Ganpat University U. V. Patel College of Engineering

Teaching Scheme for M. Tech 1st Semester (Information Technology)

SubjectCode

Subject

Teaching Scheme Credit Examination Scheme

Lect. Tut Pract Total Theory/Tutorial Pr/TW Total

Theory PracticalGrand TotalInt.

Assess.Sem End

Total Int. Assess.

Sem End Total

Marks Hrs

3IT101 ADVANCED TOPICS IN NETWORKS 3 0 2 5 3 1 4 40 60 3 100 25 25 50 150

3IT102 COMPUTATIONAL INTELLIGENCE 3 0 2 5 3 1 4 40 60 3 100 25 25 50 150

3IT103 COMPUTER ALGORITHMS 3 0 2 5 3 1 4 40 60 3 100 25 25 50 150

3IT104 SERVICE ORIENTED COMPUTING 3 0 2 5 3 1 4 40 60 3 100 25 25 50 150

3IT105 ELECTIVE-I 3 0 2 5 3 1 4 40 60 3 100 25 25 50 150  Total Contact Hours 15 0 10 25 15 5 20 500 250 750

Elective-I1. Cryptography and Network Security 2. Grid & Cloud Computing

Teaching Scheme for M.Tech 2nd Semester (Information Technology)

SubjectCode

Subject

Teaching Scheme Credit Examination Scheme

Lect Tut Pract Total Theory/Tutorial Pr/TW Total

Theory PracticalGrand TotalInt.

Assess.Sem End

TotalInt.

Assess.

Sem End Total

Marks Hrs

3IT201 DIGITAL IMAGE PROCESSING 3 0 2 5 3 1 4 40 60 3 100 25 25 50 150

3IT202 ADVANCED OPERATING SYSTEMS 3 0 2 5 3 1 4 40 60 3 100 25 25 50 150

3IT203 DATA MINING & DATA WAREHOUSING 3 0 2 5 3 1 4 40 60 3 100 25 25 50 150

3IT204 SOFTWARE ENGINEERING 3 0 2 5 3 1 4 40 60 3 100 25 25 50 1503IT205 ELECTIVE-II 3 0 2 5 3 1 4 40 60 3 100 25 25 50 1503OS201 OPEN SUBJECT 3 0 0 3 3 0 3 40 60 3 100 00 00 00 100  Total Contact Hours 18 0 10 28 18 5 23 600 250 850

Elective-II 1. Essential Mathematics 2. Public Key Infrastructure

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Teaching Scheme for M. Tech 3rd Semester (Information Technology)

SubjectCode

Subject

Teaching Scheme Credit Examination Scheme

Lect. Tut Pract Total Theory/Tutorial Pr/TW Total

Theory PracticalGrand TotalInt.

Assess.Sem End

Total Int. Assess.

Sem End Total

Marks Hrs3IT301 ELECTIVE-III 3 0 2 5 03 01 04 40 60 3 100 - 50 50 1503IT302 ELECTIVE-IV 3 0 2 5 03 01 04 40 60 3 100 - 50 50 150

3IT303 DISSERTATION PART-I 0 0 16 16 - 08 08 - - - - 100 100 200 200

3IT304 SEMINAR 0 0 4 4 - 02 02 - - - - - 100 100 100Total Contact Hours 06 - 24 30 06 12 18 200 400 600

Elective-III1. Semantic Web and Social Networks2. Data Compression3. Embedded Systems4. Advanced Database Technology

Elective-IV 1. Satellite Networking 2. Compiler Design

Teaching Scheme for M.Tech. 4th Semester (Information Technology)

Subject

Code

Subject

Teaching Scheme Credit Examination Scheme

Lect. Tut Pract Tota

lTheory/Tutorial

Pr/TW Total

Theory PracticalGrand TotalInt.

Assess.Sem End

Total Int. Assess.

Sem End Total

Marks Hrs

3IT401 DISSERTATION PART-II - - 24 24 - 12 12 - - - - 100 200 300 300

Total Contact Hours - - 24 24 - 12 12 - - - - 100 200 300 300

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3IT101: Advanced Topics in Networks [3 0 2 3 1]

Learning Outcomes:Upon completion of this course, it is envisaged that the students will be able to:

Explain the constraints of the wireless physical layer that affect the design and performance of ad hoc and sensor networks, protocols, and applications;

Explain the performance of various unicast and multicast routing protocols that have been proposed for ad hoc networks;

Explain the operation of several media access protocols that have been proposed for ad hoc and sensor networks;

Contents: Challenged Networks and Novel Architectures: Delay Tolerant Networks (DTN),

Pocket Switched Networks, Vehicular Ad Hoc Networks (VANETs) and Peer To Peer Wireless (AdHoc)Networks.

