Abstract

Abstract

A diagnostic test pattern generator using a Satisfiability Modulo Theory (SMT) solver is proposed. Rather than targeting a single fault pair at a time, the proposed SMT approach can distinguish multiple fault pairs in a single instance. Several heuristics are proposed to constrain the SMT formula to further reduce the search space, including fault selection, excitation constraint, reduced primary output vector, and coneof-influence reduction. Experimental results for the ISCAS85 and full-scan versions of ISCAS89 benchmark circuits show that fewer diagnostic vectors are generated compared with conventional diagnostic test generation methods. Up to 73% reduction in the number of vectors generated can be achieved in large circuits.Index Terms-Satisfiability Modulo theory(SMT); fault distinguishing; diagnostic test pattern generation;

Validation and legacy test suites are often reused for achieving at speed coverage required for testing high frequency semiconductor chips. Porting validation tests to high volume manufacturing (HVM) flows involves extensive manual effort but is required to ensure high quality chips. Functional test selection is the problem of choosing a subset of tests from a large pool of existing tests to maximize the fault coverage while minimizing the test data volume, fault grading time and porting effort. We formulate a framework for test selection that allows various coverage metrics to be used for evaluation. A novel dynamic untestability analysis method is proposed to identify faults that can not be detected by a given test sequence. Conversely this method can be used to compute tight upper bound coverage and hence as a metric for functional test evaluation. Test selection using this new metric gives significant additional fault coverage than toggle based test selection.

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