Document Type : Original Paper


Model-based testing (MBT) has attracted a lot of attention and has been extensively applied in different areas such as probabilistic systems, mobile systems, concurrent systems, real-time systems, software product lines, etc. However, MBT approaches have some limitations and challenges that are mostly related to the incompleteness, high level of abstraction, complexity, and also the informal nature of input models. In the literature, there are different studies addressing these problems. In this paper, we represent a framework for model-based test case generation approaches according to the aforementioned challenges. In this regard, firstly, we categorize different coverage criteria used in MBT, and then show that MBT approaches have three main steps: preprocessing, test scenario generation, and concrete test case generation. Finally, for each step, we represent its necessity and classify the proposed methods


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