Zhi# - Programming Language Inherent Support for Ontologies

XML Schema Definition (XSD) and the Web Ontology Language (OWL) have been widely used to define programming language independent data types and to conceptualize knowledge. However, writing software that operates on XML instance documents and on ontological knowledge bases still suffers from a lack of compile time support for XSD and OWL. In this paper, a novel compiler framework is presented that facilitates the cooperative usage of external type systems with C#. For the resulting programming language Zhi#, XSD and OWL compiler plug-ins were implemented in order to provide static type checking for constrained atomic value types and ontologies. XSD constraining facets and ontological inference rules could be integrated with host language features such as method overwriting. Zhi# programs are compiled to conventional C# and are interoperable with .NET assemblies

LDTA’04 Preliminary Version Language Analysis and Tools for Ambiguous Input Streams 1 Abstract

Automatically generated lexers and parsers for programming languages have a long history. Although they are well-suited for many languages, many widely-used generators, among them Flex and Bison, fail to handle input stream ambiguities that arise in embedded languages, in legacy languages, and in programming by voice. We have developed Blender, a combined lexer and parser generator that enables designers to describe many classes of embedded languages and to handle ambiguities in spoken input and in legacy languages. We have enhanced the incremental lexing and parsing algorithms in our Harmonia framework to analyze lexical, syntactic and semantic ambiguities. The combination of better language description and enhanced analysis provides a powerful platform on which to build the next generation of language analysis tools. Key words: GLR, embedded languages, Harmonia, programming-by-voic