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The Computer Journal
Article . 1995 . Peer-reviewed
Data sources: Crossref
https://doi.org/10.1007/3-540-...
Part of book or chapter of book . 1994 . Peer-reviewed
Data sources: Crossref
DBLP
Conference object
Data sources: DBLP
DBLP
Article . 1995
Data sources: DBLP
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Binary Decision Diagrams as a HOL derived rule

Authors: John Harrison 0001;

Binary Decision Diagrams as a HOL derived rule

Abstract

Binary Decision Diagrams (BDDs) are a representation for Boolean formulas which makes many operations, in particular tautology - checking, surprisingly efficient in important practical cases. In contrast to such custom decision procedures, the HOL theorem prover expands all proofs out to a sequence of extremely simple primitive inferences. In this paper we describe how the BDD algorithm may be adapted to comply with such strictures, helping us to understand the strengths and limitations of the HOL approach.

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    popularity
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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!
18
Average
Top 10%
Average
bronze