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This paper presents a hybrid approach for modeling and assessing the performance of embedded systems. Toward this objective, we pursue an implementation independent methodology where system behavior is represented by executable models that are based on both analytical and simulation methods. To illustrate and validate our approach we apply it to the design of a robotic system for the artificial insemination of endangered species. The solution adopted reduces assessment time by modeling system behavior only in terms of the performance metrics of interest. The two performance metrics used to assess the application considered are the velocity of the robotic arm tied to the sperm membrane and the force with which the arm hits the target (i.e., the egg's membrane). Formally, the desired behavior is captured through a C/C++ executable model, which uses finite state machines (FSM) as the underlying model of computation (MOC). The results obtained demonstrate the robustness of the proposed method both in terms of design time and accuracy.