Theory of Computation or automata theory chapter 1 according to VIT vellore syllabus.

1. Theory of Computation
Gunavathi C
gunavathi.cm@vit.ac.in

2. Theory of computation
• Theory of computation (TOC) is a branch of Computer Science that is
concerned with how problems can be solved using algorithms and how
efficiently they can be solved.
• To understand the way an algorithm is meant to work
• To actually prove it works through analysing problems that may arise
with the technique used and finding solutions to these problems.
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3. Computational model
• What is Computation?
Program running in computer
Input x Algorithm f(x) Output
YES
Input w M
NO
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4. •What is computation?
 Execution of algorithms.
 Step by step procedure that produce a result from given input.
 Computation is simply a sequence of steps that can be performed
by computer.
•What is Theory?
• A theory explains known facts.
• It also allows the scientists to make predictions of what they should
observe if a theory is true.
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5. Purpose of Theory of Computation
Develop formal mathematical models of computation that reflect real-
world computers.
Models of computation can be classified in three categories:
• Sequential models
• Functional models
• Concurrent models.
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6. Models of Computation
• Sequential models:
FSM, PDA, Random Access Machine, TM
• Functional models:
Lambda Calculus, General Recursive functions, Combinatory logic
• Concurrent models:
Petri nets, DFG (Data Flow Graph), Interaction nets, Actor model
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7. Questions
• Are there problems that cannot be solved on any computing device?
• How does one determine if a given problem can or cannot be
computationally solved?
• If we place bounds on the resources (time and space) available to a
computer, then what can be said about which problems can and
which problems cannot be solved on a computer?
• How does the power of a computer change, if it has access to random
bits?
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8. Answers
• Computation models: Finite State Automata, Turing machines (TM).
• Regular Expressions and Regular Grammars.
• Context-free Grammars and Pushdown Automata.
• Computability Theory and reducibility
• Computational complexity
• Determinism and Non-determinism
• Time and Space Complexity
• NP completeness
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9. Motivation
1. What is computable,and what is not ?
2. How to analyze an algorithm ?
3. Whether a program/code is executable or not?
4. Whether a program/code is erroneous or not?
5. Is it possible to make a program more efficient?
6. What is easy
,and what is difficult,to compute?
7. What is easy
,and what is hard for computers to do?
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10. Fields Related to TOC
Web search: theory of pattern matching.
Sequential circuits: theory of finite state automata.
Compilers: theory of context free grammars.
Cryptography: theory of computational complexity.
Neural networks : Automata theory
Computational biology: DNA and proteins are strings.
Artificial intelligence: the undecidability of first-order logic.(FL and Automata)
Natural languages: mostly context-free. Speech understanding systems use
probabilistic FSMs
Algorithm Analysis: Computational complexity
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11. Module -1
Introduction to Languages and Grammars
 Recall on Proof techniques in Mathematics
 Overview of a Computational Models
 Languages and Grammars
 Alphabets
 Strings
 Operations on Languages
 Overview on Automata
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12. Introduction to TOC
⦁ TOC suggests various abstractmodelsofcomputation, whicharerepresented
mathematically
.
⦁ The machineswhich performscomputationarenot actualcomputers.
⦁ Theyareabstractmachines.
⦁ Some examplesof abstractmachineare:
1. Turingmachines- Universalmodel.
2. FiniteAutomata- RestrictedMachine
3. Push DownAutomata-Restrictedbutpowerful thanFA
⦁ Theory of computation lays foundation for various fields of computer science,
such as:
Compiler Design, Robotics, Cryptography, Artificial Intelligence
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13. Chomsky Hierarchy
Language Grammar Machine Example
Type 3 Regular languages
Regular grammars
• Right-linear grammars
• Left-linear grammars
Finite-state
automata
a*
Type 2 Context-free languages Context-free grammars
Push-down
automata
anbn
Type 1 Context-sensitive languages Context-sensitive grammars
Linear-bound
automata
anbncn
Type 0
Recursive languages
Recursively enumerable
languages
Unrestricted grammars
Turing
machines
any
computable
function
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14. Strings and Languages (1)
• Alphabet: Finite, nonempty set of symbols
• Examples:
•  = {0, 1}: binary alphabet
•  = {a, b, c, …, z}: the set of all lower case letters
• The set of all ASCII characters
• String: Finite sequence of symbols from an alphabet 
• Examples:
• 01101 where  = {0, 1}
• abracadabra where  = {a, b, c, …, z}
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15. Strings and Languages (2)
• Empty String: The string with zero occurrences of symbols from  and is
denoted e or 
• Length of String: Number of symbols in the string
• The length of a string w is usually written |w|
• |1010| = 4
• |e| = 0
• |uv| = |u| + |v|
• Reverse : wR
• If w = abc, wR = cba
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16. Strings and Languages (3)
• Concatenation: if x and y are strings, then xy is the string obtained by
placing a copy of y immediately after a copy of x
• x = a1a2 …ai, y = b1b2 …bj
• xy = a1a2 …aib1b2 …bj
• Example: x = 01101, y = 110, xy = 01101110
• xe = ex = x
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17. Strings and Languages (4)
• Power of an Alphabet: k = the set of strings of length k with symbols from 
• Example:  = {0, 1}
• 1 =  = {0, 1}
• 2 = {00, 01, 10, 11}
• 0 = {e}
• Question: How many strings are there in 3?
• The set of all strings over  is denoted *
• * = 0  1  2  3  …
• Also
• + = 1  2  3  …
• * = +  {e}
• + = * - {e}
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18. Strings and Languages (5)
• Substring: any string of consecutive characters in some string w
• If w = abc
• e, a, ab, abc are substrings of w
• Prefix and suffix:
• if w = vu
• v is a prefix of w
• u is a suffix of w
• Example
• If w = abc
• a, ab , abc are prefixes of w
• c, bc, abc are suffixes of w
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19. Strings and Languages (6)
• Suppose: S is the string banana
• Prefix : ban, banana
• Suffix : ana, banana
• Substring : nan, ban, ana, banana
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20. Strings and Languages (7)
• Language: set of strings chosen from some alphabet
• A language is a subset of *
• Example of languages:
• The set of valid Arabic words
• The set of strings consisting of n 0’s followed by n 1’s
• {e, 01, 0011, 000111, …}
• The set of strings with equal number of 0’s and 1’s
• {e, 01, 10, 0011, 0101, 1010, 1001, 1100, …}
• Empty language:  = { }
• The language {e} consisting of the empty string
• Note:   {e}
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21. Strings and Languages (8)
• Can concatenate languages
• L1L2 = {xy | x  L1, y  L2}
• Ln = L concatenated with itself n times
• L0 = {e}; L1 = L
• Star-closure
• L* = L0  L1  L2  ...
• L+ = L* - L0
• Languages can be finite or infinite
• L = {a, aba, bba}
• L = {an | n > 0}
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22. Strings and Languages (9)
OPERATION DEFINITION
union of L and M
written L  M
concatenation of L
and M written LM
Kleene closure of L
written L*
positive closure of L
written L+
L  M = {s | s is in L or s is in M}
LM = {st | s is in L and t is in M}
L+ =  Li, i=1,.., 
L* denotes “zero or more concatenations of “ L
L* =  Li , i=0,.., 
L+ denotes “one or more concatenations of “ L
L+ = LL*
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23. Strings and Languages (10)
L = {A, B, …, Z, a, b, …z} D = {1, 2, …, 9}
L  D = the set of letters and digits
LD = all strings consisting of a letter followed by a digit
L2 = the set of all two-letter strings
L4 = L2 L2 = the set of all four-letter strings
L* = { All possible strings of L plus e }, L+ = L* - e
D+ = set of strings of one or more digits
L (L  D ) = set of all strings consisting of a letter
followed by a a letter or a digit
L (L  D )* = set of all strings consisting of letters and
digits beginning with a letter 23

