Software Metrics and Software Metrology E-Book

Alain Abran

• Herausgeber: John Wiley & Sons
• Kategorie: Wissenschaft und neue Technologien
• Sprache: Englisch

Seitenzahl: 469

Veröffentlichungsjahr: 2010

Beschreibung

Most of the software measures currently proposed to the industry bring few real benefits to either software managers or developers. This book looks at the classical metrology concepts from science and engineering, using them as criteria to propose an approach to analyze the design of current software measures and then design new software measures (illustrated with the design of a software measure that has been adopted as an ISO measurement standard). The book includes several case studies analyzing strengths and weaknesses of some of the software measures most often quoted. It is meant for software quality specialists and process improvement analysts and managers.

Leseprobe

Table of Contents

Cover

Table of Contents

Half title page

Series page

Title page

Copyright page

FOREWORD

PREFACE

ACKNOWLEDGMENTS

ABOUT THE AUTHOR

Part 1: KEY CONCEPTS FOR THE DESIGN OF SOFTWARE MEASURES

1 INTRODUCTION

1.1. INTRODUCTION

1.2. SOFTWARE MEASUREMENT: IS IT MATURE OR NOT?

1.3. SOFTWARE MEASUREMENT AS A NEW TECHNOLOGY

1.4. THE DESIGNS OF SOFTWARE MEASURES MUST BE VERIFIED

ADVANCED READINGS: HOW MUCH MEASUREMENT SUPPORT IS RECOGNIZED WITHIN THE SOFTWARE ENGINEERING BODY OF KNOWLEDGE (SWEBOK)?

2 FROM MEASUREMENT METHODS TO QUANTITATIVE MODELS: A MEASUREMENT CONTEXT MODEL

2.1. INTRODUCTION: NUMBERS, MEASURES, AND QUANTITATIVE MODELS

2.2. MEASUREMENT CONTEXT MODEL

2.3. HOW TO DESIGN A MEASUREMENT METHOD

2.4. APPLICATION OF A MEASUREMENT METHOD

2.5. EXPLOITATION OF MEASUREMENT RESULTS IN QUANTITATIVE MODELS

2.6. VALIDATION OR VERIFICATION?

ADVANCED READINGS:

3 METROLOGY AND QUALITY CRITERIA IN SOFTWARE MEASUREMENT

3.1. INTRODUCTION TO METROLOGY

3.2. A MODEL FOR MEASURING DEVICES

3.3. QUALITY CRITERIA FOR THE DESIGN OF A MEASUREMENT METHOD

3.4. QUALITY CRITERIA FOR THE APPLICATION OF A MEASUREMENT METHOD

3.5. QUALITY CRITERIA FOR MEASUREMENT RESULTS

3.6. SUMMARY

ADVANCED READINGS: MEASURING CHAIN AND MEASURING SYSTEM

4 QUANTIFICATION AND MEASUREMENT ARE NOT THE SAME!

4.1. INTRODUCTION: NUMBERS ARE NOT ALL CREATED EQUALS

4.2. ISO 15939 MEASUREMENT INFORMATION MODEL

4.3. SCOPE OF THE ISO 15939 MEASUREMENT INFORMATION MODEL

4.4. THE METROLOGY PERSPECTIVE IN THE ISO 15939 MEASUREMENT INFORMATION MODEL

4.5. THE QUANTIFICATION OF RELATIONSHIPS IN ISO 15939

4.6. A PRODUCTIVITY MODEL: AN ISO 15939 MEASUREMENT INFORMATION MODEL

4.7. EXAMPLES: A METROLOGY DESIGN AND A QUANTIFICATION MODEL OF RELATIONSHIPS

4.8. SUMMARY

5 THE DESIGN OF SOFTWARE MEASUREMENT METHODS

5.1. INTRODUCTION

5.2. LINKING SOFTWARE MEASUREMENT AND METROLOGY

5.3. DEFINING THE MEASUREMENT PRINCIPLE

5.4. DETERMINING THE MEASUREMENT METHOD

5.5. PRODUCTS OF THE MEASUREMENT DESIGN PHASE

5.6. POST DESIGN ACTIVITY: DETERMINING A MEASUREMENT PROCEDURE

5.7. SUMMARY

ADVANCED READINGS 1: VERIFICATION CRITERIA FOR SOFTWARE MEASUREMENT METHODS

ADVANCED READINGS 2: RELATIONAL STRUCTURES IN ASSIGNING A NUMERICAL VALUE

Part 2: SOME POPULAR SOFTWARE MEASURES: HOW GOOD ARE THEY?