Mobility Modeling I (Scheduled or Predictable) & its impact, DTN Routing andMulticasting: Epidemic Routing, Mobility‐assisted Routing, Replication and Erasure coding,Message Ferrying, Utility‐based Routing., Mobility Modeling I ( Scheduled or Predictable)& its impact, Opportunistic Routing and Performance Modeling

Transport and other Issues: Reliability Issues in DTNs, Network Coding, BufferManagement, Flow Control, etc.

Applications and Feasibility Studies: Content distribution, Traffic Reports and AccidentPrevention, Taxi Dispatch, Delay Tolerant Broadcasting.

Social Networks and Mobility Modeling: Mobility Models for Delay Tolerant Networks,Human Mobility and Routing, Social based Routing, Vehicular Mobility.

GSM, Wi-Fi Networks

References:1. Research papers from reputed Journals & Conferences.

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3IT102: Computational Intelligence [3 0 2 3 1]Learning Outcomes:Having completed the course students will be able to do the following:

Know the conceptual model behind AI languages (Lisp and Prolog) and apply this knowledge to create efficient programs.

Design and implement an expert system that operates in a realistic problem domain Represent concepts and logic computationally in several different ways and compare and

contrast the capabilities and limitations these representations Design solutions for problems involving uncertain inputs or outcomes

Contents: Overview of Artificial Intelligence Problems and Problem Spaces & Search Heuristic Search Techniques Introduction to Computational Intelligence Artificial Neural Networks Evolutionary Computation Computational Swarm Intelligence Fuzzy Sets & Relations Artificial Immune Systems

References:

1. Computational Intelligence – Principles, Techniques & Applications By AmitKonar, Springer, 2005.2. Artificial Intelligence By Rich E. & Kevin Knight Tata McGraw Hill.3. Principles of Artificial Intelligence By N.J.Nilsson Kaufmann.4. Introduction to AI and Expert Systems By Dan .W. Patterson prentice Hall India5. Introduction to AI By Charmiak and M.DermaltAddision Wesley.6. The Engineering of Knowledge Based Systems Theory and Practice By A.J.Gongalez& D.D. Dankel Prentice Hall.7. Fundamentals of Artificial Neural Networks By Mohamad H. Hassoun

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3IT103: Computer Algorithms [3 0 2 3 1] Learning Outcomes:

The principal objective of this course is to build a solid foundation in algorithms and their applications.

Students completing this course are expected to appreciate the importance of algorithms in other areas for example routing in networks, query processing in databases, collaboration in distributed computing, efficient caching in operating systems etc.

Contents: Algorithmic paradigms Asymptotic complexity Recurrence relations and solutions techniques. Intelligent guesswork, homogeneous recurrences, Inhomogeneous recurrences, Change of

variable, substitution method, Iteration method, Recurrence trees, Master method & master theorem

Divide & Conquer , Dynamic Programming, Greedy, Branch‐and‐bound and Backtracking

Graph Algorithms Shortest paths Amortized analysis NP‐completeness Approximation algorithms

References:

1. Introduction to Algorithms By T.H. Cormen, C.E. Leiserson, R.L. Rivest, McGraw Hill, 1994.

2. Algorithms on Strings, trees and Sequences By Dan Gusfield, Cambridge, 2005.

3. Computer Algorithms: Introduction to Design and AnalysisBy Sara Baase, Addison Wesley, 1998.4. Algorithm Design: Foundations, Analysis & Internet Examples By Michael T Goodrich & Roberto Tamassia, John Wiley, 2002.5. Fundamentals of Algorithmics By Brassard &Bratley, Prentice Hall of India.6. Fundamentals of computer algorithms By Ellis Horowitz, SartajSahni, Computer Science Press.

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3IT104: Service Oriented Computing [3 0 2 3 1]Learning Outcomes:

A thorough understanding of Web services and business processes fundamentals, design and architecture, standards and protocols, composition and verification methodologies.

Knowledge of the current research work in the distributed systems and services computing area.

Design and development of enterprise wide business processes and distributed applications.