24. Strings and Languages (11)
• The language L consists of strings over {a,b} in which each string
begins with an a should have an even length
• aa, ab  L
• aaaa,aaab,aaba,aabb,abaa,abab,abba,abbb  L
• baa  L
• a  L
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25. Strings and Languages (12)
• The language L consists of strings over {a,b} in which each occurring
of b is immediately preceded by an a
• e  L
• a  L
• abaab  L
• bb  L
• bab  L
• abb  L
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26. Strings and Languages (13)
• Let X = {a,b,c} and Y = {abb, ba}. Then
• XY = {aabb, babb, cabb, aba, bba, cba}
• X0 = {e}
• X1 = X = {a,b,c}
• X2 = XX = {aa,ab,ac,ba,bb,bc,ca,cb,cc}
• X3 = XXX =
{aaa,aab,aac,aba,abb,abc,aca,acb,acc,baa,bab,bac,bba,bbb,bbc,bca,bcb,bcc,c
aa,cab,cac,cba,cbb,cbc,cca,ccb,ccc}
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27. Strings and Languages (14)
• The language L = {a,b}*{bb}{a,b}* = *{bb}*
• consists of the strings over {a,b} that contain the substring bb
• bb  L
• abb  L
• bbb  L
• aabb  L
• bbaaa  L
• bbabba  L
• abab  L
• bab  L
• b  L
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28. Strings and Languages (15)
• Let L be the language that consists of all strings that begin with
aa or end with bb
• L1 = {aa}{a,b}*
• L2 = {a,b}*{bb}
• L = L1  L2 = {aa}{a,b}*  {a,b}*{bb}
• bb  L
• abb  L
• bbb  L
• aabb  L
• bbaaa  L
• bbabba  L
• abab  L
• bab  L
• ba  L
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29. Strings and Languages (16)
• Let L1 = {bb} and L2 = {e, bb, bbbb} over b
• The languages L1
* and L2
* both contain precisely the strings
consisting of an even number of b’s.
• e , with length zero, is an element of L1
* and L2
*
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30. Strings and Languages (17)
• What is the language of all even-length strings over {a,b}
• L = {aa, bb, ab, ba}* = (aa|bb|ab|ba)*
• What is the language of all odd-length strings over {a,b}
• L = {a,b}* - {aa, bb, ab, ba}* or
• L = {a,b}{aa, bb, ab, ba}* or
• L = {aa, bb, ab, ba}* {a,b}
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