Using Quality Attributes and Computational Intelligence to Generate and Evaluate System Architecture Alternatives
This document has been relocated to http://scholarsmine.mst.edu/engman_syseng_facwork/231
There were 22 downloads as of 27 Jun 2016.
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.