![Syllabus
• Syllabus:
• Unit – 1 [8 Hours]: Introduction - Alphabets, Strings and Languages, Automata and Grammars; Deterministic finite
Automata (DFA) - Formal Definition, Simplified notation, State transition graph, Transition table, Language of DFA;
Nondeterministic finite Automata (NFA) - NFA with epsilon transition, Language of NFA, Equivalence of NFA and
DFA, Minimization of Finite Automata, Distinguishing one string from other
•
Unit – 2 [8 Hours]: Regular Expression (RE) - Definition, Operators of regular expression and their precedence,
Algebraic laws for Regular expressions; Relation with FA - Regular expression to FA, DFA to Regular expression; Non
Regular Languages - Pumping Lemma for regular Languages, Application of Pumping Lemma; Properties - Closure
properties of Regular Languages, Decision properties of Regular Languages, Applications and Limitation of FA
•
Unit – 3 [8 Hours]: Context Free Grammar (CFG) - Definition, Examples, Derivation, Derivation trees; Ambiguity in
Grammar - Inherent ambiguity, Ambiguous to Unambiguous CFG; Normal forms for CFGs - Useless symbols,
Simplification of CFGs, CNF and GNF; Context Free Languages (CFL) - Closure properties of CFLs, Decision
Properties of CFLs, Emptiness, Finiteness and Membership, Pumping lemma for CFLs
•
Unit – 4 [8 Hours]: Push Down Automata (PDA) - Description and definition, Instantaneous Description, Language
of PDA; Variations of PDA - Acceptance by Final state, Acceptance by empty stack, Deterministic PDA; Equivalence
of PDA and CFG - CFG to PDA and PDA to CFG
•
Unit – 5 [8 Hours]: Turing machines (TM) - Basic model, definition and representation, Instantaneous Description;
Variants of Turing Machine - TM as Computer of Integer functions, Universal TM; Church’s Thesis; Language
acceptance by TM - Recursive and recursively enumerable languages;
•
Unit – 6 [8 Hours]: Decidability - Halting problem, Introduction to Undecidability, Undecidable problems about
TMs; Complexity - Time Complexity, Problem classes - P, NP, NP-Hard, NP-Complete.](https://image.slidesharecdn.com/1introduction-240702160954-eb11e155/85/Theory-of-Introduction-in-Computer-Science-7-320.jpg)
Theory of Introduction in Computer Science
- 2. From high level • From a high level what this course is about? – Given a set, say S. – Let 𝐴 ⊆ 𝑆. – Both S and A are well defined. – We are given an element 𝑥 ∈ 𝑆, and asked to find whether this 𝑥 is in 𝐴 or not. – That’s all !
- 3. Surprises !! • Surprising things – This is related to decision problems. • S is set all face images. A is set of images of a particular person. {Face verification} • S is set of all graphs. A is set of graphs with Hamiltonian cycle. – Sometimes this is an unsolvable problem. ?? – Sometimes this is an easy task, sometimes quite a difficult one. • Recall, 𝑂 𝑛2 is time consuming than 𝑂(𝑛) algorithm.
- 4. We want general enough set • Set of strings over some alphabet like {0,1}. • For example set of strings that end with a 0, {0, 00, 10, 000, 010, 100, 110, …} • Eg2: Each string in the set can be seen as a positive binary number and let the set be the set of prime numbers. – Given a number (binary string of 0s and 1s) you want to find whether this is in the set (prime) or not (not a prime).
- 5. Why strings are chosen? • Any data element like number or image or any thing can be represented as a string. – Can we say DNA code represents a human being? • Even a method which solves a problem can be represented as a string. • A proof can be represented as a string. • So strings over an alphabet gives us power to represent the things… that is we have languages of strings to represent the things.
- 7. Syllabus • Syllabus: • Unit – 1 [8 Hours]: Introduction - Alphabets, Strings and Languages, Automata and Grammars; Deterministic finite Automata (DFA) - Formal Definition, Simplified notation, State transition graph, Transition table, Language of DFA; Nondeterministic finite Automata (NFA) - NFA with epsilon transition, Language of NFA, Equivalence of NFA and DFA, Minimization of Finite Automata, Distinguishing one string from other • Unit – 2 [8 Hours]: Regular Expression (RE) - Definition, Operators of regular expression and their precedence, Algebraic laws for Regular expressions; Relation with FA - Regular expression to FA, DFA to Regular expression; Non Regular Languages - Pumping Lemma for regular Languages, Application of Pumping Lemma; Properties - Closure properties of Regular Languages, Decision properties of Regular Languages, Applications and Limitation of FA • Unit – 3 [8 Hours]: Context Free Grammar (CFG) - Definition, Examples, Derivation, Derivation trees; Ambiguity in Grammar - Inherent ambiguity, Ambiguous to Unambiguous CFG; Normal forms for CFGs - Useless symbols, Simplification of CFGs, CNF and GNF; Context Free Languages (CFL) - Closure properties of CFLs, Decision Properties of CFLs, Emptiness, Finiteness and Membership, Pumping lemma for CFLs • Unit – 4 [8 Hours]: Push Down Automata (PDA) - Description and definition, Instantaneous Description, Language of PDA; Variations of PDA - Acceptance by Final state, Acceptance by empty stack, Deterministic PDA; Equivalence of PDA and CFG - CFG to PDA and PDA to CFG • Unit – 5 [8 Hours]: Turing machines (TM) - Basic model, definition and representation, Instantaneous Description; Variants of Turing Machine - TM as Computer of Integer functions, Universal TM; Church’s Thesis; Language acceptance by TM - Recursive and recursively enumerable languages; • Unit – 6 [8 Hours]: Decidability - Halting problem, Introduction to Undecidability, Undecidable problems about TMs; Complexity - Time Complexity, Problem classes - P, NP, NP-Hard, NP-Complete.
- 8. Text Books Text Books: • John E. Hopcroft, Rajeev Motwani and Jeffrey D. Ullman, Introduction to Automata Theory, Languages and Computation, Pearson Education, 3rd edition, 2014, ISBN: 978-0321455369 • Michael Sipser, Introduction to the Theory of Computation, Cengage Learning, 3rd Edition, 2014, ISBN: 978-8131525296 Reference Books: • John C. Martin, Introduction to Languages and the Theory of Computation, McGraw-Hill Education, 4th edition, 2010, ISBN: 978-0073191461 • Bernard M. Moret, The Theory of Computation, Pearson Education, 2002, ISBN: 978-8131708705
- 9. Evaluation • Quiz: Best (n-1) 20 marks • Mid1: 20 marks • Mid2: 25 marks • Endsem: 35 marks • Can be updated (and will be informed).