Cost-effective test case generation with the hyper-heuristic for software product line testing

• Main Authors: Sulaiman, Rabatul Aduni, Jawawi, Dayang N. A., Abdul Halim, Shahliza
• Format: Article
• Published: Elsevier Ltd 2023
• Subjects: QA76 Computer software
• Online Access: http://eprints.utm.my/104881/; http://dx.doi.org/10.1016/j.advengsoft.2022.103335

Implementation of optimization algorithm for test case generation in Model-Based Testing (MBT) for Software Product Line (SPL) has been increasing, due to the demand for optimal test case results with a balanced trade-off between cost and effectiveness measure. This paper proposed a hyper-heuristic test cases generation approach in MBT for SPL called Improvement Selection Rules-Modified Choice Function (ISR-MCF). ISR-MCF is implemented with three search operators which are Non-Dominated Sorting Genetic Algorithm II with low-level heuristic (NSGA-II-LLH), Strength Pareto Evolutionary with Low-Level Heuristic (SPEA 2-LLH) and Particle Swarm Optimization with Low-Level Heuristic (PSO-LLH). The approach was evaluated with a test model and the result shows that the proposed ISR-MCF with NSGA-II-LLH outperforms other existing rules for minimization measure (size of a test suite and execution time and maximization measure (coverage criteria).