This paper proposes an evolutionary algorithm based approach for evolving architecture alternatives using quality attributes as design drivers. A novel fuzzy architecture assessment approach is presented to quantitatively evaluate the set of possible solutions based on linguistic assessments of architecture quality attributes elicited from the stakeholders. The proposed approach makes a valuable contribution to the systems architecting knowledge base by presenting a measurable and quantifiable approach to architecture design and evaluation.
A. Singh and C. H. Dagli, "Using Quality Attributes and Computational Intelligence to Generate and Evaluate System Architecture Alternatives," Proceedings of the 2010 4th Annual IEEE Systems Conference, Institute of Electrical and Electronics Engineers (IEEE), Apr 2010.
The definitive version is available at https://doi.org/10.1109/SYSTEMS.2010.5482332
2010 4th Annual IEEE Systems Conference
Engineering Management and Systems Engineering
Keywords and Phrases
Fuzzy Set Theory; Artificial intelligence; Evolutionary computation; Software architecture
Article - Conference proceedings
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