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GLR-based abstract parsing. / Grigorev, S.; Kirilenko, I.

ACM International Conference Proceeding Series. 2013.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review

Harvard

Grigorev, S & Kirilenko, I 2013, GLR-based abstract parsing. in ACM International Conference Proceeding Series. https://doi.org/10.1145/2556610.2556616

APA

Grigorev, S., & Kirilenko, I. (2013). GLR-based abstract parsing. In ACM International Conference Proceeding Series https://doi.org/10.1145/2556610.2556616

Vancouver

Grigorev S, Kirilenko I. GLR-based abstract parsing. In ACM International Conference Proceeding Series. 2013 https://doi.org/10.1145/2556610.2556616

Author

Grigorev, S. ; Kirilenko, I. / GLR-based abstract parsing. ACM International Conference Proceeding Series. 2013.

BibTeX

@inproceedings{ccf06e3ffe67459a9018044a9cb843f1,
title = "GLR-based abstract parsing",
abstract = "Abstract parsing is an important step of the processing of dynamically constructed statements or string-embedded languages (such as embedded or dynamic SQL). Existing LALR-based algorithms have performance issues. To increase performance we propose to use a GLR-algorithm as a base for abstract parsing and to reuse graph-structured stack and shared packed parse forest. RNGLR-algorithm modification for abstract parsing is presented. {\textcopyright} 2013 ACM.",
author = "S. Grigorev and I. Kirilenko",
year = "2013",
doi = "10.1145/2556610.2556616",
language = "English",
isbn = "9781450326414",
booktitle = "ACM International Conference Proceeding Series",

}

RIS

TY - GEN

T1 - GLR-based abstract parsing

AU - Grigorev, S.

AU - Kirilenko, I.

PY - 2013

Y1 - 2013

N2 - Abstract parsing is an important step of the processing of dynamically constructed statements or string-embedded languages (such as embedded or dynamic SQL). Existing LALR-based algorithms have performance issues. To increase performance we propose to use a GLR-algorithm as a base for abstract parsing and to reuse graph-structured stack and shared packed parse forest. RNGLR-algorithm modification for abstract parsing is presented. © 2013 ACM.

AB - Abstract parsing is an important step of the processing of dynamically constructed statements or string-embedded languages (such as embedded or dynamic SQL). Existing LALR-based algorithms have performance issues. To increase performance we propose to use a GLR-algorithm as a base for abstract parsing and to reuse graph-structured stack and shared packed parse forest. RNGLR-algorithm modification for abstract parsing is presented. © 2013 ACM.

U2 - 10.1145/2556610.2556616

DO - 10.1145/2556610.2556616

M3 - Conference contribution

SN - 9781450326414

BT - ACM International Conference Proceeding Series

ER -

ID: 7410156