Vol.73, No.2, 2022, pp.4407-4422, doi:10.32604/cmc.2022.029096
Maintain Optimal Configurations for Large Configurable Systems Using Multi-Objective Optimization
  • Muhammad Abid Jamil1,*, Deafallah Alsadie1, Mohamed K. Nour1, Normi Sham Awang Abu Bakar2
1 Department of Computer Science, Umm Al-Qura University, Makkah, Saudi Arabia
2 Kulliyyah of Information and Communication Technology, International Islamic University, Malaysia
* Corresponding Author: Muhammad Abid Jamil. Email:
Received 25 February 2022; Accepted 06 May 2022; Issue published 16 June 2022
To improve the maintenance and quality of software product lines, efficient configurations techniques have been proposed. Nevertheless, due to the complexity of derived and configured products in a product line, the configuration process of the software product line (SPL) becomes time-consuming and costly. Each product line consists of a various number of feature models that need to be tested. The different approaches have been presented by Search-based software engineering (SBSE) to resolve the software engineering issues into computational solutions using some metaheuristic approach. Hence, multiobjective evolutionary algorithms help to optimize the configuration process of SPL. In this paper, different multi-objective Evolutionary Algorithms like Non-Dominated Sorting Genetic algorithms II (NSGA-II) and NSGA-III and Indicator based Evolutionary Algorithm (IBEA) are applied to different feature models to generate optimal results for large configurable. The proposed approach is also used to generate the optimized test suites with the help of different multi-objective Evolutionary Algorithms (MOEAs).
Software product line; search-based software engineering; metaheuristic; multiobjective evolutionary algorithms; feature model
Cite This Article
M. Abid Jamil, D. Alsadie, M. K. Nour and N. Sham Awang Abu Bakar, "Maintain optimal configurations for large configurable systems using multi-objective optimization," Computers, Materials & Continua, vol. 73, no.2, pp. 4407–4422, 2022.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.