Search results
Results from the WOW.Com Content Network
To decide whether two given regular expressions describe the same language, each can be converted into an equivalent minimal deterministic finite automaton via Thompson's construction, powerset construction, and DFA minimization. If, and only if, the resulting automata agree up to renaming of states, the regular expressions' languages agree.
That is, it performs a constant number of operations for each input symbol. This constant is quite low: GCC generates 12 instructions for the DFA match loop. [citation needed] Note that the constant is independent of the length of the token, the length of the regular expression and the size of the DFA.
Regular languages are a category of languages (sometimes termed Chomsky Type 3) which can be matched by a state machine (more specifically, by a deterministic finite automaton or a nondeterministic finite automaton) constructed from a regular expression. In particular, a regular language can match constructs like "A follows B", "Either A or B ...
the DFA with a minimum number of states for a particular regular language (Minimization Problem) DFAs are equivalent in computing power to nondeterministic finite automata (NFAs). This is because, firstly any DFA is also an NFA, so an NFA can do what a DFA can do.
Therefore, the length of the regular expression representing the language accepted by M is at most 1 / 3 (4 n+1 (6s+7)f - f - 3) symbols, where f denotes the number of final states. This exponential blowup is inevitable, because there exist families of DFAs for which any equivalent regular expression must be of exponential size.
In particular, every DFA is also an NFA. Sometimes the term NFA is used in a narrower sense, referring to an NFA that is not a DFA, but not in this article. Using the subset construction algorithm, each NFA can be translated to an equivalent DFA; i.e., a DFA recognizing the same formal language. [1] Like DFAs, NFAs only recognize regular languages.
While canonical DFA can find out if a string belongs to the language defined by a regular expression, TDFA can also extract substrings that match specific subexpressions. More generally, TDFA can identify positions in the input string that match tagged positions in a regular expression ( tags are meta-symbols similar to capturing parentheses ...
It compiles declarative regular expression specifications to deterministic finite automata. Originally written by Peter Bumbulis and described in his paper, [1] re2c was put in public domain and has been since maintained by volunteers. [3] It is the lexer generator adopted by projects such as PHP, [4] SpamAssassin, [5] Ninja build system [6] and