Change Metrics

Ieasurement of software progress and quality is an extremely complex undertaking because of the large number of product, project, and personnel parameters that have an impact on software development efforts. It is probably impossible to specify a set of absolute definitions of software measurement that will satisfy most projects. However, several aspects of software measurement are generally applicable to almost all software projects.

This is the basic hypothesis of this metrics approach:

Key Points

▲ One of the most important characteristics of good software is its ease of change.

▲ Measuring and assessing the scrap and rework effort in a succession of software baselines provides useful insight into the convergence toward, or divergence from, acceptable quality and progress.

▲ Metrics extracted directly from the evolving technical artifacts provide a foundation for process instrumentation that enables consistent, accurate, and precise project control.

The most important characteristic of software is that it is "soft": The easier the software is to change, the easier it is to achieve any of its other required characteristics.

The core metrics are therefore centered on measurements of software change trends (scrap and rework) in the software artifacts throughout the life cycle. To manage most serious software efforts, the software project manager needs several context-independent metrics (for comparison with general expectations) and several con-text-dependent metrics.

I' developed much of this material in 1987 to rationalize the metrics program used for the CCPDS-R project, which is presented as a case study in Appendix D. The material was published [Royce, Walker, 1990] after three years of field experience had demonstrated its usefulness and resulted in several refinements. There have been many other attempts over the past 20 years to define measures of software quality. For several reasons, none has really caught on in practice, although there are some recurring themes that overlap my recommendations fairly well. Some recurring obstacles are the need for subjectivity and the cost of human resources required to collect and interpret metrics.

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