PAGELEARN: Learning Semantic Functions of Attribute Grammars in Parallel

Gyongyi Szilágyi, Aggelos M. Thanos

Abstract


Attribute Grammars (AGs) are a generalization of the concept of Context-Free Grammars (CFGs). The formalism of AGs has been widely used for the specification and implementation of programming languages. On the other hand there is an intimate relationship between AGs and Logic Programming. The paper presents a parallel method for learning semantic functions of Attribute Grammars (AGs) based on AGLEARN (2) using PAGE system (12). The method is more efficient in both execution time and interaction needed than the sequential one. The method presented is adequate for S-attributed grammars and for L-attributed grammars as well.

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DOI: https://doi.org/10.2498/cit.2000.02.03

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