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On the minimization of complete test set of reversible k-CNOT circuits for Stuck-at Fault model

Authors: Muhammad Ibrahim; Ahsan Raja Chowdhury; Hafiz Md. Hasan Babu;

On the minimization of complete test set of reversible k-CNOT circuits for Stuck-at Fault model

Abstract

In this paper, we propose an algorithm that produces the complete test set (CTS) of a reversible circuit for Single stuck-at fault (SSF) and multiple-stuck-at fault (MSF) models. Our algorithm works only for an important subclass of reversible circuits - the circuits consisting of k-CNOT gates (k ges 2) though, any n-wire circuit having 0-CNOT or 1-CNOT gates can be converted to a (n + 2) wire circuit having only k-CNOT gates with k ges 2 with some additional hardware cost. Generated complete test set is not necessarily optimal, but minimizing the size of the complete test set is our key concern. Finally we provide some experimental results for the proposed method and compare it with existing methods to show how it outperforms almost all of the existing algorithms in terms of number of elements of CTS but is outperformed by some of the existing ones in terms of hardware cost.

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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
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