CS 154, Lecture 3: DFA NFA, Regular Expressions

Transcription

1 CS 154, Lecture 3: DFA NFA, Regular Expressions

2 Homework 1 is coming out

3 Deterministic Finite Automata Computation with finite memory

4 Non-Deterministic Finite Automata Computation with finite memory and verified guessing

5 From NFAs to DFAs Input: NFA N = (Q, Σ,, Q 0, F) Output: DFA M = (Q, Σ,, q 0, F ) To learn if an NFA accepts, we could do the computation in parallel, maintaining the set of all possible states that can be reached Idea: Set Q = 2 Q

6 * From NFAs to DFAs: Subset Construction Input: NFA N = (Q, Σ,, Q 0, F) Output: DFA M = (Q, Σ,, q 0, F ) Q = 2 Q : Q Σ Q (R, ) = ε( (r, ) ) r R q 0 = ε(q 0 ) * F = { R Q f R for some f F } For S Q, the ε-closure of S is ε(s) = {q q reachable from some s S by taking 0 or more ε transitions}

7 Example of the ε-closure ε({q 0 }) = {q 0, q 1, q 2 } ε({q 1 }) = {q 1, q 2 } ε({q 2 }) = {q 2 }

8 Given: NFA N = ( {1,2,3}, {a,b},, {1}, {1} ) Construct: Equivalent DFA M = (2 {1,2,3}, {a,b},, {1,3}, ) N 1 a {1,3} a M {3} b a b ε a b b b a,b a, b 2 3 ε({1}) = {1,3} {2} a {2,3} {1}, {1,2}? a b {1,2,3} a

9 Reverse Theorem for Regular Languages Theorem: The reverse of a regular language is also a regular language If a language can be recognized by a DFA that reads strings from right to left, then there is an normal DFA that accepts the same language Proof? Given a DFA for a language L, reverse its arrows and flip its start and accept states, getting an NFA. Convert that NFA back to a DFA!

10 Using NFAs in place of DFAs can make proofs about regular languages much easier! Remember this on homework/exams!

11 Union Theorem using NFAs?

12 Regular Languages are closed under concatenation Concatenation: A B = { vw v A and w B } Given DFAs M 1 and M 2, connect the accept states of M 1 to the start states of M 2 0 0,1 1 0 ε 0 0,1 1 0, ε L(N) = L(M 1 ) L(M 2 ) 1 1

13 Regular Languages are closed under star A* = { s 1 s k k 0 and each s i A } Let M be a DFA, and let L = L(M) We can construct an NFA N that recognizes L* ε 0 0,1 1 ε ε

14 Formally, the construction is: Input: DFA M = (Q, Σ,, q 1, F) Output: NFA N = (Q, Σ,, q 0, F ) Q = Q {q 0 } F = F {q 0 } (q,a) = (q,a) {q 1 } {q 1 } if q Q and a ε if q F and a = ε if q = q 0 and a = ε if q = q 0 and a ε else

15 Regular Languages are Closed Under Star How would we prove that this NFA construction works? Want to show: L(N) = L* 1. L(N) L* 2. L(N) L*

16 1. L(N) L* Assume w = w 1 w k is in L* where w 1,,w k L We show N accepts w by induction on k Base Cases: k = 0 k = 1 (w = ε) (w L) Inductive Step: Assume N accepts all strings v = v 1 v k L*, v i L Let u = u 1 u k u k+1 L*, u j L Since N accepts u 1 u k (by induction) and M accepts u k+1, N also accepts u (by construction)

17 2. L(N) L* Assume w is accepted by N; we want to show w L* If w = ε, then w L* I.H. N accepts u and takes at most k ε-transitions u L* u ε u L(N), so u L* By I.H. Let w be accepted by N with k+1 ε-transitions. Write w as w=uv, where v is the substring read after the last ε- transition v ε v L accept w = uv L*

18 Closure Properties for Regular Languages Union: A B = { w w A or w B } Intersection: A B = { w w A and w B } Complement: A = { w Σ* w A } Reverse: A R = { w 1 w k w k w 1 A, w i Σ} Concatenation: A B = { vw v A and w B } Star: A* = { s 1 s k k 0 and each s i A } Theorem: if A and B are regular then so are: A B, A B, A, A R, A B, and A*

19 Regular Expressions Computation as simple, logical description A totally different way of thinking about computation: What is the complexity of describing the strings in the language?

