Automated code-based testing for efficient software product line regression testing

Abstract

Regression testing for software product lines (SPLs) is challenging and can be expensive because it must ensure that all the products of a product family are correct whenever changes are made. SPL regression testing can be made efficient through a test case selection method that selects only the test cases relevant to the changes. In the past, some approaches for SPL test case selection have been proposed. However, either they are not efficient by requiring intervention from human experts or they cannot be used if requirements specifications, architecture and/or traceabilities for test cases are not available or partially eroded. To overcome these limitations, we propose an automated method of source code-based regression test selection for SPLs. Our method reduces unnecessary repetition of the test selection procedure and minimizes the in-depth analysis effort for source code and test cases based on the commonality and variability of a product family. Evaluation results of our method using six product lines show that our method reduces the overall time to perform regression testing by 14.8% ~ 49.1% compared to an approach of repetitively applying the state-of-the-art RTS method for a single product to products of a product family.