6 CYCLOMATIC COMPLEXITY NUMBER: ANALYSIS OF ITS DESIGN

6.1. INTRODUCTION

6.2. THE CYCLOMATIC NUMBER IN GRAPH THEORY

6.3. THE CYCLOMATIC NUMBER FOR SOFTWARE

6.4. OTHER DESIGN ISSUES: THE ENTITY AND ATTRITUBE MEASURED

ADVANCED READINGS: LACK OF CONSENSUS ON COMPLEXITY IN SOFTWARE

7 HALSTEAD’S METRICS: ANALYSIS OF THEIR DESIGNS

7.1. INTRODUCTION

7.2. HALSTEAD’S METRICS: DEFINITIONS

7.3. ANALYSIS OF THE DESIGN OF HALSTEAD’S METRICS

7.4. DISCUSSION ON THE FINDINGS

ADVANCED READINGS: OTHER HALSTEAD’S METRICS

8 FUNCTION POINTS: ANALYSIS OF THEIR DESIGN

8.1. INTRODUCTION

8.2. THE ORIGIN OF SOFTWARE FUNCTIONAL SIZE MEASUREMENT

8.3. THE DESIGN OF FUNCTION POINTS—FP

8.4. WEAKNESSES OF THE FUNCTION POINTS MEASUREMENT DESIGN

8.5. OTHER WEAKNESSES

8.6. WHAT IS A FUNCTION POINT?

8.7. OTHER RESEARCH FINDINGS

ADVANCED READINGS: EVOLUTION OF FUNCTIONAL SIZE MEASUREMENT

9 USE CASE POINTS: ANALYSIS OF THEIR DESIGN

9.1. INTRODUCTION

9.2. USE CASE POINTS DESCRIPTION

9.3. ANALYSIS OF THE UCP DESIGN

9.4. THE MODELING OF RELATIONSHIPS OF UCP WITH PROJECT EFFORT

9.5. SUMMARY

10 ISO 91261: ANALYSIS OF QUALITY MODELS AND MEASURES

10.1. INTRODUCTION TO ISO 9126

10.2. ANALYSIS MODELS OF ISO 9126: THE (QUANTITATIVE) MODELS

10.3. THE METROLOGY-RELATED PART OF ISO 9126: BASE AND DERIVED MEASURES

10.4. ANALYSIS OF DERIVED MEASURES

10.5. THE MISSING LINKS: FROM METROLOGY TO QUANTITATIVE ANALYSIS

10.6. OUTSTANDING MEASUREMENT DESIGN ISSUES: IMPROVEMENT STRATEGY

ADVANCED READINGS 1: ANALYSIS OF THE DESIGN OF THE PRODUCTIVITY MEASURE IN ISO 9126

ADVANCED READINGS 2: ATTRIBUTES AND RELATED BASE MEASURES WITHIN ISO 9126

Part 3: THE DESIGN OF COSMIC – ISO 19761

11 COSMIC: DESIGN OF AN INITIAL PROTOTYPE

11.1. INTRODUCTION

11.2. IMPROVEMENT PROJECT

11.3. LITERATURE REVIEW

11.4. DESIGN OF THE INITIAL PROTOTYPE

11.5. FIELD TESTS OF THE PROTOTYPE

11.6. FIRST-YEAR FEEDBACK FROM INDUSTRY

ADVANCED READINGS: KEY DIFFERENCES BETWEEN FP AND THE PROPOSED EXTENSION

12 COSMIC: SCALING UP AND INDUSTRIALIZATION

12.1. INTRODUCTION

12.2. SCALING UP OBJECTIVES

12.3. DESIGN DECISIONS

12.4. INDEPENDENT INDUSTRIAL FIELD TRIALS

12.5. OUTCOME: THE DESIGN OF THE COSMIC MEASUREMENT METHOD

12.6. STRENGTHS OF THE COSMIC DESIGN

12.7. SCALING UP—METROLOGY INFRASTRUCTURE

12.8. COMPETITIVE ADVANTAGES

Part 4: OTHER ISSUES IN THE DESIGN OF SOFTWARE MEASURES

13 CONVERTIBILITY ACROSS MEASUREMENT METHODS

13.1. INTRODUCTION

13.2. OVERVIEW OF PREVIOUS CONVERTIBILITY STUDIES

13.3. A CONVERTIBILITY STUDY OF AN INDUSTRY DATASET

13.4. FP TO COSMIC CONVERTIBILITY: ISSUES AND DISCUSSION

14 DESIGN OF STANDARD ETALONS: THE NEXT FRONTIER IN SOFTWARE MEASUREMENT

14.1. INTRODUCTION—MEASUREMENT STANDARD ETALON

14.2. CALIBRATION AND TESTING: REFERENCE MATERIAL AND UNCERTAINTY

14.3. RELATED WORK IN SOFTWARE MEASUREMENT

14.4. A (DRAFT) METHODOLOGY TO DESIGN AN FSM STANDARD ETALON

14.5. DISCUSSION

ADVANCED READINGS: THE DEVELOPMENT OF AN (INITIAL) DRAFT OF A MEASUREMENT STANDARD ETALON FOR COSMIC

Appendix A  LIST OF ACRONYMS

Appendix B  GLOSSARY OF TERMS IN SOFTWARE MEASUREMENT

B.1 SOME MEASUREMENT TERMS IN SOFTWARE ENGINEERING

B.2 SOME MEASUREMENT TERMS IN METROLOGY—VIM 2007

Appendix C  REFERENCES

Index

SOFTWARE METRICS AND SOFTWARE METROLOGY

