Abstract—A variety of tools today support the dynamic execution/simulation of models within a single modeling environment. However, they all suffer from limitations resulting from their implementation on a traditional, two-level modeling platform. The most prominent of these is the inability to represent the specification of the modeling language, the domain model and model execution state at the same time in a uniform and seamless manner. They therefore invariably have to resort to some kind of ad hoc extension mechanism or workarounds to represent all three levels, with corresponding increases in accidental complexity and potential for misunderstandings. In this paper we demonstrate how deep modeling environments provide a conceptually cleaner and more powerful environment for model execution and simulation thanks to their inherent support for the representation of arbitrary numbers of classification levels, and the ability to define customizable, domain specific languages with...