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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao https://doi.org/10.1...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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A symbol-based extension of parsing expression grammars and context-sensitive packrat parsing

Authors: Kimio Kuramitsu;

A symbol-based extension of parsing expression grammars and context-sensitive packrat parsing

Abstract

Parsing expression grammars (PEGs) are a powerful and popular foundation for describing syntax. Despite PEGs' expressiveness, they cannot recognize many syntax patterns of popular programming languages. Typical examples include typedef-defined names in C/C++ and here documents appearing in many scripting languages. We use a single unified state representation, called a symbol table, to capture various context-sensitive patterns. Over the symbol table, we design a small set of restricted semantic predicates and actions. The extended PEGs are called SPEGs, and are designed to be safe in contexts of backtracking and the linear time guarantee of packrat parsing. This paper will show that SPEGs have improved the expressive power in such ways that they recognize practical context-sensitive grammars, including back referencing, indentation-based code layout, and contextual keywords.

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citations
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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