A Tag-based Recommender System for Regression Test Case Prioritization

Abstract

In continuous integration development environments (CI), the software undergoes frequent changes due to bug fixes or new feature requests. Some of these changes may accidentally cause regression issues to the newly released software version. To ensure the correctness of the newly released software, it is important to perform enough testing prior to code submission to avoid breaking builds. Regression testing is one of the important maintenance activities that can control the quality and reliability of modified software, but it can also be very expensive. Test case prioritization can reduce the costs of regression testing by reordering test cases to meet testing objectives better. To date, various test prioritization techniques have been developed, however, the majority of the proposed approaches utilize static or dynamic analyses to decide which test cases should be selected. These analyses often have significant cost overhead and are time consuming. This paper introduces a new method for automatic test case prioritization in a CI environment intending to minimize the testing cost. Our proposed approach uses information retrieval to automatically select test cases based on their textual similarity to the portion of the code that has been changed. Our technique not only helps developers to organize and manage the software repository but also helps them to find the relevant resources quickly. To evaluate our approach, we performed an empirical study using 37 versions of 6 open source applications. The results of our empirical study indicate that our proposed method can improve the effectiveness and efficiency of test case prioritization technique.