**Syllabus of Computer Science & Engineering**

**Computer Programming **

Stored program concept (with simple computer simulator), machine language and instruction formats, assembly language for the simple computer. Characteristics of Computers, Evolution of Computing, Binary Number Systems, Types of Computer Software, Operating Systems, Programming Languages, Problem Solving Techniques using Computers: Algorithm, Flow Charts, Pseudocode. Introduction to Computer Networks, Internet, World Wide Web, Getting Connected to Internet. Problem Solving, Concept of Algorithms, Introduction to Computer Programming, Editing and Compiling a Program.

**Text/ Reference Books: **

- V. Rajaraman, N. Adabala, Fundamentals of Computers, PHI, 2014
- P. Pannu, Y. A. Tomer, ICT4D Information Communication Technology for Development, I K International Publishing House Pvt. Ltd, 2010.
- S.K.Basandra, Computer Today, Galgotia Publications, 2009.

**Data Structures**

Introduction to Data Structures, algorithms, pseudo-code, time and space complexities; arrays and their applications, sparse matrix, stacks and their applications such as recursion, queues including priority queues and their applications, linked lists and their applications, Introduction to trees, forest, static tree structures: binary tree, threaded binary tree, their traversal techniques, Binary Search Trees, including their applications, dynamic tree structures: AVL trees, B-trees, B+ trees, B* tree, including their applications, Introduction to Graphs, DFS, BFS. Sorting and searching algorithms, hashing.

**Text/ Reference Books: **

- H Ellis, S. Sahni, Fundamentals of Data Structures, W H Freeman and Co. 1995.
- J. P. Tremblay, P. G. Sorenson, Introduction to Data Structures: With Applications, McGraw Hill Higher Education, 1983.
- Kruse Robert L., “Data Structures and Program Design”, Prentice Hall, 2007
- R. Gilberg, B. A. Forouzan, Data Structures: A Pseudocode Approach with C, Course Technology Inc, 2004.

**Discrete Mathematical Structures**

Propositions and Logical Operations: Notation, Connections, Normal forms, Truth Tables, Equivalence and Implications, Theory of interference for statement calculus, Predicate calculus, Rules of Logic, Mathematical Induction and Quantifiers. Sets, Relations and Diagraphs: Review of set concepts, Relations and digraphs, Properties of relations, Equivalence relations, Computer representation of relations and digraphs, Manipulation of relations, Partially Ordered Sets (Posets), Recurrence RelationsGroups and Applications: Monoids, Semi groups, Product and quotients of algebraic structures, Isomorphism, homomorphism, automorphismElementary Graph Theory: Euler, Hamiltonian graph, Tree, Planner graph, Graph representationClassification of Languages: Overview of Formal Languages-Representation of regular languages and grammars, finite state machines.

**Text/ Reference Books: **

- J. P. Tremblay, R. Manohar, Discrete Mathematical Structures with Applications to Computer Science, McGraw Hill Education, 2001.
- C. L. Liu, Elements of Discrete Mathematics, McGraw-Hill Education,1986.
- K H. Rosen, Discrete Mathematics and Its Applications, McGraw Hill Education, 1999.
- N. Dev, Graph Theory with Applications to Engineering and Computer Science, Prentice Hall India Learning Private Limited, 1979.

**Digital Logic and Systems Design**

Introduction to Number Systems and Codes. Switching properties of Diodes, BJT and FET, Logic gates, DTL, TTL, ECL, I2L, CMOS Gates and their parameters and comparisons, Applications of switching transistors in bistable, monostable, astable and Schmitt trigger circuits.

Boolean algebra, Switching Function, minimization of switching function: Karnaugh map method and Tabulation Method don’t care terms and applications w.r.to code converters and Digital Comparators, etc.

Gated Flip Flops, Master Slave Flip Flop, Ripple and Parallel Counter, Up-Down Counter, Shift Registers and Ring Counter, designing the combinational circuits of the counters through Excitation Table.

Introduction to the circuits for Arithmetic Unit: Serial and parallel Binary Adders, 2’s compliment and principle of subtraction, Carry-Look Ahead Adder, and BCD adder: Principles of multiplication, division in ALU

Semiconductor memories: ROM, PROM, EPROM, EEPROM, Bipolar RAM, static and dynamic RAM. Encoder and Decoder/Demultiplexer, multiplexer, Designing combinational circuits with multiplexer, ROM and PLA.Introduction to advanced memory concepts.

Analog-to-Digital conversion:, dual slope integration method and voltage to frequency conversion, principal of DVM. , counter type, successive approximation type, Flash ADC ,

D-A converter: weighted resistors type, R-2-R ladder type.

**Text/ Reference Books:**

- H.Taub & D. Schilling, Digital Integrated Electronics, TMH.
- Malvino& Leach, Digital Principles and Application,TMH.
- M. Mano, Digital Electronics And Logic Design, PHI.
- B.S.Sonde Introduction To System Design Using Integrated Circuits, New Age International.
- Z. Kohavi Switching And Finite Automata Theory, TMH.
- R. P. Jain, Modern Digital Electronics, TMH.
- Gothman, Digital Electronics, PHI.

