Finite Automata and Regular Expressions i206 Fall 2010 John Chuang Some slides adapted from Marti Hearst.

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Presentation transcript:

Finite Automata and Regular Expressions i206 Fall 2010 John Chuang Some slides adapted from Marti Hearst

John Chuang2

John Chuang3 What is a Computer?  Theory of computation: -What are the fundamental capabilities and limitations of computers? -Complexity theory: what makes some problems computationally hard and others easy? -Computability theory: what makes some problems solvable and others unsolvable? -Automata theory: definitions and properties of mathematical models of computation Source: Sipser, 1997

John Chuang4 Finite Automata  Also known as finite state automata (FSA) or finite state machine (FSM)  A simple mathematical model of a computer  Applications: hardware design, compiler design, text processing

John Chuang5 A First Example  Touch-less hand-dryer hand DRYER OFF DRYER ON hand

John Chuang6 Finite Automata State Graphs The start state An accepting state A transition x A state

John Chuang7 Finite Automata  Transition:s 1  x s 2 -In state s 1 on input “x” go to state s 2  If end of input -If in accepting state => accept -Else => reject  If no transition possible => reject

John Chuang8 Language of a FA  Language of finite automaton M: set of all strings accepted by M  Example:  Which of the following are in the language? -x, tmp2, 123, a?, 2apples  A language is called a regular language if it is recognized by some finite automaton letter letter | digit S A

John Chuang9 Example  What is the language of this FA? + digit S B A -

John Chuang10 Regular Expressions  Regular expressions are used to describe regular languages  Arithmetic expression example: (8+2)*3  Regular expression example: (\+|-)?[0-9]+

John Chuang11 Example  What is the language of this FA?  Regular expression: (\+|-)?[0-9]+ + digit S B A -

John Chuang12 Three Equivalent Representations Finite automata Regular expressions Regular languages Each can describe the others Theorem: For every regular expression, there is a deterministic finite-state automaton that defines the same language, and vice versa. Adapted from Jurafsky & Martin 2000

John Chuang13 Regex Rules  Goal: match patterns  // String of characters matches the same string woodchuck “how much wood does a woodchuck chuck?” p “you are a good programmer” pink elephant “this is not a pink elephant.” ! “Keep you hands to yourself!” . Wildcard; matches any character at that position p.nt pant, pint, punt

John Chuang14 Regex Rules  ? Zero or one occurrences of the preceding character/regex woodchucks? “how much wood does a woodchuck chuck?” behaviou?r “behaviour is the British spelling of behavior”  * Zero or more occurrences of the preceding character/regex baa* ba, baa, baaa, baaaa … ba* b, ba, baa, baaa, baaaa … [ab]* , a, b, ab, ba, baaa, aaabbb, … [0-9][0-9]* any positive integer, or zero cat.*cat A string where “cat” appears twice anywhere  + One or more occurrences of the preceding character/regex ba+ ba, baa, baaa, baaaa …  {n} Exactly n occurrences of the preceding character/regex ba{3}baaa

John Chuang15 Regex Rules  * is greedy: Home  Lazy (non-greedy) quantifier: Home

John Chuang16 Regex Rules  [] Disjunction (Union) [wW]ood “how much wood does a Woodchuck chuck?” [abcd]* “you are a good programmer” [A-Za-z0-9] (any letter or digit) [A-Za-z]* (any letter sequence)  | Disjunction (Union) (cats?|dogs?)+“It’s raining cats and a dog.”  ( ) Grouping (gupp(y|ies))*“His guppy is the king of guppies.”

John Chuang17 Regex Rules  ^ $ \b Anchors (start/end of input string; word boundary) ^The“The cat in the hat.” ^The end\.$“The end.” ^The.* end\.$“The bitter end.” (the)*“I saw him the other day.” (\bthe\b)*“I saw him the other day.”  Special rule: when ^ is FIRST WITHIN BRACKETS it means NOT [^A-Z]* (anything not an upper case letter)

John Chuang18 Regex Rules  \ Escape characters \. “The + and \ characters are missing.” \+“The + and \ characters are missing.” \\“The + and \ characters are missing.”

John Chuang19 Operator Precedence  What is the difference? -[a-z][a-z]|[0-9]* -[a-z]([a-z]|[0-9])* OperatorPrecedence ()highest * + ? {} sequences, anchors |lowest

John Chuang20 Regex for Dollars  No commas \$[0-9]+(\.[0-9][0-9])?  With commas \$[0-9][0-9]?[0-9]?(,[0-9][0-9][0-9])*(\.[0-9][0-9])?  With or without commas \$[0-9][0-9]?[0-9]?((,[0-9][0-9][0-9])*| [0-9]*) (\.[0-9][0-9])?

John Chuang21 Regex in Python  import re  result = re.search(pattern, string)  result = re.findall(pattern, string)  result = re.match(pattern, string)  Python documentation on regular expressions - -Some useful flags like IGNORECASE, MULTILINE, DOTALL, VERBOSE