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Extended context-free grammars parsing with generalized LL

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Abstract

Parsing plays an important role in static program analysis: during this step a structural representation of code is created upon which further analysis is performed. Parser generator tools, being provided with syntax specification, automate parser development. Language documentation often acts as such specification. Documentation usually takes form of ambiguous grammar in Extended Backus-Naur Form which most parser generators fail to process. Automatic grammar transformation generally leads to parsing performance decrease. Some approaches support EBNF grammars natively, but they all fail to handle ambiguous grammars. On the other hand, Generalized LL parsing algorithm admits arbitrary context-free grammars and achieves good performance, but cannot handle EBNF grammars. The main contribution of this paper is a modification of GLL algorithm which can process grammars in a form which is closely related to EBNF (Extended Context-Free Grammar). We also show that the modification improves parsing performance as compared to grammar transformation-based approach.

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Gorokhov, A., & Grigorev, S. (2018). Extended context-free grammars parsing with generalized LL. In Communications in Computer and Information Science (Vol. 779, pp. 24–37). Springer Verlag. https://doi.org/10.1007/978-3-319-71734-0_3

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