**Programming Languages**

Notions of syntax and semantics of programming languages; introduction to operational/natural semantics of functional and imperative languages. Data abstractions and control constructs; block-structure and scope, principles of abstraction, qualification and correspondence; parameter passing mechanisms; runtime structure and operating environment; practical and implementation issues in run-time systems and environment; abstracts machines; features of functional and imperative languages; the untyped and simply-typed Lambda calculus' type systems for programming languages including simple types and polymorphism; objects, classes and inheritance in object-oriented languages.

**Text/ Reference Books: **

*Michael Scott, Programming Language Pragmatics, Morgan Kaufmann, 2000.**Wand andHaynes, Essentials of Programming Languages. Friedman, Prentice-Hall International (PHI), 1998.**Tennant, Principles of Programming Languages, PHI, 1981.*

**Computer Architecture **

Data Representation, Data Types, Binary Codes and Error Detection Codes, Register Transfer language, Arithmetic, logic and Shift Microoperations. Computer Registers, Instruction Codes, Timing and Control. Computer Arithmetic- Number Representation, Addition, Subtraction, Multiplication and Division Algorithms. General Register Organization, Stack Organization, Instruction Formats, Addressing Modes, RISC Computer, CISC Computer. Pipelining, Arithmetic Pipeline, Instruction Pipeline, Vector Processing. Peripheral Devices, Input-Output Interface, Asynchronous Data Transfer, Modes of Transfer, Priority Interrupt, DMA, Serial Communication. Memory Hierarchy, Main Memory, Auxillary Memory, Associative Memory, Cache Memory, Virtual Memory. Microprogrammed Control- Control Memory, Address Sequencing, Design of Control Unit.

**Text/ Reference Books:**

- M. Mano, Computer System Architecture. Pearson Education, 2012
- D. A. Patterson, J. L. Hennessy, Computer Organization and Design: The Hardware/Software Interface, Morgan Kaufmann, 2009
- W. Stallings, Computer Organization and Architecture: Designing for Performance, Pearson Education, 2007
- B. Parhami, Computer Architectures: From Microprocessors to Supercomputers, Oxford, 2005.

**Design and Analysis of Algorithms **

Growth of Functions, Summations, Recurrences, Design Techniques: Divide and conquer, Dynamic programming, Greedy algorithms, Backtracking, Branch and Bound, Graph Algorithms: shortest path problems, Network Flow Problems, Minimum spanning trees; P and NP class problems, NP-completeness and reducibility, Polynomials and the Fast Fourier transform (DFT and FFT), Number-theoretic Algorithms, String matching, Algorithms for Parallel computers, Approximation algorithms.

**Text/ Reference Books: **

- T Cormen, C Leisersson, R Rivest, C Stein, Introduction to Algorithms, PHI, 2003.
- V. Aho, J. Hopcraft, J. Ulmann, The Design and Analysis of Computer Algorithms, Addison Wesley, 1974.
- E Horowitz, S Sahni, S Rajasekaran, Fundamentals of Computer Algorithms, Universities Press, 2008.
- S. Basse, A. V. Gelder, Computer Algorithms: Introduction to Design and Analysis, Pearson Education Asia Pvt. Ltd., 2009.

**Database Management Systems **

Database Approach - System Concepts and Architecture, Database Users; Database Design - Entity-Relationship (E-R) Model, Relational Model, Mapping E-R to Relational Model; Languages - Relational Algebra, Tuple and Domain Relational Calculus , SQL; Normalization - Functional and Multivalued Dependency, 1NF to 5NF; Security; Transaction Management - Transaction, ACID properties, Concurrency, Recovery ; Query Optimization - Cost based and Heuristics based. Practical: Design E-R model for a real world, map to relational model, implement using available RDBMS and execute SQL queries.

**Text/ Reference Books: **

- R. Elmasri, S. Navathe, Fundamentals of Database Systems, Pearson, Sixth Edition, 2006.
- Silberschatz H, Korth, S. Sudarshan, Database System Concepts , McGraw-Hill,

Sixth Edition, 2010. - C. Desai, An Introdcution to Database System, Galgotia Publications Pvt Ltd, 2012.
- H G Molina, J. D. Ullman, J Widom, Database Systems: The Complete Book, Pearson, 2008.

**Operating Systems **

Introduction to Operating Systems; layered architecture, basic concepts: interrupt architecture, system calls,, Processes and Threads, CPU scheduling; Deadlocks; Main memory management including paging and segmentation schemes; Virtual memory management including page replacement algorithms; Storage management including file systems; Case studies.

**Text/ Reference Books: **

- Silberschatz, P. Galvin and G. Gagne, Operating System Concepts, Wiley, 2008.
- W. Stallings, Operating Systems: Internals and Design Principles, Pearson, 2014.
- S. Das, UNIX Concepts and Applications, McGraw Hill Education, 2006.

**Machine Learning **

An overview of Machine learning, Inductive learning: ID3, C4.5,C5; Learning Concepts and rules from Examples; Learning by analogy; Learning from observation and discovery; Learning by experimentation; Learning by training Neural Networks; Genetic Algorithm; Analysis learning; Reinforcement learning ;Applications to KDD.

