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A Topic Model and Test History-Based Test Case Recommendation Method for Regression Testing

机译:基于主题模型和基于测试的回归测试的测试用例推荐方法

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In the regression testing, an oversight of a regression is a serious problem to be avoided. A test engineer usually selects test cases to rerun for a regression testing. While the selection is a useful expert decision, there is also a risk of missing some important test cases. To support a more effective regression testing, this paper focuses on the following two kinds of data: 1) the similarity of test cases in terms of their topics, and 2) the test history. Then, the paper proposes a hybrid method for recommending test cases in two steps by using the above data. As the thirst step, it recommends test cases which are highly-similar to the manually-selected ones. Then, as the second step, the method recommends the remaining test cases in decreasing order of priority computed by using the test history. The usefulness of the proposed method is proved through an empirical study using a set of regression test data for an industrial product.
机译:在回归测试中,回归的监督是要避免的严重问题。测试工程师通常选择RERUN进行回归测试的测试用例。虽然选择是一个有用的专家决策,但也存在缺少一些重要的测试用例的风险。为了支持更有效的回归测试,本文侧重于以下两种数据:1)测试用例的相似性在其主题方面,以及2)测试历史。然后,本文通过使用上述数据提出了一种用于在两个步骤中推荐测试用例的混合方法。作为渴望步骤,它推荐测试案例,这些情况与手动所选的案例相似。然后,作为第二步,该方法推荐剩余的测试用例在通过使用测试历史记录计算的优先级顺序。通过使用工业产品的一组回归测试数据,通过实证研究证明了所提出的方法的有用性。

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