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Lecture 1 Theory of Automata

Lecture 1 Theory of Automata. Pragmatics. Pre-Requisites No Pre-Requisite Text book Introduction to Computer Theory by Daniel I.A. Cohen Quizzes Roughly once every two weeks Marks Distribution Theoretical Course

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Lecture 1 Theory of Automata

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  1. Lecture 1Theory of Automata

  2. Pragmatics • Pre-Requisites • No Pre-Requisite • Text book • Introduction to Computer Theory by Daniel I.A. Cohen • Quizzes • Roughly once every two weeks • Marks Distribution • Theoretical Course • 30% Mid-term, 40% Final, 15 % Quizzes, 15 % assignments and class behaviour

  3. Course Objectives • The major objective of this course is to introduce the student to the concepts of theory of automata in computer science. The student should acquire insights into the relationship among formal languages, formal grammars, and automata. • Upon successful completion of this course, students will be able to: • Understand the equivalence between Nondeterministic Finite State Automata and Deterministic Finite State Automata. • Understand the equivalence between Context-Free Grammars and Nondeterministic Pushdown Automata. • Appreciate the power of the Turing Machine, as an abstract automaton, that describes computation, effectively and efficiently.

  4. What does “automata” mean? • It is the plural of automaton, and it means “something that works automatically”

  5. Automata Theory • Deals with the definitions and properties of mathematical model of computation. • Examples: Finite automata, Context free grammars. • Finite Automaton: Text Processing, Compilers • Context Free grammars: Programming languages, AI

  6. Sets • A set is a group of objects, called elements (or members) of this set. For example, the students in this room form a set. • A set can be defined by listing all its elements inside braces, e.g.: • S ={ 7,21,57} • The order of elements in sets do not matter – in particular, S={7,21,57} = {21,57,7}

  7. Sets Continued… • The membership is denoted by ϵ symbol. For example, 21 ϵ S but 10 not belong to S. • If every member of A is also a member of B. We say that A is a subset of B andif A is a subset of B but not equal to B then A is proper subset of B and write as A B. If A is a subset of B and A is equal to B then A is improper subset of B and write as A B.

  8. Examples of Sets • The set with no elements is called the empty set and denoted by Λ • The empty set is a subset of every set. • The set of natural numbers N (or N): • N = {1, 2, 3, . . .} • The set of integers Z (or Z): • Z = {...,-2,-1, 0, 1, 2,…} • It is clear that N subset of Z

  9. Set Operations

  10. Languages • In English, we distinguish 3 different entities: letters, words, and sentences. • Groups of letters make up words and groups of words make up sentences. • However, not all collections of letters form valid words, and not all collections of words form valid sentences. • This situation also exists with computer languages. • Certain (but not all) strings of characters are recognizable words (e.g., IF, ELSE, FOR, WHILE …).

  11. Basic Definitions • A finite non-empty set of symbols (letters), is called an alphabet. • It is denoted by Σ ( Greek letter sigma). Example: Σ={a,b} Σ={0,1} //important as this is the language //which the computer understands. Σ={i,j,k}

  12. Strings Concatenation of finite symbols from the alphabet is called a string. • Example: If Σ= {a,b} then a, abab, aaabb, ababababababababab

  13. Words • Words are strings belonging to some language. Example: If Σ= {x} then a language L can be defined as L={xn: n=1,2,3,…..} or L={x,xx,xxx,….} Here x,xx,… are the words of L

  14. EMPTY STRING or NULL STRING • We shall allow a string to have no letters. We call this empty string or null string, and denote it by the symbol Λ. • For all languages, the null word, if it is a word in the language, is the word that has no letters. We also denote the null word by Λ.

  15. String Operations Concatenation

  16. Reverse

  17. String Length Length: Examples:

  18. Defining Languages • Example: Consider this alphabet with only one letter ∑ = { x } • We can define a language by saying that any nonempty string of alphabet letters is a word L1 = { x, xx, xxx, xxxx, … } or L1 = { xn for n = 1, 2, 3, … } Note that because of the way we have defined it, the language L1 does not include the null word Λ.

  19. Example: The language L of strings of odd length, defined over Σ={a}, can be written as L={a, aaa, aaaaa,…..} • Example: The language L of strings that does not start with a, defined over Σ={a,b,c}, can be written as L={b, c, ba, bb, bc, ca, cb, cc, …}

  20. Example: The language L of strings of length 2, defined over Σ={0,1,2}, can be written as L={00, 01, 02,10, 11,12,20,21,22} • Example: The language L of strings ending in 0, defined over Σ ={0,1}, can be written as L={0,00,10,000,010,100,110,…}

  21. Example: • The language EQUAL, of strings with number of a’s equal to number of b’s, defined over Σ={a,b}, can be written as {Λ ,ab,aabb,abab,baba,abba,…} • The language EVEN-EVEN, of strings with even number of a’s and even number of b’s, defined over Σ={a,b}, can be written as {Λ, aa, bb, aaaa,aabb,abab, abba, baab, baba, bbaa, bbbb,…}

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