What Are Software Metrics?

Software metrics are an integral part of the state-of- the-practice in software engineering.  More and more customers are specifying software and/or quality metrics reporting as part of their contractual requirements. Industry standards like ISO 9000 and industry models like the Software Engineering Institute’s (SEI) Capability Maturity Model Integrated (CMMI®) include measurement.  Companies are using metrics to better understand, track, control and predict software projects, processes and products.

The term software metrics means different things to different people. When we buy a book or pick up an article on software metrics, the topic can vary from project cost and effort prediction and modeling, to defect tracking and root cause analysis, to a specific

test coverage metric, to computer performance modeling. These are all examples of metrics when the word is used as a noun.

I prefer the activity based view taken by Goodman.  He defines software metrics as, "The continuous application of measurement-based techniques to the software development process and its products to supply meaningful and timely management information, together with the use of those techniques to improve that process and its products." [Goodman-93] Figure 1, illustrates an expansion of this definition to include software-related services such as installation and responding to customer issues. Software metrics can provide the information needed by engineers for technical decisions as well as information required by management.

If a metric is to provide useful information, everyone involved in selecting, designing, implementing, collecting, and utilizing it must understand its definition and purpose. This paper outlines twelve steps to selecting, designing and implementing software metrics in order to insure this understanding.

Software Metrics

Philosophy:

It has been noted frequently that we are experiencing a software crisis, characterized by our inability to 

produce correct, reliable software within budget and on time. No doubt, many of our failures are caused by the inherent complexity of the software develop- ment process, for which there often is no analytical description. These problems can be ameliorated, however, by improving our software management capabilities. This requires both the development of improved software metrics and improved utilization of such metrics.

ware properties to be measured. As a result, the same metric has been used to measure very different software properties. Moreover, we have virtually no theoretical models and a multitude of metrics, only a few of which have enjoyed any widespread use or acceptance.

Faced with this situation, the author has chosen to

indicate the great diversity of metrics that have been proposed and to discuss some of the most common ones in detail. In the process, the underlying as- sumptions, environment of application, and validity of various metrics are examined. The author be- lieves that current metrics and models are far from perfect, but that properly applied metrics and models can provide significant improvements in the soft- ware development process

Software Metrics

 Capsule Description

Effective management of any process requires quan- tification, measurement, and modeling. Software metrics provide a quantitative basis for the develop- ment and validation of models of the software devel- opment process. Metrics can be used to improve software productivity and quality. This module in- troduces the most commonly used software metrics and reviews their use in constructing models of the software development process. Although current metrics and models are certainly inadequate, a num- ber of organizations are achieving promising results through their use. Results should improve further as we gain additional experience with various metrics and models.

ware properties to be measured. As a result, the same metric has been used to measure very different software properties. Moreover, we have virtually no theoretical models and a multitude of metrics, only a few of which have enjoyed any widespread use or acceptance.

Faced with this situation, the author has chosen to

indicate the great diversity of metrics that have been proposed and to discuss some of the most common ones in detail. In the process, the underlying as- sumptions, environment of application, and validity of various metrics are examined. The author be- lieves that current metrics and models are far from perfect, but that properly applied metrics and models can provide significant improvements in the soft- ware development process.