Tuesday, June 04, 2002
Back to Me? Linda is absolutely correct - the foundation of any process improvement or quality initiative is measurement. There are two excellent books on the subject that are specifically for software professionals:
- Applied Statistics for Software Managers. If you're working in SQA or managing software development projects this book is an excellent introductory text to statistical analysis.
What I like about this book is that it's a tutorial on the statistical skills and knowledge that you'll need, and it combines this learning goal with the basics of software metrics and how they can be employed to measure productivity, estimate projects, and manage costs and organizational quality. The core approach is data analysis, and the main tools that the book employs are multi-variate techniques, regression analysis and correlation and sensitivity tests. The author has a talent for clearly explaining a dry subject, and while it will take a good deal of effort to master the material because of its nature, the excellent writing and illustrations will make it easy to quickly grasp statistical fundamentals and put them to use.
The lessons are taught within the framework of four case studies that are realistic and apply to the real world. The case study topics are: productivity analysis, analysis of time to market factors, development cost analysis, and maintenance cost drivers. These cover the full range of both internal development and product-line software engineering. I especially like the inclusion of maintenance costs as a topic of study because this area contributes significantly to total costs of ownership, but is often overlooked.
- Measuring the Software Process. This book contains the keys to meeting core CMM level 5 requirements, which defines key processes for optimizing and continuous improvement, and for achieving 6-sigma processes. However, you need not be striving for either (or both) of these goals to use the techniques and approach in this book to full advantage.
Implementing and employing statistical process controls are the basis of this book. The authors lead you through the steps and techniques necessary to implement and use SPC, starting with background information on processes and a process measurement framework, and moving through topics such as planning your measurement strategy, data collection and analysis, and developing and interpreting process behavior charts using common SPC chart types. The most common controls are x-bar (mean) and r (range) charts. Be aware that any SPC approach requires two conditions to be met:
- defined processes
- the processes are in statistical control (meaning that the data points being measured have settled into a normal distribution that are randomly clustered around a mean and have defined upper and lower control limits)
This book requires knowledge and skills in basic statistical analysis. If you require a refresher I recommend reading Visual Statistics before tackling this book.
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