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As production automation systems have been and are becoming more and more complex, the task of quality assurance is increasingly challenging. Model-based testing is a research field addressing this challenge and many approaches have been suggested for different applications. The goal of this paper is to review these approaches regarding their suitability for the domain of production automation in order to identify current trends and research gaps. The different approaches are classified and clustered according to their main focus which is either testing and test case generation from some form of model automatons, test case generation from models used within the development process of production automation systems, test case generation from fault models or test case selection and regression testing.

Review of Model-Based Testing Approaches in Production Automation and Adjacent Domains—Current Challenges and Research Gaps