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Overview

PSM provides you with a way to realize the significant benefits of a software measurement program, while understanding and avoiding the risks involved with a “blind jump.” You’ll find this book a worthwhile starting point for your future software measurement initiatives, as well as a source of continuing guidance as you chart your way through the sea of complex opportunities ahead.
—Barry Boehm, from the Foreword

Objective, meaningful, and quantifiable measurement is critical to the successful development of today’s complex software systems. Supported by the U.S. Department of Defense and a rapidly increasing number of commercial practitioners, Practical Software Measurement (PSM) is a process for designing and implementing a project-based software measurement program. PSM provides essential information on scheduling, resource allocation, and technological performance. It enables software managers and developers to make decisions that will affect the project’s outcome positively.

This book is the official, definitive guide to PSM written by the leaders of the PSM development initiative. It describes the principles and practices for developing, operating, and continuously improving your organization’s measurement program. It uses real-world examples to illustrate practical solutions and specific measurement techniques. This book examines the foundations of a software measurement program in depth, defining and prioritizing information needs, developing a project-specific information model, tailoring a process model to integrate measurement activities, and analyzing and understanding the results.

Specific topics include:

  • The relationship between project- and organizational-level measurement
  • Defining an information-driven, project-specific measurement plan
  • Performing measurement activities and collecting data
  • The basics of data analysis, including estimation, feasibility analysis, and performance analysis
  • Evaluating the effectiveness of the measurement processes and activities
  • Sustaining organizational commitment to a measurement program
  • Key measurement success factors and best practices

In addition, this book includes numerous detailed examples of measurement constructs typically applied to software projects, as well as two comprehensive case studies that illustrate the implementation of a measurement program in different types of projects. With this book you will have the understanding and information you need to realize the significant benefits of PSM as well as a guide for a long-term, organization-wide measurement program.

PSM is founded on the contributions and collaboration of key practitioners in the software measurement field. The initiative was established in 1994 by John McGarry and is currently managed by Cheryl Jones. Both are civilians employed by the U.S. Army. David Card is an internationally known software measurement expert, and is with the Software Productivity Consortium. Beth Layman, Elizabeth Clark, Joseph Dean, and Fred Hall have been primary contributors to PSM since its inception.

0201715163B10012001

This book examines in depth the foundations of a software measurement program: defining and prioritizing information needs, developing a project-specific information model, tailoring a process model to integrate measurement activities, and analyzing and understanding the results.

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Product Details

  • ISBN-13: 9780201715163
  • Publisher: Addison-Wesley
  • Publication date: 8/17/2001
  • Edition description: New Edition
  • Edition number: 1
  • Pages: 304
  • Product dimensions: 6.44 (w) x 9.62 (h) x 0.84 (d)

Meet the Author

0201715163AB06252001

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Read an Excerpt

Management by fact has become an increasingly popular concept in the software engineering and information technology communities. Organizations are focusing attention on measurement and the use of objective information to make decisions. Quantitative performance information is essential to fact-based management. Practical Software Measurement: Objective Information for Decision Makers describes an approach to management by fact for software project managers based on integrating the concepts of a Measurement Information Model and a Measurement Process Model. While these concepts apply to non-software activities as well, the examples and terminology presented in this book focus primarily on software.

The information needs of the decision maker drive the selection of software measures and associated analysis techniques. This is the premise behind the widely accepted approaches to software measurement, including goal/question/metric (Basili and Weiss, 1984) and issue/category/measure (McGarry et al., 1997). Information needs result from the efforts of managers to influence the outcomes of projects, processes, and initi-atives toward defined objectives. Information needs are usually derived from two sources: (1) goals that the manager seeks to achieve and (2) obstacles that hinder the achievement of these goals. Obstacles, also referred to as issues, include risks, problems, and a lack of information in a goal-related area. Unless there is a manager or other decision maker with an information need, measurement serves no purpose. The issues faced by a software project manager are numerous. Typically they include estimating and allocating project resources,tracking progress, and delivering products that meet customer specifications and expectations.

