CS 154. Finite Automata, Nondeterminism, Regular Expressions

Transcription

1 CS 54 Finite Automata, Nondeterminism, Regular Expressions

2 Read string left to right The DFA accepts a string if the process ends in a double circle

3 A DFA is a 5-tuple M = (Q, Σ, δ, q, F) Q is the set of states (finite) Σ is the alphabet (finite) δ : Q Σ Q is the transition function q Q is the start state F Q is the set of accept/final states L(M) = set of all strings that M accepts = the language recognized by M

4 A DFA is a 5-tuple M = (Q, Σ, δ, q, F) L(M) = set of all strings that M accepts = the language recognized by M Definition: A language L is regular if it is recognized by a DFA; that is, there is a DFA M where L = L(M).

5 Union Theorem for Regular Languages The union of two regular languages is also a regular language Intersection Theorem for Regular Languages The intersection of two regular languages is also a regular language

6 Complement Theorem for Regular Languages The complement of a regular language is also a regular language

7 The Reverse of a Language Reverse of L: L R = { w w k w k w L, w i Σ} If L is recognized by the usual kind of DFA, Then L R is recognized by a DFA that reads its strings from right to left! Question: If L is regular, then is L R also regular? Can every Right-to-Left DFA be replaced by a normal Left-to-Right DFA?

8 ,, L(M) = { w w begins with } Suppose our machine reads strings from right to left Then L(M) = {w w ends with a }. Is this regular?

9 Reversing DFAs Assume L is a regular language. Let M be a DFA that recognizes L We ll build a machine M R that accepts L R If M accepts w, then w describes a directed path in M from start to an accept First Attempt: Try to define M R as M with the arrows reversed, turn start state into a final state, turn final states into starts

10 Problem: M R IS NOT ALWAYS A DFA! It could have many start states Some states may have more than one outgoing edge, or none at all!

11 ,

12 Non-deterministic Finite Automata (NFA), What happens with? We will say this new machine accepts a string x if there is some path reading in x that reaches some accept state from some start state

13 Non-deterministic Finite Automata (NFA), Then, this machine recognizes: {w w contains } We will say this new machine accepts a string x if there is some path reading in x that reaches some accept state from some start state

14 Another Example of an NFA,,, ε At each state, we can have any number of out arrows for a letter σ Σ, including ε Set of strings accepted by this NFA = {w w contains a }

15 Multiple Start States We allow multiple start states for NFAs, and Sipser allows only one Can easily convert NFA with many start states into one with a single start state: ε ε ε

16 A non-deterministic finite automaton (NFA) is a 5-tuple N = (Q, Σ, δ, Q, F) where Q is the set of states Σ is the alphabet δ : Q Σ ε 2 Q is the transition function Q Q is the set of start states F Q is the set of accept states 2 Q is the set of all possible subsets of Q Σ ε = Σ {ε}

17 Def. Let w Σ*. Let N be an NFA. N accepts w if there s a sequence of states r, r,..., r k Q and w can be written as w... w k with w i Σ {ε} such that. r Q 2. r i+ δ(r i, w i+ ) for all i =,..., k-, and 3. r k F L(N) = the language recognized by N = set of all strings machine N accepts A language L is recognized by an NFA N if L = L(N).

18 q 2 q 4 ε q 3 N = (Q, Σ, δ, Q, F) Q = {q, q 2, q 3, q 4 } Σ = {,} Q = {q, q 2 } q F = {q 4 } L(N) = {,,} δ(q 2,) = {q 4 } δ(q 3,) = δ(q,) = {q 3 }

19 Deterministic Computation Non-Deterministic Computation reject accept or reject accept Are these equally powerful???

20 NFAs are generally simpler than DFAs A DFA recognizing the language {},, An NFA recognizing the language {}

21 Every NFA can be perfectly simulated by some DFA! Theorem: For every NFA N, there is a DFA M such that L(M) = L(N) Corollary: A language L is regular if and only if L is recognized by an NFA Corollary: L is regular iff L R is regular

22 From NFAs to DFAs Input: NFA N = (Q, Σ, δ, Q, F) Output: DFA M = (Q, Σ, δ, q, F ) accept reject 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

23 * From NFAs to DFAs: Subset Construction Input: NFA N = (Q, Σ, δ, Q, F) Output: DFA M = (Q, Σ, δ, q, F ) Q = 2 Q δ : Q Σ Q δ (R,σ) = ε( δ(r,σ) ) r R q = ε(q ) 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 or more ε transitions} *

24 Example of the ε-closure,,,ε,ε q q q 2 ε({q }) = {q, q, q 2 } ε({q }) = {q, q 2 } ε({q 2 }) = {q 2 }

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

26 Reverse Theorem for Regular Languages 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.

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

28 Union Theorem using NFAs?

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

30 Regular Languages are closed under star A* = { s s k k 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, ε ε

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

32 Regular Languages are closed under star How would we prove that this NFA construction works? Want to show: L(N) = L*. L(N) L* 2. L(N) L*

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

34 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* Let w be accepted by N with k+. Write w as w=uv, where v is the substring read after the last ε-transition v u ε ε accept u L(N), so u L* v L By I.H. w = uv L*

35 Regular Languages are closed under all of the following operations: 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 w k w k w A } Concatenation: A B = { vw v A and w B } Star: A* = { w w k k and each w i A }

36 Homework is coming out today watch for it!

37 Regular Expressions

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

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

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

41 Regexps Represent Languages For every regexp R, define L(R) to be the language that R represents A string w Σ* is acceptedby R (or, w matches R) if w L(R) Example: matches the regexp ()*

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