**Text/ Reference Books: **

- T.M. Mitchell, Machine Learning McGraw-Hill, 1997.
- S. Marsland, Machine learning: an algorithmic perspective, CRC Press, Taylor and Francis Group, 2015.
- E Alpaydin, Introduction to Machine Learning, MIT Press, 2010.
- C M. Bishop, Pattern Recognition and Machine Learning (Information Science and Statistics), Springer, 2010.

**Theory of Computation **

Regular language Models: Finite state machines (deterministic, non-deterministic), regular languages and regular grammars, properties; Context-free language models: Context-free languages, properties of CFL, Pushdown automata; Turing Machines, limits of algorithmic computation; Grammars, hierarchy of formal languages, properties of models of computation, Computational complexity, complexity class P and NP.

**Text/ Reference Books: **

- L, Peter, An introduction to Formal Languages and Automata, Narosa Publishing House, 2007
- H. R. Lewis, C. H. Papadimitriou, Elements of Theory of Computation, Pearson Education, 2002
- J. E. Hofcroft, J. D. Ullman, Introduction to Automata Theory, Languages and Computation, Narosa Publishing house, 2008.
- J. C. Martin, Introduction to Languages and Theory of Computation, Tata McGraw-Hill Publication, 2007

**Computer Networks **

Overview of Computer Network, OSI and TCP/IP Reference Models, Guided and Unguided Transmission Media, Analog and Digital communication, Encoding and Modulation, Nyquist theorem, Shannon’s capacity, Switching techniques, multiplexing techniques-TDM, FDM, Framing, Error detection and Error correction – VRC, LRC, CRC, Stop and Wait Protocol, Sliding Window Protocol, Go-back-n ARQ, Selective-Reject ARQ, HDLC, Channel Allocation, ALOHA Systems, CSMA Protocols, Collision Free Protocols, Local Area Networks, Bridges, ATM, Routing: Flooding, Spanning tree, Distance Vector routing, Link state routing, Bellman-Ford and Dijkstra routing algorithms, Congestion control - Leaky Bucket and Token Bucket algorithms , IP Protocol, IP Addressing, ARP, RARP, OSFP, BGP, TCP, UDP, Application Protocols-DHCP, DNS, Telnet, SMPT, Network Security-RSA

**Text/ Reference Books: **

- A. S. Tanenbaum, Computer Networks, Pearson Education India, 2013.
- B. A. Ferouzan, Data Communications and Networking, McGraw Hill Education, 2006.
- A. L. Garcia, I. Widjaja, Communication Networks, McGraw-Hill Education, 2003.
- W. Stallings, Data and computer Communications, Pearson Education India, 2013.

**Compiler Design **

Lexical Analysis (Scanner): Regular language, finite automata, regular expression, regular expression to finite automata, scanner generator (lex/flex). Syntax Analysis (Parser): Context-free grammar, push-down automata, ambiguity, associativity, precedence, transformations on the grammars; top down parsing, recursive descent predictive parsing, LL(1) parsing; bottom up parsing, LR parsers (SLR, LALR, LR), LALR(1) parser generator (yacc/bison). Semantic Analysis: Attribute grammar, syntax directed definitions, inherited and synthesized attributes, dependency graph, evaluation order, S- and L-attributed definitions, type-checking. Run time system: storage organization, activation tree, activation record, stack allocation of activation records, parameter passing mechanisms, Symbol table. Intermediate Code Generation: intermediate representations, translation of declarations, assignments, control flow, Boolean expressions and procedure calls. Code Improvement: Analysis: control-flow, data-flow analysis, local optimization, global optimization, loop optimization, peep-hole optimization, instruction scheduling. Register allocation and target code generation.

**Text/ Reference Books: **

- A. V. Aho, M S. Lam, J. D. Ullman, R. Sethi, Compilers: Principles, Techniques, and Tools, Pearson, 2011.
- K. C. Louden, Compiler Construction: Principles and Practices, PWS Publishing, 1997.
- A W. Appel: Modern Compiler Implementation in C / Java, Cambridge Univ. Press, 2004.
- S. Muchnick, Advanced Compiler Design and Implementation, Morgan Kaufmann, 1997.

**Numerical Methods \**

Computing Arithmetic, Significant Digits and Numerical Instability, Root finding methods. Bisection, Newton Raphson, Secant and Regula Falsi, methods for multiple roots. System of Linear Algebraic Equations and Eigenvalue problems-Gauss Elimination, LU Decomposition. Jacobi-Gauss-Seidel and SOR methods, Interpolation and Approximation-spline approximation. Linear, quadratic and Cubic, Differentiation and Integration-Richardson’s extrapolation, Gauss Quadrature methods, ordinary differential equations-Initial and Boundary Value Problems, introduction to numerical solutions of Partial Differential Equations.

