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2nd April 2016, 09:20 AM
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Join Date: May 2012
Re: IIT Kgp B.Tech Syllabus

The Indian Institute of Technology Kharagpur is a public engineering institution established by the government of India in 1951. It is recognized as an Institute of National Importance by the government of India. The Institute was established in 1951.

IIT Kharagpur B. Tech. (Hons.) in Computer Science & Engineering syllabus

Semester III-

CourseCode Name
D1 Discrete Structures
D2 Algorithms – I
IC9 Introduction to electronics
D3 Signals and Networks
B1 Breadth –1 (HSS)
L1 Algorithms Laboratory
IL7 Introduction to Electronics Lab
L2 Signals &Networks Lab
IP-3 EAA – 3

Semester IV-

Course Code Name
D4 Switching Circuits and Logic Design
D5 Formal Languages and Automata Theory
D6 Software Engineering
IC10 Probability and Statistics
D7 HSS –Core
L3 Switching Circuits Laboratory
L4 Software Engineering Laboratory
IP-4 EAA – 4
Total

Semester V-

CourseCode Name

D8 Computer Organization & Architecture
D9 Compilers
D10 Algorithms – II
E1 MathematicsElective(Elective-1)
B3 Breadth –2(Non EE/Sc)
L5 Computer Organization Laboratory
L6 Compilers Laboratory

Semester VI-

Course Code Name
D11 Operating Systems
D12 Computer Networks
E2 Elective – 2
E3 Elective – 3
IC11 Bio-Science
IC12 Environmental Science
L7 Operating Systems Lab
L8 Networks Lab
L9 Project Seminar
Total
Semester VII

Course Code Name
D13 Theory of Computation
E4 Elective – 4
E5 Elective – 5
E6 Elective – 6
E7 Elective –7 (Open)
ST Summer Training
P1 Project –Part 1

Semester VIII-

Course Code Name
E8 Elective – 8
E9 Elective – 9
E10 Elective –10(Open)
B4 Breadth –3(Entre/MNMG/HSS/IPL)
CV Comprehensive Viva
P2 Project –Part 2


IIT Kharagpur B. Tech. (Hons.) in Computer Science & Engineering syllabus
CS11001/CS11002 PROGRAMMING AND DATA STRUCTURES (3-1-0 : 4 Credit) Introduction to digital computers; introduction to programming – variables, assignments; expressions; input/output; conditionals and branching; iteration; functions; recursion; arrays; introduction to pointers; character strings; time and space requirements; searching and sorting; structures; introduction to data-procedure encapsulation; dynamic allocation; linked structures; introduction to data structures – stacks and queues. (A programming language like C/C++ may be used as a basis language. The same language must be used for the laboratory).
CS19001/CS19002 PDS Laboratory
Suggested assignments to be conducted on a 3-hour slot. It will be conducted in tandem with the theory course so that the topics for problems given in the lab are already initiated in the theory class. The topics taught in the theory course should be appropriately sequenced for synchronization with the laboratory. A sample sequence of topics and lab classes for the topic are given below:
1. Familiarization of a computer and the environment and execution of sample programs
2. Expression evaluation
3. Conditionals and branching
4. Iteration
5. Functions
6. Recursion
7. Arrays
8. Structures
9. Linked lists
10. Data structures

It is suggested that some problems related to continuous domain problems in engineering and their numerical solutions are given as laboratory assignments. It may be noted that some of basic numerical methods are taught in the Mathematics course. References
1. Brian W. Kernighan and Dennis M. Ritchie, The C Programming Language, Prentice Hall of India.

2. E. Balaguruswamy, Programming in ANSI C, Tata McGraw-Hill.

3. Byron Gottfried, Schaum's Outline of Programming with C, McGraw-Hill.

4. Seymour Lipschutz, Data Structures, Schaum’s Outlines Series, Tata McGraw-Hill.

5. Ellis Horowitz, Satraj Sahni and Susan Anderson-Freed, Fundamentals of Data Structures in C, W. H. Freeman and Company.

6. R. G. Dromey, How to Solve it by Computer, Prentice-Hall of India.

CS20006 SOFTWARE ENGINEERING (3-0-0 : 3 Credit) Introduction, software life-cycle models, software requirements specification, formal requirements specification and verification – axiomatic and algebraic specifications, function-oriented software design, object-oriented design, UML, design patterns, user interface design, coding and unit testing, integration and systems testing, debugging techniques, software quality – SEI CMM and ISO-9001. software reliability and fault-tolerance, software project planning, monitoring, and control, software maintenance, computer-aided software engineering (CASE), software reuse, component-based software development, extreme programming. CS29006 Software Engineering Laboratory (0-0-3 : 2 Credit) Development of requirements specification, function oriented design using SA/SD, Object-oriented design using UML, test case design, implementation using Java and testing. Use of appropriate CASE tools and other tools such as configuration management tools, program analysis tools in the software life cycle. References
1. Rajib Mall, Fundamentals of Software Engineering, Prentice Hall India.

