Software metrics: using measurement theory to describe the properties and scales of static software complexity metrics
Horst Zuse, P. Bollmann
Abstract
Open-access reader
Horst Zuse, P. Bollmann
Abstract
Open-access reader
Over the last decade many software metrics have been introduced by researchers and many software tools have been developed using software metrics to measure the "quality" of programs. These metrics for measuring productivity, reliability, maintainability, and complexity, for example, are vital to software development planning and management. In this paper a new approach is presented to describe the properties of the software metrics and their scales using measurement theory. Methods are shown to describe a software complexity metric as an ordinal, an interval or a ratio scale. The use of this concept is shown by application to the Metric of McCabe. These results are very important for selecting appropriate software metrics for software measurement and for developing tools which use software metrics to evaluate the "quality" of software.
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Over the last decade many software metrics have been introduced by researchers and many software tools have been developed using software metrics to measure the "quality" of programs. These metrics for measuring productivity, reliability, maintainability, and complexity, for example, are vital to software development planning and management. In this paper a new approach is presented to describe the properties of the software metrics and their scales using measurement theory. Methods are shown to describe a software complexity metric as an ordinal, an interval or a ratio scale. The use of this concept is shown by application to the Metric of McCabe. These results are very important for selecting appropriate software metrics for software measurement and for developing tools which use software metrics to evaluate the "quality" of software.
Key concepts: Software metric, Computer science, Software sizing, Verification and validation, Software construction, Software measurement, Software quality, Software development