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C.-H. Chen, “A Neural Network Arhitecture for Syntax Analysis,” IEEE Transactions of Neural Networks, Vol. 10, No. 1, 1999, pp. 94-114. doi:10.1109/72.737497

has been cited by the following article:

• TITLE: An Automata-Based Approach to Pattern Matching

  AUTHORS: Ali Sever

  KEYWORDS: Computation and Automata Theory; Pattern Matching; Regular Languages

  JOURNAL NAME: Intelligent Control and Automation, Vol.4 No.3, August 8, 2013

  ABSTRACT: Due to its importance in security, syntax analysis has found usage in many high-level programming languages. The Lisp language has its share of operations for evaluating regular expressions, but native parsing of Lisp code in this way is unsupported. Matching on lists requires a significantly more complicated model, with a different programmatic approach than that of string matching. This work presents a new automata-based approach centered on a set of functions and macros for identifying sequences of Lisp S-expressions using finite tree automata. The objective is to test that a given list is an element of a given tree language. We use a macro that takes a grammar and generates a function that reads off the leaves of a tree and tries to parse them as a string in a context-free language. The experimental results indicate that this approach is a viable tool for parsing Lisp lists and expressions in the abstract interpretation framework