Optimization methods for the fault injection tool SEInjector

In the space environment, computer is easily affected by high-energy particle irradiation, which may incur transient faults, also known as soft errors. Soft error is one of the serious problems for space computation, making the space computer system unreliable. Many efforts have been made in this research area. One of them is fault injection technique, an experimental method for software reliability evaluation. To evaluate the software reliability running on x86/x64 architecture, we have designed a fault injection framework SEInjector. Like many other fault injection tools, SEInjector has been designed as making statistically sampling by randomized selection of fault locations. But, in some cases, we need detail analysis for fault-tolerance related design decisions, and full fault space exploration is required. However, the vast fault space makes the complete fault space exploration impractical. In this paper, we propose several methods to prune the fault space. We prune the known-outcome faults by the registers usage information, and we prune faults leading to the same outcome by classify the faults into equivalence classes. Experiment and calculation show that using these methods, the full fault space coverage time consumption can be largely reduced.