Bypassing the Combinatorial Explosion: Using Similarity to Generate and Prioritize T-Wise Test Configurations for Software Product Lines

摘要

Large Software Product Lines (SPLs) are common in industry, thus introducing the need of practical solutions to test them. To this end, $t$-wise can help to drastically reduce the number of product configurations to test. Current $t$-wise approaches for SPLs are restricted to small values of $t$. In addition, these techniques fail at providing means to finely control the configuration process. In view of this, means for automatically generating and prioritizing product configurations for large SPLs are required. This paper proposes (a) a search-based approach capable of generating product configurations for large SPLs, forming a scalable and flexible alternative to current techniques and (b) prioritization algorithms for any set of product configurations. Both these techniques employ a similarity heuristic. The ability of the proposed techniques is assessed in an empirical study through a comparison with state of the art tools. The comparison focuses on both the product configuration generation and the prioritization aspects. The results demonstrate that existing $t$-wise tools and prioritization techniques fail to handle large SPLs. On the contrary, the proposed techniques are both effective and scalable. Additionally, the experiments show that the similarity heuristic can be used as a viable alternative to $t$ -wise.