**Text/ Reference Books: **

- M.K. Jain, SRK Iyengar, R.K.Jain, Numerical Methods for Scientific and Engineering Computation, New Age International Publishers, 2003.
- S.C. Chopra and R. P. Canale, Numerical Methods for Engineers, McGraw-Hill Higher Education, 2005.
- S.D. Conte h C. de Boor, Elementary Numerical Analysis: An Algorithmic Approach, McGraw-Hill Book Company, 1980.
- E.W. Cheney and D. R. Kincaid, Numerical Analysis, Brooks Cole, 1996.

**Artificial Intelligence **

Overview of AI: Foundations, history and sate of art; Problem Solving: Search, Game playing; Knowledge Representation and Reasoning: First Order Logic, building knowledge-bases, Logic based Reasoning Systems, Semantic Networks, Frames; Uncertainty and Reasoning: Bayesian networks, Demster-Shafer theory, Fuzzy Sets; Planning; Machine Learning: learning from observations, Artificial Neural Networks, Reinforcement learning; Intelligent Agents; Natural Language Processing; Robotics

**Text/ Reference Books: **

- Knight, Kevin, Rich, Elaine, Nair, B., artificial Intelligence, Tata McGraw-Hills, 2008
- Russell, Stuart, Artificial Intelligence: A Modern Approach, Pearson Edition 2013
- Winston, P.H. Artificial Intelligence, Pearson, 2002

**Cloud Computing **

Overview of Distributed Computing: Trends of computing, Introduction to Parallel/distributed computing, Grid Computing, Cloud computing, Introduction to Cloud Computing: What’s cloud computing, Properties and Characteristics, Service models, Deployment models. Components of a computing cloud, Different types of clouds: public, private, hybrid, Delivering services from the cloud, Categorizing service types, Comparing vendor cloud products: Amazon, Google, Microsoft and others, Infrastructure as a Service (IaaS): Introduction to IaaS, Resource Virtualization, Server, Storage, Network, Case studies, Platform as a Service (PaaS): Introduction to PaaS, Cloud platforms and Management, Computation, Storage, Case studies, Software as a Service (SaaS): Introduction to SaaS, Web services, Web 2.0, Web OS, Case studies, Cloud Issues and Challenges: Cloud provider Lock-in, Security.

**Text/ Reference Books: **

- K Hwang, G Fox, J Dongarra, Distributed and Cloud Computing, Elsevier, 2012.
- R Buyya, C Vecchiola, T Selvi, Mastering Cloud Computing, TMH, 2013.
- D C. Marinescu, Cloud Computing: Theory and Practice, Elsevier, 2013.
- B Sosinsky, Cloud Computing Bible, Wiley, 2011.

**Computer Graphics **

Input devices, Video display devices, Area filling algorithms with irregular boundaries, Cohen-Sutherland and Cyrus-Beck line clipping algorithms, Basic 2-dimensional and 3-dimensional geometric transformations, Homogeneous coordinate system, Parallel projection, Isometric projection and its construction, Perspective projection, Hidden surface elimination algorithms, Basic illumination models, Gouraud and Phong surface rendering models, Representation of curves and surfaces.

**Text/ Reference Books: **

- J.D. Foley, A. V Dam, J.F. Hughes and S.K. Feiner, Computer Graphics: Principles and Practice, Addison Wesley, 2013
- D. Hearn and P. M. Baker, Computer Graphics, Prentice Hall of India, 1996
- D. F. Rogers, Procedural Elements for Computer Graphics, McGraw-Hill Inc. 1997
- D. F. Rogers, J. A. Adams, Mathematical elements for computer graphics, McGraw-Hill, Inc. New York, NY, 1990

**Digital Image Processing **

Digital Image fundamentals; Image sensing and acquisition; Image sampling and Quantization; Image Enhancement in Spatial Domain; Grey level transformation; Histogram Processing; Image Transforms; Spatial filters; Fourier Transforms and their properties; Fast Fourier Transforms; Image Enhancement in Frequency Domain; Image Segmentation: edge detection, Hough Transform, Region based segmentation; Image Compression.

**Text/ Reference Books: **

- R. E. Woods, R C. Gonzalez, Digital Image Processing, Pearson, 2007.
- A K. Jain, Fundamentals of Digital Image Processing, PHI, 1989.

**Modeling& Simulation **

Advantages and disadvantages of simulation systems, Components of system, Discrete and continuous systems, Examples – Simulation of queuing and network protocols, concepts in discrete-event simulation; Statistical models in simulation; Analysis of simulation data, Verification and validation of simulation models, Output analysis for single model, Simulation of computer systems, Queuing models – long run measures of performance, steady-state behavior, M/M/1, M/M/C/∞/∞, M/M/C/N/∞, M/M/C/K/K; Pseudo random numbers, random variate generation, Inverse transform technique. Deterministic v/s probabilistic systems, Elements of Stochastic process, Markov chains, Markov process, Poisson process, Brownian motion process. Principles of Monte Carlo, Geomatric Brownian motion and generation of sample paths, Black-Scholes model

**Text/ Reference Books: **

- R Jain, Art of Computer Systems Performance Analysis, John Wiley and Sons, Inc, 1991.
- A M. Law and W. D. Kelton, Simulation Modeling and Analysis, 3
^{rd}Ed. Tata McGraw-Hill, 2003 - W.J.Stewart, Probability, Markov Chains, Queues and Simulation, Princeton University, 2009.
- P. Glasserman, Monte Carlo Methods in Financial Engineering, Springer, 2004

