Department of Computer Science Engineering
COURSE STRUCTURE (AR-12)
Applicable for the batches admitted from 2012-13
B.Tech. 1st Semester
Code Name of the Subject Lecture Tutorial Practical Credits
HS 1401 English – I 3 1 - 4
MATH 1401 Mathematics – I 3 1 - 4
CHE 1401 Engineering Chemistry 3 1 - 4
EEE 1401 Elements of Electrical
Engineering 3 1 - 4
CHEM 1401 Environmental Studies 3 1 - 4
HS 1203 English Lab - - 3 2
CHE 1202 Engineering chemistry Lab - - 3 2
ME 1203 Engineering Work Shop - - 3 2
Total 15 5 09 26
B.Tech. 2nd
Semester
Code Name of the Subject Lecture Tutorial Practical Credits
HS 1401 English – II 3 1 - 4
MATH 1401 Mathematics – II 3 1 - 4
PHY 1401 Engineering Physics 3 1 - 4
ME 1401 Elements of Mechanical
Engineering 3 1 - 4
CSE 1401 Fundamentals of Computer
Programming 3 1 - 4
PHY 1202 Engineering Physics Lab - - 3 2
CSE 1202 Computer Programming Lab - - 3 2
ME 1202 Engineering Drawing - - 3 2
Total 15 5 09 26
B. Tech 3rd
Semester
Code Subject Lecture Tutorial Practical Credits
MATH 2404 Mathematical Methods 3 1 - 4
ECE 2406 Digital Logic Design 3 1 - 4
IT 2401 Data Structures 3 1 - 4
CSE 2403 Computer Organization 3 1 - 4
CSE 2404 Discrete Structures and Graph
Theory 3 1 - 4
IT 2203 Data Structures Lab - - 3 2
CSE 2205 Digital Logic Design Lab - - 3 2
Total 15 05 06 24
B. Tech 4th Semester
Code Subject Lecture Tutorial Practical Credits
IT 2405 Database Management Systems 3 1 - 4
IT 2402 Object Oriented Programming
through Java 3 1 - 4
CSE 2406 Data Communication Systems 3 1 - 4
CSE 2407 Operating Systems 3 1 - 4
CSE 2408 Theory of Computation 3 1 - 4
IT 2207 Database Management Systems Lab - - 3 2
IT 2204 Object Oriented Programming
through Java Lab - - 3 2
Total 15 05 06 24
B.Tech. 5th
Semester
Code Name of the Subject Lecture Tutorial Practical Credits
ECE 3428 Microprocessors and Interfacing 3 1 - 4
IT 3409 Computer Networks 3 1 - 4
IT 2406 Design and Analysis of Algorithms 3 1 - 4
CSE 3409 Software Engineering 3 1 - 4
CSE 3410 Unix Programming 3 1 - 4
ECE 3230 Microprocessors and Interfacing Lab - - 3 2
IT 3211 Computer Networks Lab - - 3 2
CSE 3211 Unix Programming Lab - - 3 2
Total 15 05 9 26
B.Tech. 6th
Semester
Code Subject Lecture Tutorial Practical Credits
CSE 3412 Computer Graphics 3 1 - 4
CSE 3413 Information Security 3 1 - 4
CSE 3414 Language Processors 3 1 - 4
Elective - I
ECE 3421 Digital Signal Processing
3 1
- 4 ECE 4433 Embedded systems
CSE 3415 Advanced Databases
Elective - II (Open Elective)
IT 3418 Cloud Computing ( IT)
3 1 4
Disaster Management (Civil)
ECE 3425 Fundamentals of Global Positioning
System (ECE)
CHEM 3425 Industrial Safety and Hazards
Management (Chem.)
ME 3431 Operations Research (Mech.)
EEE 3427 Renewable Energy Resources(EEE)
CSE 3416 Soft Computing (CSE)
