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Stuck-at fault: a fault model for the next millennium

Authors: Janak H. Patel;

Stuck-at fault: a fault model for the next millennium

Abstract

One of the common misconceptions about a stuck-at fault model is that it does not model a physical defect accurately and therefore is not adequate for testing defects in advancing technologies. Stuck-at fault model can be described as anything but a physical defect model. You can call it abstract, logical, Boolean, symbolic, functional or behavioral model, but don't call it a physical defect model! But that is not a weakness of the stuck-at fault model. To the contrary, abstraction is the main strength of this model and the reason for its longevity. Abstraction is also the reason that it will be the model of choice in the next millenium. By staying away from physical details stuck-at fault model remains effective with changing technologies and design styles. Stuck-at fault model operates in the logic domain while most physical level models operate in analog domain or even in the electromagnetic domain. With the rapidly growing number of transistors on a chip, abstraction is a necessity to manage complexity. So if anything the trend for the next millenium is likely to be a higher level of abstraction. Does the abstraction come at a cost in loss of defect detection? To answer this let us consider two major classes of defects: defects internal to a gate and defects external to a gate.

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Powered by OpenAIRE graph
Found an issue? Give us feedback
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!
17
Average
Top 10%
Average
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