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Test Pattern Selection for Defect-Aware Test

Authors: Yoshinobu Higami; Hiroshi Furutani; Takao Sakai; Shuichi Kameyama; Hiroshi Takahashi;

Test Pattern Selection for Defect-Aware Test

Abstract

With shrinking of LSIs, the diversification of defective mode becomes a critical issue. As a result, test patterns for stuck-at faults and transition faults are insufficient to detect such defects. N-detection tests have been known as an effective way for achieving high defect coverage, but the large number of test pattern counts is the problem. In this paper, we propose metrics based on the fault excitation functions and the propagation path function to evaluate test patterns for transition faults. We also propose the method for selecting the test patterns from the N-detection test set. From the experimental results, we show that the set of selected test patterns can detect the larger number of faults than other test set with the same number of test 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!
2
Average
Average
Average
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