Software Engineering with Computational Intelligence

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.

State of the art of technologies developed in computational intelligence applied and extended to software engineering Presentation of software systems dealing with complex applications and imprecise and uncertain information

Autorentext
Jonathan Lee, geboren 1981 in Surrey, studierte englische Literatur, lebte eine Zeitlang in Südamerika und arbeitete in einer Anwaltskanzlei in London City. 2007 wurde er nach Tokio versetzt. Zurück in England ließ er sich beurlauben und schrieb einen Roman, der Leser und Presse gleichermaßen begeisterte. Inzwischen lebt Jonathan Lee in New York City, arbeitet nebenbei für das das Literaturmagazin A Public Space. Seine Texte und Geschichten erscheinen unter anderem in Granta, Tin House & Narrative, im Guernica Magazine und The Paris Review Daily; eine seiner Kurzgeschichten war auf der Longlist für den Sunday Times Short Story Award. Sein zweiter Roman wird derzeit von der BBC verfilmt. Der Guardian nennt Jonathan Lee "eine bedeutende neue Stimme der englischen Literatur".

Klappentext

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.

Inhalt
to Software Engineering with Computational Intelligence.- Fuzzy Concepts and Formal Methods.- Trade-off Requirement Engineering.- A Generalized Object-Oriented Data Model Based on Level-2 Fuzzy Sets.- Modelling Imperfect Spatial Information in a Fuzzy Object Oriented Database.- Using Classical Object-Oriented Features to Build a Fuzzy O-O Database System.- Domain Analysis for the Engineering of Spatiotemporal Software.- Object-Oriented Framework of Fuzzy Knowledge Systems.- Fuzzy Evaluation of Domain Knowledge.- Application of Fuzzy Rule Extraction to Minimize the Costs of Misclassification on Software Quality Modeling.- Processing Software Engineering Data: Granular-based Approach.