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    COMPUTATIONAL INTELLIGENCE IN SOFTWARE QUALITY ASSURANCE

    by S Dick (University of Alberta, Canada) & A Kandel (University of South Florida, USA)

    Table of Contents (122k)
    Preface (125k)

    Software systems surround us. Software is a critical component in everything from the family car through electrical power systems to military equipment. As software plays an ever-increasing role in our lives and livelihoods, the quality of that software becomes more and more critical. However, our ability to deliver high-quality software has not kept up with those increasing demands. The economic fallout is enormous; the US economy alone is losing over US$50 billion per year due to software failures. This book presents new research into using advanced artificial intelligence techniques to guide software quality improvements. The techniques of chaos theory and data mining are brought to bear to provide new insights into the software development process. Written for researchers and practitioners in software engineering and computational intelligence, this book is a unique and important bridge between these two fields.

     
    Contents:
    • Software Engineering and Artificial Intelligence
    • Software Testing and Artificial Intelligence
    • Chaos Theory and Software Reliability
    • Data Mining and Software Metrics
    • Skewness and Resampling
     
    Readership: Primarily, researchers working in the areas of software quality assurance or in computational intelligence, and particularly those interested in interdisciplinary research between these two topics. The book is also intended for practicing software engineers interested in the use of novel technologies for software quality engineering. In addition, the book is appropriate for an advanced graduate-level course in computational intelligence or software engineering.
     
    “Written for researchers and practitioners in software engineering and computational intelligence, this book is a unique and important bridge between these two fields.”
    Zentralblatt MATH

     
    200pp    Pub. date: Oct 2005  
    ISBN:   978-981-256-172-5
    981-256-172-2
       US$101 / £56

     


    200pp    Pub. date: Oct 2005  
    ISBN:   978-981-270-347-7(ebook)
    981-270-347-0(ebook)
       US$133 / £76

     


     

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    Updated on 6 November 2009