Contents: Introduction to SOA and the SOC paradigm Foundations of services SOA Concepts, XML Standards, Web Services, SOAP, WSDL, UDDI Basic SOA Architecture, Services, Service orchestration and composition, , BPEL Semantic Web Technologies

References:

1. Service-oriented computing by D. Georgakopoulos, M. Papazoglou, The MIT Press, November 2009

2. Service-Oriented Computing: Semantics, Processes, Agents by Munindar P. Singh and Michael N. Huhns, John Wiley & Sons, Ltd., 2005

3. Service‐Oriented Architecture Concepts, Technology and Design by Thomas Erl, Pearson Education.

4. A Semantic Web Primer by Grigoris Antoniou Frank van Harmelen, The MIT Press

Cambridge

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3IT105: Cryptography and Network Security (Elective - I) [3 0 2 3 1]

Learning Outcomes: Provide students with a highlevel understanding of how information security functions in an organization.  Topics will be both business and technologycentric. To master information security governance, and related legal and regulatory issues, To master understanding external and internal threats to an organization, To be familiarity with information security awareness and a clear understanding of its importance, To be familiar with how threats to an organization are discovered, analyzed, and dealt with, To master fundamentals of secret and public cryptography

Contents: Introduction Classical Encryption Techniques Symmetric Key Cryptography Number Theory: Public Key Cryptography, Cryptographic Hash Functions Digital Signatures Authentication Protocols, Applications and Biometrics Security Introduction to Public Key Infrastructure Concepts Kerberos, e‐voting system, Intrusion detection system Secure socket layer, IPsec, E‐mail Security, Firewall

References:

1. William Stallings: “Cryptography and Network Security – Principles and Practice”, 4/E,Pearson Education, 2005.2. Bruce Scheneir: “Applied Cryptography”, 2/E, John Wiley, 1996.3. BehrouzForouzan: “Cryptography & Network Security”, 1/E, TMH, 2007.

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3IT105: Grid & Cloud Computing [3 0 2 3 1]Learning Outcomes:After completion of the course the student will be able to

Students will understand the concepts of Grid and Cloud Computing. Students will know about the applications and technologies of grid and cloud computing.

Contents: Introduction Grid Computing organizations and their roles Service oriented architecture and Grid, Semantic Grids Merging the Grid services Architecture with the web services Architecture Open Grid services Architecture Open grid services Infrastructure Grid Security Grid Computing Middlewares Introduction to Cloud Computing, Definition, Characteristics, Components, Cloud

provider, SAAS, PAAS, IAAS and Others, Organizational scenarios of clouds Introduction to Cloud Technologies, Study of Hypervisors Data in the cloud: Relational databases, Cloud file systems: GFS and HDFS, BigTable,

HBase and Dynamo Cloud security fundamentals, Vulnerability assessment tool for cloud, Privacy and

Security in cloud

References:

1. The Grid 2: Blueprint for a New Computing Infrastructure by Ian Foster and Carl

Kesselman, Morgan Kaufmann, Nov 2003

2. Grid Computing: Making The Global Infrastructure a Reality by Fran Berman, Geoffrey

Fox , Anthony J.G. Hey, John Wiley & Sons, April 2003

3. Grid Computing: A Practical Guide to Technology and Applications by Ahmar Abbas,

Charles River Media, 2004

4. Grid Computing by JoshyJosheph and Craig Fellenstein, IBM press, Pearson, 2011

5. Cloud Computing for Dummies by Judith Hurwitz, R.Bloor, M.Kanfman, F.Halper,

Wiley India

6. Enterprise Cloud Computing by GautamShroff, Cambridge

7. Cloud Security by Ronald Krutz and Russell Dean Vines, Wiley-India

8. Cloud Computing : A Practical Approach, Antohy T Velte, et.al McGraw Hill

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3IT201: Digital Image Processing [3 0 2 3 1]

Learning Outcomes: When a student completes this course, s/he should be able to:

Understand the fundamental concepts of 2D signals and systems; Perform image enhancement and restoration;

Contents: Introduction Digital Image Fundamentals Image Enhancement Image Segmentation Morphological Image Processing Representation & Description Object Recognition

References:

1. Digital Image Processing By Rafael C. Gonzalez and Richard E. Woods2. Computer Vision A modern approach By Forsyth & Ponce3. Fundamentals of Image Processing By Anil K jain4. The Image Processing Handbook By John C Russ, CRC, IEEE Press5. Research papers

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3IT202: Advanced Operating Systems [3 0 2 3 1]

Learning Outcomes:The course balances the following objectives.

Read classic systems papers that shaped the field. Understand technical details of systems concepts like virtualization. Gain some practical experience with systems programming and tools. Gain experience with defining a project and refining the design. Build, experiment with, and evaluate computer systems.

