BACINOL

Bayesian Circuit Analysis by Topology

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Abstract

Due to the high availability demands placed on modern hardware systems and the high cost associated with downtime, finding and fixing faults in these systems is an important problem. Unfortunately, the complexity of these systems is very large, making this problem very difficult. While recent innovations in the field of model-based diagnosis have brought increased performance, making it a viable method for diagnosing large systems, constructing a model is still required. This is difficult and time-consuming, therefore this thesis introduces a new method, BACINOL, based on diagnosing software systems using spectra. BACINOL attempts to diagnose multiple faults in hardware systems without the aid of a model. Using the theory behind BACINOL the concept of ambiguity sets is used to calculate a lower bound on the quality of the diagnoses obtained. A series of experiments is performed on the ISCAS85 benchmark, comparing BACINOL with SAFARI, to assess the performance obtained.