**Object Oriented Programming **

Concept of Object-Oriented Programming paradigm: Abstraction, Encapsulation, Inheritance, Polymorphism, Classes, Objects, member function, static member function, Data types, Arrays, Memory Allocation for Objects, Storage Management, constructors, destructor, Inheritance: single and multiple inheritances, operator overloading, function overloading, Polymorphism, abstract class, overriding, memory layout of objects; Exception Handling, Template class and function, Packages and Interfaces, Multithreaded programming, Input/Output

**Text/ Reference Books: **

- B. Stroustrup, The C++ Programming Language, Addison Wesley, 2013.Lipman, S. B. C++ Primer, 3
^{rd}ed. Pearson Education. - H.M. Deitel, P.J.Deitel, Java : how to program, Fifth edition, Prentice Hall Publication.
- H. Schildt, The Java 2: Complete Reference, Fourth edition, TMH.

**Parallel and Distributed Systems **

Introduction to Parallel and Distributed Systems, Classification, Various Speedup Laws, Interconnection Network Architecture, Algorithms On Parallel/Distributed Machine, PRAM Model, EREW, ERCW, CREW, CRCW Algorithms, Sorting Networks 0-1 Principle, Bitonic Sorter, Merger, Sorter, Distributed Systems, Interprocess Communication, Message Passing Communication, Distributed Coordination, Physical And Logical Clocks.

**Text/ Reference Books: **

- K Hwang, Advanced Computer Architecture, TMH, 2011
- M.J. Quinn, Parallel Computing, Mc-Graw Hill, 1994
- T. H. Cormen, Algorithms, PHI, 2009
- A. S. Tanenbaum, Distributed System, Pearson Education, 2002

**Software Engineering **

Introduction, Software Product and Process, Software Process Models, Requirements Engineering, Requirements Analysis–Data Flow Diagram, Requirement Specification, Requirement Validation; Design- Concepts, Coupling, Cohesion, Mapping Requirements to Design, User Interface Design, Structure Charts, Coding Principles, Coding Standards and Guidelines, Software Testing Techniques and Strategies, Software Debugging, Software Project Metrics and Estimation Techniques – Empirical, Heuristic and Analytical Techniques, Software Quality Assurance, CASE Tools.

**Text/ Reference Books: **

- R. Pressman, Software Engineering – A Practitioner’s approach, Sixth Edition, McGraw-Hill International Edition, 2014.
- I. Sommerville, Software Engineering, Sixth Edition, Pearson Education, 2010.
- R. Mall, Fundamentals of Software Engineering, Prentice Hall India, 2014.
- P. Jalote, An Integrated Approach to Software Engineering, Second Edition, Narosa Publishing House, 2005.

**Courses for MTech in Computer Science & Engineering:**

**Advanced Algorithms **

Probabilistic Recurrence, Basic Power and Efficiency of Randomization and Approximation, Computation Model and Complexity Classes, Reducibility, Classification of randomized algorithms: Las Vegas and Monte Carlo, Minimum cut algorithm, Bin-Balls Problem, Birthday-Paradox, Coupon-Collector, Stable Marriage Problem, Game Theory, Random variables and Basic inequalities (Markov, Chebyshev), Chernoff Bounds, Martingale Bound, Max-cut, Random Graphs, Markov chains and random walks, Random graph models for real-world networks, social networks, etc. Algorithms for 2-SAT and 3-SAT, Particle Swarm optimization (PSO), Multi-swarm optimization, Ant Colony optimization, Intelligent Water Drops algorithm, Genetic algorithm, Hill-Climbing optimization algorithm

**Text/ Reference Books: **

- V Vazirani, Approximation Algorithms, Springer-Verlag, 2001
- D. Williamson, D. Shmoys, The Design of Approximation Algorithms, Cambridge University Press, 2011.
- T Cormen, C Leisersson, R Rivest, C Stein, Introduction to Algorithms, PHI, 2003.
- R. Motwani, P Raghavan, Randomized Algorithms, Cambridge University Press, 1995

**Optimization Techniques **

Mathematical preliminary, Linear programming, Simplex method, Duality in linear programming, Convex optimization and quadratic programming, Least squares optimization, Unconstrained optimization problems, Nonlinear constrained optimization, Problems with equality constraints, Problems with inequality constraints, Application of mathematical programming in machine learning.

**Text/ Reference Books: **

- S. Chandra, Jayadeva, A. Mehra, Numerical Optimization with Applications, Alpha Science International Ltd, 2008.
- I Griva, S. G. Nash, A Sofer, Linear and Nonlinear Optimization, Society for Industrial Mathematics, 2008.
- W Forst, D Hoffmann, Optimization—Theory and Practice, Springer-Verlag New York, 2010.

