AML: Attribute Grammars in ML
Efremidis, Sofoklis G.; Mughal, Kahlid A.; Reppy, John H.
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.
computer science; technical report
Previously Published As