Modular well-definedness analysis for attribute grammars

Ted Kaminski, Eric Van Wyk

Research output: Chapter in Book/Report/Conference proceedingConference contribution

23 Scopus citations

Abstract

We present a modular well-definedness analysis for attribute grammars. The global properties of completeness and non-circularity are ensured with checks on grammar modules that require only additional information from their dependencies. Local checks to ensure global properties are crucial for specifying extensible languages. They allow independent developers of language extensions to verify that their extension, when combined with other independently developed and similarly verified extensions to a specified host language, will result in a composed grammar that is well-defined. Thus, the composition of the host language and user-selected extensions can safely be performed by someone with no expertise in language design and implementation. The analysis is necessarily conservative and imposes some restrictions on the grammar. We argue that the analysis is practical and the restrictions are natural and not burdensome by applying it to the Silver specifications of Silver, our boot-strapped extensible attribute grammar system.

Original languageEnglish (US)
Title of host publicationSoftware Language Engineering - 5th International Conference, SLE 2012, Revised Selected Papers
Pages352-371
Number of pages20
DOIs
StatePublished - 2013
Event5th International Conference on Software Language Engineering, SLE 2012 - Dresden, Germany
Duration: Sep 26 2012Sep 28 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7745 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other5th International Conference on Software Language Engineering, SLE 2012
Country/TerritoryGermany
CityDresden
Period9/26/129/28/12

Bibliographical note

Funding Information:
This work is partially supported by NSF Awards No. 0905581 and 1047961.

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