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Software Engineering Measurement
 
 

Software Engineering Measurement [Hardcover]

John C. Munson Ph.D.
3.7 out of 5 stars  See all reviews (3 customer reviews)
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Product Description

The product of many years of practical experience and research in the software measurement business, this technical reference helps you select what metrics to collect, how to convert measurement data to management information, and provides the statistics necessary to perform these conversions. The author explains how to manage software development measurement systems, how to build software measurement tools and standards, and how to construct controlled experiments using standardized measurement tools.

There are three fundamental questions that this book seeks to answer. First, exactly how do you get the measurement data? Second, how do you convert the data from the measurement process to information that you can use to manage the software development process? Third, how do you manage all of the data?

Millions of dollars are being spent trying to secure software systems. When suitable instrumentation is placed into the systems that we develop, their activity can be monitored in real time. Measurement based automatic detection mechanisms can be designed into systems. This will permit the detection of system misuse and detect incipient reliability problems.

By demonstrating how to develop simple experiments for the empirical validation of theoretical research and showing how to convert measurement data into meaningful and valuable information, this text fosters more precise use of software measurement in the computer science and software engineering literature. Software Engineering Measurement shows you how to convert your measurement data to valuable information that can be used immediately for software process improvement.

Book Info

Text lays the basis for measurement standards so that software engineers and system developers can begin to share experimental results in a more meaningful way. Text answers three fundamental questions: how is measurement data obtained, how is this data then converted to information useful for managing the software development process, and how is all that data managed? Includes index.

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Front Cover | Copyright | Table of Contents | Excerpt | Index | Back Cover
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Average Customer Review
3.7 out of 5 stars (3 customer reviews)
 
 
 
 
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5.0 out of 5 stars Mathematically correct - excellent book, July 13 2004
By 
Rachel Tozier (Brea, CA USA) - See all my reviews
(REAL NAME)   
This review is from: Software Engineering Measurement (Hardcover)
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.
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1.0 out of 5 stars Unsound Statistics, July 13 2004
By A Customer
This review is from: Software Engineering Measurement (Hardcover)
There are better-written and more mathematically sound papers available on the topics covered. Not recommended.
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5.0 out of 5 stars Advanced combination of concept and pragmatic, July 3 2004
By 
Mike Tarrani "Jazz Drummer" (Deltona, FL USA) - See all my reviews
(REAL NAME)   
This review is from: Software Engineering Measurement (Hardcover)
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.

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