JNTUH CSE-AIML CS416PC: FORMAL LANGUAGES AND AUTOMATA THEORY SYLLABUS

JNTUH CSE-AIML CS416PC: FORMAL LANGUAGES AND AUTOMATA THEORY SYLLABUS

Course Objectives:
 To provide introduction to some of the central ideas of theoretical computer science from the perspective of formal languages.
 To introduce the fundamental concepts of formal languages, grammars and automata theory.
 Classify machines by their power to recognize languages.
 Employ finite state machines to solve problems in computing.
 To understand deterministic and non-deterministic machines.
 To understand the differences between decidability and undecidability.
Course Outcomes:
 Able to understand the concept of abstract machines and their power to recognize the languages.
 Able to employ finite state machines for modeling and solving computing problems.
 Able to design context free grammars for formal languages.
 Able to distinguish between decidability and undecidability.
 Able to gain proficiency with mathematical tools and formal methods.
UNIT – I
Introduction to Finite Automata: Structural Representations, Automata and Complexity, the Central Concepts of Automata Theory – Alphabets, Strings, Languages, Problems. Nondeterministic Finite Automata: Formal Definition, an application, Text Search, Finite Automata with Epsilon-Transitions.Deterministic Finite Automata: Definition of DFA, How A DFA Process Strings, The language of DFA, Conversion of NFA with €-transitions to NFA without €-transitions. Conversion of NFA to DFA, Moore and Melay machines
UNIT – II
Regular Expressions: Finite Automata and Regular Expressions, Applications of Regular Expressions, Algebraic Laws for Regular Expressions, Conversion of Finite Automata to Regular Expressions. Pumping Lemma for Regular Languages, Statement of the pumping lemma, Applications of the Pumping Lemma. Closure Properties of Regular Languages: Closure properties of Regular languages, Decision Properties of Regular Languages, Equivalence and Minimization of Automata.
UNIT – III
Context-Free Grammars: Definition of Context-Free Grammars, Derivations Using a Grammar, Leftmost and Rightmost Derivations, the Language of a Grammar, Sentential Forms, Parse Tress, Applications of Context-Free Grammars, Ambiguity in Grammars and Languages. Push Down Automata: Definition of the Pushdown Automaton, the Languages of a PDA, Equivalence of PDA’s and CFG’s, Acceptance by final state, Acceptance by empty stack,
Deterministic Pushdown Automata. From CFG to PDA, From PDA to CFG.
UNIT – IV
Normal Forms for Context- Free Grammars: Eliminating useless symbols, Eliminating €- Productions. Chomsky Normal form Griebech Normal form. Pumping Lemma for Context-Free Languages: Statement of pumping lemma, Applications Closure Properties of Context-Free Languages: Closure properties of CFL’s, Decision Properties
of CFL’s Turing Machines: Introduction to Turing Machine, Formal Description, Instantaneous description,
The language of a Turing machine

UNIT – V
Types of Turing machine: Turing machines and halting Undecidability: Undecidability, A Language that is Not Recursively Enumerable, An Undecidable Problem That is RE, Undecidable Problems about Turing Machines, Recursive languages, Properties of recursive languages, Post’s Correspondence Problem, Modified Post Correspondence problem,Other Undecidable Problems, Counter machines.
TEXT BOOKS:
1. Introduction to Automata Theory, Languages, and Computation, 3nd Edition, John E. Hopcroft,Rajeev Motwani, Jeffrey D. Ullman, Pearson Education.
2. Theory of Computer Science – Automata languages and computation, Mishra and Chandrashekaran, 2nd edition, PHI.
REFERENCE BOOKS:
1. Introduction to Languages and The Theory of Computation, John C Martin, TMH.
2. Introduction to Computer Theory, Daniel I.A. Cohen, John Wiley.
3. A Text book on Automata Theory, P. K. Srimani, Nasir S. F. B, Cambridge University Press.
4. Introduction to the Theory of Computation, Michael Sipser, 3rd edition, Cengage Learning.
5. Introduction to Formal languages Automata Theory and Computation Kamala Krithivasan, Rama R, Pearson

