Evaluation of fault injection tools for reliability estimation of microprocessor-based embedded systems

Statistical fault injection is widely used to estimate the reliability of mission-critical microprocessor-based systems when exposed to radiation and to evaluate the performance of fault mitigation strategies. However, further research is needed to gain a better understanding of the accuracy of the results and the feasibility of their application under realistic radiation conditions. In this article, an understanding of scenarios in which Instruction Set Architecture simulators or emulators may be relied upon for realistic statistical fault injection campaigns is advanced. An analysis is presented of the results from two simulation-based fault injection tools versus a set of fault emulation results on a real processor. The conclusions of the analysis assist the selection of the most efficient tool and method for testing many different software-based fault mitigation techniques within reasonable time periods and at affordable costs throughout an irradiation campaign. In particular, it was established that a partially ordered set of relations could be defined on the basis of statistical fault injection in relation to the effects of different versions of an application and a given simulator that remained unaltered during the irradiation experiments. The tests were conducted with a Texas Instruments MSP430 microcontroller to perform both fault injection campaigns and irradiation experiments using neutrons at the Los Alamos Neutron Science Center (LANSCE) Weapons Neutron Research Facility at Los Alamos, USA.

Automated summary

This article advances the understanding of scenarios where Instruction Set Architecture simulators or emulators can be relied upon for realistic statistical fault injection campaigns. It presents an analysis of simulation-based fault injection tools compared to fault emulation results on a real processor. The conclusions assist in selecting the most efficient tool and method for testing software-based fault mitigation techniques.