Abstract. Software maintenance is becoming more challenging with the increased complexity of software and frequent applied changes to accommodate the rapidly changing technologies and user requirements. In this paper we provide model-based metrics to estimate the maintainability of state-based systems. The purpose of the provided metrics is to give the system maintenance team a tool to identify critical artifact of the underlying system and consequently to allow them to better plan and manage the change process. The provided metrics is based on Extended Finite State Machine models (EFSM), and it provides two measures to identify critical transitions in the model. The empirical study shows that the metrics is highly effective in spotting transitions that can cause severe propagation of a change when they are being changed, as well as transitions that are highly sensitive to changes applied to an EFSM model.
Keywords. Maintainability, EFSM, Critical Transitions, Sensitive Transitions
Acknowledgement. This research is sponsored by Kuwait Foundation for the Advancement of Science (KFAS) as part of project P116-18QA-01.