Using regression testing to analyze the impact of changes to variability models on products

Abstract

Industrial product lines are typically maintained for a long time and evolve continuously to address changing requirements and new technologies. Already derived products often have to be re-derived after such changes to benefit from new and updated features. Product line engineers thus frequently need to analyze the impact of changes to variability models to prevent unexpected changes of re-derived products. In this paper we present a tool-supported approach that informs engineers about the impacts of variability model changes on existing products. Regression tests are used to determine whether existing product configurations and generated product outputs can be re-derived without unexpected effects. We evaluate the feasibility of the approach based on changes observed in a real-world software product line. More specifically, we show how our approach helps engineers performing specific evolution tasks to analyze the change impacts on existing products. We also evaluate the performance and scalability of our approach. Our results show that variability change impact analyses can be automated using model regression testing and can help reducing the gap between domain engineering and application engineering.