Software Engineering with Computational Intelligence

Overview

The software engineering field has recently observed an increased integration with the computational intelligence (CI) field, which is primarily comprised of the mature technologies of fuzzy logic, artificial 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 CI umbrella.

Software Engineering with Computational Intelligence, an edited volume, was ...

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Paperback (Softcover reprint of the original 1st ed. 2003)
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Overview

The software engineering field has recently observed an increased integration with the computational intelligence (CI) field, which is primarily comprised of the mature technologies of fuzzy logic, artificial 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 CI umbrella.

Software Engineering with Computational Intelligence, an edited volume, was initially selected for a special volume of "The Annals of Software Engineering" (ANSE) Journal, which has been discontinued. The contributions in this book are grouped into four chapters according to the software engineering categories of: software project management and effort estimation; software quality assurance and estimation; software testing, verification, and validation; and software design. The contributions focus on applying CI techniques to address various software engineering problems.

This book is designed to meet the needs of a professional and academic software engineering audience, and those of graduate students in Computer Science, Computer Engineering, and Software Engineering programs.

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Product Details

Table of Contents

Preface. Acknowledgment.
1. Applying Machine Learners to GUI Specifications in Formulating Early Life Cycle Project Estimations; G.D. Boetticher.
2. Applying Fuzzy Logic Modeling to Software Project Management; S.G. MacDonell, A.R. Gray.
3. Integrating Genetic Algorithms With Systems Dynamics To Optimize Quality Assurance Effort Allocation; B. Ramesh, T.K. Abdel-Hamid.
4. Improved Fault-Prone Detection Analysis of Software Modules Using an Evolutionary Neural Network Approach; R. Hochman, T.M. Khoshgoftaar, E.B. Allen, J.P. Hudepohl.
5. A Fuzzy Model and the AdeQuaS Fuzzy Tool: a theoretical and a practical view of the Software Quality Evaluation; K.R. Oliveira, A.D. Belchior.
6. Software Quality Prediction Using Bayesian Networks; M. Neil, P. Krause, N. Fenton.
7. Towards the Verification and Validation of Online Learning Adaptive Systems; A. Mili, B. Cukic, Yan Liu, R. Ben Ayed.
8. Experimenting with Genetic Algorithms to Devise Optimal Integration Test Orders; L.C. Briand, Jie Feng, Y. Labiche.
9. Automated Test Reduction Using an Info-Fuzzy Network; M. Last, A. Kandel.
10. A Genetic Algorithm Approach to Focused Software Usage Testing; R.M. Patton, A.S. Wu, G.H. Walton.
11. An Expert System for Suggesting Design Patterns - A Methodology and a Prototype; D.C. Kung, H. Bhambhani, R. Shah, G. Pancholi.
12. Condensing Uncertainty via Incremental Treatment Learning; T. Menzies, E. Chiang, M. Feather, Ying Hu, J.D. Kiper.

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