CSE-AIML

SEMESTER SUBJECT CODE SUBJECT Lession Plan Lecturer Notes & Question Bank SYLLABUS ABOUT TUTOR
I MA101BS Mathematics – I Click Here
I AP102BS Applied Physics Click Here
I CS103ES Programming for Problem Solving Click Here
I ME104ES Engineering Graphics Click Here
I AP105BS Applied Physics Lab Click Here
I CS106ES Programming for Problem Solving Lab Click Here
I MC109ES Environmental Science Click Here
II MA201BS Mathematics – II Click Here
II CH202BS Chemistry Click Here
II EE203ES Basic Electrical Engineering Click Here
II ME205ES Engineering Workshop Click Here
II EN205HS English Click Here
II CH206BS Engineering Chemistry Lab Click Here
II EN207HS English Language and Communication Skills Lab Click Here
II EE208ES Basic Electrical Engineering Lab Click Here
II-I CS310PC Discrete Mathematics Click Here
II-I CS302PC Data Structures Click Here
II-I MA313BS Mathematical and Statistical Foundations Click Here
II-I CS304PC Computer Organization and Architecture Click Here
II-I CS311PC Python Programming Click Here
II-I SM306MS Business Economics & Financial Analysis Click Here
II-I CS307PC Data Structures Lab Click Here
II-I CS312PC Python Programming Lab Click Here
II-I MC309 Gender Sensitization Lab Click Here
II-II CS416PC Formal Language and Automata Theory Click Here
II-II CS417PC Software Engineering Click Here
II-II CS403PC Operating Systems Click Here
II-II CS404PC Database Management Systems Click Here
II-II CS412PC Object Oriented Programming using Java Click Here
II-II CS406PC Operating Systems Lab Click Here
II-II CS407PC Database Management Systems Lab Click Here
II-II CS408PC Java Programming Lab Click Here
II-II MC409 Constitution of India Click Here
III-I Design and Analysis of Algorithms Click Here
III-I Machine Learning Click Here
III-I Computer Networks Click Here
III-I Compiler Design Click Here
III-I Graph Theory (PE1) Click Here
III-I Introduction to Data Science(PE1) Click Here
III-I Web Programming(PE1) Click Here
III-I Image Processing(PE1) Click Here
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III-I Software Testing Methodologies(PE2) Click Here
III-I Information Retrieval Systems(PE2) VIJAYANAND S
III-I Pattern Recognition(PE2) Click Here
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III-I Data Warehousing and Business Intelligence(PE2) Click Here
III-I Machine Learning Lab Click Here
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III-I Intellectual Property Rights Click Here
III-II Artificial Intelligence Click Here Click Here
III-II DevOps Click Here Click Here
III-II Natural Language Processing Click Here Click Here
III-II Internet of Things(PE3) Click Here Click Here
III-II Data Mining(PE3) Click Here Click Here
III-II Scripting Languages(PE3) Click Here Click Here
III-II Mobile Application Development(PE3) Click Here Click Here
III-II Cryptography and Network Security(PE3) Click Here Click Here
III-II Artificial Intelligence and Natural Language Processing Lab Click Here Click Here
III-II DevOps Lab Click Here Click Here
IV-I Neural Networks & Deep Learning Click Here Click Here
IV-I Reinforcement Learning Click Here Click Here
IV-I Quantum Computing(PE4) Click Here Click Here
IV-I Expert Systems(PE4) Click Here Click Here
IV-I Cloud Computing(PE4) Click Here Click Here
IV-I Game Theory(PE4) Click Here Click Here
IV-I Mobile Computing(PE4) Click Here Click Here
IV-I Expert Systems(PE4) Click Here Click Here
IV-I Cloud Computing(PE4) Click Here Click Here
IV-I Game Theory(PE4) Click Here Click Here
IV-I Mobile Computing(PE4) Click Here Click Here
IV-I Social Network Analysis(PE5) Click Here Click Here
IV-I Federated Machine Learning(PE5) Click Here Click Here
IV-I Augmented Reality & Virtual Reality(PE5) Click Here Click Here
IV-I Web Security(PE5) Click Here Click Here
IV-I Ad-hoc & Sensor Networks Click Here Click Here
IV-I Deep Learning Lab Click Here Click Here
IV-II Organizational Behaviour Click Here Click Here
IV-II Speech and Video Processing(PE6) Click Here Click Here
IV-II Robotics Process Automation(PE6) Click Here Click Here
IV-II Randomized Algorithms(PE6) Click Here Click Here
IV-II Cognitive Computing(PE6) Click Here Click Here
IV-II Semantic Web(PE6) Click Here Click Here

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