Feature-oriented Test Case Selection and Prioritization During the Evolution of Highly-Configurable Systems

TL;DR

This paper introduces FeaTestSelPrio, a feature-oriented approach for selecting and prioritizing test cases in highly-configurable systems during evolution, improving failure detection and reducing testing costs.

Contribution

It proposes a novel feature-based method linking test cases to feature implementations, enhancing test selection and prioritization over existing variability model-based approaches.

Findings

Better failure detection than baseline methods

Reduces testing time by approximately 50%

Significantly decreases test budget in failed commits

Abstract

Testing Highly Configurable Systems (HCSs) is a challenging task, especially in an evolution scenario where features are added, changed, or removed, which hampers test case selection and prioritization. Existing work is usually based on the variability model, which is not always available or updated. Yet, the few existing approaches rely on links between test cases and changed files (or lines of code), not considering how features are implemented, usually spread over several and unchanged files. To overcome these limitations, we introduce FeaTestSelPrio, a feature-oriented test case selection and prioritization approach for HCSs. The approach links test cases to feature implementations, using HCS pre-processor directives, to select test cases based on features affected by changes in each commit. After, the test cases are prioritized according to the number of features they cover. Our approach selects a greater number of tests and takes longer to execute than a changed-file-oriented approach, used as baseline, but FeaTestSelPrio performs better regarding detected failures. By adding the approach execution time to the execution time of the selected test cases, we reached a reduction of $\approx$50%, in comparison with retest-all. The prioritization step allows reducing the average test budget in 86% of the failed commits.