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 metrics is to provide a tool that can be used by the system maintenance team to identify critical artifacts of the underlying system and to allow for better planning of the change process. The provided metrics is based on Extended Finite State Machine models (EFSM), and it provides two measures to identify critical transitions. The experimental 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.
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This research is sponsored by Kuwait Foundation for the Advancement of Science (KFAS) as part of project P116-18QA-01.
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© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Almasri, N., Tahat, L. (2018). Model-Based Metrics to Estimate Maintainability. In: Miraz, M., Excell, P., Ware, A., Soomro, S., Ali, M. (eds) Emerging Technologies in Computing. iCETiC 2018. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 200. Springer, Cham. https://doi.org/10.1007/978-3-319-95450-9_5
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DOI: https://doi.org/10.1007/978-3-319-95450-9_5
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