Probabilistic mixed-model fault diagnosis

  • Authors:
  • David B. Lavo;Brian Chess;Tracy Larrabee;Ismed Hartanto

  • Affiliations:
  • -;-;-;-

  • Venue:
  • ITC '98 Proceedings of the 1998 IEEE International Test Conference
  • Year:
  • 1998

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Abstract

Previously-proposed strategies for VLSI fault diagnosishave suffered from a variet y of self-imposed limitations.Some techniques are limited to a specific fault model, andmany will fail in the face of any unmodeled behavior orunexpected data. Others apply ad-hoc or arbitrary scoring mechanisms to fault candidates, making the resultsdifficult to interpret or to compare with the results fromother algorithms. This paper outlines an approach to faultdiagnosis that is robust, comprehensive, extendable, andpractical. By introducing a probabilistic framework fordiagnostic prediction, it is designed to incorporate disparate diagnostic algorithms, different sets of data, anda mixture of fault models into a single diagnostic result.Results from diagnosis experiments on a Hewlett-PackardASIC and FIB'd defects are presented.