**Advanced Software Engineering **

Overview of Software Engineering, Methods of Analysis and Design of Software Systems: Structured and Object Oriented, Coding Standards and Guidelines, Theoretical Foundation of Testing: Coverage Criterions, Software Testing Techniques and Strategies, Software Debugging; Software Project Metrics and Estimation Techniques: Empirical, Heuristic and Analytical Techniques; Software Project Planning and Scheduling: PERT and CPM; Software Project Crashing; Software Reliability Metrics and Models, Software Availability, Software Risk and Configuration Management; Software Reuse and Re-engineering; CASE Tools and Support; Software Quality Assurance.

**Text/ Reference Books: **

- Pressman, R., Software Engineering – A Practitioner’s approach, Sixth Edition, McGrawHill International Edition.
- Ghezzi, C., Jazayeri, M., Mandrioli, D., Fundamentals of Software Engineering, Second Edition, Pearson Education.
- Peters, J.F., Pedreyz, W., Software Engineering - An Engineering Approach, John Wiley and Sons. Sommerville, I., Software Engineering, Sixth Edition, Pearson Education.
- Taha, H.A., Operations Research – An Introduction, Seventh Edition, Pearson Education.

**Big Data Analytics **

Introduction to Data Mining, Data Analytics, Predictive Analysis and Business Intelligence, Large Scale File System, Mining Big Data, Advanced Data Analytics and Machine Learning, Big Data Streams and Real Time Predictive Analysis, Tools and Visualization, Link Analysis, Web Analytics, Collaborative Filtering, Social Network Analysis, Issues, Challenges and Opportunities with Big Data and its Analytics

**Text/ Reference Books: **

- Rajaraman, A., Ullman, J. D., Mining of Massive Datasets, Cambridge University Press, United Kingdom, 2012
- Barlow, M., Real-Time Big Data Analytics: Emerging Architecture, O Reilly, 2013
- Baesens, B., Analytics in a Big Data World, Wiley, 2016
- Bell, J., Machine Learning for Big Data, Wiley, 2016

**Computer Vision **

Introduction to vision; Camera models; Camera calibration; Multi-view geometry and reconstruction; Edge/ Feature extraction; Correspondence and tracking; 3D structure/ motion estimation; basics of object recognition.

**Text/ Reference Books: **

- R Szeliski, Computer Vision: Algorithms and Applications, Springer, 2011.
- R Hartley, A Zissermann, Multi-view Geometry in Computer Vision, Cambridge University Press, 2004.
- D A. Forsyth, J Ponce, Computer Vision: A Modern

**Data Communication and Computer Networks**

Data Communication – Analog and digital communications, Channel characteristics, modulation, encoding schemes; Error Detection and correction, Flow control, multiplexing switching, Multiple access techniques, Routing – shortest path algorithms, routing protocols, virtual path routing, Network Protocols – IP, TCP, UDP, FTP, SMTP, etc, Performance Evaluation – Queuing models, Traffic model – deterministic and stochastic

**Text/ Reference Books: **

- Leon Garcia and Indra Widjaja, Communication Networks: Fundamental Concepts and Key Architecture, 2 nd ed., Tata McGraw-Hill, 2004
- Anurag Kumar, D. Manjunath and Joy Kuri, Communication Networking: An analytical approach, Elsevier, 2004.
- Dimitri Bertsekas and Robert Gallager, Data Networks, 2 nd ed., PHI, 2001.
- Thomas G. Roberttazzi, Computer Networks and Systems, 3 rd ed. Springer, 2002.

**Data Mining and Knowledge Discovery**

Concepts of data mining and knowledge discovery: Input – concepts, instances, attributes; Knowledge representation of outputs; Data mining methodologies – classification, prediction, regression, association, clustering, outlier analysis, Advanced data mining models – Machine learning: incremental learning, reinforcement learning, genetic algorithms, neural networks, intelligent agents based learning; Soft Computing: Concepts and ML models using Fuzzy set theory and Rough set theory. Applications of data mining in complex data: world-wide web, Streams, Scientific, spatial Current topics

**Text/ Reference Books: **

- Han, J. and Kamber, M., Data Mining: Concepts and Techniques, Morgan Kaufmann, 2e, 2007. 2. Witten, Ian H. and Frank Eibe, Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations. Morgan Kaufmann, 2e,2005
- Tan, P., Kumar, V. and Steinbach, M., Introduction to Data Mining, Pearson Education Inc. 2007
- Hand, David, Mannila Heikki and Smyth Padheaic, Principles of Data Mining, PrenticeHall India, 2004 (Indian reprint)
- Thuraisingham, B., Data Mining: Technologies, Techniques, Tools, and Trends, CRC Press, 1999.

