Multiobjective evolutionary algorithms NSGA-II and NSGA-III for software product lines testing optimization
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 h...
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| Main Authors: | , , , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
Institute of Electrical and Electronics Engineers Inc.
2020
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| Subjects: | |
| 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 |
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| Institution: | Universiti Islam Antarabangsa Malaysia |
| Language: | English |
| Summary: | 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. |
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