Abstract
Diagnostic fault simulation can generate enormous amounts of data. The techniques used to manage this data can have significant effect on the outcome of the fault diagnosis procedure. We first demonstrate that if information is removed from a fault dictionary, its ability to diagnose unmodeled faults may be severely curtailed even if dictionary quality metrics remain unaffected; we, therefore, focus on methods for producing small, lossless dictionaries, We present a new dictionary organization based on error sets, which is amenable to standard data-compression techniques. We compare several dictionary organizations and the effect of standard data-compression techniques on each of them. An appropriate organization and encoding makes dictionary-based diagnosis practical for very large circuits

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