Software Metrics: A Rigorous and Practical Approach, Third Edition

Norman Fenton

ISBN 10: 0367659026 / ISBN 13: 9780367659028

Published by Taylor & Francis Ltd, 2020

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Bibliographic Details

• Title: Software Metrics: A Rigorous and Practical Approach, Third Edition
• Publisher: Taylor & Francis Ltd
• Publication Date: 2020
• Language: English
• ISBN 10: 0367659026
• ISBN 13: 9780367659028
• Binding: Paperback / softback
• Edition: 3rd Edition
• Condition: New

About this title

Synopsis

A Framework for Managing, Measuring, and Predicting Attributes of Software Development Products and ProcessesReflecting the immense progress in the development and use of software metrics in the past decades, Software Metrics: A Rigorous and Practical Approach, Third Edition provides an up-to-date, accessible, and comprehensive introduction to software metrics. Like its popular predecessors, this third edition discusses important issues, explains essential concepts, and offers new approaches for tackling long-standing problems.

New to the Third EditionThis edition contains new material relevant to object-oriented design, design patterns, model-driven development, and agile development processes. It includes a new chapter on causal models and Bayesian networks and their application to software engineering. This edition also incorporates recent references to the latest software metrics activities, including research results, industrial case studies, and standards.

Suitable for a Range of ReadersWith numerous examples and exercises, this book continues to serve a wide audience. It can be used as a textbook for a software metrics and quality assurance course or as a useful supplement in any software engineering course. Practitioners will appreciate the important results that have previously only appeared in research-oriented publications. Researchers will welcome the material on new results as well as the extensive bibliography of measurement-related information. The book also gives software managers and developers practical guidelines for selecting metrics and planning their use in a measurement program.

About the Author

Norman Fenton, PhD, is a professor of risk information management at Queen Mary London University and the chief executive officer of Agena, a company that specializes in risk management for critical systems. He is renowned for his work in software engineering and software metrics. His current projects focus on using Bayesian methods of analysis to risk assessment. He has published 6 books and more than 140 refereed articles and has provided consulting to many major companies worldwide.

James M. Bieman, PhD, is a professor of computer science at Colorado State University, where he was the founding director of the Software Assurance Laboratory. His research focuses on the evaluation of software designs and processes, including ways to test nontestable software, techniques that support automated software repair, and the relationships between internal design attributes and external quality attributes. He serves on the editorial boards of the Software Quality Journal and the Journal of Software and Systems Modeling.