HAL will be down for maintenance from Friday, June 10 at 4pm through Monday, June 13 at 9am. More information
Skip to Main content Skip to Navigation
Reports

Space optimization in the FNC-2 attribute grammar system

Abstract : Memory space management for attribute evaluators is a vital requirement in practice. In fact, using attribute grammars (AGs) will very quickly meet the problem of memory space if it isn't taken into special consideration. We consider this problem for evaluators of the simple multi-visit class, also called l-ordered, because it is the largest possible AGs class for which we can find, at construction time, a method for memory space optimization. We present a new algorithm which decides, at generation time, if it is possible to store attribute instances in global stacks or global variables. The purpose of this approach is to reduce not only memory space, but also as much as possible the number of attributes to be stored in the nodes of the tree. This method is implemented in the new attribute grammar processing system, named FNC-2. Finally we present our first practical results which seem very promising.
Document type :
Reports
Complete list of metadata

https://hal.inria.fr/inria-00075393
Contributor : Rapport de Recherche Inria Connect in order to contact the contributor
Submitted on : Wednesday, May 24, 2006 - 6:07:48 PM
Last modification on : Friday, February 4, 2022 - 3:23:55 AM
Long-term archiving on: : Tuesday, April 12, 2011 - 10:54:56 PM

Identifiers

  • HAL Id : inria-00075393, version 1

Collections

Citation

C. Julie, Didier Parigot. Space optimization in the FNC-2 attribute grammar system. RR-1165, INRIA. 1990. ⟨inria-00075393⟩

Share

Metrics

Record views

44

Files downloads

94