对现有软件的更改不会破坏软件。在软件演变时，开发后的测试套件经常重复使用并更新。因此，在测试套件中的某些测试用例可能变得冗余，因为随着时间的推移被修改，因为它们所涵盖的要求也被其他测试用例覆盖。由于重新执行大型测试套件的资源和时间约束，开发技术以通过去除冗余测试用例来最小化可用测试套件的技术。通常，测试套件最小化问题是NP完成。在本文中，我们提出了一种新的贪婪启发式算法，用于选择测试套件的最小子集 t ，其涵盖 t所涵盖的所有要求。我们展示了我们的算法是如何灵感来自概念分析框架。我们进行了实验，以测量我们的算法和现有启发式测试套件的测试套件减少，以进行测试套件最小化。在我们的实验中，我们的算法总是选择相同的尺寸或更小的测试套件，而不是通过现有启发式选定的测试套件，并且具有可比的时间性能。
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