Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование
Generalized LR parsing for grammars with contexts. / Barash, Mikhail; Okhotin, Alexander.
Computer Science - Theory and Applications - 10th International Computer Science Symposium in Russia, CSR 2015, Proceedings. ред. / Lev D. Beklemishev; Daniil V. Musatov; Daniil V. Musatov. Springer Nature, 2015. стр. 67-79 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Том 9139).Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование
}
TY - GEN
T1 - Generalized LR parsing for grammars with contexts
AU - Barash, Mikhail
AU - Okhotin, Alexander
PY - 2015/1/1
Y1 - 2015/1/1
N2 - The Generalized LR parsing algorithm for context-free grammars is notable for having a decent worst-case running time (cubic in the length of the input string), as well as much better performance on “good” grammars. This paper extends the Generalized LR algorithm to the case of “grammars with left contexts” (M. Barash, A. Okhotin, “An extension of context-free grammars with one-sided context specifications”, Inform. Comput., 2014), which augment the context-free grammars with special operators for referring to the left context of the current substring, as well as with a conjunction operator (as in conjunctive grammars) for combining syntactical conditions. All usual components of the LR algorithm, such as the parsing table, shift and reduce actions, etc., are extended to handle the context operators. The resulting algorithm is applicable to any grammar with left contexts and has the same worst-case cubic-time performance as in the case of context-free grammars.
AB - The Generalized LR parsing algorithm for context-free grammars is notable for having a decent worst-case running time (cubic in the length of the input string), as well as much better performance on “good” grammars. This paper extends the Generalized LR algorithm to the case of “grammars with left contexts” (M. Barash, A. Okhotin, “An extension of context-free grammars with one-sided context specifications”, Inform. Comput., 2014), which augment the context-free grammars with special operators for referring to the left context of the current substring, as well as with a conjunction operator (as in conjunctive grammars) for combining syntactical conditions. All usual components of the LR algorithm, such as the parsing table, shift and reduce actions, etc., are extended to handle the context operators. The resulting algorithm is applicable to any grammar with left contexts and has the same worst-case cubic-time performance as in the case of context-free grammars.
UR - http://www.scopus.com/inward/record.url?scp=84943660307&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-20297-6_5
DO - 10.1007/978-3-319-20297-6_5
M3 - Conference contribution
AN - SCOPUS:84943660307
SN - 9783319202969
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 67
EP - 79
BT - Computer Science - Theory and Applications - 10th International Computer Science Symposium in Russia, CSR 2015, Proceedings
A2 - Beklemishev, Lev D.
A2 - Musatov, Daniil V.
A2 - Musatov, Daniil V.
PB - Springer Nature
T2 - 10th International Computer Science Symposium in Russia, CSR 2015
Y2 - 13 July 2015 through 17 July 2015
ER -
ID: 41143465