標題: Mealy machines are a better model of lexical analyzers
作者: Yang, W
交大名義發表
資訊工程學系
National Chiao Tung University
Department of Computer Science
關鍵字: automata;finite-lookahead automata;lexical analysis;Mealy machines;Moore machines;parallel algorithms;regular expressions;suffix automata
公開日期: 1-四月-1996
摘要: Lexical analyzers partition input characters into tokens. When ambiguities arise during lexical analysis, the longest-match rule is generally adopted to resolve the ambiguities. The longest-match rule causes the look-ahead problem in traditional lexical analyzers, which are based on Moore machines. In Moore machines, output tokens are associated with stares of the automata. By contrast, because Mealy machines associate output tokens with state transitions, the look-ahead behaviors can be encoded in their state transition tables. Therefore, we believe that lexical analyzers should be based on Mealy machines, rather than Moore machines, in order to solve the look-ahead problem. We propose techniques to construct Mealy machines from regular expressions and to perform sequential and data-parallel lexical analysis with these Mealy machines. Copyright (C) 1996 Elsevier Science Ltd
URI: http://dx.doi.org/10.1016/0096-0551(96)00003-3
http://hdl.handle.net/11536/1379
ISSN: 0096-0551
DOI: 10.1016/0096-0551(96)00003-3
期刊: COMPUTER LANGUAGES
Volume: 22
Issue: 1
起始頁: 27
結束頁: 38
顯示於類別:期刊論文


文件中的檔案:

  1. A1996VK93300003.pdf