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Untestable Fault Identification Using Implications

Authors: Syal, Manan;

Untestable Fault Identification Using Implications

Abstract

Untestable faults in circuits are defects/faults for which there exists no test pattern that can either excite the fault or propagate the fault effect to an observable point, which could be either a Primary output (PO) or a scan flip-flop. The current state-of-the-art automatic test pattern generators (ATPGs) spend a lot of time in trying to generate a test sequence for the detection of untestable faults, before aborting on them, or identifying them as untestable, given enough time. Thus, it would be beneficial to quickly identify faults that are redundant/untestable, so that tools such as ATPG engines or fault simulators do not waste time targeting these faults. Our work focuses on the identification of untestable faults at low cost in terms of both memory and execution time. A powerful and memory efficient implication engine, which is used to identify the effect(s) of asserting logic values in a circuit, is used as the basic building block of our tool. Using the knowledge provided by this implication engine, we identify untestable faults using a fault independent, conflict based analysis. We evaluated our tool against several benchmark circuits (ISCAS '85, ISCAS '89 and ISCAS '93), and found that we could identify considerably more untestable faults in sequential circuits compared to similar conflict based algorithms which have been proposed earlier.

Master of Science

Country
United States
Related Organizations
Keywords

ATPG, Implications, symbolic simulation, Untestable faults, fault models

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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