<< 1 >>
Rating: 
Summary: Mathematically correct - excellent book
Review: Excellent book on measurement techniques with solid math and statistical formulas that I worked through using Maple. The measurement process presented is a great template for getting to CMM level 4 or 5. As a software engineering manager concerned with quality, measurement and metrics I found this book to be worthy of including in our workgroup library and using it for the development of a measurement process. I highly recommend it.
Rating:
Summary: Mathematically correct - excellent book
Review: Excellent book on measurement techniques with solid math and statistical formulas that I worked through using Maple. The measurement process presented is a great template for getting to CMM level 4 or 5. As a software engineering manager concerned with quality, measurement and metrics I found this book to be worthy of including in our workgroup library and using it for the development of a measurement process. I highly recommend it.
Rating:
Summary: Excellent quantitative analysis
Review: Munson shows you how to apply empirical validation to the software development process. I say software development instead of engineering because that is where the industry is happily situated at the moment. To move beyond the reality of software craftsmanship, as glorified by popular books such as "The Pragmatic Programmer", the software industry MUST embrace an engineering discipline. To that end, Munson uses proven statistical analysis methods to measure and thus quantify the use of software metrics in the software engineering process.
This book is an eye opener for any software engineer. I consider it a must read...
Rating: 
Summary: Unsound Statistics
Review: There are better-written and more mathematically sound papers available on the topics covered. Not recommended.
Rating:
Summary: Advanced combination of concept and pragmatic
Review: This book differs from most software metrics books in that it doesn't cover specific metrics, but, instead, provides the underlying concepts, principles and mathematics, and a pragmatic approach to developing a measurement and metrics strategy.The first three sections cover goals, fundamentals of scientific investigation, and measurement points within the development process. I view the latter as akin to instrumenting software development, and the author does a good job of dividing the process into measurement domains. The next section addresses validation, using criterion, content, construct and empirical validity as attributes. This is an excellent taxonomy of validation. Static software measurement (discreet metrics, such as source code and quality attributes) and derived measures (variation and complexity) covered in the next two sections provide a foundation for the discussions on metrics and modeling, specification and design attributes, and dynamic measurement. These sections are a blend of concept and concrete examples most software engineers will recognize and relate to. I liked the sections on measuring testing and availability - both of these were in areas of direct personal interest, and the information contained in these sections, especially statistical testing, were excellent. The book wraps up with a section on implementing a measurement strategy, and an approach for a research plan. Overall this is a book that empowers you to develop the best measurement and metrics approach for your particular environment. It accomplishes this by providing the knowledge for understanding metrics within the context of software engineering and measurement concepts that can be employed to create a tailored strategy.
<< 1 >>
| 
