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2015
ACM

Linearly Ordered Attribute Grammars: with Automatic Augmenting Dependency Selection

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Linearly Ordered Attribute Grammars: with Automatic Augmenting Dependency Selection
Attribute Grammars (AGs) extend Context-Free Grammars with attributes: information gathered on the syntax tree that adds semantics to the syntax. AGs are very well suited for describing static analyses, code-generation and other phases incorporated in a compiler. AGs are divided into classes based on the nature of the dependencies between the attributes. In this paper we examine the class of Linearly Ordered Attribute Grammars (LOAGs), for which strict, bounded size evaluators can be generated. Deciding whether an Attribute Grammar is linearly ordered is an NP-hard problem. The Ordered Attribute Grammars form a subclass of LOAG for which membership is tested in polynomial time by Kastens’ algorithm (1980). On top of this algorithm we apply an augmenting dependency selection algorithm, allowing it to determine membership for the class LOAG. Although the worst-case complexity of our algorithm is exponential, the algorithm turns out to be efficient for practical full-sized AGs. As a r...
L. Thomas van Binsbergen, Jeroen Bransen, Atze Dij
Added 16 Apr 2016
Updated 16 Apr 2016
Type Journal
Year 2015
Where PEPM
Authors L. Thomas van Binsbergen, Jeroen Bransen, Atze Dijkstra
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