Contents: Multiprocessor Operating Systems Network Operating Systems (NOS): Distributed Operating Systems: Database Operating Systems Real Time Operating Systems

Text/Reference Book:1. Advanced Concepts in Operating Systems By Mukesh Singhal, Niranjan G.Shivaratri ,

McGraw-Hill 2. Real Time Systems By C.M.Krishna, Kang G.Shin , McGraw-Hill, 1997.Philip Hunter, 3. Network Operating Systems - Making Right Choices By Addison Wesley, 1995. 4. Modern Operating Systems By Andrew S. Tanenbaum, Prentice Hall, NJ (Section 9 –

13 only). 5. Distributed Operating Systems Concepts and Design By Pradeep K. Sinha , PHI, 1997.

Operating Systems – A Modern Perspective By Gary Nutt, Addison Wesley, 2000.

3IT203: Data Mining & Data Warehousing [3 0 2 3 1]

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Learning Outcomes:After completing this course the student must demonstrate the knowledge and ability to:

Define the concepts and definition of the information systems Differentiate between several types of information system Understand the difference between database and data warehouse Differentiate between transaction processing system and functional area information

system

Contents: Introduction Data Mining Algorithms & Knowledge Discovery Visualization mining class comparisons Data Mining Primitives, Languages, and System Architectures Application and Trends in Data Mining Overview & Concepts Architecture and Infrastructure Data Design and Data Representation Information Access & Delivery

References:1. PaulrajPonniah, “Data Warehousing Fundamentals” , John Wiley.2. M.H. Dunham, “Data Mining Introductory and Advanced Topics”, Pearson Education.3. Han, Kamber ,“Data Mining Concepts and Techniques”, Morgan Kaufmann4. Ralph Kimball ,”The Data Warehouse Lifecycle toolkit”, John Wiley.5. M Berry and G. Linoff ,”Mastering Data Mining”, John Wiley.6. W.H. InmonWiley ,”Building the Data Warehouses”, ,Dreamtech.

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3IT204: Software Engineering [3 0 2 3 1]

Learning Outcomes:After completion of the course the student will be able to

The ability to analyze, design, verify, validate, implement, apply, and maintainsoftware systems.

The ability to appropriately apply discrete mathematics, probability and statistics, andrelevant topics in computer science and supporting disciplines to complex softwaresystems.

The ability to work in one or more significant application domains. The ability to manage the development of software systems.

Contents: Introduction of Software Engineering Requirements Engineering Structured System Design Data Oriented Analysis & Design Analysis & Design Of Real Time Systems Software Quality Assurance User Interface Design Software Complexity & Reliability Software Project Management

References:1. Pressman R.S. “Software Engineering: A Practitioner's Approach”, Mcgraw Hill.2. Ghezzi C., Jazayeri M., Mandrioli D. “Fundamentals of Software Engineering”, Prentice Hall.3. Ghezzi C., Jazayeri M., Mandrioli D. “Software Engineering: The Production Of Quality Software”.4. Radice R. A. And Phillips R.W “Software Engineering, An Industrial Approach”, Vol. I,Prentice Hall.5. S.R. Software Engineering, Aksen Associates Incorporated Publishers.6. Boehm B.W., “A Spiral Model of Software Development and Enhancement”, IEEE Computer.7. Fairely R., “Software Engineering Concepts”, Tata Mcgraw Hill.8. Sommerville I., “Software Engineering”, Addision&Wesley.

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3IT205: Essential Mathematics (Elective - I) [3 0 2 3 1]

Learning Outcomes:After completing this course, the student will be able to:

Perform fundamental operations using whole numbers, integers, fractions, and decimals. Solve word problems involving proportions, percentages, and measurements. Identify and calculate area and perimeter of basic plane figures. Solve word problems using whole numbers, fractions, decimals and integers

Contents: Optimization Introduction to Probability Foundations of Queuing Theory Statistics Linear Algebra Game Theory

References:1. An Engineering Approach to Computer Networking by S. Keshav, Second Edition2. Linear Algebra by Gilbert Strang

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3IT205: Public Key Infrastructure (Elective - II) [3 0 2 3 1]

Learning Outcomes:After completing this subject, students should be able to:

Read some articles in a professional computer and network security magazine, such as IEEE Security & Privacy and SC Magazine

Use various network diagnosis tools, such as wireshark, to study network security protocols, and educational tools, such as CrypTool, to study cryptographic algorithms;

