Search results for keyword `ML'

[233]

Sofoklis G. Efremidis, Khalid A. Mughal, and John H. Reppy. AML: Attribute grammars in ML. Technical Report TR93-1401, Cornell University, Computer Science Department, December 1993.

Attribute grammars are a valuable tool for constructing compilers and building user interfaces. This paper reports on a system we are developing, called AML (for Attribution in ML), which is an attribute grammar toolkit for building such applications as language-based programming environments using SML. This system builds on the proven technology of efficient attribute evaluation, while using a higher-level foundation for the implementation of interactive systems. It supports a general and uniform platform for building applications that can manipulate attributed terms and allow access to attribute values. We describe the design of the AML system, its current implementation status, and our plans for the future.

[234]

Sofoklis Efremidis, Khalid A. Mughal, Lars Søraas, and John Reppy. AML: Attribute grammars in ML. Nordic Journal of Computing, March 1997.

Attribute grammars are a valuable tool for constructing compilers and building user interfaces. This paper reports on a system we are developing, called AML (for Attribution in ML), which is an attribute grammar toolkit for building such applications as language-based programming environments using SML. This system builds on the proven technology of efficient attribute evaluation, while using a higher-level foundation for the implementation of interactive systems. It supports a general and uniform platform for building applications that can manipulate attributed terms and allow access to attribute values. We describe the design of the AML system, its current implementation status, and our plans for the future.

[454]

T. Johnsson. Target code generation from the G-machine code. Technical Report 39, Programming Methodology Group, University of Goteborg and Chalmers University of Technology, February 1987. Part of the PhD thesis: Compiling Lazy Functional Languages, 1987. Presented at the Graph Reduction Workshop, Santa Fe, Sep 1986.

G machine is a stack machine for von-Neumann-like execution of lazy functional languages using graph reduction. Paper describes target code generation from G-machine code in a compiler for lazy-ML. 2 methods: (a) generates naive code like macro expansion (b) better, avoids redundant operations Code generation expressed as an attribute grammar over G-machine code sequences. http://cs.chalmers.se/welcome.eng.html (CSci Chalmers) ('94)

[538]

Khalid A. Mughal, John H. Reppy and Lars Søraas. ML code generation for AML specifications. In In Proceedings of the Nordic Workshop on Programming Environments Research (NWPER'94), 1994.

[603]

Gilles Le Bâtard. Réalisation dans le système FNC-2 d'un traducteur vers ML. rapport de stage de maîtrise, IFI, Université de Marne-la-Vallée, July 1995.

[707]

Andrea Mößle and Heiko Vogler. Efficient call-by-value evaluation strategy of primitive recursive program schemes. In Proceedings of the Fuji International Workshop in Functional and Logic Programming. World Scientific Publishing Co. Pte Ltd., 1995.

[1003]

G. O. Uddeborg. A functional parser generator. Technical Report 43, Programming Methodology Group, University of Goteborg and Chalmers University of Technology., February 1988.

a parser generator, written in LML, to accept attribute grammars.