GMR 30001 Audit Course
Laboratories
CSE 3217 Information Security Lab - 3 2
CSE 3218 Language processor Lab - 3 2
GMR 30206 Term Paper - 3 2
Total 15 05 9 26
B.Tech. 7th
Semester
Code Subject Lecture Tutorial Practical Credits
IT 3413 Data Warehousing and Data Mining 3 1 - 4
IT 3414 Object Oriented Analysis and Design 3 1 - 4
IT 3415 Web Technologies 3 1 - 4
Elective-III
CSE 4419 Distributed Systems
3 1 - 4 CSE 4420 Middleware Technologies
CSE 4421 Software Project Management
#MOOCs Available and Selected MOOCs courses
Elective-IV
ECE 4431 Digital Image Processing
3 1 - 4 CSE 4422 Mobile Computing
CSE 4423 Multimedia Systems
#MOOCs Available and Selected MOOCs courses
Laboratories
IT 3219 Object Oriented Analysis and Design Lab - - 3 2
IT 3220 Web Technologies Lab - - 3 2
GMR 40203 Internship 2
GMR 40204 Mini Project 2
Total 15 05 06 28
# List of the Available and Selected MOOCs courses will be intimated before the commencement of class work.
B.Tech. 8th
Semester
Code Subject Lecture Tutorial Practical Credits
HS 3405 Engineering Economics & Project
management 3 1
- 4
Elective-V
IT 4423 Information Retrival System
3 1
-
4 CSE 4424 Big Data Analytics
CSE 4425 Bio-Informatics
#MOOCs Available and Selected MOOCs courses
Elective-VI
CSE 4426 E-commerce
3 1 - 4 CSE 4427 Object Oriented Software Engineering
CSE 4428 Pattern Recognition
#MOOCs Available and Selected MOOCs courses
GMR
41205 Project
12
Total 09 03 24
# List of the Available and Selected MOOCs courses will be intimated before the commencement of class work.
Department of Computer Science & Engineering
B. Tech- 7th
Semester
SYLLABUS
(Applicable for 2012-13 admitted batch)
Course Title: DATA WAREHOUSING AND DATA MINING Course Code: IT 3413
L T P C
3 1 0 4
Course Objectives: The course content enables students to:
1. Analyze the difference between On Line Transaction Processing and On Line analytical processing
2. Create Multidimensional schemas suitable for data warehousing
3. Understand various data mining functionalities
4. Understand in detail about data mining algorithms
Course Outcomes: At the end of the course students are able to:
1. Design a data mart or data warehouse for any organization
2. Extract knowledge using data mining techniques
3. Adapt to new data mining tools
4. Explore recent trends in data mining such as web mining, multimedia mining
UNIT- I 15 Hrs
Introduction: Fundamentals of data mining, Data Mining Functionalities, Major issues in Data Mining
Data Preprocessing: Needs Preprocessing the Data, Data Cleaning, Data Integration and Transformation,
Data Reduction, Data Warehouse and OLAP Technology for Data Mining Data Warehouse, Multi-
dimensional Data Model, Data Warehouse Architecture
UNIT-II 14 Hrs
Data Mining Primitives, Languages, and System Architectures : Data Mining Primitives, Data Mining
Query Languages, Designing Graphical User Interfaces Based on a Data Mining Query Language,
Architectures of Data Mining Systems.
Concepts Description: Characterization and Comparison: Data Generalization and Summarization-
Based Characterization, Analytical Characterization: Analysis of Attribute Relevance, Mining Class
Comparisons: Discriminating between Different Classes
UNIT- III 15 Hrs
Mining Association Rules in Large Databases: Association Rule Mining, Mining Single-Dimensional
Boolean Association Rules from Transactional Databases, Mining Multilevel Association Rules from
Transaction Databases.
Classification and Prediction: Issues Regarding Classification and Prediction, Classification by Decision
Tree Induction, Bayesian Classification, Classification by Back propagation, Prediction.
UNIT IV 16 Hrs
Cluster Analysis Introduction: Types of Data in Cluster Analysis, A Categorization of Major Clustering
Methods, Partitioning Methods, Density-Based Methods, Grid-Based Methods, Model-Based Clustering
Methods, Outlier Analysis.
Mining Complex Types of Data: Multidimensional Analysis and Descriptive Mining of Complex, Data
Objects, Mining Multimedia Databases, Mining Text Databases, Mining the World Wide Web.
Text Books:
1. Data Mining – Concepts and Techniques - Jiawei Han & Micheline Kamber Harcourt, India.
2. Data Mining Techniques – Arun K Pujari, University Press.
Reference Books:
1. Data Mining Introductory and advanced topics –Margaret H Dunham, Pearson Education
2. Data Warehousing in the Real World – Sam Anahory & Dennis Murray. Pearson Edn
3. Data Warehousing Fundamentals – Paulraj Ponnaiah Wiley Student Edition.
Department of Computer Science & Engineering
B. Tech- 7th
Semester
SYLLABUS
(Applicable for 2012-13 admitted batch)
Course Title: OBJECT ORIENTED ANALYSIS AND DESIGN Course Code: IT 3414
L T P C
3 1 0 4
Course objectives: The course content enables students to:
1. Develop the different UML diagrams for a software system based on the given requirements.
2. Apply forward engineering to convert diagram to code and reverse engineering to convert code to
diagram.