A Measurement Information Model defines the relationship between the information needs of the manager and the objective data to be collected, commonly called measures. It also establishes a consistent terminology for basic measurement ideas and concepts, which is critical to communicating the measurement information to decision makers. The information model in Practical Software Measurement (PSM) defines three levels of measures, or quantities: (1) base measures, (2) derived measures, and (3) indicators. It is interesting to note that the three levels of measurement defined in the PSM information model roughly correspond to the three-level structures advocated by many existing measurement approaches. Examples include the goal/question/metric (Basili and Weiss, 1984), factor/criteria/metric (Walters and McCall, 1977), and issue/category/measure (McGarry et al., 1997) approaches already in use within the software community. A similar approach for defining a generic data structure for measurement was developed by Kitchenham et al., who defined their structure as an Entity Relationship Diagram (1995).

An effective measurement process must address the selection of appropriate measures as well as provide for effective analysis of the data collected. The Measurement Process Model describes a set of related measurement activities that are generally applicable in all circumstances, regardless of the specific information needs of any particular situation. The process consists of four iterative measurement activities: establish, plan, perform, and evaluate. This process is similar to the commonly seen Plan-Do-Check-Act cycle (Deming, 1986).

Recognition of a need for fact-based, objective information leads to the establishment of a measurement process for a project or an organization. The specific information needs of the decision makers and measurement users drive the selection and definition of appropriate measures during measurement planning. The resulting measurement approach instantiates a project-specific information model identifies the base measures, derived measures, and indicators to be employed, and the analysis techniques to be applied in order to address the project’s prioritized information needs.

As the measurement plan is implemented, or performed, the required measurement data is collected and analyzed. The information product that results from the perform measurement activity is provided to the decision makers. Feedback from these measurement users helps in the evaluation of the effectiveness of the measures and measurement process so that they can be improved on a continuing basis.

The basic concepts presented in this book evolved from extensive measurement experience and prior research. They were previously introduced in sequentially released versions of Practical Software Measurement (McGarry et al., 1997) and were formalized in ISO/IEC Standard 15939—Software Measurement Process (2001). The measurement process model and measurement terminology from ISO/IEC 15939 have also been adopted as the basis of a new Measurement and Analysis Process Area in the Software Engineering Institute’s Capability Maturity Model Integration (CMMI) project (CMMI Development Team, 2000). This book explains how software development and maintenance organizations can implement a viable measurement process based on the proven measurement concepts of ISO/IEC 15939 and the CMMI in a practical and understandable manner.

In simplistic terms, implementing an objective measurement-by-fact process for a software-intensive project encompasses defining and prioritizing the information needs of the project decision makers through the development of a project-specific information model and then tailoring and executing a project-specific set of measurement process activities. The PSM approach to accomplishing this integrates prior experience and research from many sources across many application domains. How to Use This Book Practical Software Measurement is structured to provide progressive guidance for implementing a software measurement process. It provides comprehensive descriptions of the Measurement Information Model and the Measurement Process Model, as well as experience-based guidance for applying these models in an actual project environment. No book could ever capture all of the pertinent information and practical examples related to software measurement. As such, the Practical Software Measurement Web site at www.psmsc.com contains additional information, guidance, examples, and tools to augment Practical Software Measurement.

To enhance readability, the authors have limited most of the in-text references to suggestions for further reading on specific topics. Additional references are provided in the bibliography.

The following topics are addressed in this book:

Chapter 1: Measurement: Key Concepts and Practices. Chapter 1 provides an overview of software measurement, explaining how measurement supports today’s information-oriented business models and how measurement can become a corporate resource. It describes the relationships between project- and organizational-level measurement, and introduces the two primary concepts of PSM: the Measurement Information Model and the Measurement Process Model.

Chapter 2: Measurement Information Model. Chapter 2 presents an in-depth discussion of the Measurement Information Model and its measurement components. It relates the Measurement Information Model to measurement planning and implementation activities.

Chapter 3: Plan Measurement. Chapter 3 is the first of five chapters that look at the individual measurement process activities in detail. Chapter 3 focuses on the Plan Measurement activity and describes what is required to define an information-driven, project-specific measurement plan.

