Previous    Next

FURTHER READING

Lex was the first lexical-analyzer generator based on regular expressions [Lesk 1975]; it is still widely used. Computing ∊-closure can be done more efficiently by keeping a queue or stack of states whose edges have not yet been checked for ∊-transitions [Aho et al. 1986]. Regular expressions can be converted directly to DFAs without going through NFAs [McNaughton and Yamada 1960; Aho et al. 1986]. DFA transition tables can be very large and sparse. If represented as a simple two-dimensional matrix (states × symbols), they take far too much memory. In practice, tables are compressed; this reduces the amount of memory required, but increases the time required to look up the next state [Aho et al. 1986]. Lexical analyzers, whether automatically generated or handwritten, must manage their input efficiently. Of course, input is buffered, so that a large batch of characters is obtained at once; then the lexer can process one character at a time in the buffer. The lexer must check, for each character, whether the end of the buffer is reached. By putting a sentinel - a character that cannot be part of any token - at the end of the buffer, it is possible for the lexer to check for end-of-buffer only once per token, instead of once per character [Aho et al. 1986]. Gray [1988] uses a scheme that requires only one check per line, rather than one per token, but cannot cope with tokens that contain end-of-line characters. Bumbulis and Cowan [1993] check only once around each cycle in the DFA; this reduces the number of checks (from once per character) when there are long paths in the DFA.

Automatically generated lexical analyzers are often criticized for being slow. In principle, the operation of a finite automaton is very simple and should be efficient, but interpreting from transition tables adds overhead. Gray [1988] shows that DFAs translated directly into executable code (implementing states as case statements) can run as fast as hand-coded lexers. The Flex "fast lexical-analyzer generator" [Paxson 1995] is significantly faster than Lex.


JaVaScreenshot Previous    Next
Comments