3. Analyze & design a s/w system in object oriented approach, using unified modeling language.
4. Select appropriate models for a s/w system depending upon the complexity of the system
Course outcomes: At the end of the course students are able to:
1. Understand the use of unified modeling language for object oriented analysis and design
2. Know the syntax of different UML diagrams.
3. Develop different models for a software system.
4. Apply object oriented analysis and design to build a software system
5. Apply forward and reverse engineering for a software system.
UNIT – I 14 Hrs
Introduction to UML: Importance of modeling, principles of modeling, object oriented modeling,
conceptual model of the UML, Architecture, Software Development Life Cycle.
Basic Structural Modeling: Classes, Relationships, common Mechanisms, and diagrams.
Advanced Structural Modeling: Advanced classes, advanced relationships, Interfaces, Types and Roles,
Packages.
UNIT – II 16 Hrs
Class & Object Diagrams: Terms, concepts, modeling techniques for Class & Object Diagrams.
Basic Behavioral Modeling-I: Interactions, Interaction diagrams.
UNIT-III 15 Hrs
Basic Behavioral Modeling-II: Use cases, Use case Diagrams, Activity Diagrams.
Advanced Behavioral Modeling: Events and signals, state machines, processes and Threads, time and
space, state chart diagrams.
UNIT-IV 15 Hrs
Architectural Modeling: Component, Deployment, Component diagrams and Deployment diagrams.
Case Study: The Unified Library application.
Text Books:
1. Grady Booch, James Rumbaugh, IvarJacobson : The Unified Modeling Language User Guide, Pearson
Education.
2. Hans-Erik Eriksson, Magnus Penker, Brian Lyons, David Fado: UML 2 Toolkit, WILEY-Dreamtech India
Pvt. Ltd.
Reference Books:
1. Meilir Page-Jones: Fundamentals of Object Oriented Design in UML, Pearson Education.
2. Atul Kahate: Object Oriented Analysis & Design, The McGraw-Hill Companies.
3. Gandharba Swain: Object Oriented Analysis & Design Through Unified Modeling Language, Lakshmi
Publications Pvt. Ltd , New Delhi.
Department of Computer Science & Engineering
B.Tech- 7th
Semester
SYLLABUS
(Applicable for 2012-13 admitted batch)
Course Title: WEB TECHNOLOGIES Course Code: IT 3415
L T P C
3 1 0 4
Course Objectives: The course content enables students to:
1. understand best technologies for solving web client/server problems
2. analyze and design real time web applications
3. use Java script for dynamic effects and to validate form input entry
4. Analyze to Use appropriate client-side or Server-side applications
Course Outcomes: At the end of the course students are able to:
1. Choose, understand, and analyze any suitable real time web application.
2. Integrate java and server side scripting languages to develop web applications.
3. To develop and deploy real time web applications in web servers and in the cloud.
4. Extend this knowledge to .Net platforms.
UNIT – I 17 Hrs
HTML Common tags- List, Tables, images, forms, Frames, Links and Navigation, Image Maps
CSS: Introduction, CSS Properties, Controlling Fonts, Text Formatting, Pseudo classes, Selectors, CSS for
Links, Lists, Tables.
Java Script: Learning Java script: Variables, operators, Functions, Control structures, Events, Objects,
Validations.
UNIT – II 14 Hrs
PHP Programming: Introducing PHP: Creating PHP script, Running PHP script.
Working with Variables and constants: Using variables, Using constants, Data types, Operators.
Controlling program flow: conditional statements, control statements, arrays, functions, working with
forms.
UNIT-III 16 Hrs
AJAX: Introduction, AJAX with XML
Servlets: introduction to servlets, Life cycle of servlets, JSDK, The servlet API, the javax. servlet package,
Reading servlet parameters and initialization parameters, The javax. servlet HTTP package, Handling Http
request and responses, Using cookie, session tracking,
Introduction to JSP: The problem with servlet, the anatomy of JSP page, JSP processing, JSP application
design with MVC, Tomcat server and testing tomcat, Generic dynamic content, using scripting elements
implicit JSP objects,
UNIT-IV 14 Hrs
JSP application development: Conditional processing display values using an expression to set an attribute,
Declaring variables and methods, sharing data between JSP pages, Requests and users passing control and
data between pages, Sharing sessions and application data, memory usage considerations
JDBC connectivity in JSP: Data base programming using JDBC, Studying javax.sql.* package, Accessing
a database from a JSP page, Application specific database actions, Deploying JAVA beans in JSP page.
