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Reference Book: INTRODUCTION TO THE THEORY OF COMPUTATION, SECOND EDITION, by: MICHAEL SIPSER 3
objectives Finite automaton Infinite automaton Formal definition State diagram Regular and Non-regular languages The regular operations Regular expression Non determinism/ determinism Equivalence of NFAS and DFAS Equivalence of regular expression with finite automata 4
REGULAR LANGUAGES 5
FINITE AUTOMATA Finite automata are good models for computers with an extremely limited amount of memory. The controller for an automatic door is one example of such a device. The controller is in either of two states: "OPEN" or "CLOSED," 6
State transition table? Closed Open N F R B 7
Shapes Figures State End state arrow State transition table? input State 8 8
Finite automaton It has three states, labeled ql, q2, and q3. The start state, q1, is indicated by the arrow pointing at it from nowhere. The accept state, q2, is the one with a double circle. The arrows going from one state to another are called transitions. 9
For example, when we feed the input string 1101 to the machine (state diagram), the processing proceeds as follows. Start in state q1. 2. Read 1, follow transition from q1 to q2. 3. Read 1, follow transition from q2 to q2. 4. Read 0, follow transition from q2 to q3. 5. Read 1, follow transition from q3 to q2-6. Accept because Machine is in an accept state q2 at the end of the input. 10
FORMAL DEFINITION OF A FINITE AUTOMATON 11
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Case M1..100 13
EXAMPLES OF FINITE AUTOMATA 14
EXAMPLES OF FINITE AUTOMATA 15
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REGULAR LANGUAGES 18
DESIGNING FINITE AUTOMATA you want to construct a finite automaton to recognize (the/a) language. you have determined the necessary information For example, suppose that the alphabet is { 0,1 } and that the language consists of all strings with an odd number of 1 s. You want to construct a finite automaton E1 to recognize this language. 19
1 s (even or odd)? Formal description????? Final state?????? 20
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THE REGULAR OPERATIONS In arithmetic, the basic objects are numbers and the tools are operations for manipulating them, such as + and x. In the theory of computation the objects are languages and the tools include operations specifically designed for manipulating them. 22
THE REGULAR OPERATIONS (cont.) 23
Examples Concatenation aabaab = aabaab Union aa baab = aa and baab Closure ab*a = aa and abbba Parentheses a(a b)aab = aaaab and abaab (0* U 1*)?????????????? 24
NON DETERMINISM/ DETERMINISM In a nondeterministic machine, several choices may exist for the next state at any point. Nondeterminism is a generalization of determinism. Deterministic computation - when the machine is in a given state and reads the next input symbol, we know what the next state will be-it is determined. 25
NON DETERMINISM/ DETERMINISM (cont.) The difference between a deterministic finite automaton, abbreviated DFA, and a nondeterministic finite automaton NFA: 1. State: every state of a DFA always has exactly one exiting transition arrow for each symbol in the alphabet. 2. Transition arrow s Label: in a DFA, labels on the transition arrows are symbols from the alphabet. This NFA has an arrow with the label ɛ. 3. Nondeterminism may be viewed as a kind of parallel computation. 26
NON DETERMINISM/ DETERMINISM (cont.) If a state with an ɛ symbol on an exiting arrow is encountered, something similar happens. Without reading any input, the machine splits into multiple copies, one following each of the exiting є -labeled arrows and one staying at the current state. 27
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The nondeterministic finite automaton State q1 has one exiting arrow for 0, but it has two for 1 = NDFA 29
The computation of input 010110 30
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FORMAL DEFINITION OF A NONDETERMINISTIC FINITE AUTOMATON 32
FORMAL DEFINITION OF A NONDETERMINISTIC FINITE AUTOMATON 33
