Substring parsing for arbitrary context-free grammars

Rekers, J.G.; Koorn, Wilco

doi:10.1145/122501.122505

Cited by 19 publications

(8 citation statements)

References 16 publications

(18 reference statements)

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“…In related work, only a study by Valkering [2007], based on substring parsing [Rekers and Koorn 1991], offered a partial approach to error recovery with SGLR parsing. To report syntactic errors, Valkering inspects the stack of the parser to determine the possible strings that can occur at that point.…”

Section: Recovery For Composite Languagesmentioning

confidence: 99%

Natural and Flexible Error Recovery for Generated Modular Language Environments

Jonge¹,

Kats²,

Visser³

et al. 2012

ACM Trans. Program. Lang. Syst.

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Integrated development environments (IDEs) increase programmer productivity, providing rapid, interactive feedback based on the syntax and semantics of a language. Unlike conventional parsing algorithms, scannerless generalized-LR parsing supports the full set of context-free grammars, which is closed under composition, and hence can parse languages composed from separate grammar modules. To apply this algorithm in an interactive environment, this paper introduces a novel error recovery mechanism. Our approach is language-independent, and relies on automatic derivation of recovery rules from grammars. By taking layout information into consideration it can efficiently suggest natural recovery suggestions.

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Section: Recovery For Composite Languagesmentioning

confidence: 99%

Natural and Flexible Error Recovery for Generated Modular Language Environments

Jonge¹,

Kats²,

Visser³

et al. 2012

ACM Trans. Program. Lang. Syst.

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show abstract

“…In related work, only a study by Valkering [26], based on substring parsing [23], offered a partial approach to error recovery with SGLR parsing. Composed languages are also supported by parsing expression grammars (PEGs) [9].…”

Section: Related Workmentioning

confidence: 99%

Natural and Flexible Error Recovery for Generated Parsers

Jonge

Nilsson-Nyman

Kats

et al. 2010

Software Language Engineering

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Abstract. Parser generators are an indispensable tool for rapid language development. However, they often fall short of the finesse of a hand-crafted parser, built with the language semantics in mind. One area where generated parsers have provided unsatisfactory results is that of error recovery. Good error recovery is both natural, giving recovery suggestions in line with the intention of the programmer; and flexible, allowing it to be adapted according to language insights and language changes. This paper describes a novel approach to error recovery, taking into account not only the context-free grammar, but also indentation usage. We base our approach on an extension of the SGLR parser that supports fine-grained error recovery rules and can be used to parse complex, composed languages. We take a divide-and-conquer approach to error recovery: using indentation, erroneous regions of code are identified. These regions constrain the search space for applying recovery rules, improving performance and ensuring recovery suggestions local to the error. As a last resort, erroneous regions can be discarded. Our approach also integrates bridge parsing to provide more accurate suggestions for indentation-sensitive language constructs such as scopes. We evaluate our approach by comparison with the JDT Java parser used in Eclipse.

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“…Furthermore, he constructs partial parse trees for the fragments that follow an error using substring parsing, introduced by Rekers and Koorn [31]. Based on these partial parsing techniques, the result of the parser is a set of (often highly ambiguous) partial parse trees.…”

Section: Related Workmentioning

confidence: 99%

Providing rapid feedback in generated modular language environments

et al. 2009

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Integrated development environments (IDEs) increase programmer productivity, providing rapid, interactive feedback based on the syntax and semantics of a language. A heavy burden lies on developers of new languages to provide adequate IDE support. Code generation techniques provide a viable, efficient approach to semi-automatically produce IDE plugins. Key components for the realization of plugins are the language's grammar and parser. For embedded languages and language extensions, constituent IDE plugin modules and their grammars can be combined. Unlike conventional parsing algorithms, scannerless generalized-LR parsing supports the full set of context-free grammars, which is closed under composition, and hence can parse language embeddings and extensions composed from separate grammar modules. To apply this algorithm in an interactive environment, this paper introduces a novel error recovery mechanism, which allows it to be used with files with syntax errors -common in interactive editing. Error recovery is vital for providing rapid feedback in case of syntax errors, as most IDE services depend on the parser -from syntax highlighting to semantic analysis and cross-referencing. We base our approach on the principles of island grammars, and derive permissive grammars with error recovery productions from normal SDF grammars. To cope with the added complexity of these grammars, we adapt the parser to support backtracking. We evaluate the recovery quality and performance of our approach using a set of composed languages, based on Java and Stratego.

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Substring parsing for arbitrary context-free grammars

Cited by 19 publications

References 16 publications

Natural and Flexible Error Recovery for Generated Modular Language Environments

Natural and Flexible Error Recovery for Generated Modular Language Environments

Natural and Flexible Error Recovery for Generated Parsers

Providing rapid feedback in generated modular language environments

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