A Guide to Selecting Software Measures and Metrics

by Capers Jones

Overview

Going where no book on software measurement and metrics has previously gone, this critique thoroughly examines a number of bad measurement practices, hazardous metrics, and huge gaps and omissions in the software literature that neglect important topics in measurement. The book covers the major gaps and omissions that need to be filled if data about software development is to be useful for comparisons or estimating future projects.

Among the more serious gaps are leaks in reporting about software development efforts that, if not corrected, can distort data and make benchmarks almost useless and possibly even harmful. One of the most common leaks is that of unpaid overtime. Software is a very labor-intensive occupation, and many practitioners work very long hours. However, few companies actually record unpaid overtime. This means that software effort is underreported by around 15%, which is too large a value to ignore. Other sources of leaks include the work of part-time specialists who come and go as needed. There are dozens of these specialists, and their combined effort can top 45% of total software effort on large projects.

The book helps software project managers and developers uncover errors in measurements so they can develop meaningful benchmarks to estimate software development efforts. It examines variations in a number of areas that include:

• Programming languages
• Development methodology
• Software reuse
• Functional and nonfunctional requirements
• Industry type
• Team size and experience

Filled with tables and charts, this book is a starting point for making measurements that reflect current software development practices and realities to arrive at meaningful benchmarks to guide successful software projects.

Product Details

ISBN-13:	9781138033078
Publisher:	Taylor & Francis
Publication date:	03/16/2017
Pages:	372
Product dimensions:	6.12(w) x 9.19(h) x (d)

Table of Contents

Preface vii

Acknowledgments xi

About the Author xiii

1 Introduction 1

2 Variations in Software Activities by Type of Software 17

3 Variations in Software Development Activities by Type of Software 29

4 Variations in Occupation Groups, Staff Size, Team Experience 35

5 Variations due to Inaccurate Software Metrics That Distort Reality 45

6 Variations in Measuring Agile and CMMI Development 51

7 Variations among 60 Development Methodologies 59

8 Variations in Software Programming Languages 63

9 Variations in Software Reuse from 0% to 90% 69

10 Variations due to Project, Phase, and Activity Measurements 77

11 Variations in Burden Rates or Overhead Costs 83

12 Variations in Costs by Industry 87

13 Variations in Costs by Occupation Group 93

14 Variations in Work Habits and Unpaid Overtime 97

15 Variations in Functional and Nonfunctional Requirements 105

16 Variations in Software Quality Results 115

Missing Software Defect Data 116

Software Defect Removal Efficiency 117

Money Spent on Software Bug Removal 119

Wasted Time by Software Engineers due to Poor Quality 121

Bad Fixes or New Bugs in Bug Repairs 121

Bad-Test Cases (An Invisible Problem) 122

Error-Prone Modules with High Numbers of Bugs 122

Limited Scopes of Software Quality Companies 123

Lack of Empirical Data for ISO Quality Standards 134

Poor Test Case Design 135

Best Software Quality Metrics 135

Worst Software Quality Metrics 136

Why Cost per Defect Distorts Reality 137

Case A Poor Quality 137

Case B Good Quality 137

Case C Zero Defects 137

Be Cautious of Technical Debt 139

The SEI CMMI Helps Defense Software Quality 139

Software Cost Drivers and Poor Quality 139

Software Quality by Application Size 140

17 Variations in Pattern-Based Early Sizing 147

18 Gaps and Errors in When Projects Start. When Do They End? 157

19 Gaps and Errors in Measuring Software Quality 165

Measuring the Cost of Quality 179

20 Gaps and Errors due to Multiple Metrics without Conversion Rules 221

21 Gaps and Errors in Tools, Methodologies, Languages 227

Appendix 1 Alphabetical Discussion of Metrics and Measures 233

Appendix 2 Twenty-Five Software Engineering Targets from 2016 through 2021 333

Suggested Readings on Software Measures and Metric Issues 343

Summary and Conclusions on Measures and Metrics 349

Index 351