Disambiguation Filters for Scannerless Generalized LR Parsers

Brand, Mark van den; Scheerder, Jeroen; Vinju, Jurgen; Visser, Eelco

doi:10.1007/3-540-45937-5_12

Cited by 94 publications

(112 citation statements)

References 16 publications

Supporting

Mentioning

112

Contrasting

Order By: Relevance

“…Each filter type targets a particular kind of ambiguity. Each filter is derived from a corresponding declarative disambiguation construct in the SDF grammar formalism [7]. Formally, each filter is a function that removes certain derivations from parse forests (sets of derivations).…”

Section: Sglr and Rnglrmentioning

confidence: 99%

“…Scanners are often too simplistic to be able to deal with the actual syntax of a language and they prohibit modular implementation of parsers. Scannerless parsing [20,21,29] is a technique that avoids such issues that would be introduced by having a separate scanner [7]. Intuitively, a scannerless parser uses the power of context-free grammars instead of regular expressions to tokenize an input string.…”

Section: Introductionmentioning

confidence: 99%

“…Fortunately, it has been shown [7] that scannerless parsers can be implemented fast enough to be applied to real programming languages. In this paper we investigate the implementation of the Scannerless GLR (SGLR) parser provided with SDF [29,7].…”

Section: Introductionmentioning

confidence: 99%

“…In this paper we investigate the implementation of the Scannerless GLR (SGLR) parser provided with SDF [29,7]. It makes scannerless parsing feasible by rigorously limiting the non-determinism that is introduced by scannerless parsing using disambiguation filters.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Faster Scannerless GLR Parsing

Economopoulos

Klint

Vinju

2009

Lecture Notes in Computer Science

View full text Add to dashboard Cite

Abstract. Analysis and renovation of large software portfolios requires syntax analysis of multiple, usually embedded, languages and this is beyond the capabilities of many standard parsing techniques. The traditional separation between lexer and parser falls short due to the limitations of tokenization based on regular expressions when handling multiple lexical grammars. In such cases scannerless parsing provides a viable solution. It uses the power of context-free grammars to be able to deal with a wide variety of issues in parsing lexical syntax. However, it comes at the price of less efficiency. The structure of tokens is obtained using a more powerful but more time and memory intensive parsing algorithm. Scannerless grammars are also more non-deterministic than their tokenized counterparts, increasing the burden on the parsing algorithm even further. In this paper we investigate the application of the Right-Nulled Generalized LR parsing algorithm (RNGLR) to scannerless parsing. We adapt the Scannerless Generalized LR parsing and filtering algorithm (SGLR) to implement the optimizations of RNGLR. We present an updated parsing and filtering algorithm, called SRNGLR, and analyze its performance in comparison to SGLR on ambiguous grammars for the programming languages C, Java, Python, SASL, and C++. Measurements show that SRNGLR is on average 33% faster than SGLR, but is 95% faster on the highly ambiguous SASL grammar. For the mainstream languages C, C++, Java and Python the average speedup is 16%.

show abstract

Section: Sglr and Rnglrmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Faster Scannerless GLR Parsing

Economopoulos

Klint

Vinju

2009

Lecture Notes in Computer Science

View full text Add to dashboard Cite

show abstract

“…In both of these systems, a grammar is defined using an EBNF syntax. In the realm of transformation, perhaps the most widely known and freely available GLR-based parser generator is that provided by the Syntax Definition Formalism (SDF) [20] [19]. SDF is a realization of a scannerless generalized LR parser (SGLR) supporting declarative disambiguation rules.…”

Section: Parsing: From Strings To Termsmentioning

confidence: 99%

Program Transformation Using HATS 1.84

Winter

Beranek

2006

Generative and Transformational Techniques in Software Engineering

View full text Add to dashboard Cite

show abstract

Program Compilers

Sloane¹

2009

Wiley Encyclopedia of Computer Science and Engineering

View full text Add to dashboard Cite

Program compilers implement translations from the high‐level language world of programmers to the low‐level world of hardware. A compiler reads program text written in a source language and translates it into an equivalent program written in a different target language. A standard pipeline architecture for compiler construction consists of lexical analysis, syntax analysis, semantic analysis, translation, and code generation phases, with optional optimization phases interspersed. Support for the phases is provided by a symbol table containing the properties of program entities. Some compiler phases can be automatically generated from formal specifications.

show abstract

Disambiguation Filters for Scannerless Generalized LR Parsers

Abstract: C e n t r u m v o o r W i s k u n d e e n I n f o r m a t i c a Software ENgineeringDisambiguation filters for scannerless generalized LR parsers

Cited by 94 publications

References 16 publications

Faster Scannerless GLR Parsing

Faster Scannerless GLR Parsing

Program Transformation Using HATS 1.84

Program Compilers

Contact Info

Product

Resources

About