Chapter 4: Perform Measurement. Chapter 4 addresses the Perform Measurement activity and discusses how to collect and analyze measurement data. It introduces several concepts related to measurement analysis, including the types of analysis and how to relate information needs and associated issues in terms of cause and effect.

Chapter 5: Analysis Techniques. Chapter 5 provides an in-depth treatment of the three primary types of measurement analysis: estimation, feasibility analysis, and performance analysis.

Chapter 6: Evaluate Measurement. Chapter 6 describes the Evaluate Measurement activity. It focuses on the assessment, evaluation, and improvement of applied project measures and the implemented project measurement processes.

Chapter 7: Establish and Sustain Commitment. Chapter 7 explains the final measurement activity, Establish and Sustain Commitment, which addresses the organizational requirements related to implementing a viable project measurement process. Chapter 7 also addresses measurement “lessons learned.”

Chapter 8: Measure for Success. Chapter 8 reviews some of the major concepts presented in this book and identifies key measurement success factors.

Appendix A: Measurement Construct Examples. Appendix A provides detailed examples of measurement constructs typically applied to software-intensive projects.

Appendix B: Information System Case Study Appendix B provides a comprehensive case study that addresses the implementation of a measurement process for a typical information system.

Appendix C: Synergy Integrated Copier Case Study. Appendix C is a second case study that describes how measurement can be applied to a major software-intensive upgrade project.

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Table of Contents

Foreword.

Preface.

Acknowledgements.

1. Measurement: Key Concepts and Practices.

Motivation for Measurement.

Measurement as an Organizational Discriminator.

The Foundation—Project Measurement.

What Makes Measurement Work.

Measurement Information Model.

Measurement Process Model 10.

2. Measurement Information Model.

Information Needs.

Measurement Construct.

Measurement Construct Examples.

3. Plan Measurement.

Identify and Prioritize Information Needs.

Select and Specify Measures.

Integrate the Measurement Approach into Project Processes.

4. Perform Measurement.

Collect and Process Data.

Analyze Data.

Make Recommendations.

5. Analysis Techniques.

Estimation.

Feasibility Analysis.

Performance Analysis.

6. Evaluate Measurement.

Evaluate the Measures.

Evaluate the Measurement Process.

Update the Experience Base.

Identify and Implement Improvements.

7. Establish and Sustain Commitment.

Obtain Organizational Commitment.

Define Measurement Responsibilities.

Provide Resources.

Review the Measurement Program.

Lessons Learned.

8. Measure For Success.

Appendix A: Measurement Construct Examples.

Milestone Completion.

Work Unit Progress: Software Design Progress.

Incremental Capability.

Personnel Effort.

Financial Performance: Earned Value.

Appendix B. Information System Case Study.

Project Overview.

Getting the Project Under Control.

Evaluating Readiness for Test.

Installation and Software Support.

Appendix C. Xerox Case Study.

Product and Project Overview.

Estimation and Feasibility Analysis.

Performance Analysis.

Redesign and Replanning.

Glossary.

Bibliography.

Index. 0201715163T09252001

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Preface

Management by fact has become an increasingly popular concept in the Software Engineering and Information Technology communities. It is one of the key factors leading organizations to focus attention on measurement and the use of objective information to make decisions. Quantitative performance information is essential to fact-based management. Practical Software Measurement: Objective Information for Decision Makers, describes an approach to management by fact for software project managers based on the concepts of integrating a measurement information model and a measurement process model. While the concepts apply to non-software activities as well, the examples and terminology presented in the book focus on software to facilitate understanding within that community.

The information needs of the decision maker drive the selection of software measures and associated analysis techniques. This is the premise behind the widely accepted approaches to software measurement, including Goal/Question/Metric 1 and Issue/Category/Measure 2. Information needs result from the efforts of managers to influence the outcomes of projects, processes, and initiatives towards defined objectives. Information needs are usually derived from two sources: 1) goals that the manager seeks to achieve and, 2) obstacles that hinder the achievement of these goals. Obstacles, or issues, include risks, problems, and a lack of information in a goal related area. Unless there is a manager or other decision-maker with an information need, measurement serves no purpose. The issues faced by a software project manager are numerous. Typically they includeestimating and allocating project resources, and tracking progress, and delivering products that meet customer specifications and expectations.

