Evolutionary many-objective satisfiability solver for configuring software product lines
Author:
Funder
national natural science foundation of china
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence
Link
https://link.springer.com/content/pdf/10.1007/s10489-021-02918-x.pdf
Reference33 articles.
1. Guo J, Shi K (2018) To preserve or not to preserve invalid solutions in search-based software engineering: a case study in software product lines. In: Proceedings of the 40th international conference on software engineering, ICSE ’18, pp 1027–1038
2. Hierons RM, Li M, Liu X, Segura S, Zheng W (2016) SIP: Optimal product selection from feature models using many-objective evolutionary optimization. ACM Trans Softw Eng Methodol 25(2):39. Article 17. https://doi.org/10.1145/2897760
3. Guo J, Liang HJ, Shi K, Yang D, Zhang J, Czarnecki K, Ganesh V, Yu H (2017) SMTIBEA: A Hybrid Multi-Objective Optimization Algorithm for Confifiguring Large Constrained Software Product Lines. Software and System Modeling. https://doi.org/10.1007/s10270-017-0610-0
4. Shi K (2017) Combining evolutionary algorithms with constraint solving for confifiguration optimization. In: Proceedings of the IEEE international conference on software maintenance and evolution (ICSME), pp 665–669
5. Herbawi W, Weber M (2011) Comparison of multiobjective evolutionary algorithms for solving the multiobjective route planning in dynamic multi-hop ridesharing. Evolutionary Computation IEEE
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