3.3 Software Quality Metrics

	Measurement of the various aspects of software quality is considered to be an effective tool for the support of
	control activities and the initiation of process improvements during the development and the maintenance
	phases.

These measurements apply to the functional quality, productivity, and organizational aspects of the project.

The software quality metrics can be classified as the following:

The first classification category distinguishes between life cycle and other phases of the software system:

Process metrics, related to the software development process.

Product metrics, related to software maintenance.

The second classification category refers to the subjects of the measurements:

Quality.

Timetable.

Effectiveness (of error removal and maintenance services).

Productivity.

3.3 Software Quality Metrics

Software Process Quality Metrics

Software process quality metrics may be classified into two classes:

Error density metrics.

Error severity metrics.

A-Error density metrics

		This section describes six different types of metrics. Calculation of error density metrics involves two
		measures:

			Software volume measures. Some density metrics use the number of lines of code while others apply
			function points.

			Errors counted measures. Some relate to the number of errors and others to the weighted number of
			errors. Weighted measures that ascertain the severity of the errors are considered to provide more
			accurate evaluation of the error situation. A common method applied to arrive at this measure is
			classification of the detected errors into severity classes, followed by weighting each class. The weighted
			error measure is computed by summing up multiples of the number of errors found in each severity class
			by the adequate relative severity weight.

3.3 Software Quality Metrics

		Example 1: This example demonstrates the calculation of the number of code errors (NCE) and the
		weighted number of code errors (WCE). A software development department applies two alternative
		measures, NCE and WCE, to the code errors detected in its software development projects.

Three classes of error severity and their relative weights are also defined:

		The code error summary for the department's Atlantis project indicated that there were 42 low severity
		errors, 17 medium severity errors, and 11 high severity errors.

3.3 Software Quality Metrics

Calculation of NCE and WCE gave these results:

3.3 Software Quality Metrics

Software Process Timetable Metrics

	Software process timetable metrics may be based on accounts of success (completion of milestones per
	schedule) in addition to failure events (non completion per schedule).

An alternative approach calculates the average delay in completion of milestones.

The metrics presented here are based on the two approaches;

The TTO and ADMC metrics are based on data for all relevant milestones scheduled in the project plan.

	In other words, only milestones that were designated for completion in the project plan stage are considered in
	the metrics' computation.

	Therefore, these metrics can be applied throughout development and need not wait for the project's
	completion.

Error Removal Effectiveness Metrics

	Software developers can measure the effectiveness of error removal by the software quality assurance system
	after a period of regular operation (usually 6 or 12 months) of the system.

	The metrics combine the error records of the development stage with the failures records compiled during the
	first year (or any defined period) of regular operation.

3.3 Software Quality Metrics

Software Process Productivity Metrics

	This group of metrics includes "direct" metrics that deal with a project's human resources productivity as well
	as "indirect" metrics that focus on the extent of software reuse.

Software reuse substantially affects productivity and effectiveness.

	An additional term - "benchmarking software development productivity"- has recently entered the list of metrics
	used to measure software process productivity (see Maxwell, 2001; Symons, 2001).

Product Metrics

	Product metrics refer to the software system's operational phase - years of regular use of the software system
	by customers, whether "internal" or "external" customers, who either purchased the software system or
	contracted for its development.

	In most cases, the software developer is required to provide customer service during the software's operational
	phase.

3.3 Software Quality Metrics

Customer services are of two main types:

Help desk services (HD)

			Software support by instructing customers regarding the method of application of the software and
			solution of customer implementation problems.

			Demand for these services depends to a great extent on the quality of the user interface as well as the
			quality of the user manual and integrated help menus.

Corrective maintenance services

			Correction of software failures identified by customers/users or detected by the customer service team
			prior to their discovery by customers.

The number of software failures and their density are directly related to software development quality.

			It is recommended that all software failures detected by the customer service team be recorded as
			corrective maintenance calls to achieve the completeness of information and better control of failure
			correction.

3.3 Software Quality Metrics

	Commonly, all customer services - namely, HD and corrective maintenance services - are provided to
	customers/users by a software support center.

It is expected that very few customer calls will be related to identify failures.

In other words, most of the software support center's customer calls will be "nonfailure" calls.

	For those calls that deal with an identified failure and for cases where the maintenance team has detected a
	failure, a failure report is expected.

	The difference between the two types is that HD metrics are based on all customer calls while corrective
	maintenance metrics are based on failure reports.

	Generally product metrics rely on performance records compiled during one year (or any other specified period
	of time).

	This policy enables comparisons of successive years in addition to comparisons between different units and
	software systems.

3.3 Software Quality Metrics

The array of software product metrics presented here is classified as follows:

HD quality metrics

HD productivity and effectiveness metrics

Corrective maintenance quality metrics

Corrective maintenance productivity and effectiveness metrics.

It should be remembered that software maintenance activities include:

Corrective maintenance - correction of software failures detected during regular operation of the software.

Adaptive maintenance - adaptation of existing software to new customers or new requirements.

		Functional improvement maintenance - addition of new functions to the existing software, improvement of
		reliability, etc.

In the metrics presented here we limit our selection to those that deal with corrective maintenance.

	For other components of software maintenance, the metrics suggested for the software development process
	(process metrics) can be used as is or with minor adaptations.