Norman Fenton, James Bieman

Software Metrics (eBook, PDF)

A Rigorous and Practical Approach, Third Edition

• Format: PDF

Produktbeschreibung

Reflecting the immense progress in the development and use of software metrics in the past decades, this third edition provides an up-to-date, accessible, and comprehensive introduction to software metrics. This 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.

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Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 617
• Erscheinungstermin: 1. Oktober 2014
• Englisch
• ISBN-13: 9781439838235
• Artikelnr.: 57533910

Autorenporträt

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.

Inhaltsangabe

Fundamentals of Measurement and Experimentation: Measurement: What Is It
and Why Do It? The Basics of Measurement. A Goal-Based Framework for
Software Measurement. Empirical Investigation. Software Metrics Data
Collection. Analyzing Software Measurement Data. Metrics for Decision
Support: The Need for Causal Models. Software Engineering Measurement:
Measuring Internal Product Attributes: Size. Measuring Internal Product
Attributes: Structure. Measuring External Product Attributes. Software
Reliability: Measurement and Prediction. Appendix. Bibliography. Index.