Computational intelligence in software quality assurance /
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 a...
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Main Authors: | |
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Corporate Authors: | |
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Published: |
World Scientific Pub. Co.,
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Publisher Address: | Singapore ; Hackensack, N.J. : |
Publication Dates: | 2005. |
Literature type: | eBook |
Language: | English |
Series: |
Series in machine perception and artificial intelligence ;
v. 63 |
Subjects: | |
Online Access: |
http://www.worldscientific.com/worldscibooks/10.1142/5760#t=toc |
Summary: |
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. |
Carrier Form: | 1 online resource (xvii,180pages) : illustrations. |
Bibliography: | Includes bibliographical references (pages 157-177) and index. |
ISBN: | 9789812703477 (electronic bk.) |
CLC: | TP31 |
Contents: | ch. 1. Software engineering and artificial intelligence. 1.1. Introduction. 1.2. Overview of software engineering. 1.3. Artificial intelligence in software engineering. 1.4. Computational intelligence. 1.5. Computational intelligence in software engineering. 1.6. Remarks -- ch. 2. Software testing and artificial intelligence. 2.1. Introduction. 2.2. Software quality. 2.3. Software testing. 2.4. Artificial intelligence in software testing. 2.5. Computational intelligence in software testing. 2.6. Remarks -- ch. 3. Chaos theory and software reliability. 3.1. Introduction. 3.2. Reliability engineering for software. 3.3. Nonlinear time series analysis. 3.4. Experimental results. 3.5. Remarks -- ch. 4. Data mining and software metrics. 4.1. Introduction. 4.2. Review of related work. 4.3. Software change and software characteristic datasets. 4.4. Fuzzy cluster analysis. 4.5. Data mining. 4.6. Remarks -- ch. 5. Skewness and resampling. 5.1. Introduction. 5.2. Machine learning in skewed datasets. 5.3. Experimental results. 5.4. Proposed usage. 5.5. Remarks -- ch. 6. Conclusion. |