HSFI: Accurate Fault Injection Scalable to Large Code Bases

Abstract

When software fault injection is used, faults are typically inserted at the binary or source level. The former is fast but provides poor fault accuracy while the latter cannot scale to large code bases because the program must be rebuilt for each experiment. Alternatives that avoid rebuilding incur large run-time overheads by applying fault injection decisions at run-time. HSFI, our new design, injects faults with all context information from the source level and applies fault injection decisions efficiently on the binary. It places markers in the original code that can be recognized after code generation. We implemented a tool according to the new design and evaluated the time taken per fault injection experiment when using operating systems as targets. We can perform experiments more quickly than other source-based approaches, achieving performance that come close to that of binary-level fault injection while retaining the benefits of source-level fault injection.