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https://doi.org/10.1...arrow_drop_down
https://doi.org/10.1007/bfb003...
Part of book or chapter of book . 1998 . Peer-reviewed
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Construction of efficient generalized LR parsers

Authors: Miguel A. Alonso 0001; David Cabrero Souto; Manuel Vilares Ferro;

Construction of efficient generalized LR parsers

Abstract

We show how LR parsers for the analysis of arbitrary context-free grammars can be derived from classical Earley's parsing algorithm. The result is a Generalized LR parsing algorithm working at complexity O(n3) in the worst case, which is achieved by the use of dynamic programming to represent the non-deterministic evolution of the stack instead of graph-structured stack representations, as has often been the case in previous approaches. The algorithm behaves better in practical cases, achieving linear complexity on LR grammars. Experimental results show the performance of our proposal.

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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!
5
Average
Top 10%
Average
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