Mutlu BeyazitTugkan TuglularDilek Ozturk KayaBeyazit, MutluTuglular, TugkanKaya, Dilek Ozturk2025-10-0620232169-353610.1109/ACCESS.2023.32341862-s2.0-85147230304http://dx.doi.org/10.1109/ACCESS.2023.3234186https://gcris.yasar.edu.tr/handle/123456789/7025https://doi.org/10.1109/ACCESS.2023.3234186One way of developing fast effective and high-quality software products is to reuse previously developed software components and products. In the case of a product family the software product line (SPL) approach can make reuse more effective. The goal of SPLs is faster development of low-cost and high-quality software products. This paper proposes an incremental model-based approach to test products in SPLs. The proposed approach utilizes event-based behavioral models of the SPL features. It reuses existing event-based feature models and event-based product models along with their test cases to generate test cases for each new product developed by adding a new feature to an existing product. Newly introduced featured event sequence graphs (FESGs) are used for behavioral feature and product modeling, thus generated test cases are event sequences. The paper presents evaluations with three software product lines to validate the approach and analyze its characteristics by comparing it to the state-of-the-art ESG-based testing approach. Results show that the proposed incremental testing approach highly reuses the existing test sets as intended. Also it is superior to the state-of-the-art approach in terms of fault detection effectiveness and test generation effort but inferior in terms of test set size and test execution effort.Englishinfo:eu-repo/semantics/openAccessTest pattern generators, Software product lines, Software testing, Behavioral sciences, Computational modeling, Time complexity, Incremental testing, model-based testing, software product lineTEST-GENERATION, MODEL, TOOLSoftware Product LinesSoftware Product LineSoftware TestingBehavioral SciencesIncremental TestingModel-Based TestingTest Pattern GeneratorsTime ComplexityComputational ModelingArticle