20 Inductive Definition of Regexp Let Σ be an alphabet. We define the regular expressions over Σ inductively: For all Σ, is a regexp ε is a regexp is a regexp If R 1 and R 2 are both regexps, then (R 1 R 2 ), (R 1 + R 2 ), and (R 1 )* are regexps

21 Precedence Order: * then then + Example: R 1 *R 2 + R 3 = ( ( R 1 * ) R 2 ) + R 3

22 Definition: Regexps Represent Languages The regexp Σ represents the language { } The regexp ε represents {ε} The regexp represents If R 1 and R 2 are regular expressions representing L 1 and L 2 then: (R 1 R 2 ) represents L 1 L 2 (R 1 + R 2 ) represents L 1 L 2 (R 1 )* represents L 1 *

23 Regexps Represent Languages For every regexp R, define L(R) to be the language that R represents A string w Σ* is accepted by R (or, w matches R) if w L(R) Examples: 0, 010, and match (01)* matches (0+1)*0

24 Assume Σ = {0,1} { w w has exactly a single 1 } 0*10* { w w contains 001 } (0+1)*001(0+1)*

25 Assume Σ = {0,1} What language does the regexp * represent? {ε}

26 Assume Σ = {0,1} { w w has length 3 and its 3rd symbol is 0 } (0+1)(0+1)0(0+1)*

27 Assume Σ = {0,1} { w every odd position in w is a 1 } (1(0 + 1))*(1 + ε)

28 Assume Σ = {0,1} { w w has equal number of occurrences of 01 and 10} = { w w = 1, w = 0, or w = ε, or w starts with a 0 and ends with a 0, or w starts with a 1 and ends with a 1 } Claim: A string w has equal occurrences of 01 and 10 w starts and ends with the same bit ε + 0(0+1)*0 + 1(0+1)*1

29 DFAs NFAs Regular Expressions! L can be represented by some regexp L is regular

30 L can be represented by some regexp L is regular

31 L can be represented by some regexp L is regular Base Cases (R has length 1): Given any regexp R, we will construct an NFA N s.t. N accepts exactly the strings accepted by R R = Proof by induction on the length of the regexp R R = ε R =

32 Induction Step: Suppose every regexp of length < k represents some regular language. Consider a regexp R of length k > 1 Three possibilities for R: R = R 1 + R 2 R = R 1 R 2 R = (R 1 )*

33 Induction Step: Suppose every regexp of length < k represents some regular language. Consider a regexp R of length k > 1 Three possibilities for R: R = R 1 + R 2 R = R 1 R 2 R = (R 1 )* By induction, R 1 and R 2 represent some regular languages, L 1 and L 2 But L(R) = L(R 1 + R 2 ) = L 1 L 2 so L(R) is regular, by the union theorem!

34 Induction Step: Suppose every regexp of length < k represents some regular language. Consider a regexp R of length k > 1 Three possibilities for R: R = R 1 + R 2 R = R 1 R 2 R = (R 1 )* By induction, R 1 and R 2 represent some regular languages, L 1 and L 2 But L(R) = L(R 1 R 2 ) = L 1 L 2 so L(R) is regular by the concatenation theorem

35 Induction Step: Suppose every regexp of length < k represents some regular language. Consider a regexp R of length k > 1 Three possibilities for R: R = R 1 + R 2 R = R 1 R 2 R = (R 1 )* By induction, R 1 and R 2 represent some regular languages, L 1 and L 2 But L(R) = L(R 1 *) = L 1 * so L(R) is regular, by the star theorem

36 Induction Step: Suppose every regexp of length < k represents some regular language. Consider a regexp R of length k > 1 Three possibilities for R: R = R 1 + R 2 R = R 1 R 2 R = (R 1 )* By induction, R 1 and R 2 represent some regular languages, L 1 and L 2 But L(R) = L(R 1 *) = L 1 * so L(R) is regular, by the star theorem Therefore: If L is represented by a regexp, then L is regular

37 Give an NFA that accepts the language represented by (1(0 + 1))* ε 1 0,1 ε Regular expression: ( 1(0+1) )*

38 Generalized NFAs (GNFA) L can be represented by a regexp L is a regular language Idea: Transform an NFA for L into a regular expression by removing states and re-labeling the arcs with regular expressions Rather than reading in just letters from the string on a step, we can read in entire substrings

39 Generalized NFA (GNFA) Is aaabcbcba accepted or rejected? Is bba accepted or rejected? Is bcba accepted or rejected? This GNFA recognizes L(a*b(cb)*a)

40 NFA Add unique start and accept states

41 NFA While the machine has more than 2 states: Pick an internal state, rip it out and re-label the arrows with regexps, to account for paths through the missing state 0 01*0 0 1

42 GNFA While the machine has more than 2 states: In general: R(q 1,q 3 ) R(q 1,q 2 )R(q 2,q 2 )*R(q 2,q 3 ) + R(q 1,q 3 ) R(q 1,q 2 ) R(q 2,q 3 ) q 1 q 2 q 3 R(q 2,q 2 )

43 a a,b ε a*b(a*b)(a+b)* b ε q 0 q 1 q 2 q 3 R(q 0,q 3 ) = (a*b)(a+b)* represents L(N)

44 DFAs NFAs DEFINITION Regular Languages Regular Expressions

45 Parting thoughts: Regular Languages can be defined by their closure properties NFA=DFA, does it mean that nondeterminism is free for Finite Automata? Questions?