Text Books:
1. Web Technologies, Uttam Roy, OXFORD University press
2. Web programming with HTML, XHTML and CSS, 2e, Jon Duckett, Wiley India
Reference Books:
1. Web programming Bai, Michael Ekedahl, CENAGE Learning , India edition.
2. An Introduction to Web Design + Programming, Paul S.Wang, India Edition
Department of Computer Science & Engineering
B. Tech- 7th
Semester
SYLLABUS
(Applicable for 2012-13 admitted batch)
Course Title: DISTRIBUTED SYSTEMS Course Code: CSE 4419
L T P C
3 1 0 4
Course Objectives: The course content enables students to:
1. Understand the principles and techniques behind the design of distributed systems
2. Familiar with naming and synchronization mechanisms
3. Learn the concepts of fault tolerance and file systems used in distributed systems.
4. Know the Importance of the distributed transactions , coordination and agreement
Course Outcomes: At the end of the course students are able to:
1. Learn the core concepts underlying distributed systems designs.
2. Identify entities and resources in distributed systems and examine the naming conventions
3. Apply and compare the various communication mechanisms in distributed systems.
4. Identify issues on how to coordinate and synchronize multiple tasks in a distributed system.
UNIT-1 14 Hrs
Definition of Distributed systems, goals of distributed systems ,types of distributed systems, Distributed
system architecture, architectural styles, system architectures, middleware Communication Fundamentals,
Remote Procedure Call, Message-Oriented Communication, Stream-Oriented Communication, Multicast
Communication.
UNIT-2 16 Hrs
Naming: Names, Identifiers, and Addresses, Flat Naming, Structured Naming, Attribute-Based
Synchronization: Clock Synchronization, Stream Synchronization, Synchronization Mechanisms, Logical
Clocks, Physical clocks
Consistency and Replication: Introduction, Data-Centric Consistency Models, Client-Centric Consistency
Models, Consistency Protocols.
UNIT-3 14 Hrs
Fault Tolerance: Introduction to Fault Tolerance, Process Resilience, Reliable Client-Server
Communication, Reliable Group Communication, peer to peer communications, Distributed Commit,
Recovery.
Distributed File Systems: Introduction to distributed file systems, Architecture, Process, communications,
consistency and replication, Sun network file system.
UNIT-4 16 Hrs
Distributed Transactions: Introduction, Flat and nested distributed transitions, Atomic commit protocol,
concurrency control in distributed transactions, distributed dead locks, Transaction and recovery.
Coordination and Agreement: Introduction, Distributed Mutual exclusion, Elections, multi cast
communication, consensus and related problems.
CASE STUDY: CORBA RMI, CORBA Services.
Text Books:
1. Distributes Systems Principles and paradigms, Second Edition-Andrew S.Tanenbaum, Maarten Van
Steen.
2. Distributed Systems: Concepts and Design, George Coulouris, Jean Dollimore& Tim Kindberg, 4th
ed,
2005, Addison-Wesley
Reference books
1. Distributed Operating Systems, Andrew S.Tanenbaum, Pearson
Department of Computer Science & Engineering
B. Tech- 7th
Semester
SYLLABUS
(Applicable for 2012-13 admitted batch)
Course Title: MIDDLEWARE TECHNOLOGIES Course Code: CSE 4420
L T P C
3 1 0 4
Course Objectives: The course content enables students to:
1. Understand different types, benefits and pitfalls of client server computing models.
2. Establish communication between client and server through java RMI and JDBC.
3. Implement C#.Net applications using Assemblies, and Callback Interfaces.
4. Develop client server applications using heterogeneous programming languages with CORBA
5. Learn java bean component model with EJBS and CORBA.
Course Outcomes: At the end of the course students are able to:
1. Choose appropriate client server computing model for given problem.
2. Design a dynamic remote application with RMI and JDBC Connectivity.
3. Develop client server applications using C#.net
4. Select appropriate language for homogeneous and heterogeneous objects.
5. Develop real time projects by combining CORBA and database interfacing
UNIT – I 15 Hrs
Introduction to client server computing: Evolution of corporate computing models from centralized to
Distributed computing, client server models. Benefits of client server computing, pitfalls of client server
Programming.
Advanced Java: Review of Java concept like RMI, and JDBC.
UNIT – II 15 Hrs
Introducing C# and the .NET Platform; Understanding .NET Assemblies, Object –Oriented Programming
with C#, Callback Interfaces.
Building c# applications: Type Reflection, Late Binding, and Data Access with ADO.NET.
UNIT-III 15 Hrs
Core CORBA / Java: Two types of Client/ Server invocations-static, dynamic. The static CORBA, first
CORBA program, ORBlets with Applets, Dynamic CORBA-The portable count, the dynamic count
Existential CORBA: CORBA initialization protocol, CORBA activation services, Introduction to Service
Oriented Architecture (SOA)
UNIT-IV 15 Hrs
Java Bean Component Model: Events, properties, persistency, Introspection of beans, CORBA Beans.
