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Multiobjective Evolutionary Algorithms NSGA-II and NSGA-III for Software Product Lines Testing Optimization
- Source :
- 2019 IEEE 6th International Conference on Engineering Technologies and Applied Sciences (ICETAS).
- Publication Year :
- 2019
- Publisher :
- IEEE, 2019.
-
Abstract
- 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.
Details
- Database :
- OpenAIRE
- Journal :
- 2019 IEEE 6th International Conference on Engineering Technologies and Applied Sciences (ICETAS)
- Accession number :
- edsair.doi...........f0c360fa6ed90b4ff10100a413f585a9
- Full Text :
- https://doi.org/10.1109/icetas48360.2019.9117500