Review "The wait for a new edition of this book is over. Long considered the go-to text for its thorough coverage of software measurement and experimentation, the new edition succeeds splendidly in bringing the field up to date while including new and important topics. … updated with the latest results from recent advances in software measurement research and practice. … The authors do an outstanding job of balancing formal analysis topics with examples that ground the reader in practical application. … Both researchers and practitioners alike will gain a valuable understanding of why measurement is critical for quality improvements in software development processes and software products. … With this updated edition, this book solidifies its standing as the most complete reference text for software measurement."―Computing Review, April 2015 "I have been using this book as my primary reference on software metrics for over 20 years now. It still remains the best book by far on the science and practice of software metrics. This latest edition has some important updates, especially with the inclusion of material on Bayesian networks for prediction and risk assessment."―Paul Krause, University of Surrey, Guildford, UK "Great introduction to software metrics, measurement, and experimentation. This will be a must-read for my software engineering students."―Lukasz Radlinski, PhD, West Pomeranian University of Technology, Szczecin, Poland "I have loved this book from the first edition and with each new edition it just keeps getting better and better. I use this book constantly in my software engineering research and always recommend it to students. It is so much more than a software metrics book; to me it is an essential companion to rigorous empirical software engineering."―Dr. Tracy Hall, Department of Computer Science, Brunel University, Uxbridge, UK "This new edition of Software Metrics succeeds admirably in bringing the field of software measurement up to date and in delivering a wider range of topics to its readers as compared to its previous edition. I have both reviewed and used the book in my software measurement courses and find it to be one of the most advanced and well structured on the market today, tailored for training software engineers in both theoretical and practical aspects of software measurement. I look forward to continuing the use of the book for teaching purposes and am very comfortable offering my recommendation for this book as a primary textbook for graduate or undergraduate courses on software measurement. Thank you again for providing such a quality book to our software engineering education programs."―Olga Ormandjieva, Associate Professor, Department of Computer Science and Software Engineering, Concordia University, Canada "This book lucidly and diligently covers the nuts and bolts of software measurement. It is an excellent reference on software metric fundamentals, suitable as a comprehensive textbook for software engineering students and as a definitive manual for industry practitioners."―Mohammad Alshayeb, Associate Professor of Software Engineering, King Fahd University of Petroleum and Minerals Read more 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. Read more
K**L
Very comprehensive and explains the needed background to allow readers ...
Very comprehensive and explains the needed background to allow readers to not only use metrics well, but to understand the limitations of metric.
H**R
Very good book to keep by your side!
This book saved me from a class a took. This book also serves as a very good reference. I'm glad I have this handy and will certainly reuse it.
B**G
Five Stars
Excellent Book Great Condition
F**I
Five Stars
Thank you!!
M**I
Complete, wide in scope and essential
I have a large number of metrics books, including everything written by Grady, Jones, and Florac & Carleton, and this is one of my personal favorites. It not only goes into measurement theory and practice, but covers nearly every key metric associated with software engineering.Instead of writing a tome about what this book contains, I'll confine my comments to what I especially like about it and why.First, the measurement fundamentals, the goal-based measurement framework, and information about data collection and management alone make this book worth owning. Data collection, for example, can waste resources if you try to collect everything, or worse, don't properly manage or analyze it. Follow the process given in the first part of this book and you'll have a solid basis for a metrics initiative.Second, the scope of software engineering metrics is wide and given fairly detailed treatment. I especially like the fact that object-oriented metrics are addressed, and the multi-dimensional approach to measuring internal and external product attributes. Moreover, the scope of this book extends to productivity and resource management, which is where development projects and lifecycle costs associated with maintenance have gaps. Finally, the section on software reliability metrics was excellent and added yet another dimension to the coverage the authors give.Overall, this book is both rigorous and practical as the title implies. The theory and practical applications of measurement and metrics are carefully balanced, and the breadth of material ensures that coverage is complete and addresses all major aspects of software engineering.
G**)
excellent survey and critique
(For the full text of this review, see <a href="[...] Dobbs Journal</a>) Software Metrics is not just a thorough, readable survey of the various proposals that have been made over the years for measuring the characteristics of programs; it is also a detailed critique of the sloppy way in which people have tried to use such measurements to predict how much effort would be required to develop and maintain software, and how reliable that software would be. The first part of Software Metrics introduces the fundamentals of measurement theory. What does it mean to measure something? What kinds of measures are there, and -- more importantly -- what kinds of conclusions can we draw from different kinds of measurements? The second part of the book looks at software measurement in particular. Popular measures (COCOMO, function points, cyclometric complexity, and the like) are all described, and their weaknesses pointed out. Again and again, the authors show that the proponents of various metrics have failed to validate their metrics in even the most basic ways... Part Three looks at implementing software measurement in the workplace, and includes an interesting discussion about the nature of empirical research in software engineering. The book closes with a comprehensive annotated bibliography. If you have ever thought about measuring the progress of a software project, or about trying to predict the effort required to develop or maintain a program, this book will tell you what is feasible, what is just hype, and how to tell the difference between the two.
A**Y
A book that every software engineer should have a look at.
The previous two editions have been quite popular within the software engineering field; perhaps the best source of information on software metrics. I used those books for my primary source on SE research, and students seemed to find them very easy to read and understand its content (quite uncommon, I must say). This third edition looks even better with a very good structure and with some very key discussions on Bayesian networks and how they can be used to solve SE issues. I do believe that this is a book that every software engineer should have a look at.
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