FORMAL DEFINITION OF A NONDETERMINISTIC FINITE AUTOMATON The following example explains a NFA M, with a binary alphabet, which determines if the input contains an even number of 0s or an even number of 1s. (Note that 0 occurrences is an even number of occurrences as well.) -Let M = (Q, Σ, T, s 0, F). -Describe the formal description? -Describe state transition table? -Describe the state diagram? 34
FORMAL DEFINITION OF A NONDETERMINISTIC FINITE AUTOMATON Formal description: Σ = {0, 1}, Q = {s 0, s 1, s 2, s 3, s 4 }, E({s 0 }) = { s 0, s 1, s 3 } F = {s 1, s 3 }, and The transition function T can be defined by this state transition table. 35
state diagram 1 The input contains an even number of 0s 36
state diagram 2 The input contains an even number of 1s 37
state diagram 1+2 38
state diagram 1+2 39
NFA An NFA for a language can be smaller and easier to construct than a DFA Strings whose next-to-last symbol is 1: 0 DFA: 1 NFA: 0 0 1 1 0,1 1 0,1 0 1 40
EQUIVALENCE OF NFAS AND DFAS NFAS AND DFAS machines are equivalent if they recognize the same language. THEOREM 1.39 Every nondeterministic finite automaton has an equivalent deterministic finite automaton 41
PROOF IDEA How would you simulate the NFA if you were pretending to be a DFA? What do you need to keep track of as the input string is processed? In the examples of NFAs you kept track of the various branches of the computation by placing a finger on each state that could be active at given points in the input. You updated the simulation by moving, adding, and removing fingers according to the way the NFA operates. All you needed to keep track (the set of states having fingers on them). 42
Regular Expressions and Nonregular Languages 43
REGULAR EXPRESSIONS In arithmetic, we can use the operations + and x to build up expressions such as (5 + 3) x 4. Similarly, we can use the regular operations to build up expressions describing languages, which are called regular expressions. An example is: (O U 1)0*. 44
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EQUIVALENCE WITH FINITE AUTOMATA Fact: Regular expressions and finite automata are equivalent in their descriptive power. Any regular expression can be converted into a finite automaton that recognizes the language it describes, and vice versa. 47
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Non-regularity B, C, and D seem to require machines with infinite number of to recognize them. B {0 n 1 n n 0} C { w w has an equal number of 0s and1s} D { w w has an equal number of occurrences of 01and 10 as substrings}. B and C will turn out to be nonregular while D regular. states 52
Theorem - Pumping Lemma If A is a regular language, then there is a number p (the pumpinglength) where, if s A with s p, then s can be divided into three pieces, s xyz, satisfyingthe following conditions : 1. for each i 0, xy 2. y 0, and 3. xy p. i z A, 53
54 Proof of Th 1.37 an accepting state. is where ) )( )( ( 2 1 2 1 2 1 a n l k a k k n l k q xyz s s s s s q q q q q s s s s s s
Example Claim: B {0 Proof. Assume the contrary that B is regular. Let p be the pumpinglength. Then, s 0 as s xyz with y 1, and There can be three cases y 1 nonzero k, l. In each case, we can eazily see that xy leads to contradiction. ( n n n n 0} is not regular. xy n 0 2) z B for any n 0. k, y 0 k p 1 p can be decomposed l l 1, and y 1, for some n z B, which 55
Example Claim: C { w w has an equal number of 0s and 1s} is not regular. Proof. Assume the contrary that C is regular. Let p be the pumpinglength. Then, s 0 as s xyz with y 1and xy p, and xy Then we must have y We can eazily see that xy 0 k n 1 for some nonzero k. p n p can be decomposed z C for any n 0. z C, which contradicts the assumption. 56
Example Claim: F { ww w {0,1} Proof. Assume the contrary that F is regular. Let p be the pumpinglength and let s into pieces like s xyz Then we must have y We can eazily see that xy with y 1and xy p, and xy 0 k n * } is not regular. 0 10 for some nonzero k. p p 1 F.This s can be split z F for any n z F, which contradicts the assumption. n 0. 57
Example - Pumping Down Claim: i E {0 1 Proof. Assume the contrary that E is regular. p 1 p Let p be the pumpinglength and let s 0. This s can be split n into s xyz with y 1and xy p, and xy z E for any n 0. Then we must have y We can eazily see that xy j i j} is not regular. 0 k 0 for some nonzero k. z xz E, which contradicts the assumption. 58