Titlebook: Software Engineering with Computational Intelligence; Jonathan Lee Book 2003 Springer-Verlag Berlin Heidelberg 2003 Computational Intellig

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Fuzzy Concepts and Formal Methods,ed as a ‘process of discovery, refinement, modelling and specification’ [36] . System modelling is a useful tool in this process. We can create models to express our understanding of a current system problem, to identify areas for change or to describe the final product to be built. They permit the

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Trade-off Requirement Engineering,onflicting with each other [25,37,48]. Balzer et al. have argued that informality is an inevitable (and ultimately desirable) feature of the specification process [2]. Similar ideas are also advocated by other researchers such as Borgida [5], Feather [16]‚ Fickas [12], Waters [36], Niskier [33] and

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A Generalized Object-Oriented Data Model Based on Level-2 Fuzzy Sets,rely available in a fuzzy and/or uncertain form. Therefore, information modeling and handling in classical software applications is subject to a loss of semantics. This problem is especially recognized in the database and knowledge base research communities and is seen as a challenge for the near fu

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Domain Analysis for the Engineering of Spatiotemporal Software, “hard” engineering disciplines. Well-defined blocks of smaller solutions that can be used in the synthesis of any system have been the key behind fast and reliable design. For any engineering field there are widely recognized sets of building blocks that facilitate development. The alternative is t

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Fuzzy Evaluation of Domain Knowledge,ically initiated by the client’s requirement specification and the solution is defined as a software program. Providing a solution for a given problem is not trivial and involves the accumulation and utilization of a huge amount of knowledge. This process of identifying the solution domain knowledge

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