Model-based design of embedded control systems becomes more and more popular. Control engineers prefer to use MATLAB Simulink and suitable automatic code generators for the development and deployment of the software. Simulink provides a vast variety of functionally equivalent design solutions. For instance, a proportional-integral-derivative (PID) controller can be implemented in Simulink using i) separate blocks for the P, I, D terms, ii) a dedicated Discrete PID Controller block, iii) a Discrete Transfer Function block, or iv) a Discrete State-Space block. However, these functionally equivalent implementations of the PID controller show completely different reliability properties. This article introduces a new analytical method for the overall system reliability evaluation under data errors occurred in RAM and CPU. The method is based on a stochastic dual-graph error propagation model that captures control and data flow structures of the assembly code and allows the computation of system level reliability metrics in critical system outputs for specified faults probabilities. The analytical method enables an early system reliability evaluation. Also, application of this analytical method to possible implementations of the particular control algorithm helps to select the most reliable one.