A simulation-based method for obtaining numerical estimates of the reliability of N-version, real-time software is proposed. An extended stochastic Petri net is used to represent the synchronization structure of N versions of the software, where dependencies among versions are modeled through correlated sampling of module execution times. The distributions of execution times are derived from automatically generated test cases that are based on mutation testing. Since these test cases are designed to reveal software faults, the associated execution times and reliability estimates are likely to be conservative. Experimental results using specifications for NASA's planetary lander control software suggest that mutation-based testing could hold greater potential for enhancing reliability than the desirable but perhaps unachievable goal of independence among N versions. Nevertheless, some support for N-version enhancement of high-quality, mutation-tested code is also offered. Mutation analysis could also be valuable in the design of fault-tolerant software systems.