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Rating: Summary: Measuring Software Review: This book is written poorly and it does not provide any information about measuring software. It simply rehashes theoretical statistics taught in 101 and that too in a difficult and hard to understand way.
Rating: Summary: Solid introductory text Review: This is among the best introductory texts on software metrics I've read in a long time. The author carefully and meticulously leads you through the basics of measurement and metrics, including some interesting views about how measurement is an integrated activity that has three distinct phases - cognitive, semantic, and quantitative. Key software metrics are covered, divided into simple and complex classes, and traced to quality standards and a common metrics vocabulary. This part of the book is solid and especially suited to someone who is exploring software metrics and may have been put off by the dense, overly technical approach in other books. Like the preceding material, the chapters on designing a metrics system and data visualization are basic, but straightforward. I especially like the three chapters on data analysis that classify metrics into frequency, time and relationship domains. This is one of the clearest approaches to cutting through the complex morass of data analysis, and will put metrics into perspective instead of overwhelming. The next chapters, covering process and estimation models were adequate in my opinion. They covered the essentials. However, the chapter on defect metrics was outstanding. I liked the complete and concise coverage of this topic. The remainder of the book ramped down and seemed to lack the detail or clarity that characterizes the preceding parts of the book. However, this material was more operational and not (in my opinion) as important as communicating the fundamentals, collection and analyses, or metrics classification that were so exceptionally well covered in this book. I highly recommend this book to anyone who wants to quickly learn the basics of software metrics.
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