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Description :
Despite decades of research, developing software that is fit for purpose, developed on time, and within budget remains a challenge. Many researchers have advocated the use of artificial intelligence techniques such as knowledge-based systems, neural networks, and data mining as a way of addressing these difficulties.
Artificial Intelligence Applications for Improved Software Engineering Development: New Prospects provides an overview of useful techniques in artificial intelligence for future software development along with critical assessment for further advancement. A compendium of latest industry findings, this Premier Reference Source offers researchers, academicians, and practitioners developmental ideas within the field.
Content :
Foreword
............................................................................................................................................
xiii
Preface
.................................................................................................................................................
xv
Acknowledgment
..............................................................................................................................
xxii
Section 1
Project Management and Cost Estimation
Chapter 1
Software Project and Quality Modelling Using Bayesian Networks
.....................................................
1
Norman Fenton, Queen Mary, University of London, United Kingdom
Peter Hearty, Queen Mary, University of London, United Kingdom
Martin Neil, Queen Mary, University of London, United Kingdom
Łukasz
Radliński,
Queen
Mary,
University
of
London,
United
Kingdom,
and
University
of
Szczecin,
Poland
Chapter 2
Using Bayesian Networks for Web Effort Estimation
.........................................................................
26
Emilia Mendes, The University of Auckland, New Zealand
Chapter 3
Optimizing Software Development Cost Estimates using Multi-Objective Particle
Swarm Optimization
............................................................................................................................
45
Tad Gonsalves, Sophia University, Japan
Kei Yamagishi, Sophia University, Japan
Ryo
Kawabata,
Sophia
University,
Japan
Kiyoshi Itoh, Sophia University, Japan
Chapter 4
Auto-Associative Neural Networks to Improve the Accuracy of Estimation Models
.........................
66
Salvatore
A.
Sarcia,
Università
di
Roma
Tor
Vergata,
Italy
Giovanni Cantone, University of Maryland, USA
Victor
R.
Basili,
University
of
Maryland,
USA
Table of Contents
Section 2
Requirements Engineering and Specification
Chapter 5
From Textual Scenarios to Message Sequence Charts
.........................................................................
83
Leonid Kof, Technische Universität München, Germany
Chapter 6
A Bayesian Network for Predicting the Need for a Requirements Review
.......................................
106
José
del
Sagrado
Martínez,
University
of
Almería,
Spain
Isabel
María
del
Águila
Cano,
University
of
Almería,
Spain
Chapter 7
Knowledge Engineering Support for Software Requirements, Architectures and Components
.......
129
Muthu
Ramachandran,
Leeds
Metropolitan
University,
UK
Chapter 8
MUSTER: A Situational Tool for Requirements Elicitation
..............................................................
146
Chad
Coulin,
University
of
Technology
Sydney,
Australia
&
LAAS
CNRS,
France
Didar Zowghi, University of Technology Sydney, Australia
Abd-El-Kader
Sahraoui,
LAAS
CNRS,
France
Section 3
Software Design and Implementation
Chapter 9
An Intelligent Computational Argumentation System for Supporting Collaborative Software
Development Decision Making
.........................................................................................................
167
Xiaoqing (Frank) Liu, Missouri University of Science and Technology, USA
Ekta Khudkhudia, Missouri University of Science and Technology, USA
Lei Wen, Missouri University of Science and Technology, USA
Vamshi Sajja, Missouri University of Science and Technology, USA
Ming C. Leu, Missouri University of Science and Technology, USA
Chapter 10
Supporting Quality-Driven Software Design through Intelligent Assistants
.....................................
181
Alvaro
Soria,
ISISTAN
Research
Institute
and
CONICET,
Argentina
J.
Andres
Diaz-Pace,
Software
Engineering
Institute,
USA
Len Bass, Software Engineering Institute, USA
Felix Bachmann, Software Engineering Institute, USA
Marcelo
Campo,
ISISTAN
Research
Institute
and
CONICET,
Argentina
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