Press Operating Committee

Chair

Linda Shafer

former Director, Software Quality Institute

The University of Texas at Austin

Editor-in-Chief

Alan Clements

Professor

University of Teesside

Board Members

Mark J. Christensen, Independent Consultant

James W. Cortada, IBM Institute for Business Value

Richard E. (Dick) Fairley, Founder and Principal Associate, Software Engineering Management Associates (SEMA)

Phillip Laplante, Professor of Software Engineering, Penn State University

Evan Butterfield, Director of Products and Services

Kate Guillemette, Product Development Editor, CS Press

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FOREWORD

Software organizations must respond to increasingly demanding customers in a globally competitive market and must implement best industry practices. With services and products available from vendors the world over, customers are insisting that their software systems be of high quality and with support services that challenge those of the competition while costing as little as possible.

To satisfy these demands, software organizations must have the ability to develop and maintain software to meet the customer’s needs, and it must have access to software that support the company’s business processes.

How do you know and how do you objectively demonstrate to your customers that your software organization is performing at the top of the industry?Can you leverage this knowledge to develop estimation skills as a competitive advantage?

Benchmarking and estimation is based on measurements. There is a tremendous need for software measures to support software performance measurement, benchmarking and software project estimation, even more so when software is contracted out to third party suppliers.

There is currently available a large number of software measures and quantitative models proposed to the practitioners’ community for estimating software projects and measuring the quality of the software delivered. For instance, there are hundreds of measures proposed for software quality, software complexity, objects oriented as well as an impressive number of estimation models

But …

How many software organizations today have in place software measurement programs and use these measures and models as a basis for decision-making?

There must be then something at work that impairs the use of quantitative data for decision making in software-base organizations.

What is it?

Within the software measurement community that has produced this large inventory of measures and quantitative models, there is a presumption that the lack of use of software measures in industry is caused by the practitioners’ and managers’ resistance to change.

This book is based on a different analysis and understanding of this lack of use of software measures by industry: this chasm comes from a lack of credibility in the practitioners communities, and this lack of credibility comes from the immaturity and unreliability of the measures themselves proposed to date to the industry.

Up until recently, software ‘metrics’ have been most often proposed as the quantitative tools of choice in software engineering, and the analysis of these had been most often discussed from the perspective referred to as ‘measurement theory’.