**Large Scale Graph Algorithms and Application**

Introduction and Application of Large-scale Graph, Characteristics, Complex Data Sources - Social Networks, Simulations, Bioinformatics; Categories- Social, Endorsement, Location, Co-occurrence graphs; Basic and Advanced Large-scale Graph Analysis- List Ranking, Link Analysis, Page Ranking Algorithms; Distributed Computation for Massive Data Sets- Spectral, Modularity-based Clustering, Random Walks; Large Graph Representation and ImplementationV-Graph Representation, MapReduce, Surfer, GraphLab; Advanced Topics- Power Law Distribution, Game-Theoretic Approach, Rank Aggregation and Voting Theory, Recommendation Systems, Social network analysis: case study ‐Facebook, LinkedIn, Google+, and Twitter

**Text/ Reference Books: **

- Social and Economic Networks by Matthew O. Jackson (Nov 21, 2010)
- Stanley Wasserman, Katherine Faust "Social Network Analysis Methods and Applications" (Structural Analysis in the Social Sciences) 1995
- Tanja Falkowski "Community Analysis in Dynamic Social Networks" 2009
- Ladislav Novak, Alan Gibbons, "Hybrid Graph Theory and Network Analysis" Cambridge Tracts in Theoretical Computer Science 2009
- Eric D. Kolaczyk, "Statistical Analysis of Network Data Methods and Models" Springer Series in Statistics 2009
- Akihito Hora, Nobuaki Obata Quantum Probability and Spectral Analysis of Graphs" 2007

**Mobile Ad Hoc Networks**

Fundamentals of Wireless Communication Technology – Radio Propagation Mechanisms, Multiple Access Techniques, Characteristics of wireless Channel. Ad Hoc Networks – Definition, Application, challenges, Traffic profile, and challenges, Media Access protocols Topology-based routing; Position-based routing, Mobility and location Management, Transport Protocols, Energy Conservation Issues QoS, Security issue, Simulation of protocols.

**Text/ Reference Books: **

- C. Siva Ram Murthy and B.S. Manoj, Ad Hoc Wireless Networks – Architecture and Protocols, Pearson Education, 2004 (Low price edition)
- C.K. Toh, Ad hoc Mobile Wireless Networks – Protocols and Systems, Prentice Hall, 2002
- Ivan Stojmenovic (ed), Handbook of Wireless Networks and Mobile Computing, John Wiley, 2002

**Multicast Communication **

Introduction, Application, Characteristics, Multicast Backbone Architecture, Multicast Routing, Basic Routing Algorithm, Group Dynamics, Multicast routing between domains, Ip multicast, Multicast in transport protocols, address allocation, Multicast LANs, Reliable Multicast, Congestion control, Security issues.

**Text/ Reference Books: **

- Morgan Kaufmann, Ralph Wittmann, Martina Zitterbart ,Multicast Communication: Protocols, Programming and Applications, Edition 2000, Academic Press, USA.
- Kennet Miller, Multicast Networking and Application, AW publication, 2008.
- David Makofske, Kevin Almeroth, Multicast sockets: Practical Guide for Programmers, Edition 2003, Elsevier, USA.

**Natural Language Processing **

General Characteristics of Natural language – ambiguity, incompleteness, imprecision; Linguistic Essentials – Part of speech, Lexicography, morphology, Phrase structure grammar, theory, Semantics and pragmatics; Grammatical frameworks – Chomsky hierarchy, X-bar theory, LFG, Unification grammar; Efficient parsing for Natural languages; Knowledge Representations – Frames, Scripts, Conceptual graphs; Statistical Techniques – Elementary Probability theory, Essential information theory; Applications of Statistical Techniques - Word Sense Disambiguation, Lexical Acquisition, Markov Model for Part-of-speech tagging , Probabilistic CFG, Probabilistic parsing, Statistical Alignment and machine translation, Clustering.

**Text/ Reference Books: **

- Manning D. Statistical Foundation of Natural language Processing, MIT Press, 1999.
- James A. Introduction to Natural Language Understanding, Addison Wesley, 1991.
- Harris M.D. Natural Language Processing, Benjamin/Cumming, 1991

**Network Security **

Introduction, Security goals, attacks, services and mechanisms, cryptography and steganography, Symmetric Key cipher-substitution ciphers, Transposition ciphers, stream and block ciphers, Modern block ciphers, Modern stream ciphers, DES and AES, Elliptic curve cryptosystems, RSA, Message integrity, Digital signature, Public key distribution, IPSec, SET, ESP, PGP, SSL, Security in wireless.

**Text/ Reference Books: **

- Stallings, Cryptography and Network Security: Theory and practice, JohnWiley, 2013.
- Behrouz A. Forouzan, Cryptography and Network security, Tata Mcgraw Hill 2010.
- Bible Eric Cole, Ronald L.Krutz, Network security, Welley 2009.
- Stinson D., Cryptography, Theory and Practice, CRC Press, Boca Raton, FA 2005.

**Object Oriented Software Engineering **

Object Oriented Concepts; Modeling with UML; Analysis - Object Model, Dynamic Model; System Design - Addressing Design Goals; Object Design; Reusability - Introduction to Design Patterns; Mapping Models to Code; Testing Techniques - Unit, Integration and System Testing

**Text/ Reference Books: **

- Bruegge B. and Dutoit A.H., Object-Oriented Software Engineering, Using UML, Patterns, and Java, 3rd Edition, Prentice-Hall, 2010
- Booch G., Rumbaugh J and Jacobson I., The Unified Modeling User Guide, Addison Wesley Longmen, 2nd Edition, 2005
- Gamma, et al., Design Patterns, Elements of Reusable Object Oriented Software", Addison Wesley, Ist Edition,1994
- Craig Larman, Applying UML and Patterns - An Introduction to Object-Oriented Analysis and Design and Iterative Development, Prentice Hall, 3rd Edition, 2008.

