5.2 Mapping from Non-recursive DCharts to DEVS

Intuitively, since non-recursive DCharts can be mapped to statecharts with variables, and statecharts with variables are at most as powerful as DEVS, one should be able to map DCharts to DEVS. Spencer Borland has already shown the mapping from statecharts to DEVS in his Master's thesis [9]. A general method that transforms statecharts models to DEVS models has been found.

Mapping variables to DEVS is trivial, since DEVS supports variables in its nature. The state space of a statecharts with variables is transformed into $S \times v_1 \times v_2 \times \ldots \times v_n$, where $S$ is the state set of the statecharts, and $v_1,v_2,\ldots,v_n \in V$ are the variables that appear in the model. The total state space is the Cartesian product of the state space of the enumerable states and the state space of all those variables. This total state space, which is usually infinite and continuous, becomes the state space of a DEVS model. The values of the variables are changed by the DEVS' external transitions and internal transitions as a modification on the current state.

From the discussion above, since original statecharts have been mapped to DEVS, and variables can be easily transformed into DEVS states, statecharts with variables can be mapped to DEVS models. As a result, non-recursive DCharts can also be mapped to DEVS models. This proves that non-recursive DCharts are at most as powerful as DEVS.