However, in other disciplines, it is the domain of knowledge referred to as ‘metrology’ that is the foundation for the development and use of measurement instruments and measurement processes.

In this book, we use as a foundation the sets of measurement concepts documented in the ISO VIM (International Vocabulary of Basic and General Terms in Metrology) to document and compare the state of maturity of measures in software with respect to classic domains of science and engineering.

This helps in particular to document practical aspects with respect to the current design of software measures and to identify the strengths and weaknesses of their own design as measures.

What was still missing is the know-how about how to correctly design software measures, and how to recognize if a software measure is well designed, and worth using as a basis for decision-making. This book focuses precisely on these two issues.

It is up to you:

to acquire such know-how about the design of a software measure andto run with it for the benefit of your organization.

PREFACE

A book on the design of software measures must be suited to software engineers, both practitioners and researchers.

This book presents a perspective on software measurement that, on the one hand, is new in software engineering and, on the other hand, is fairly classical in most domains of sciences, engineering, and even in all areas of business.

Here, we share years of experience in the design of software measures for their successful use as decision making tools by software managers.

Because measurement is a fundamental engineering concept, software organizations of all sizes can use this book, and managers will find in it effective strategies for improving software management, along with numerous illustrative examples.

Applying the best practices in software measurement will ensure that software engineers and managers are equipped to respond to the most demanding customers, feel supported by senior executives and are proud to be part of the software team.

In addition, this book introduces many of the theoretical concepts and references needed by professionals, managers and students to help them understand the fundamentals of the identification and evaluation of software development and maintenance processes, and of improvements to them.

This book is intended for those developing, maintaining and managing software as well as for those in software process improvements.

STRUCTURE AND ORGANIZATION OF THIS BOOK

This book is organized into four (4) parts and fourteen (14) chapters.

Part 1: Key Concepts for the Design of Software Measures

A number of the software measures proposed to the industry have deficiencies severe enough to make some of them useless to practitioners. Part 1 presents in chapters one through five the key concepts in measurement that are necessary to recognize whether the design of a software measure is sufficiently strong to be meaningful in practice. Part 1 introduces, as well, the measurement terminology that is common in most fields of science and engineering; that is, of the metrology and related ISO standards on software measurement.

Chapter 1: Introduction.

This chapter presents the current level of maturity of software measurement within the software engineering discipline.

Chapter 2: From Measurement Methods to Quantitative Models: A Measurement Context Model.

This chapter presents a model to understand the key concepts of software measurement as well as the measurement terminology that is consistent with measurement in all disciplines. This chapter also discusses the process necessary to design a software measurement method.

Chapter 3: Metrology and Quality Criteria in Software Measurement.

This chapter presents the set of classical concepts in metrology, and presents various definitions and quality criteria in classical measurement.

Chapter 4: Quantification and Measurement are not the Same.

This chapter presents some of the differences between quantification and measurement, and establishes a parallel with the ISO 15939 Measurement Information Model.

Chapter 5: The Design of Software Measurement Methods.

This chapter presents the key concepts and steps required to design and evaluate software measurement methods, including defining the measurement principle in software measurement up to post-design activities.

Part 2: Some Popular Software Measures: How Good Are They?

Some software measures are currently popular in the industry, often because they are easy to collect or because they appear to take into account a large number of the practitioners concerns. However, in software measurement, being popular and widely quoted is not synonym to being good. Part 2 uses in chapters six through ten the criteria from Part 1 to illustrate some of the major weaknesses in the design of a few of the software measures that are either widely used or widely quoted in the software industry.

Chapter 6: Cyclomatic Complexity Number: Analysis of its Design

Chapter 7: Hasltead’s Metrics: Analysis of their Designs

Chapter 8: Function Points: Analysis of their Design.

Chapter 9: Use Case Points: Analysis of their Design.

Chapter 10: ISO 9126: Analysis of its Quality Models and Measures.

Part 3: The Design of COSMIC—ISO 10761

Part 3 illustrates in chapters eleven and twelve how the lessons learned from the analysis of the key concepts for the design of a software measure have been put into practice to design a software measurement method conformant to the ISO criteria for a measurement method of the functional size of the software, that is the COSMIC—ISO 19761. Part 3 focuses on the design process rather than on the details of this specific measurement method.