**Performance Modeling of Computer Communication Networks **

Role of Modeling and Analysis, Examples of Performance Modeling, Analytic Models, Elements of Stochastic process, Poisson Process, Basic Queuing models, M/M/1; M/M/∞; M/G/ ∞; M/M/m; M/M/m/m Queues with Product formula. Cell and Burst scale Traffic Models: Round trip time distribution, PING data, Markov modulated Poisson Process, Long Range Dependence, Heavy Tail Distribution. Traffic Control: Admission Control, Effective Bandwidth, Statistical Multiplexing gain, Access Control: Leaky bucket System. Multi access Modelling: Slotted ALOHA Markov chain, Diffusion Approximation Approach, CSMA, Congestion Control, Window Control, Modelling TCP, Window Size, TCP Window Dynamics.

**Text/ Reference Books: **

- M. N. O. Sadiku, S. M. Musa, Performance Analysis of Computer Networks, Springer, 2013.
- I. Kaj, Stochastic Modeling in Broadband Communications Systems, SIAM, 2002 .
- H. Kobayashi, B. L. Mark, System Modeling and Analysis, Foundations of System Performance Evaluation, Pearson Prentice Hall, 2009.
- M.H. Balter, Performance Modeling and Design of Computer Systems, Cambridge Univ. Press , 2013.

**Swarm Intelligence **

Introduction to Models and Concept of Computational Intelligence, Social Behavior as Optimization: Discrete and Continuous Optimization Problems, Classification of Optimization Algorithms, Evolutionary Computation Theory and Paradigm, Swarm and Collective intelligence, Swarm Intelligence Techniques: Particle Swarm Optimization, Ant Colony Optimization, Artificial Bees and Firefly Algorithm etc., Hybridization and Comparisons of Swarm Techniques, Application of Swarm Techniques in Different Domains and Real World Problems.

**Text/ Reference Books: **

- Engelbrecht, A.P. Computational Intelligence: An Introduction, Second Edition, John Wiley and Sons, 2007.
- Kennedy, J. and Eberhart, R.C., Swarm Intelligence, Morgan Kaufmann Publishers, 2001
- Bonabeau, E., Dorigo, M. and Theraulaz, G., Swarm Intelligence: From Natural to Artifical Systems, Oxford University Press, 1999
- Dorigo, M., Stutzle, T., Ant Colony Optimization, MIT Press, 2004
- Parsopoulos, K.E., Vrahatis, M.N., Particle Swarm Optimization and Intelligence: Advances and Applications, Information Science Reference, IGI Global, 2010
- Clerc, M., Particle Swarm Optimization, ISTE, 2006 7. Nature Inspired Metaheuristic Algorithms, Xin-She Yang, Luniver Press, 2010

**Service Oriented Architecture **

SOA Fundamentals - definition, characteristics; Architecture; Evolution; Web Service; Web Service Composition - Orchestration and Choreography; Interoperability; WS*, Metadata; Security; XML Technology - name-spaces, schema, well-formed XML documents; WSDL - name spaces, Abstract and Concrete Models; Universal Description, Discovery and Integration (UDDI), SOAP (messaging framework); Composition Languages - BPEL and CDL 19 | 23

**Text/ Reference Books: **

- Thomas Erl, Service Oriented Architecture (SOA) : Concepts, Technology and Design, Prentice Hall, 2008 2. Newcomer E. and Lomow G, Understanding SOA with Web Services, Addison Wesley, 2004
- http://www.w3.org/xml
- http://www.w3.org/TR/wsdl
- http://docs.oasis-open.org/wsbpel/2.0/OS/wsbpel-v2.0-OS.html
- http://www.w3.org/TR/ws-cdl-10/

**Wireless Communication and Mobile Computing **

Mobile radio systems-, Paging systems, cordless telephone system, cellular telephone system, Cellular Concept: Frequency reuse, channel assignment, hand off, Interference and cell splitting, sectoring, Improving Coverage and capacity in Cellular systems. Propagation modeling: Outdoor/ Indoor Propagation models, Small scale Multipath propagation- Rayleigh fading, Ricean Fading, Nakagami fading, Shadowing, lognormal shadowing fading model, outage probability, coverage estimation under shadowing, and multipath fading. Wireless Networks 802.11, frequency-hopping, encoding and modulation, MAC Layer Protocol Architecture Multiple access with collision avoidance protocol, Virtual Carrier-Sensing, DCF Protocol, PCF Operation. Mobility: challenges, limits and connectivity, mobile TCP, mobile IP and cellular IP in mobile computing.

**Text/ Reference Books: **

- Rappaport, Wireless communications: principal and practice , Pearson ed.
- Matthew s. Gast, 802.11 wireless networks, o’reilly
- Andrea Goldsmith ,Wireless communication , cambridge university press ed .
- Jochen Schiller , Mobile communications, phi/person edu., 2 nd ed.,