EJBs and CORBA: Object transaction monitors CORBA OTM’s, EJB and CORBA OTM’s, EJB container
frame work, Session and Entity Beans.
Text Books:
1. Client/Server programming with Java and CORBA Robert Orfali and Dan Harkey, John Wiley & Sons ,
SPD 2nd Edition
2. Java programming with CORBA 3rd Edition, G.Brose, A Vogel and K.Duddy, Wiley-dreamtech, India
John wiley and sons
Reference Books:
1. Distributed Computing, Principles and applications, M.L.Liu, Pearson Education
2. Client/Server Survival Guide 3rd edition Robert Orfali Dan Harkey & Jeri Edwards, John Wiley & Sons
3. Client/Server Computing D T Dewire, TMH.
4. Programming C#, Jesse Liberty, SPD-O’Reilly.
5. C# Preciesely Peter Sestoft and Henrik I. Hansen, Prentice Hall of India
6. Intoduction to C# Using .NET Pearson Education
Department of Computer Science & Engineering
B. Tech- 7th
Semester
SYLLABUS
(Applicable for 2012-13 admitted batch)
Course Title: SOFTWARE PROJECT MANAGEMENT Course Code: CSE 4421
L T P C
3 1 0 4
Course Objectives: The course content enables students to:
1. Overview of software project evaluation and the project planning. It also covers the Step Wise
framework in project planning.
2. Evaluate and assess the projects and to find the cost of the project using cost benefit evaluation
techniques.
3. To produce an activity plan for a project and to estimate the overall duration of the project by
analyzing the risks involved in it.
4. Identifying the factors that influence people’s behavior in a project environment and project quality.
5. Overview of project possible change management and review of some free open source project
management tools.
Course Outcomes: At the end of the course students are able to:
1. Apply and practice Project Management principles while developing a software.
2. Defining and implementing software project planning.
3. Analyzing software risks and risk management strategies
4. Defining the concepts of software quality and reliability on the basis of international quality
standards.
5. Knowing and implementing the software project management tools
UNIT-1
Project Evaluation and Planning 16 Hrs
Activities in Software Project Management, Overview of Project Planning, Stepwise planning, contract
management, Software processes and process models. Cost Benefit Analysis, Cash Flow Forecasting, Risk
Evaluation. Project costing, Function point analysis, COCOMO 2, Staffing pattern, Effect of schedule
compression, Putnam’s equation, Capers Jones estimating rules of thumb.
UNIT-2
Monitoring and Control 15 Hrs
Project Sequencing and Scheduling Activities, work breakdown structure, Gantt chart, Scheduling resources,
Critical path analysis, Network Planning.
Collecting Data, Visualizing Progress, Cost Monitoring, review techniques, project termination review,
Earned Value analysis, Change Control, Software Configuration Management (SCM), Managing Contracts,
Types of Contracts, Stages In Contract Placement, Typical Terms of A Contract, Contract Management and
Acceptance.
UNIT-3
Quality Management and People Management 14Hrs
Risk Management, Nature and Types of Risks, Managing Risks, Hazard Identification, Hazard Analysis,
Risk Planning and Control, PERT and Monte Carlo Simulation techniques.
Introduction, Understanding Behavior, Organizational Behaviour, Selecting The Right Person For The Job,
Motivation, The Oldman – Hackman Job Characteristics Model , Working in Groups, Organization and team
structures, Decision Making, Leadership, Organizational Structures, ISO and CMMI models,
UNIT-4
Project Change Management 13 Hrs
Introduction, Impact of change, Change as a process, Emotional behavior pattern of change, Change
Management plan, dealing with resistance and conflict.
Closure of a Project: Introduction, Project Implementation, Administrative closure, Project Evaluation.
Testing, and Software reliability, test automation, Overview of project management tools: open-source tools
Gantt project or similar tools
Agile methodologies: scrum and Extreme programming.
Text Book
1. Bob Hughes, Mike Cotterell and Rajib Mall: Software Project Management – Fifth Edition, Tata
McGraw Hill, New Delhi, 2012.
