Themes of This Book

This book has several themes. First, balancing theory, techniques, and real-life examples, it provides practical guidelines in the practice of quality engineering in software development. Although equations and formulas are involved, the focus is on the understanding and applications of the metrics and models rather than mathematical derivations. Throughout the book, numerous real-life examples are used from the software development laboratory at IBM Rochester, Minnesota, home of the AS/400 and the IBM eServer iSeries computer systems, and from other companies in the software industry. IBM Rochester won the Malcolm Baldrige National Quality Award in 1990. A number of metrics described in this book were being used at that time, and many have been developed and refined since then. All metrics are substantiated by ample implementation experience. IBM Rochester develops and delivers numerous projects of different sizes and types every year, including very large and complex as well as small ones; and they range from firmware, to operating systems, to middleware, to applications.

Second, I attempt to provide a good coverage of the various types of metrics and models in the emerging field of software quality engineering. In addition to general discussions about metrics and techniques, this book categorizes and covers four types of metrics and models: (1) quality management models; (2) software reliability and projection models; (3) complexity metrics and models; and (4) customer-view metrics, measurements, and models. These metrics and models cover the entire software development process from high-level design to testing and maintenance, as well as all phases of reliability. Furthermore, although this book is not on total quality management (TQM), it is a major consideration in the coverage of metrics. The philosophy of TQM is the linking of product quality and customer satisfaction for the purpose of achieving long-term success. TQM is the reason for including two chapters on customer-view metrics and measurements—availability metrics and customer satisfaction—in addition to the many chapters on product and process metrics. In other discussions in the book, the customer's perspective is included where appropriate.

Third, by linking metrics and models to quality improvement strategies and improvement actions, we attempt to focus on using, not just describing, metrics. A framework for interpreting in-process metrics and assessing in-process quality status—the effort/outcome model—is presented. The direct link between a recommended quality strategy during development and the defect-removal model is shown. Examples of actions tied to specific metrics and analysis are given. Furthermore, to illustrate the metrics, many figures and graphs are used. This is a reflection of the fact that in real-life project and quality management, a clear visual presentation often improves understanding and increases the effectiveness of the metrics.

Fourth, following up on quality and process improvement at a more general level than specific metric discussions, the book continues with chapters that discuss the inprocess quality assessment process, a method for conducting software project assessments, practical advice on process improvement dos and don'ts, and quantitative analysis of software process improvement. The common thread underlying these chapters, as with other chapters on metrics and models, is practical experience with industry projects.


My Best Regards,