منابع مشابه
LR Parsing for LCFRS
LR parsing is a popular parsing strategy for variants of Context-Free Grammar (CFG). It has also been used for mildly context-sensitive formalisms, such as Tree-Adjoining Grammar. In this paper, we present the first LRstyle parsing algorithm for Linear ContextFree Rewriting Systems (LCFRS), a mildly context-sensitive extension of CFG which has received considerable attention in the last years.
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In data-driven parsing with Linear Context-Free Rewriting System (LCFRS), markovized grammars are obtained through the annotation of binarization non-terminals during grammar binarization, as in the corresponding work on PCFG parsing. Since there is indication that directional parsing with a non-binary LCFRS can be faster than parsing with a binary LCFRS, we present a debinarization procedure w...
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LR-parsing Kyung-Goo Doh, Hyunha Kim, David A. Schmidt 1 Hanyang University, Ansan, South Korea 2 Kansas State University, Manhattan, Kansas, USA Abstract. We combine LR(k)-parsing technology and data-flow analysis to analyze, in advance of execution, the documents generated dynamically by a program. Based on the document language’s context-free reference grammar and the program’s control struc...
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The LR(k)-parsing algorithm is derived, i.e., presented and proved as an interplay between program development and parsing theory. The program development uses invariants and the new concept of weakest angelic precondition. The parsing theory involved relates rightmost derivability to three other transitive relations on strings. The usual stack of item sets and the finite automaton appear in an...
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We give a new treatment of tabular LR parsing, which is an alternative to Tomita’s generalized LR algorithm. The advantage is twofold. Firstly, our treatment is conceptually more attractive because it uses simpler concepts, such as grammar transformations and standard tabulation techniques also know as chart parsing. Secondly, the static and dynamic complexity of parsing, both in space and time...
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ژورنال
عنوان ژورنال: Algorithms
سال: 2016
ISSN: 1999-4893
DOI: 10.3390/a9030058