Overview
- Editors:
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Taghi M. Khoshgoftaar
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Florida Atlantic University, USA
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Table of contents (12 chapters)
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- Stephen G. MacDonell, Andrew R. Gray
Pages 17-43
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- Balasubramaniam Ramesh, Tarek K. Abdel-Hamid
Pages 44-68
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- Robert Hochman, Taghi M. Khoshgoftaar, Edward B. Allen, John P. Hudepohl
Pages 69-100
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- Kelly R. Oliveira, Arnaldo D. Belchior
Pages 101-135
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- Martin Neil, Paul Krause, Norman Fenton
Pages 136-172
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- Ali Mili, Bojan Cukic, Yan Liu, Rahma Ben Ayed
Pages 173-203
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- Lionel C. Briand, Jie Feng, Yvan Labiche
Pages 204-234
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- Mark Last, Abraham Kandel
Pages 235-258
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- Robert M. Patton, Annie S. Wu, Gwendolyn H. Walton
Pages 259-286
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- David C. Kung, Hitesh Bhambhani, Riken Shah, Gaurav Pancholi
Pages 287-318
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- Tim Menzies, Eliza Chiang, Martin Feather, Ying Hu, James D. Kiper
Pages 319-361
About this book
The constantly evolving technological infrastructure of the modem world presents a great challenge of developing software systems with increasing size, complexity, and functionality. The software engineering field has seen changes and innovations to meet these and other continuously growing challenges by developing and implementing useful software engineering methodologies. Among the more recent advances are those made in the context of software portability, formal verification· techniques, software measurement, and software reuse. However, despite the introduction of some important and useful paradigms in the software engineering discipline, their technological transfer on a larger scale has been extremely gradual and limited. For example, many software development organizations may not have a well-defined software assurance team, which can be considered as a key ingredient in the development of a high-quality and dependable software product. Recently, the software engineering field has observed an increased integration or fusion with the computational intelligence (Cl) field, which is comprised of primarily the mature technologies of fuzzy logic, neural networks, genetic algorithms, genetic programming, and rough sets. Hybrid systems that combine two or more of these individual technologies are also categorized under the Cl umbrella. Software engineering is unlike the other well-founded engineering disciplines, primarily due to its human component (designers, developers, testers, etc. ) factor. The highly non-mechanical and intuitive nature of the human factor characterizes many of the problems associated with software engineering, including those observed in development effort estimation, software quality and reliability prediction, software design, and softwaretesting.
Editors and Affiliations
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Florida Atlantic University, USA
Taghi M. Khoshgoftaar