2. Pankaj Jalote, An integrated approach to Software Engineering, Springer/Narosa.

3. Roger S. Pressman, Software Engineering: A practitioner's approach, McGraw Hill.

4. Ian Sommerville, Software Engineering, Addison-Wesley.

CS21001 DISCRETE STRUCTURES (3-1-0 : 4 Credit) Propositional logic: Syntax, semantics, valid, satisfiable and unsatisfiable formulas, encoding and examining the validity of some logical arguments. Proof techniques: forward proof, proof by contradiction, contrapositive proofs, proof of necessity and sufficiency. Sets, relations and functions: Operations on sets, relations and functions, binary relations, partial ordering relations, equivalence relations, principles of mathematical induction. Size of a set: Finite and infinite sets, countable and uncountable sets, Cantor's diagonal argument and the power set theorem, Schroeder-Bernstein theorem. Introduction to counting: Basic counting techniques – inclusion and exclusion, pigeon-hole principle, permutation, combination, summations. Introduction to recurrence relation and generating function. Algebraic structures and morphisms: Algebraic structures with one binary operation – semigroups, monoids and groups, congruence relation and quotient structures. Free and cyclic monoids and groups, permutation groups, substructures, normal subgroups. Algebraic structures with two binary operations – rings, integral domains and fields. Boolean algebra and Boolean ring. Introduction to graphs: Graphs and their basic properties – degree, path, cycle, subgraphs, isomorphism, Eulerian and Hamiltonian walks, graph coloring, planar graphs, trees. References
1. Kenneth H. Rosen, Discrete Mathematics and its Applications, Tata McGraw-Hill.

2. C. L. Liu, Elements of Discrete Mathematics, Tata McGraw-Hill.

3. Norman L. Biggs, Discrete Mathematics, Oxford University Press.

4. Kenneth Bogart, Clifford Stein and Robert L. Drysdale, Discrete Mathematics for Computer Science, Key College Publishing.

5. Thomas Koshy, Discrete Mathematics with Applications, Elsevier.

6. Ralph P. Grimaldi, Discrete and Combinatorial Mathematics, Pearson Education, Asia.

CS21002 SWITCHING CIRCUITS AND LOGIC DESIGN (3-1-0 : 4 Credit) Switching Circuits: Logic families: TTL, nMOS, CMOS, dynamic CMOS and pass transistor logic (PTL) circuits, inverters and other logic gates, area, power and delay characteristics, concepts of fan-in, fan-out and noise margin. Switching theory: Boolean algebra, logic gates, and switching functions, truth tables and switching expressions, minimization of completely and incompletely specified switching functions, Karnaugh map and Quine-McCluskey method, multiple output minimization, representation and manipulation of functions using BDDs, two-level and multi-level logic circuit synthesis. Combinational logic circuits: Realization of Boolean functions using NAND/NOR gates, Decoders, multiplexers. logic design using ROMs, PLAs and FPGAs. Case studies. Sequential circuits: Clocks, flip-flops, latches, counters and shift registers, finite-state machine model, synthesis of synchronous sequential circuits, minimization and state assignment, asynchronous sequential circuit synthesis. ASM charts: Representation of sequential circuits using ASM charts, synthesis of output and next state functions, data path control path partition-based design. CS29002 Switching Laboratory (0-0-3 : 2 Credit) Pulse Circuits: Bistable, Astable and monostable MVs and Schmitt Triggers using transistors, OP Amps and 555 timers. TTL and CMOS Gates: Study the characteristics of TTL and CMOS gates. Combinational logic circuits: Design and implementation of combinational circuits such as, ALU, 7-segment LED display driver, etc. Sequential Circuits: Design of sequence genera-tors and detectors, counters, Design of ASMs such as, traffic light controllers, lift controllers, etc. References
1. H. Taub and D. Schilling, Digital Integrated Electronics, McGraw-Hill .

