Eliminating Unnecessary Items from the One-Pass Evaluation of Attribute Grammars
Summary :
We present two efficient attribute evaluator construction methods for a wide subclass of L-attributed grammars by enumeration of attributed items during one-pass bottom-up parsing. We have already proposed a construction method of a parser/evaluator for the subclass of L-attributed grammar. However the evaluator produced by our previous method uses a great number of attributed items to evaluate all attributes of a given input string. In this paper we propose two generalized methods to reduce the number of attributed itmes used in attribute evaluation. Our methods allow us to evaluate all attributes taking advantage of the use of available lookahead information.
- Publication
- IEICE TRANSACTIONS on Information Vol.E79-D No.4 pp.312-320
- Publication Date
- 1996/04/25
- Publicized
- Online ISSN
- DOI
- Type of Manuscript
- PAPER
- Category
- Software Theory
Authors
Keyword
Latest Issue
Copyrights notice of machine-translated contents
The copyright of the original papers published on this site belongs to IEICE. Unauthorized use of the original or translated papers is prohibited. See IEICE Provisions on Copyright for details.
Cite this
Copy
Yoshimichi WATANABE, Takehiro TOKUDA, "Eliminating Unnecessary Items from the One-Pass Evaluation of Attribute Grammars" in IEICE TRANSACTIONS on Information,
vol. E79-D, no. 4, pp. 312-320, April 1996, doi: .
Abstract: We present two efficient attribute evaluator construction methods for a wide subclass of L-attributed grammars by enumeration of attributed items during one-pass bottom-up parsing. We have already proposed a construction method of a parser/evaluator for the subclass of L-attributed grammar. However the evaluator produced by our previous method uses a great number of attributed items to evaluate all attributes of a given input string. In this paper we propose two generalized methods to reduce the number of attributed itmes used in attribute evaluation. Our methods allow us to evaluate all attributes taking advantage of the use of available lookahead information.
URL: https://global.ieice.org/en_transactions/information/10.1587/e79-d_4_312/_p
Copy
@ARTICLE{e79-d_4_312,
author={Yoshimichi WATANABE, Takehiro TOKUDA, },
journal={IEICE TRANSACTIONS on Information},
title={Eliminating Unnecessary Items from the One-Pass Evaluation of Attribute Grammars},
year={1996},
volume={E79-D},
number={4},
pages={312-320},
abstract={We present two efficient attribute evaluator construction methods for a wide subclass of L-attributed grammars by enumeration of attributed items during one-pass bottom-up parsing. We have already proposed a construction method of a parser/evaluator for the subclass of L-attributed grammar. However the evaluator produced by our previous method uses a great number of attributed items to evaluate all attributes of a given input string. In this paper we propose two generalized methods to reduce the number of attributed itmes used in attribute evaluation. Our methods allow us to evaluate all attributes taking advantage of the use of available lookahead information.},
keywords={},
doi={},
ISSN={},
month={April},}
Copy
TY - JOUR
TI - Eliminating Unnecessary Items from the One-Pass Evaluation of Attribute Grammars
T2 - IEICE TRANSACTIONS on Information
SP - 312
EP - 320
AU - Yoshimichi WATANABE
AU - Takehiro TOKUDA
PY - 1996
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E79-D
IS - 4
JA - IEICE TRANSACTIONS on Information
Y1 - April 1996
AB - We present two efficient attribute evaluator construction methods for a wide subclass of L-attributed grammars by enumeration of attributed items during one-pass bottom-up parsing. We have already proposed a construction method of a parser/evaluator for the subclass of L-attributed grammar. However the evaluator produced by our previous method uses a great number of attributed items to evaluate all attributes of a given input string. In this paper we propose two generalized methods to reduce the number of attributed itmes used in attribute evaluation. Our methods allow us to evaluate all attributes taking advantage of the use of available lookahead information.
ER -
English
