Quantifying Software: Global and Industry Perspectives, 1st Edition (Hardback) book cover

Quantifying Software

Global and Industry Perspectives, 1st Edition

By Capers Jones

Auerbach Publications

533 pages

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pub: 2017-10-20
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Description

Software is one of the most important products in human history and is widely used by all industries and all countries. It is also one of the most expensive and labor-intensive products in human history. Software also has very poor quality that has caused many major disasters and wasted many millions of dollars. Software is also the target of frequent and increasingly serious cyber-attacks.

Among the reasons for these software problems is a chronic lack of reliable quantified data. This reference provides quantified data from many countries and many industries based on about 26,000 projects developed using a variety of methodologies and team experience levels. The data has been gathered between 1970 and 2017, so interesting historical trends are available.

Since current average software productivity and quality results are suboptimal, this book focuses on "best in class" results and shows not only quantified quality and productivity data from best-in-class organizations, but also the technology stacks used to achieve best-in-class results. The overall goal of this book is to encourage the adoption of best-in-class software metrics and best-in-class technology stacks. It does so by providing current data on average software schedules, effort, costs, and quality for several industries and countries.

Because productivity and quality vary by technology and size, the book presents quantitative results for applications between 100 function points and 100,000 function points. It shows quality results using defect potential and DRE metrics because the number one cost driver for software is finding and fixing bugs. The book presents data on cost of quality for software projects and discusses technical debt, but that metric is not standardized. Finally, the book includes some data on three years of software maintenance and enhancements as well as some data on total cost of ownership.

Table of Contents

1. Introduction to Quantifying Software Results

Software Revenue Generation

Operating Cost Reductions

Market Expansion.

2. The Origin and Evolution of Function Point Metrics.

The Origins of Function Point Metrics at IBM

New and Old Function Point Business Models

The Costs and Limitations of Standard Function Point Metrics

Expanding the Role and Advancing the Start Time of Function Point Analysis

The Current Business Model of Function Point Analysis in the United States.

A New Business Model for Function Point Analysis

The Hazards and Errors of LOC Metrics

A Short History of LOC Metrics

The Hazards and Errors of the Cost per Defect Metric

The Hazards of Multiple Metrics without Conversion Rules

Extending Function Point Logic into New Domains

Potential Expansion of Function Points to Other Business Topics

Example of Multi-Metric Software Economic Analysis

The Probable Effort and Skill Sets to Create Additional Metrics

Size and Cost Growth over Multiple-Year periods

3. Software Information Needed by Corporate Executives

Answers to the 60 Software Questions

Primary Software Metrics for High Precision

Supplemental Software Metrics for High Precision

Answers to the Current "Hot Topic" Questions

Answers to the Security, Quality, and Governance Questions

Answers to the Software Usage, Value, and User Satisfaction Questions

Answers to the Employee Satisfaction and Demographic Questions

Answers to the Software Economic Impact Questions

Answers to the Competitive Analysis Questions

Twenty-Five Quantitative Software Engineering Targets

Technologies Useful in Achieving Software Engineering Goals

Six Hazardous Software Engineering Methods to be Avoided

4. Metrics to Solve Problems and Improve Software Engineering Quality and Productivity

Reducing Software Wastage

Reuse of Certified Materials for Software Projects

Achieving Excellence in Software Quality Control

Excellent Quality Control

Average Quality Control

Poor Quality Control

Metrics to Improve Software Quality

Software Quality and Software Security

Software Quality and Technical Debt

SNAP Metrics for Nonfunctional Size

Economic Value of High Software Quality

A Primer on Manufacturing Economics and the Impact of Fixed Costs

Software’s Lack of Accurate Data and Poor Education on Quality and Cost of Quality

Summary and Conclusions on Metrics for Problem-Solving

Improving Software Project Management Tools and Training

Project Management Knowledge Acquisition.

The History of Software Project Management Tools

Usage Patterns of Software Project Management Tools

Recent Evolution of Software Project Management Tools

The Costs and Value of Software Project Management Tools

The Future of Software Project Management Tools

5. Measures, Metrics, and Management

Improving Software Project Management Tools and Training

Summary and Conclusions on Software Project Management

6. 50 Years of Global Software Benchmark Results

Measuring U.S. Software Productivity and Quality

Life Expectancy of Software Benchmark Data

U.S. Software Benchmark Results

Software Cost Drivers

Phase-Based Costs versus Activity-Based Costs

The Strange Mystery of Why Software Has 3000 Programming Languages

U.S. Industry Work Hour Variations

U.S. Industry Productivity and Quality Results circa 2017

Comparing Software Globally

Topics that Cannot Be in Benchmarks due to Laws or Union Regulations

Examples of Three Software Benchmarks

Benchmark Section 0: Executive Summary

Benchmark Section 1: Input Data

Benchmark Section 2: Output Data Schedule, Effort, and Cost Benchmark Data

Benchmark Section 3: Technology Stack Evaluation

Benchmark Section 4: Topics Observed During Benchmark Process

Benchmark Section 5: Maintenance, Enhancement, and Support Benchmarks

7. Advancing Software Benchmark Technology

Synthetic Benchmarks Using Parametric Estimation to Improve

Speed and Accuracy

Measuring Brand New Tools, Methods, and Programming Languages

Executive Interest Levels in Software Benchmark Types

Software Benchmark Providers

About the Author

Capers Jones is currently vice president and chief technology officer of Namcook Analytics LLC (www.Namcook.com). Namcook Analytics LLC designs leading edge risk, cost, and quality estimation and measurement tools. Software Risk Master (SRM) is the company’s advanced estimation tool with a patent-pending early sizing feature that allows sizing before requirements via pattern matching. Namcook Analytics also collects software benchmark data and engages in longer range software process improvement, quality, and risk assessment studies. These Namcook studies are global and involve major corporations and some government agencies in many countries in Europe, Asia, and South America.

Subject Categories

BISAC Subject Codes/Headings:
COM032000
COMPUTERS / Information Technology
COM051230
COMPUTERS / Software Development & Engineering / General
MAT000000
MATHEMATICS / General