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

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.