Why study the Theory of Computation, Languages and Strings:
Strings, Languages. A Language Hierarchy, Computation,
Finite State Machines (FSM):
Deterministic FSM, Regular languages, Designing FSM, Nondeterministic FSMs, From FSMs to Operational Systems, Simulators for FSMs, Minimizing FSMs, Canonical form of Regular languages, Finite State Transducers, Bidirectional Transducers.
Textbook 1: Ch 1,2, 3,4, 5.1 to 5.10 RBT: L1, L2
Regular Expressions (RE):
what is a RE?, Kleene’s theorem, Applications of REs, Manipulating and Simplifying REs. Regular Grammars: Definition, Regular Grammars and Regular languages. Regular Languages (RL) and Non-regular Languages: How many RLs, To show that a language is regular, Closure properties of RLs, to show some languages are not RLs. Textbook 1: Ch 6, 7, 8: 6.1 to 6.4, 7.1, 7.2, 8.1 to 8.4 RBT: L1, L2, L3
Context-Free Grammars(CFG):
Introduction to Rewrite Systems and Grammars, CFGs and languages, designing CFGs, simplifying CFGs, proving that a Grammar is correct, Derivation and Parse trees, Ambiguity, Normal Forms. Pushdown Automata (PDA): Definition of non-deterministic PDA, Deterministic and Non-deterministic PDAs, Nondeterminism and Halting, alternative equivalent definitions of a PDA, alternatives that are not equivalent to PDA.
Textbook 1: Ch 11, 12: 11.1 to 11.8, 12.1, 12.2, 12,4, 12.5, 12.6
RBT: L1, L2, L3
Algorithms and Decision Procedures for CFLs:
Decidable questions, Un-decidable questions.
Turing Machine:
Turing machine model, Representation, Language acceptability by TM, design of TM, Techniques for TM construction. Variants of Turing Machines (TM), The model of Linear Bounded automata. Textbook 1: Ch 14: 14.1, 14.2,
Textbook 2: Ch 9.1 to 9.8
RBT: L1, L2, L3
Decidability:
Definition of an algorithm, decidability, decidable languages, Undecidable languages, halting problem of TM, Post correspondence problem.
Complexity:
Growth rate of functions, the classes of P and NP, Quantum Computation: quantum computers, ChurchTuring thesis.
Applications:
G.1 Defining syntax of programming language, Appendix J: Security
Textbook 2: 10.1 to 10.7, 12.1, 12.2, 12.8, 12.8.1, 12.8.2 Textbook 1: Appendix: G.1(only), J.1 & J.2 RBT: L1, L2, L3
Course Outcomes:
The student will be able to :
• Acquire fundamental understanding of the core concepts in automata theory and Theory of Computation
• Learn how to translate between different models of Computation (e.g., Deterministic and Non-deterministic and Software models).
• Design Grammars and Automata (recognizers) for different language classes and become knowledgeable about restricted models of Computation (Regular, Context Free) and their relative powers.
• Develop skills in formal reasoning and reduction of a problem to a formal model, with an emphasis on semantic precision and conciseness.
• Classify a problem with respect to different models of Computation.
Question Paper Pattern:
• The question paper will have ten questions.
• Each full Question consisting of 20 marks
• There will be 2 full questions (with a maximum of four sub questions) from each module.
• Each full question will have sub questions covering all the topics under a module.
• The students will have to answer 5 full questions, selecting one full question from each module.
Textbooks:
1. Elaine Rich, Automata, Computability and Complexity, 1st Edition, Pearson education,2012/2013
2. K L P Mishra, N Chandrasekaran , 3rd Edition, Theory of Computer Science, PhI, 2012.
Reference Books:
1. John E Hopcroft, Rajeev Motwani, Jeffery D Ullman, Introduction to AutomataTheory, Languages, and Computation, 3rd Edition, Pearson Education, 2013
2. Michael Sipser : Introduction to the Theory of Computation, 3rd edition, Cengage learning,2013
3. John C Martin, Introduction to Languages and The Theory of Computation, 3rd Edition, Tata McGraw –Hill Publishing Company Limited, 2013
4. Peter Linz, “An Introduction to Formal Languages and Automata”, 3rd Edition, Narosa Publishers, 1998
5. Basavaraj S. Anami, Karibasappa K G, Formal Languages and Automata theory, Wiley India, 2012
6. C K Nagpal, Formal Languages and Automata Theory, Oxford University press, 2012.
Faculty can utilize open source tools (like JFLAP) to make teaching and learning more interactive.