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Error propagation analysis is one of the main objectives of fault injection experiments. This analysis helps designers to detect design mistakes and to provide effective mechanisms for fault tolerant systems. However, error propagation analysis requires that the chosen fault injection technique provides a high degree of observability (i.e., the ability to observe the internal values and events of a circuit after a fault is injected). Simulation-based fault injection provides a high observability adequate for error propagation analysis. However, the performance of the simulation-based technique is inadequate to handle today's hardware complexity. As an alternative, FPGA-based fault injection... 

In this paper, we propose a very fast analytical approach to measure the overall circuit Soft Error Rate (SER) and to identify the most vulnerable gates and flip-flops. In the proposed approach, we first compute the error propagation probability from an error site to primary outputs as well as system bistables. Then, we perform a multi-cycle error propagation analysis in the sequential circuit. The results show that the proposed approach is four to five orders of magnitude faster than the Monte Carlo (MC) simulation-based fault injection approach with 92% accuracy. This makes the proposed approach applicable to industrial-scale circuits