Validating Quality Metrics of State Machine Models
DOI:
https://doi.org/10.59421/joeats.v3i2.2534Keywords:
Software engineering, Model-based development, software quality, Model ttransformation, Software developmentAbstract
Software metrics are widely used to measure the quality of software and to give an early indication of the efficiency of the development process in industry. There are many well-established frameworks for measuring the quality of source code through metrics, but limited attention has been paid to the quality of software models. In this article, we introduce new metrics that are tailored to measure the quality of models of state machines and then apply the metrics to evaluate the quality of state machine models specified using the Analytical Software Design (ASD) tooling. We discuss how we applied a number of metrics to ASD models in an industrial setting and report about results and lessons learned while collecting these metrics. Furthermore, we recommend some quality limits for each metric and validate them on models developed in a number of real industrial projects. This paper extends [19] by providing a formal and empirical validation of the metrics and their related limits. The results of our work provide a framework to measure the quality of state machine models, developed in ASD, and give a basis for future research on introducing quality metrics for other type of models of which quality metrics are missing.
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