State-Based Models in Model-Based Testing: A Systematic Review

Model-Based Testing (MBT) is an effective approach to automate test case generation process by utilizing different models of the System under Test (SUT). Many of the today's software systems are state-based and their behavior can be determined by their states. Such systems may respond differently to the same event in different states, and this makes testing them difficult. Among the various types of SUT models, state-based models have a significant role to test state-based system. In this paper, we conduct a systematic review of the most widely used state-based models in MBT. We discuss their strengths and weaknesses, highlight the challenges faced by them in order to effectively and efficiently generate test cases and summarize the existing studies in the literature which address these challenges.