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Mobile application testing requires the use of a model to guide such efforts as test selection and test verification. Often, such models are implicit, existing only in the head of a human tester, applying test inputs in an ad hoc fashion. The mental model testers build encapsulates application behavior, allowing testers to understand the application’s capabilities and more effectively test its range of possible behaviors. When these mental models are written down, they become sharable, reusable testing artifacts. In this case, testers are performing what has become to be known as model-based testing. Model-based testing is a new and evolving technique for generating a suite of test cases from requirements. Testers using this approach concentrate on a data model and generation infrastructure instead of hand-crafting individual tests. In this paper we discuss the characteristics of automotive model-based development processes, the consequences for test development and the need to reconsider testing procedures in practice. Furthermore, we introduce the test tool HMBT (Hybrid Model Based Testing) which masters the complexity of model-based testing in the automotive domain. To illustrate this statement we present a small mobile applications case study. HMBT is based on graphical test models that are not only easy to understand but also powerful enough to express very complex, fully automated closed loop tests in real-time.