Improving Fault Injection of Soft Errors Using Program Dependencies

Research has shown that modern micro-architectures are vulnerable to soft errors, i.e., temporary errors caused by voltage spikes produced by cosmic radiation. Soft-error impact is usually evaluated using fault injection, a black-box testing approach similar to mutation testing. In this paper, we complement an existing evaluation of a prototype brake-by-wire controller, developed by Volvo Technology, with static-analysis techniques to improve test effectiveness. The fault-injection tests are both time- and data-intensive, which renders their qualitative and quantitative assessment difficult. We devise a prototype visualization tool, which groups experiments by injection point and provides an overview of both instruction and fault coverage, and the ability to detect patterns and anomalies. We use the program-dependence graph to identify experiments with a priori known outcome, and implement a static analysis to reduce the test volume. The existing pre-injection heuristic is extended with liveness analysis to enable an unbiased fault-to-failure probability.