Predictive Shift-Reduce Parsing for Hyperedge Replacement Grammars
F. Drewes, B. Hoffmann, and M. Minas. Graph Transformation: 10th International Conference, ICGT 2017, Held as Part of STAF 2017, Marburg, Germany, July 18-19, 2017, Proceedings, volume 10373 of Lecture Notes in Computer Science, page 106--122. Cham, Springer International Publishing, (2017)
DOI: 10.1007/978-3-319-61470-0_7
Abstract
Graph languages defined by hyperedge replacement grammars can be NP-complete. We study predictive shift-reduce (PSR) parsing for a subclass of these grammars, which generalizes the concepts of SLR(1) string parsing to graphs. PSR parsers run in linear space and time. In comparison to the predictive top-down (PTD) parsers recently developed by the authors, PSR parsing is more efficient and more general, while the required grammar analysis is easier than for PTD parsing.
%0 Conference Paper
%1 Drewes-Hoffmann-Minas:2017
%A Drewes, Frank
%A Hoffmann, Berthold
%A Minas, Mark
%B Graph Transformation: 10th International Conference, ICGT 2017, Held as Part of STAF 2017, Marburg, Germany, July 18-19, 2017, Proceedings
%C Cham
%D 2017
%E de Lara, Juan
%E Plump, Detlef
%I Springer International Publishing
%K 2017 ConferencePaper DiaPlan GraGra GraphParsing myown parsing
%P 106--122
%R 10.1007/978-3-319-61470-0_7
%T Predictive Shift-Reduce Parsing for Hyperedge Replacement Grammars
%U http://dx.doi.org/10.1007/978-3-319-61470-0_7
%V 10373
%X Graph languages defined by hyperedge replacement grammars can be NP-complete. We study predictive shift-reduce (PSR) parsing for a subclass of these grammars, which generalizes the concepts of SLR(1) string parsing to graphs. PSR parsers run in linear space and time. In comparison to the predictive top-down (PTD) parsers recently developed by the authors, PSR parsing is more efficient and more general, while the required grammar analysis is easier than for PTD parsing.
%@ 978-3-319-61470-0
@inproceedings{Drewes-Hoffmann-Minas:2017,
abstract = {Graph languages defined by hyperedge replacement grammars can be NP-complete. We study predictive shift-reduce (PSR) parsing for a subclass of these grammars, which generalizes the concepts of SLR(1) string parsing to graphs. PSR parsers run in linear space and time. In comparison to the predictive top-down (PTD) parsers recently developed by the authors, PSR parsing is more efficient and more general, while the required grammar analysis is easier than for PTD parsing.},
added-at = {2017-09-28T18:19:47.000+0200},
address = {Cham},
author = {Drewes, Frank and Hoffmann, Berthold and Minas, Mark},
bdsk-url-1 = {http://dx.doi.org/10.1007/978-3-319-61470-0_7},
biburl = {https://www.bibsonomy.org/bibtex/2083a6071ca5872fb1e7aa2fae46ba575/minas},
booktitle = {Graph Transformation: 10th International Conference, ICGT 2017, Held as Part of STAF 2017, Marburg, Germany, July 18-19, 2017, Proceedings},
date-added = {2017-07-06 07:58:35 +0000},
date-modified = {2017-09-28 14:40:57 +0000},
doi = {10.1007/978-3-319-61470-0_7},
editor = {de Lara, Juan and Plump, Detlef},
interhash = {05d42ad17315c06f231237c9dce9525f},
intrahash = {083a6071ca5872fb1e7aa2fae46ba575},
isbn = {978-3-319-61470-0},
keywords = {2017 ConferencePaper DiaPlan GraGra GraphParsing myown parsing},
pages = {106--122},
publisher = {Springer International Publishing},
series = {Lecture Notes in Computer Science},
timestamp = {2017-09-28T18:59:13.000+0200},
title = {Predictive Shift-Reduce Parsing for Hyperedge Replacement Grammars},
url = {http://dx.doi.org/10.1007/978-3-319-61470-0_7},
volume = 10373,
year = 2017
}