Take on a self-study on more advanced network security topics that require foundational understanding of cryptographic algorithms and network security protocols

Contents: Understand Basic Encryption Concepts, Attacks against Encryption, Understand Private KeyEncryption Understand Public Key Encryption, Cryptography Fundamentals,

CryptographicAlgorithm and protocols Symmetric Key Encryption Algorithms, Public Key Algorithms,Cryptographic issues, Strong Authentication

Digital Signatures, PKI Standards, PKIFundamentals, Implementing Security, Understand Key Management Understand Trust in theSystem, Sign-On Solutions, Secure E-Mail Implementation,

File Encryption Solutions PKISolutions and Applications, Legal Issues of Network Security.

References:1. Cryptography & network Security: Principles and Practices, 4/e, William Stallings2. Computer security basics, Rick Lehtinen, Deborah Russell, G. T. Gangemi

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3IT301: Semantic Web and Social Networks (Elective - III) [3 0 2 3 1] Learning Outcomes:

To learn Web Intelligence To learn Knowledge Representation for the Semantic Web To learn Ontology Engineering To learn Semantic Web Applications, Services and Technology To learn Social Network Analysis and semantic web

Contents: The Semantic Web Vision Structured Web Documents in XML Describing Web Resources in RDF Web Ontology Language: OWL Logic and Inference: Rules Applications Ontology Engineering Social Network Analysis and semantic web

References:1. ASemanticWebPrimer

By Grigoris AntoniouFrank van Harmelen, The MIT PressCambridge2. Building an intelligent Web: theory and practice

By RajendraAkerkar, PawanLingras

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3IT301: Data Compression (Elective-III) [3 0 2 3 1]

Learning Outcomes:When a student completes this course, s/he should be able to:

Perform image compression and decompression; Perform video compression and decompression.

Contents: Introduction: Basics of information theory Lossless compression: run length coding, variable length coding, Dictionary based

coding, Arithmatic coding, lossless image compression Lossy compression: Distortion measures, Rate distortion theory, Scalar/Vector

Quantization, Transform coding. Still image compression: JPEG/JPEG2000 Video compression: Introduction, Motion compensation, Motion vectors, H.261, H.263,

H.264, MPEG1, MPEG2, MPEG4.

References:

1. David Salomon, “Data Compression – The Complete Reference,” 4th Edi.Springer, 2006.2. Thomas M. Cover and Joy A. Thomas, “Elements of Information Theory,” Wiley‐

IntersciencePublication, John Wiley & Sons, Inc., 1991.3. K. Sayood, Introduction to Data Compression, Harcourt India Pvt. Ltd. & Morgan

Kaufmann Publishers, 1996.4. Li and Drew “Fundamentals of Multimedia”, PHI

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3IT301: Embedded Systems (Elective - III) [3 0 2 3 1]

Learning Outcomes: After completing this program, the student will be able to obtain the technical skills

needed to effectively play the entry level design engineer role in an engineering organization. The student will be able to:

Understand various types of Embedded Systems Describe Embedded Systems and its uses Appreciate the impact of Embedded System on our daily lives Understand the role played by various companies in embedded product development

Contents: An overview of embedded systems: Embedded Software development: Embedded C Language: Hardware for embedded systems: Study of ATMEL RISC Processor: Case studies and Applications of embedded systems:

References:1. Raj Kamal, “Embedded Systems”, TMH2. David E. Simon, “An Embedded Software Primer ", Pearson Education3. Muhammad Ali Mazidi and Janice GillispieMazidi, “The 8051Microcontroller

andEmbedded Systems", Pearson Education4. Frank Vahid, Tony Givargis, “Embedded System Design: A UnifiedHardware/Software

Introduction", John Wiley5. Craig Hollabaugh, “Embedded Linux", Pearson Education6. Daniel Lewis, “Fundamentals of Embedded Software”, Pearson Education.

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3IT301: Advanced Database Technology (Elective - III) [3 0 2 3 1]

Learning Outcomes:By the end of this, students should be able to:

Explain and evaluate the fundamental theories and requirements that influence the design of modern database systems

Assess and apply database functions and packages suitable for enterprise database development and database management

Critically evaluate alternative designs and architectures for databases and data warehouses

Discuss and evaluate methods of storing, managing and interrogating complex data

Contents: Relational Databases: Object Oriented Databases: Emerging Systems: Current Issues: Database Design Issues:

References:

1. An Introduction to database systems –CJ.Date .Adission wisely2. Databse system concepts, Abraham Silberschataz, Henry F. Korth& S.

