An EFSM-Based Passive Fault Detection Approach

Extended Finite State Machine (EFSM)-based passive fault detection involves modeling the system under test (SUT) as an EFSM M, monitoring the input/output behaviors of the SUT, and determining whether these behaviors relate to faults within the SUT. We propose a new approach for EFSM-based passive fault detection which randomly selects a state in M and checks whether there is a trace in M starting from this state which is compatible with the observed behaviors. If a compatible trace is found, we determine that observed behaviors are not sufficient to declare the SUT to be faulty; otherwise, we check another unchecked state. If all the states have been checked and no compatible trace is found, we declare that the SUT is faulty. We use a Hybrid method in our approach which combines the use of both Interval Refinement and Simplex methods to improve the performance of passive fault detection.