Reference Books:
1. Pankaj Jalote, “Software Project Management in Practice”, 2002, Pearson, Education Asia.
2. Jack T Marchewka, “Information Technology Project Management”, Third Edition (International
Student Version) , Wiley India
3. Samuel J mantel et.el “Project Management- Core Textbook”, First India Edition, Wiley India
4. Robert K. Wysocki, Effective Software Project Management, Wiley, 2009
Department of Computer Science & Engineering
B. Tech- 7th
Semester
SYLLABUS
(Applicable for 2012-13 admitted batch)
Course Title: DIGITAL IMAGE PROCESSING Course Code: ECE 4431
L T P C
3 1 0 4
Course Objectives: Students undergoing this course are expected to:
1. be familiar with basic concepts , image manipulations and methodologies for digital image Processing
2. Learn various image processing techniques like image enhancement, restoration
3. know segmentation ,image compression
4. Understand pseudo and full color processing
5. appreciate the usage of image transforms in image processing
6. Know about MATLAB tool for image processing
Course Outcomes: After undergoing the course students will be able to :
1. Appreciate image manipulations and different digital image processing techniques in various fields.
2. Perform basic operations like – Enhancement, Image transform and restoration techniques on image.
3. Make use of image segmentation , compression for various applications.
4. Analyze pseudo and full color image processing techniques.
5. Apply the various image transforms used in image processing
6. Apply MATLAB to implement the image processing techniques.
UNIT I 18 Hrs
Digital Image Fundamentals: Fundamental steps in Digital image processing, Digital image representation,
Elements of visual perception, light and electromagnetic spectrum, Image sensing and acquisition, Image
sampling and quantization, basic relationships between pixels. An introduction to mathematical tools in
digital image processing
Color Image Processing: Color fundamentals, color models, Pseudo color Image Processing, Full Color
Image Processing , color transformations.
UNIT II 16 Hrs
Image transforms: : 2D DFT and its properties, Discrete cosine transform, STFT, Introduction to Wavelet.
Image Enhancement : Enhancement in spatial domain, Intensity transformations, Histogram Processing, ,
smoothing and sharpening. Image Enhancement in Frequency Domain Filters, Smoothing Frequency
Domain Filters, Sharpening Frequency Domain Filters,
UNIT III 12 Hrs
Color image enhancement: Image smoothing and sharpening-spatial domain and frequency domain
Image Restoration: A Model of the Image Degradation/Restoration Process, Linear Position-Invariant
Degradations, Inverse filtering, Minimum Mean Square Error (Wiener) Filter, Constrained Least squares
filtering.
UNIT IV 14 Hrs
Image segmentation: Fundamentals, point, Line and Edge detection, , Thresholding, Region based
Segmentation.
Image Compression: Fundamentals, Image Compression Models, Elements of Information Theory,Error
Free Compression, Lossy Compression, Image compression using DCT and DWT, Introduction to Digital
Image water marking.
Text Book:
1. Rafel C.Gonzalez and Richard E.Woods, “Digital Image Processing”, Pearson Education,3rd
edition
2011
Reference Books:
1. Anil K. Jain, “Fundamentals of Digital Image Processing”, 2003, Pearson Education.
2. S.Jayaraman S.Esakirajan T.Veerakaumar” Digital Image Processing” Mc Graw Hill publishres, 2009
3. S.Sridhar,” Digital Image Processing” oxford publishers, 2011
4. Chanda & Majumdar, “Digital Image Processing and Analysis” 2003, PHI.
5. M.Sonka,V. Hlavac, R. Boyle, “Image Processing, Analysis and Machine Vision”, Vikas Publishing
House
Department of Computer Science & Engineering
B. Tech- 7th
Semester
SYLLABUS
(Applicable for 2012-13 admitted batch)
Course Title: MOBILE COMPUTING Course Code: CSE 4422
L T P C
3 1 0 4
Course Objectives: The course content enables students to:
1. Differentiate between various medium access schemes
2. Understand the concept of Mobile IP and packet delivery
3. Know the importance of Wireless Sensor Networks
4. Configure an Ad hoc network using NS3
Course Outcomes: At the end of the course students are able to:
1. Demonstrate knowledge of different voice and data communication standards
2. Analyze the need for optimizations in Mobile IP
3. Distinguish between proactive and reactive routing in an Ad hoc network
4. Develop simple app using Android
UNIT – I 16 Hrs
Mobile Communications - Overview: Wireless transmission, voice and data communication standards –
1G/2G/3G/4G, WPAN, WLAN, applications, limitations, mobile computing architecture, overview on
mobile devices and systems
Wireless Medium Access Control: Motivation for a specialized MAC (Hidden and exposed terminals, Near
and far terminals, MACA), modulation, Spread spectrum, SDMA, FDMA, TDMA, CDMA
GSM: services, system architecture, radio interface, localization, call handling, handover, security, GPRS,