Chapter 11: COSMIC: Design of an Initial Prototype.

This chapter illustrates how this software measure of the functional size of software for real-time and embedded software was designed in response to an industry need. It describes in particular the process used to design the initial prototype of COSMIC, its field trials and its initial deployment.

Chapter 12: COSMIC—Scaling up and Industralization.

This chapter illustrates the additional effort to scale up COSMIC to increase its international acceptance and to bring it to be adopted as an international standard: ISO 19761. The key concepts of the COSMIC measurement method are also presented in this chapter.

Part 4: Other Issues in the Design of Software Measures

Part 4 illustrates in chapters thirteen and fourteen some additional issues that are traditional in measurement in day-to-day life, but that have not yet been seriously addressed in software measurement. Two specific examples are presented: convertibility across measurement design and measurement standard etalons.

Chapter 13: Convertibility across Measurement Methods

While numerous software measures are proposed for the same attributes, there is a scarcity of convertibility studies across alternative ways of measuring. This chapter presents a convertibility analysis across two functional size measurement methods: IFPUG Function Points and COSMIC Function Points.

Chapter 14: Design of Standard Etalons: The Next Frontier in Software Measurement

While measurement in science relies on well established standard etalons (such as for the meter and kilograms) to ensure the correctness and consistency of measurement results across contexts and countries, not a single standard etalon has yet been established for measuring software. This chapter looks at this next frontier in software measurement and reports on an initial attempt to design a first draft of a standard etalon for a referenced set of software requirements.

This book also contains three appendices:

AppendixA: List of Acronyms

AppendixB: Glossary of Terms in Software Measurement.

AppendixC: References

Additional material to complement the information contained in this book can be found at http://profs.logti.etsmtl.ca/aabran

If you are a software manager, you should:

If you are a software engineering practitioner or a software quality analystusing or planning to use existing software measures you should:

If you are in software process improvement or a researcherplanning to analyze existing software measures or to design new software measures or if you are taking an undergraduate or graduate course on software measurement you should:

This book is not about:

A compendium of all software measures:The purpose of this book is not to present an exhaustive list of measures of any type, or of a specific type (for instance on OO metrics).There exists already on the market a number of books presenting inventories of alternative measures, as well as hundreds of research papers on emerging designs, which at this stage would still be fairly immature.A compendium of software estimation models:This book does not list or discuss any of the estimation models for software.For instance, COCOMO [Boehm 1981, 2000] is an ‘estimation model’ which attempts to predict the relationships across a large number of factors. COCOMO is not about measurement but a lot more about experimentation (as in science) to build prediction models. COCOMO, for instance, should be used and evaluated as an estimation model. This will be discussed in another book looking into the design and evaluation of estimation models.A compendium of analyses of all software measures:This book presents from chapters six through ten analyses that have already been carried out in research and published at a number of international conferences.A large number of software metrics, such as the ones in (or derived from) Chidamber & Kemerer metrics suite [Chidamber 1993], has not yet been analyzed from a metrology perspective. The analysis from a metrology perspective of these other measures still has to be done.

COSMIC Function Points

The COSMIC Function Points have been adopted in 2003 as an international standard—ISO 19761—for measuring the functional size of software. Having been designed to meet metrology criteria, COSMIC Function Points are at times used in this book to illustrate a number of measurement concepts. For more details on the design of COSMIC Function Points, see Section 5 of Chapter 12.

