Computing FIRST and FOLLOW Functions for Feature-Theoretic Grammars

Abstract

This paper describes an algorithm for the computation of FIRST and FOLLOW sets for use with feature-theoretic grammars in which the value of the sets consists of pairs of feature-theoretic categories. The algorithm preserves as much information from the grammars as possible, using negative restriction to define equivalence classes. Addition of a simple data structure leads to an order of magnitude improvement in execution time over a naive implementation.