EDGE
UNIT – II 13 Hrs
Mobile Network Layer: Mobile IP, IP packet delivery, agent advertisement and discovery, registration,
tunneling and encapsulation, optimizations, Dynamic Host Configuration Protocol
Mobile Transport Layer: Traditional TCP, Indirect TCP, Snooping TCP, Mobile TCP
UNIT – III 16 Hrs
Mobile Ad hoc Network (MANET): Introduction, Properties, applications, limitations, routing issues,
routing algorithms – proactive (DSDV & OLSR) and reactive (DSR & AODV)
Wireless Sensor Network (WSN): Introduction, architecture, applications, security in ad hoc networks
Wireless LAN: IEEE 802.11, System architecture, Protocol layers
UNIT – IV 15 Hrs
Network Simulator: Overview on different network simulators (NS2, NS3, Qualnet, Omnet++, Netsim
etc.), configuration of MANET and WSN on NS2/NS3
Mobile OS: Overview on different mobile Oss (Android OS, IOS, Windows 8, Blackberry OS etc.), Android
OS architecture, app development examples
Wireless Application Protocol (WAP): Introduction, architecture
Text Books:
1. Mobile Computing, Raj Kamal, Oxford press, Second Edition
2. Mobile Communications, Jochen Schiller, Pearson Education, Second Edition
Reference Books:
1. Mobile Computing, Asoke K Talukder, Hasan Ahmed and Roopa Yavagal, McGraw Hill
2. Fundamentals of Mobile Computing, Prasant Kumar Pattnaik and Rajib Mall, PHI Learning
3. http://www.isi.edu/nsnam/ns/doc/ns_doc.pdf (NS2 manual)
Department of Computer Science & Engineering
B. Tech- 7th
Semester
SYLLABUS
(Applicable for 2012-13 admitted batch)
Course Title: MULTIMEDIA SYSTEMS Course Code: CSE 4423
L T P C
3 1 0 4
Course Objective: The course content enables students to:
1. Employ different realizations of multimedia tools.
2. Put into practice various multimedia applications and Action scripts.
3. Examine various storage technologies.
4. Relate video compression Techniques for real time applications.
Course Outcome: At the end of the course students are able to:
1. Use different realizations of multimedia tools.
2. Implement various multimedia applications and Action scripts.
3. Analyze various storage technologies.
4. Apply video compression Techniques for real time applications.
UNIT-I 16 Hrs
Fundamental concepts in Text and Image: Multimedia and hypermedia, World Wide Web, overview
of multimedia software tools. Graphics and image data representation graphics/image data types,
file formats, Color in image and video: color science, color models in images, color models in
video. Fundamental concepts in video and digital audio: Types of video signals, analog video, digital
video, digitization of sound, MIDI
UNIT – II 15 Hrs
Action Script I: ActionScript Features, Object-Oriented ActionScript, Datatypes and Type
Checking, Classes, Authoring an ActionScript Class.
Action Script II: Inheritance, Authoring an ActionScript 2.0 Subclass, Interfaces, Packages, Exceptions.
UNIT – III 14 Hrs
Application Development: An OOP Application Frame work, Using Components with
ActionScript MovieClip Subclasses.
Multimedia data compression: Lossless compression algorithm: Run-Length Coding, Variable
Length Coding, Dictionary Based Coding, and Arithmetic Coding.
UNIT – IV 15 Hrs
Basic Video Compression Techniques: Introduction to video compression, video compression based
on motion compensation, search for motion vectors, MPEG.
TEXT BOOKS:
1. Fudamentals of Multimedia by Ze-Nian Li and Mark S. Drew PHI/Pearson Education.
2. Essentials ActionScript 2.0, Colin Moock, SPD O, REILLY.
REFERENCES:
1. Digital Multimedia, Nigel chapman and jenny chapman, Wiley-Dreamtech
2. Macromedia Flash MX Professional 2004 Unleashed, Pearson.
3. Multimedia and communications Technology, Steve Heath, Elsevier(Focal Press).
Department of Computer Science & Engineering
B. Tech- 7th
Semester
SYLLABUS
(Applicable for 2012-13 admitted batch)
Course Title: OBJECT ORIENTED ANALYSIS AND DESIGN LAB Course Code: IT 3219
L T P C
0 0 3 2
Course Objectives: This course is designed to enable the students to:
1. Know the practical issues of the different Object oriented analysis and design concepts.
2. Inculcate the art of object oriented software analysis design.
3. Apply forward and reverse engineering of a software system.
4. Carry out the analysis and design of a system in an object oriented way.
Course outcomes: After undergoing the course students are able to:
1. Know the syntax of different UML diagrams.
2. Create different UML diagrams for a software system
3. Identify appropriate models to represent a software system.
4. Analyze and design a software system in an object oriented style using tools like Rational Rose.
List of Experiments
1. The student should take up the case study of Unified Library application which is mentioned in the theory,
and Model it in different views i.e. Use case view, logical view, component view, Deployment view,
Database design, forward and Reverse Engineering, and Generation of documentation of the project.