2. Z. Kohavi, Switching and Finite Automata Theory, Tata McGraw-Hill.

3. Randy H. Katz and Gaetano Borriello, Contemporary Logic Design, Prentice Hall of India.

4. Giovanni De Micheli, Synthesis and Optimization of Digital Circuits, Tata McGraw-Hill.

CS21003 ALGORITHMS I (3-1-0 : 4 Credit) Asymptotic notations and their significance, introduction to RAM model of computation, complexity analysis of algorithms, worst case and average case. Basic introduction to algorithmic paradigms like divide and conquer, recursion, greedy, etc. Searching: binary search trees, balanced binary search trees, AVL trees and Red-black trees, B-trees, skip lists, hashing. Priority queues, heaps, Interval trees, tries. Order statistics. Sorting: comparison based sorting -- quick sort, heap sort, merge sort: worst and average case analysis. Decision tree model and (worst case) lower bound on sorting. Sorting in linear time -- radix sort, bucket sort, counting sort, etc. String matching Graph Algorithms: BFS, DFS, connected components, topological sort, minimum spanning trees, shortest paths -- single source and all pairs. CS29003 Algorithms Laboratory (0-0-3 : 2 Credit) The laboratory component will emphasize two areas:
• Implementation of algorithms covered in class: This will involve running the algorithms under varying input sets and measuring running times, use of different data structures for the same algorithm (wherever applicable) to see its effect on time and space, comparison of different algorithms for the same problem etc.

• Design of Algorithms: This will involve design and implementation of algorithms for problems not covered in class but related to a topic covered in class.

The exact set of algorithms to design and implement is to be decided by the instructor. In addition, there will be at least one significantly large design project involving some real world application. An efficient design of the project should require the use of multiple data structures and a combination of different algorithms/ techniques. References
1. T. H. Cormen, C. L. Leiserson, R. L. Rivest, and C. Stein, Introduction to Algorithms, MIT Press.

2. J. Kleinberg and E. Tardos, Algorithm Design, Addison-Wesley.

3. Harry R. Lewis and Larry Denenberg, Data Structures and Their Algorithms, Harper Collins.

4. A. Gibbons, Algorithmic Graph Theory, Cambridge University Press.

5. Michael T. Goodrich and Roberto Tamassia, Algorithm Design: Foundations, Analysis, and Internet Examples, John Wiley.

6. R. Sedgewick, Algorithms in C (Parts 1-5), Addison Wesley.

7. M. H. Alsuwaiyel, Algorithm Design Techniques and Analysis, World Scientific.

8. Gilles Brassard and Paul Bratley, Algorithmics : theory and practice, Prentice-Hall.

9. Udi Manber, Introduction to Algorithms: A Creative Approach, Addison-Wesley.

10. Sara Baase and Allen Van Gelder, Computer Algorithms: Introduction to Design and Analysis, Addison-Wesley.

CS21004 FORMAL LANGUAGES AND AUTOMATA THEORY (3-1-0 : 4 Credit) Introduction: Alphabet, languages and grammars, productions and derivation, Chomsky hierarchy of languages. Regular languages and finite automata: Regular expressions and languages, deterministic finite automata (DFA) and equivalence with regular expressions, nondeterministic finite automata (NFA) and equivalence with DFA, regular grammars and equivalence with finite automata, properties of regular languages, pumping lemma for regular languages, minimization of finite automata. Context-free languages and pushdown automata: Context-free grammars (CFG) and languages (CFL), Chomsky and Greibach normal forms, nondeterministic pushdown automata (PDA) and equivalence with CFG, parse trees, ambiguity in CFG, pumping lemma for context-free languages, deterministic pushdown automata, closure properties of CFLs. Context-sensitive languages: Context-sensitive grammars (CSG) and languages, linear bounded automata and equivalence with CSG. Turing machines: The basic model for Turing machines (TM), Turing-recognizable (recursively enumerable) and Turing-decidable (recursive) languages and their closure properties, variants of Turing machines, nondeterministic TMs and equivalence with deterministic TMs, unrestricted grammars and equivalence with Turing machines, TMs as enumerators. Undecidability: Church-Turing thesis, universal Turing machine, the universal and diagonalization languages, reduction between languages and Rice's theorem, undecidable problems about languages. References
1. Harry R. Lewis and Christos H. Papadimitriou, Elements of the Theory of Computation, Pearson Education Asia.

2. John E. Hopcroft, Rajeev Motwani and Jeffrey D. Ullman, Introduction to Automata Theory, Languages, and Computation, Pearson Education Asia.

3. Dexter C. Kozen, Automata and Computability, Undergraduate Texts in Computer Science, Springer.

4. Michael Sipser, Introduction to the Theory of Computation, PWS Publishing.

5. John Martin, Introduction to Languages and The Theory of Computation, Tata McGraw Hill.


Contact address

Indian Institute of Technology Kharagpur
Kharagpur, West Bengal 721302


For complete syllabus here is the attachment;


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