A Constrained Covering Array Generator using Adaptive Penalty based Parallel Tabu Search

Since Combinatorial Testing (CT) was first proposed in 1980s, there have been more than 50 algorithms or tools published for Covering Array Generation (CAG). This paper introduces the APPTS tool, which uses an Adaptive Penalty based Parallel Tabu Search (APPTS) algorithm to generate as small-sized Constrained Covering Arrays (CCA) as possible. Instead of simply reusing constraint solvers or forbidden tuple-based techniques to handle constraints, APPTS incorporates a penalty term into the fitness function to handle the constrained search space, and employs an adaptive penalty mechanism to dynamically adjust the penalty weight in different search phases. Our experiments on benchmarks of CT-competition demonstrate the effectiveness of the APPTS tool in covering array sizes. The APPTS tool executable is available at https://github.com/GIST-NJU/apptstool.