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Range based system simulations are increasingly preferred in recent years to cope with the performance issues inherent with standard multi-run simulations. Traditionally, deviations of nominal system parameters are considered statistically by steadily varying the system parameters and simulating all of these parameter space realizations in multiple simulation runs. In range based or semi-symbolic simulations, deviations of system parameters are modeled in continuous ranges expressed as symbolic quantities. Therefore, a range based system simulation achieves in one simulation run the result for all the modeled parameter deviations, thus significantly reducing the computation effort. This work uses a semi-symbolic simulation environment to obtain a range based system response. Subsequently the symbolic labeling of ranges is used to trace back the resulting sub-ranges of the system response to their respective parameter origin to identify potential refinement candidates. Based on this capability a refinement design flow is introduced which allows by refinements to improve the robustness and accuracy of cyber physical systems. Identifying refinement candidates is manifold and is demonstrated in an example by assessing a communication receiver SNR metric.