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Consider an NMR system with N-Version software, and a non-diagnosing medianselect voter. There is a non-zero "correlation" probability that a fault in one software module also occurs in another software module simultaneously. The probability of a triple software fault is nil. The system has the following parameters: $λ_{2}=$ Processor fault rate, $λ_{s}=$ Software module fault rate, $λ_{y}=$ Voter fault rate, $P_{c}=$ Probability that a software fault affects two versions. Draw a SAN model (Petrinet) for determining the unreliability of this system. Be sure all timed-transitions, transition rates, and inhibitor arcs (input gates) are clearly shown and defined. Notes: - To draw the model, you may need to take advantage of the following submodel (example). The model shows that once the transition T1 fires, e.g., due to a component failure, a token will be placed in P2 or P3 with probability of 0.7 or 0.3 , respectively. For instance, a token will be placed in $P2$ with probability of 0.7 and no token in P3. - A median-select, after sorting, simply selects the middle value from $N$ results (Even if a processor crashes completely, its null result will be one of the $N$ results). The median-select ensures the middle value selected is within the range of the correct results - Obviously this happens if at least half of the versions are still functioning. - A non-diagnosing voter means that the voter does not attempt to diagnose which version result is correct, or whether the median selected is correct or not.

To model the unreliability of the NMR system with N-Version software and a non-diagnosing median-select voter using a Stochastic Petri Net (SPN), we can define the following places, transitions, and arcs:

Places:

1. P0: Initial state