Sudarshan,McGraw Hill3. Gary W. Hanson and James V. Hanson, Database Management and Design, PrenticeHall

of India Pvt Ltd, 1999.4. Alex Benson, Stephen Smith and Kurt Thearling, Building Data Mining Applicationsfor

CRM, Tata McGraw-Hill, 2000.5. R. Elmasri and S.B. Navathe, Fundamentals of Database Systems, Addison Wesley,2000.6. N.TamerOzsu& Patrick Valduriez, Principles of Distributed Database Systems,Prentice

Hall International Inc., 19997. Data Mining concepts and Techniques by Jiawei Han, MichelineKamber –Elsevier.

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3IT302: Satellite Networking (Elective- IV) [3 0 2 3 1]

Learning Outcomes:On successful completion of this course, you will be able to: 

Specify systems design for satellite communications Analyse the performance of satellite communications systems Conduct further research on satellite communication systems engineering

Contents: Introduction Satellite Orbits and Networking Concepts ATM and Internet Protocols Satellite Internetworking with Terrestrial Networks ATM over Satellite Networks Internet Protocol (IP) over Satellite Networks Impact of Satellite Networks on Transport Layer Protocols Next Generation Internet (NGI) over Satellite

References:1. Satellite Networking Principles & Protocols, Zhili Sun, Wiley publication.2. Research papers from reputed Journals & Conferences.

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3IT302: Compiler Design (Elective - IV) [3 0 2 3 1]Learning Outcomes:By the end of this, students should be able to:

To apply the knowledge of lex tool & yacc tool to devleop a scanner & parser. To design & conduct experiments for Intermediate Code Generation in compiler. To design & implement a software system for backend of the compiler. To deal with different translators. To develop program to solve complex problems in compiler

Contents: Introduction: Introduction to programming language, linker, loader, assembler,

interpreter, compiler, one pass compiler, multi pass compiler, cross compiler, difference between interpreter, assembler and compiler. Syntax and semantics of the language, characteristics of compiler, challenges in compiler design, components of compiler, Front and Back end analysis.

Lexical Analysis: The Role of the Lexical Analyzer, regular expression, regular languages, Specification of Lexemes, Tokens and pattern. Recognition of Tokens, Finite Automata, From a Regular Expression to an NFA, Design of a Lexical Analyzer Generator, Optimization of DFA-Based Pattern Matchers.

Syntax Analysis: The Role of the Parser, Types of grammar, CFG, Restriction on CFG, Ambiguous grammar, Top-Down Parsing: Left Factoring, Left Recursion, Construction of Predictive Parsing Table , LL (1) Grammar, String Parsing using M-Table, Bottom-Up Parsing: Handle, Shift-reduce parser, LR parsers: LR (0), SLR (1), LALR (1), CLR (1), String parsing procedure using LR parser, R-R and S-R Conflicts, Operator Precedence Parser

Syntax-Directed Translation: Introduction of syntax directed, Basic definition of attributes and semantic rules, Syntax Directed Definitions, construction of syntax tree, L-Attributed Definitions, Bottom up evaluation of S-attribute definition.

Intermediate Code Generation: Intermediate Languages, Declarations, Assignment Statements, Boolean Expressions, Case Statements, Back patching, Procedure Calls, three address code.

Code Optimization: Introduction, The Principal Sources of Optimization, Optimization of Basic Blocks, Loop Optimization techniques

Symbol Table Management: Symbol Table, Implementation, Entering information into symbol table, Various approaches to Symbol Table organization, Representing the scope information in Symbol table.

References:1. Compilers: Principles, Techniques and Tools

By Aho, Sethi, and Ullman, Addison-Wesley, 19862. Concept of Compiler Design,

By Adesh K. Pandey3. Compiler Design

By O G Kakade, 4th Edition4. Advanced Compiler Design and Implementation

By Muchnick, Morgan and Kaufmann, 1998. 5. Compiler Design in C -By Holub, Prentice-Hall, 1990.

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3IT303: Dissertation Part-I [0 0 16 0 8]

Students have to do Dissertation under guidance of faculty and have to submit their Dissertation definition and planning at the starting of the semester and mid evaluation is done at the end of the 3rd semester and Dissertation work continues.

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3IT401: Dissertation Part-II [0 0 24 0 12]

Dissertation work continues from previous semester and an expert committee will do end term evaluation. Student should prepare paper based on his/her dissertation work and submit it to any national/international conference/journal.

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