
Computational Intelligence In Software Quality Assurance
World Scientific Publishing Co Pte Ltd
Published on 24. October 2005
Book
Hardback
200 pages
978-981-256-172-5 (ISBN)
Description
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.
Reviews / Votes
"Written for researchers and practitioners in software engineering and computational intelligence, this book is a unique and important bridge between these two fields." Zentralblatt MATHMore details
Series
Language
English
Place of publication
Singapore
Singapore
Target group
Professional and scholarly
Researchers in software quality assurance, computational intelligence, practicing software engineers, advanced graduate-level course in computational intelligence or software engineering.
Product notice
sewn/stitched
Paper over boards
Dimensions
Height: 229 mm
Width: 160 mm
Thickness: 18 mm
Weight
476 gr
ISBN-13
978-981-256-172-5 (9789812561725)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Persons
UNIV OF ALBERTA, CANADA
Content
Overview of Software Engineering; Artificial Intelligence in Software Engineering; Computational Intelligence; Computational Intelligence in Software Engineering; Software Quality; Software Testing; Artificial Intelligence in Software Testing; Computational Intelligence in Software Testing; Reliability Engineering for Software; Nonlinear Time Series Analysis; Experimental Results; Review of Related Work; Software Change and Software Characteristic Datasets; Fuzzy Cluster Analysis; Data Mining; Machine Learning in Skewed Datasets; Experimental Results; Proposed Usage.