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.
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.
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.
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.
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