Machine Learning Applications in Software Engineering

By: Du Zhang (Editor), Jeffrey J P Tsai (Editor)

Write A Review

Hardcover | 1 February 2005

At a Glance

Hardcover
368 Pages

Dimensions(cm)
27.94 x 21.59 x 2.54

Hardcover

RRP $352.99

$317.75

10%OFF

or 4 interest-free payments of $79.44 with

Ships in 15 to 25 business days

Machine learning deals with the issue of how to build computer programs that improve their performance at some tasks through experience. Machine learning algorithms have proven to be of great practical value in a variety of application domains. Not surprisingly, the field of software engineering turns out to be a fertile ground where many software development and maintenance tasks could be formulated as learning problems and approached in terms of learning algorithms. This book deals with the subject of machine learning applications in software engineering. It provides an overview of machine learning, summarizes the state-of-the-practice in this niche area, gives a classification of the existing work, and offers some application guidelines. Also included in the book is a collection of previously published papers in this research area.

Shipping

	Standard Shipping	Express Shipping
Metro postcodes:	$9.99	$14.95
Regional postcodes:	$9.99	$14.95
Rural postcodes:	$9.99	$14.95

Orders over $79.00 qualify for free shipping.

How to return your order

At Booktopia, we offer hassle-free returns in accordance with our returns policy. If you wish to return an item, please get in touch with Booktopia Customer Care.

Additional postage charges may be applicable.

Defective items

If there is a problem with any of the items received for your order then the Booktopia Customer Care team is ready to assist you.

For more info please visit our Help Centre.

You Can Find This Book In

Non-Fiction Computing & I.T.Computer Science Mathematical Theory of Computation Artificial Intelligence Machine Learning Computer Programming & Software Development Software Engineering Systems Analysis & Design Algorithms & Data Structures Booktopia Publisher Services World Scientific Publishing

Introduction of machine learning and software engineering	p. 1
ML applications in prediction and estimation	p. 37
Bayesian analysis of empirical software engineering cost models	p. 41
Machine learning approaches to estimating software development effort	p. 52
Estimating software project effort using analogies	p. 64
A critique of software defect prediction models	p. 72
Using regression trees to classify fault-prone software modules	p. 87
Can genetic programming improve software effort estimation? : a comparative evaluation	p. 95
Optimal software release scheduling based on artificial neural networks	p. 106
ML applications in property and model discovery	p. 125
Identifying objects in procedural programs using clustering neural networks	p. 127
Bayesian-learning based guidelines to determine equivalent mutants	p. 150
ML applications in transformation	p. 165
Using neural networks to modularize software	p. 167
ML applications in generation and synthesis	p. 199
Generating software test data by evolution	p. 201
ML applications in reuse	p. 227
On the reuse of software : a case-based approach employing a repository	p. 229
ML applications in requirement acquisition	p. 261
Inductive specification recovery : understanding software by learning from example behaviors	p. 263
Explanation-based scenario generation for reactive system models	p. 286
ML applications in management of development knowledge	p. 307
Case-based knowledge management tools for software development	p. 309
Guidelines and conclusion	p. 331
Table of Contents provided by Blackwell. All Rights Reserved.

Machine Learning Applications in Software Engineering

At a Glance

Hardcover

Shipping

How to return your order

Defective items

You Can Find This Book In

More in Systems Analysis & Design

Risk-First Software Development, Second Edition

Deliver Better Systems in a Post-Agile, AI World

Untangling AI

Driving Business Success Through Enterprise Automation and AI Agents

Algorithms in C, Parts 1-4

3rd Edition - Fundamentals, Data Structures, Sorting, Searching

Systems Analysis and Design

12th edition

The Software Architect Elevator

Redefining the Architect's Role in the Digital Enterprise

The Product-Minded Engineer

Building the Right Solutions for Your Users

Artificial Intelligence for HR

Use AI to Support and Develop a Successful Workforce

Business Driven Information Systems ISE

9th Edition

DAMA-DMBOK

Data Management Body of Knowledge: 2nd Edition, Revised

Implementing Service Level Objectives

A Practical Guide to SLIs, SLOs, and Error Budgets

Linux Pocket Guide

4th Edition - Essential Commands

Cloud Native Application Protection Platforms

A Guide to CNAPPs and the Foundations of Comprehensive Cloud Security

Building Event-Driven Microservices

Leveraging Organizational Data at Scale

Learning Systems Thinking

Essential Non-Linear Skills and Practices for Software Professionals

System Design on AWS

Building and Scaling Enterprise Solutions

Exploring Research Through Co-Design

Multiple Perspectives for Collaborative Inquiry

Rust Programming in easy steps

In Easy Steps

The Bloomsbury Handbook of Service Design

Plural perspectives and a critical contemporary agenda

The Designer's Guide to VHDL, third edition

Volume 3

Computer Organization and Design RISC-V Edition

2nd Edition - The Hardware Software Interface

Artificial Intelligence and Data Science in Healthcare Applications

Transformative applied research

Breakthrough research in a changing world

Blockchain of Things

Research Challenges and Applications

The Science of Talent Dynamics

Smart Workforce Design for Biomanufacturing and Industry 4.0

This product is categorised by