ACKNOWLEDGMENTS

A number of collaborators, including colleagues in industry and university as well as PhD students, have helped me over the years improve my understanding of many of the concepts presented in this book, in particular:

ChapterCo-Contributor2: From Measurement Methods to Quantitative Models: A Measurement Context ModelDr. Jean-Philippe Jacquet (France)3: Metrology and Quality Criteria in Software MeasurementDr. Asma Sellami—University of Sfax (Tunisia)4: Quantification and Measurement are not the Same.Dr. Jean-Marc Desharnais—Ecole de technologie supérieure (Canada) & Bogaziçi University (Turkey)5: The Design of a Software Measurement MethodDr. Naji Habra—Facultés Universitaires Notre-Dame de la Paix—FUNDP, Namur (Belgium)6: Cyclomatic Complexity Number: Analysis of its DesignDr. Naji Habra—FUNDP (Belgium)7: Halstead’s Metrics: Analysis of their DesignsDr. Rafa Al-Qutaish—Alain University of Science and Technology, Abu Dhabi Campus, United Arab Emirates8: Function Points: Analysis of their Design 9: Use Case Points: Analysis of their designJoost Ouwerkerk—Expedia (Canada)10: ISO 9126: Analysis of its Quality Models and MeasuresDr. Rafa Al-Qutaish—Alain University of Science and Technology, Abu Dhabi Campus, United Arab Emirates11: COSMIC—Design of an Initial PrototypeD. St-Pierre, Dr. Desharnais, Dr. P. Bourque and M. Maya (École de technologie supérieure—University of Québec—Canada)12: COSMIC—Scaling up and IndustralizationC. Symons, M. O’Neil, P. Fagg, and a number of the COSMIC members of the measurement practices committee13: Convertibility Across Measurement MethodsDr Desharnais—Ecole de technologie supérieure (Canada) & Bogaziçi University Turkey14: Design of Standards Etalons: The Next Frontier in Software MeasurementDr. Adel Khelifi—University Al Hosn (United Arab Emirates)

Above all, this book is dedicated to all those who provided me with feedback and insights on software measures over the years and who are contributing, each in his or her own way, to the improvement of software measures as a foundation for sound, quantitatively-based decision making.

ABOUT THE AUTHOR

Dr. Alain Abran is a professor and the director of the research group in Software Engineering Management at the École de Technologie Supérieure (ETS)—Université du Québec, Montréal, Canada (www.gelog.etsmtl.ca)

He is a co-editor of the Guide to the Software Engineering Body of Knowledge (www.swebok.org). He is actively involved with software engineering standards with ISO/IEC JTC1 SC7—Software and System Engineering—and has been its international secretary in 2001–2003. He is chairman of the Common Software Measurement International Consortium (COSMIC).

Dr. Abran has more than 20 years of industry experience in information systems development and software engineering and 15 years of university teaching. He holds a PhD in electrical and computer engineering (1994) from the École Polytechnique de Montréal (Canada) and Master’s degrees in management sciences (1974) and electrical engineering (1975) from the University of Ottawa (Canada).

His research interests include software productivity and estimation models, software engineering foundations, software quality, software measurement, functional size measurement methods, software risk management and software maintenance management.

Most of his publications can be downloaded from: http://profs.logti.etsmtl.ca/aabran/Publications/index.html

Part 1: KEY CONCEPTS FOR THE DESIGN OF SOFTWARE MEASURES

1

INTRODUCTION

This chapter covers:

Software measurement: is it mature or not?Software measurement as a new technologyThe designs of software measures must be verifiedAdvanced Readings: Measurement within the Software Engineering Body of Knowledge

1.1. INTRODUCTION

In the field of software engineering, the term “metrics” is used in reference to multiple concepts; for example, the quantity to be measured (measurand1), the measurement procedure, the measurement results or models of relationships across multiple measures, or measurement of the objects themselves. In the software engineering literature, the term was, up until recently, applied to:

measurement of a concept: e.g. cyclomatic complexity [McCabe 1976],quality models: e.g. ISO 9126—software product quality, andestimation models: e.g. Halstead’s effort equation [Halstead 1977], COCOMO I and II [Boehm, 1981, 2000], Use Case Points, etc.

This has led to many curious problems, among them a proliferation of publications on metrics for concepts of interest, but with a very low rate of acceptance and use by either researchers or practitioners, as well as a lack of consensus on how to validate so many proposals.

The inventory of software metrics is at the present time so diversified and includes so many individual proposals that it is not seen as economically feasible for either the industry or the research community to investigate each of the hundreds of alternatives proposed to date (for instance, to measure software quality or software complexity).

This chapter illustrates the immaturity of both the software measures themselves and the necessity to verify the designs of these measures.