TY  - BOOK
AU  - Zhang, Du. 
AU  - Tsai, Jeffery J.P. 
TI  - Advances in machine learning applications in software engineering
SN  - 9781591409410
U1  - 005.1 22
PY  - 2007///
CY  - United States
PB  - Idea Group Publishing
KW  - Machine Learning
KW  - Software Engineering
N1  - Section I: Data Analysis and Refinement
Chapter I

; A Two-Stage Zone Regression Method for Global Characterization of a Project
Database; Chapter II
; Intelligent Analysis of Software Maintenance Data; Chapter III
; Improving Credibility of Machine Learner Models in Software Engineering; Chapter IV
; ILP Applications to Software Engineering; Chapter V; MMIR: An Advanced Content-Based Image Retrieval System Using a
Hierarchical Learning Framework; Chapter VI
; A Genetic Algorithm-Based QoS Analysis Tool for Reconfigurable
Service-Oriented Systems; Section II: Applications to Software Development
Chapter IV; ILP Applications to Software Engineering; Chapter V
; MMIR: An Advanced Content-Based Image Retrieval System Using a
Hierarchical Learning Framework; Chapter VI
; A Genetic Algorithm-Based QoS Analysis Tool for Reconfigurable
Service-Oriented Systems; Section III: Predictive Models for Software Quality and Relevancy
Chapter VII
; Fuzzy Logic Classifiers and Models in Quantitative Software Engineering; Chapter VIII
; Modeling Relevance Relations Using Machine Learning Techniques; Chapter IX
; A Practical Software Quality Classification Model Using Genetic
Programming; Chapter X
; A Statistical Framework for the Prediction of Fault-Proneness; Chapter XI
; Applying Rule Induction in Software Prediction; Chapter XII
; Application of Genetic Algorithms in Software Testing; Section V: Areas of Future Work
Chapter XIII
; Formal Methods for Specifying and Analyzing Complex Software Systems; Chapter XIV
; Practical Considerations in Automatic Code Generation; Chapter XV
; DPSSEE: A Distributed Proactive Semantic Software Engineering
Environment; Chapter XVI
; Adding Context into an Access Control Model for Computer Security Policy
N2  - Machine learning is the study of building computer programs that improve their performance through experience. To meet the challenge of developing and maintaining larger and complex software systems in a dynamic and changing environment, machine learning methods have been playing an increasingly important role in many software development and maintenance tasks.

Advances in Machine Learning Applications in Software Engineering provides analysis, characterization, and refinement of software engineering data in terms of machine learning methods. This book depicts applications of several machine learning approaches in software systems development and deployment, and the use of machine learning methods to establish predictive models for software quality. Advances in Machine Learning Applications in Software Engineering offers readers direction for future work in this emerging research field

ER  -