A measurement information model defines the relationship between the information needs of the manager and the objective data to be collected, commonly called measures. It also establishes a consistent terminology for basic measurement ideas and concepts, which is critical to communicating the measurement information to decision makers. The information model in Practical Software Measurement (PSM) defines three levels of measures, or quantities: 1) base measures, 2) derived measures, and 3) indicators. It is interesting to note that the three levels of measurement defined in the PSM information model roughly correspond to the three level structures advocated by many existing measurement approaches. Examples include the goal/question/metric 1, factor/criteria/metric 3, and issue/category/measure 2) approaches already in use within the software community. A similar approach for defining a generic data structure for measurement was developed by Kitchenham, et al, who defined their structure as an Entity Relationship Diagram 4.

An effective measurement process must address the selection of appropriate measures as well as provide for effective analysis of the data that is collected. The measurement process model describes a set of related measurement activities that are generally applicable in all circumstances, regardless of the specific information needs of any particular situation. The process consists of four iterative measurement activities: Establish, Plan, Perform, and Evaluate. This process is similar to the commonly seen Plan-Do-Check-Act 5 cycle.

Recognition of a need for fact-based, objective information leads to the establishment of a measurement process for a project or an organization. The specific information needs of the decision makers and measurement users drive the selection and definition of appropriate measures during the measurement planning activity. The resulting measurement approach instantiates a project specific information model, and identifies the base measures, derived measures, and indicators to be employed, and the analysis techniques to be applied, to address the project's prioritized information needs.

As the measurement plan is implemented, or performed, the required measurement data is collected and analyzed. The information product that results from the perform measurement activity is provided to the decision makers. Feedback from these measurement users help to evaluate the effectiveness of the measures and measurement process so that they can be improved on a continuing basis.

The basic concepts presented in this book are evolved from extensive measurement experience and prior research. They were previously introduced in sequentially released versions of Practical Software Measurement 2, and were formalized in ISO/IEC Standard 15939 - Software Measurement Process 6. The measurement process model and measurement terminology work from ISO/IEC 15939 have also been adopted as the basis of a new Measurement and Analysis Process Area in the Software Engineering Institute's Capability Maturity Model - Integrated (CMM-I) 7. This book explains how software development and maintenance organizations can implement a viable measurement process based on the proven measurement concepts of ISO/IEC 15939 and the CMM-I in a practical and understandable manner.

In simplistic terms, implementing an objective "measurement by fact" process for a software intensive project encompasses defining and prioritizing the information needs of the project decision makers through the development of a project specific information model, and then tailoring and executing a project specific set of measurement process activities. The PSM approach to accomplishing this integrates prior experience and research from many sources across many application domains.

To enhance understandability, the authors limit further references to suggestions for additional reading on specific topics.

References

1 V. Basili and D. Weiss, A Methodology for Collecting Valid Software Engineering Data, IEEE Transactions on Software Engineering, October 1984.

2 J. McGarry, D. Card, et al., Practical Software Measurement, Joint Logistics Commanders and Office of the Undersecretary of Defense for Acquisition, 1997.

3 G. Walters and J. McCall, Factors in Software Quality, Rome Air Development Center, 1977.

4 B. Kitchenham, S.L. Pfleeger, and N. Fenton, Towards a Framework for Software Measurement Validation, IEEE Transactions on Software Engineering, December 1995.

5 W.E. Deming, Out of the Crisis, MIT Center for Advanced Engineering Study, 1986.

6 K. el Emam and D. Card (Editors), ISO/IEC Standard 15939, Software Measurement Process, International Organization for Standardization, January 2001 (final coordination draft).

7 CMMI Development Team, Capability Maturity Model - Integrated Systems/Software Engineering (Version 1), Software Engineering Institute, 2000.

 



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