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Digital library of University of Maribor
Bachelor thesis . 2017
License: CC BY NC ND
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Razširjanje urejevalnikov programske kode z razpoznavalniki LPeg

Authors: Fajfar, Rok;

Razširjanje urejevalnikov programske kode z razpoznavalniki LPeg

Abstract

Cilj diplomskega dela je predstaviti razpoznavalnike LPeg kot alternativo regularnim izrazom ter prikazati njihovo uporabo v namene razširjanja urejevalnikov programske kode. Razpoznavalniki tipa PEG so vrsta navzdoljnih razpoznavalnikov, LPeg pa je implementacija razpoznavalnikov PEG za skriptni programski jezik Lua. Po izgledu so podobni kontekstno prostim gramatikam z dodanimi regularnimi izrazi in imajo številne značilnosti zaradi katerih so odlična izbira za obdelavo sintakse programskih jezikov. S pomočjo knjižnice LPeg smo izdelali razširitev za urejevalnik programske kode Howl, ki dodaja podporo za funkcijski jezik Elixir.

The goal of this diploma thesis is to present LPeg parsers as an alternative to regular expressions and to show their usage for the means of extending code editors. PEG parsers are a form of top-down parsers and LPeg is their implementation for the Lua scripting language. They look a lot like context free grammars with added regular expressions and have several attibutes that make them perfect for working with programming language syntax. With help of the LPeg library we've extended the editor Howl with Elixir support.

Country
Slovenia
Related Organizations
Keywords

programski jeziki, info:eu-repo/classification/udc/004.4'42:004.43(043.2), parsers, programming languages, editors, razpoznavalniki, Lua, urejevalniki

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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!
0
Average
Average
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