Software Engineering with Computational Intelligence

Jonathan Lee

ISBN 10: 3540004726 / ISBN 13: 9783540004721

Published by Springer Berlin Heidelberg, Springer Berlin Heidelberg, 2003

About this Item

Druck auf Anfrage Neuware - Printed after ordering - It is not an exaggeration to view Professor Lee's book,' Software Engineer ing with Computational Intelligence,' or SECI for short, as a pioneering contribution to software engineering. Breaking with the tradition of treat ing uncertainty, imprecision, fuzziness and vagueness as issues of peripheral importance, SECI moves them much closer to the center of the stage. It is ob vious, though still not widely accepted, that this is where these issues should be, since the real world is much too complex and much too ill-defined to lend itself to categorical analysis in the Cartesian spirit. As its title suggests, SECI employs the machineries of computational intel ligence (CI) and, more or less equivalently, soft computing (SC), to deal with the foundations and principal issues in software engineering. Basically, CI and SC are consortia of methodologies which collectively provide a body of con cepts and techniques for conception, design, construction and utilization of intelligent systems. The principal constituents of CI and SC are fuzzy logic, neurocomputing, evolutionary computing, probabilistic computing, chaotic computing and machine learning. The leitmotif of CI and SC is that, in general, better performance can be achieved by employing the constituent methodologies of CI and SC in combination rat her than in a stand-alone mode. In what follows, I will take the liberty of focusing my attention on fuzzy logic and fuzzy set theory, and on their roles in software engineering. But first, a couple of points of semantics which are in need of clarification.

Seller Inventory # 9783540004721

Bibliographic Details

• Title: Software Engineering with Computational Intelligence
• Publisher: Springer Berlin Heidelberg, Springer Berlin Heidelberg
• Publication Date: 2003
• Language: English
• ISBN 10: 3540004726
• ISBN 13: 9783540004721
• Binding: Buch
• Condition: Neu
• Dimensions: 241W x 160H x 21D millimeters 241 millimeters width by 160 millimeters height by 21 millimeters depth
• Weight: 606 grams

About this title

Synopsis

It is not an exaggeration to view Professor Lee's book," Software Engineer­ ing with Computational Intelligence," or SECI for short, as a pioneering contribution to software engineering. Breaking with the tradition of treat­ ing uncertainty, imprecision, fuzziness and vagueness as issues of peripheral importance, SECI moves them much closer to the center of the stage. It is ob­ vious, though still not widely accepted, that this is where these issues should be, since the real world is much too complex and much too ill-defined to lend itself to categorical analysis in the Cartesian spirit. As its title suggests, SECI employs the machineries of computational intel­ ligence (CI) and, more or less equivalently, soft computing (SC), to deal with the foundations and principal issues in software engineering. Basically, CI and SC are consortia of methodologies which collectively provide a body of con­ cepts and techniques for conception, design, construction and utilization of intelligent systems. The principal constituents of CI and SC are fuzzy logic, neurocomputing, evolutionary computing, probabilistic computing, chaotic computing and machine learning. The leitmotif of CI and SC is that, in general, better performance can be achieved by employing the constituent methodologies of CI and SC in combination rat her than in a stand-alone mode. In what follows, I will take the liberty of focusing my attention on fuzzy logic and fuzzy set theory, and on their roles in software engineering. But first, a couple of points of semantics which are in need of clarification.

From the Back Cover

This edited book invites the reader to explore how the latest technologies developed in computational intelligence can be extended and applied to software engineering. Leading experts demonstrate how this recent confluence of software engineering and computational intelligence provides a powerful tool to address the increasing demand for complex applications in diversified areas, the ever-increasing complexity and size of software systems, and the inherently imperfect nature of the information. The presented treatments to software modeling and formal analysis permit the extension of computational intelligence to various phases in software life cycles, such as managing fuzziness resident in the requirements, coping with fuzzy objects and imprecise knowledge, and handling uncertainty encountered in quality prediction.