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Compressed pattern diagnosis for scan chain failures

Authors: Yu Huang 0005; Wu-Tung Cheng; Janusz Rajski;

Compressed pattern diagnosis for scan chain failures

Abstract

In scan based designs, 10%-30% defects are in scan chains. Hence scan chain fault diagnosis becomes an important process for silicon debug and yield ramp up. With embedded compression techniques getting popular, chain diagnosis on devices with the embedded compression techniques becomes a challenge. In this paper, we provide a general methodology that can be applied for performing chain diagnosis in the context of any embedded compression techniques with any existing chain diagnosis algorithms. The proposed methodology enables seamless reuse of the existing chain diagnosis infrastructure with compressed test data. Experimental results show that with compressed patterns, the chain diagnosis resolution can be enhanced up to one order of magnitude with only 25% of failure cycles collected from ATE, compared to the diagnosis results with uncompressed patterns

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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!
27
Top 10%
Top 10%
Top 10%
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