Multiobjective evolutionary algorithms NSGA-II and NSGA-III for software product lines testing optimization

• Main Authors: Jamil, Muhammad Abid, Alhindi, Ahmad, Arif, Muhammad, Nour, Mohamed K, Awang Abu Bakar, Normi Sham, Aljabri, Tareq Fahad
• Format: Conference or Workshop Item
• Language: English
• Published: Institute of Electrical and Electronics Engineers Inc. 2020
• Subjects: QA76 Computer software; T Technology (General)
• Online Access: http://irep.iium.edu.my/86601/1/86601_Multiobjective%20evolutionary.pdf; http://irep.iium.edu.my/86601/; https://ieeexplore.ieee.org/document/9117500

Software Product line (SPL) engineering methodology utilizes reusable components to generate a new system for a specific domain. In fact, the product line establishes requirements, reusable components, architecture, and shared products to develop new products’ functionalities. In order to maintain high quality, there is a need for a thorough testing process. Each product in SPL having a different number of features need to be tested. Hence, the testing process of SPL can utilize a multi-objective optimization algorithm to optimize the testing process. This research, reports on the performance of a multi-objective Evolutionary Algorithms Non-Dominated Sorting Genetic Algorithm II (NSGA-II) and NSGA-III on Feature Models (FMs) to optimize SPL testing.