Software Engineering is inherently knowledge intensive. Software processes and products are human centered. The technology of Computational Intelligence (CI) intensively exploits various mechanisms of interaction with humans and processes domain knowledge with intent of building intelligent systems. As commonly perceived, CI dwells on three highly synergistic technologies of neural networks, fuzzy sets (or granular computing, in general) and evolutionary optimization. As the software complexity grows and the diversity of software systems skyrocket, it becomes apparent that there is a genuine need for a solid, efficient, designer-oriented vehicle to support software analysis, design, and implementation at various levels. The research agenda makes CI a highly compatible and appealing vehicle to address the needs of knowledge rich environment of Software Engineering. The objective of this study is to identify and discuss synergistic links emerging between Software Engineering and Computational Intelligence. We show how CI --- based models contribute to the methodology of constructing models of software processes and products. Several selected examples (including software cost estimation, quality, and software measures) are included.
Yingxu Wang, Witold Kinsner, James A. Anderson, Du Zhang, Yiyu Yao, Phillip C.‐Y. Sheu, Jeffrey J. P. Tsai, Witold Pedrycz, Jean‐Claude Latombe, Lotfi A. Zadeh, Dilip Patel, Christine W. Chan
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