An Experimental Evaluation of the Effectiveness of Automatic Rule-Based Transformations for Safety-Critical Applications

Over the last years, an increasing number of safety-critical tasks have been demanded to computer systems. In particular, safety-critical computer-based applications are hitting markets where costs is a major issue, and thus solutions are required which conjugate fault tolerance with low costs. In this paper, a softwarebased approach for developing safety-critical applications is analyzed. By exploiting an ad-hoc automatic tool implementing the proposed technique, several benchmark applications have been hardened against transient errors. Fault Injection campaigns have been performed to evaluate the fault detection capability of the hardened applications. Moreover, a comparison of the proposed techniques with the AlgorithmBased Fault Tolerance (ABFT) approach is proposed. Experimental results show that the proposed approach is far more effective than ABFT in terms of fault detection capability when injecting transient faults in data and code memory, at a cost of an increased memory overhead. Moreover, the performance penalty introduced by the proposed technique is comparable, and sometimes lower, than that ABFT requires.