2. Student has to take up another case study of his/her own interest and do the same whatever mentioned in
first problem. Some of the ideas regarding case studies are given in reference books which were mentioned
in theory syllabus can be referred for some idea.
Reference Books:
1. Meilir Page-Jones: Fundamentals of Object Oriented Design in UML, Pearson Education.
2. Pascal Roques: Modeling Software Systems Using UML2, WILEY-Dream tech India Pvt. Ltd.
3. Atul Kahate: Object Oriented Analysis & Design, The McGraw-Hill Companies.
4. Mark Priestley: Practical Object-Oriented Design with UML, TATA Mc Graw Hill
5. Gandharba Swain: Object Oriented Analysis & Design Through Unified Modeling Language, Lakshmi
Publications Pvt. Ltd , New Delhi.
Department of Computer Science & Engineering
B. Tech- 7th
Semester
SYLLABUS
(Applicable for 2012-13 admitted batch)
Course Title: WEB TECHNOLOGIES LAB Course Code: IT 3220
L T P C
0 0 3 2
Course Objectives: This course is designed to enable the students to:
1. Understand the web technologies to create adaptive web pages for web application.
2. use CSS to implement a variety of presentation effects to the web application
3. know the concept and implementation of cookies as well as related privacy concerns
4. Develop a sophisticated web application that employs the MVC architecture.
Course Outcomes: At the end of this course the student can answer how to:
1. Integrate frontend and backend web technologies in distributed systems.
2. Facilitate interface between frontend and backend of a web application.
3. Debug, test and deploy web applications in different web servers.
4. Migrate the web applications to the other platforms like .Net
Experiment-1: Design the following static web pages required for a Training and placement cell web site.
1) Home Page 2) Login Page 3) Registration page
Experiment-2: 4) Company Details Page 5) Alumni Details Page 6) Placement Staff Details Page
Experimen-3: 7) Student personal Info Page 8) Student Academic Info page 9) Semester Wise Percentage &
their Aggregate page
Experiment-4: Validate login page and registration page using regular expressions.
Experiment-5: Apply different font styles, font families, font colors and other formatting styles to the above
static web pages.
Experiment-6: Install wamp server and tomcat server, access above developed static web pages using these
servers.
Experiment-7: Write a servlet/PHP to connect to the database, Insert the details of the users who register
with the web site, whenever a new user clicks the submit button in the registration.
Experiment-8: Write a JSP/PHP to connect to the database, Insert the details of the student academic
information with student academic info page.
Experiment-9: User Authentication:
Assume four users user1user2, user3 and user4 having the passwords pwd1, pwd2, pwd3 and pwd4
respectively. Write a servlet for doing the following.
1. Create a Cookie and add these four user id’s and passwords to this Cookie.
2. Read the user id and passwords entered in the Login form (week1) and authenticate with the values (user
id and passwords) available in the cookies.
If he is a valid user (i.e., user-name and password match) you should welcome him by name (user-name) else
you should display “You are not an authenticated user “.
Use init-parameters to do this. Store the user-names and passwords in the webinf.xml and access them in the
servlet by using the get In it Parameters () method.
Experiment-10: Write a JSP which does the following job:
Authenticate the user when he submits the login form using the user name and password from the
database.
Experiment-11: write a JSP to insert the student’s semester wise percentages and calculate aggregate and
insert into database.
Experiment-12: write a JSP to search the students according to their aggregate and produce sorted list or
according to their Enroll number.
Department of Computer Science & Engineering
B.Tech- 8th
Semester
SYLLABUS
(Applicable for 2012-13 admitted batch)
Course Title: ENGINEERING ECONOMICS AND PROJECT MANAGEMENT
Course Code: HS 3405
L T P C
3 1 0 4
Course Objectives: The course content enables students to:
1. Acquaint the basic concepts of Engineering Economics and its application
2. Know various methods available for evaluating the investment proposals
3. Make the optimal decisions acquiring the knowledge on financial accounting
4. Gain the relevant knowledge in the field of management theory and practice
5. Understand the project management lifecycle and be knowledgeable on the various phases from
project initiation through closure
Course Outcomes: At the end of the course students are able to:
1. Understand basic principles of engineering economics
2. Evaluate investment proposals through various capital budgeting methods
3. Apply the knowledge to prepare the simple financial statements of a company for measuring
performance of business firm
4. Analyze key issues of organization, management and administration
5. Evaluate project for accurate cost estimates and plan future activities
UNIT-I:
Introduction to Engineering Economics: 13 Hrs
Concept of Engineering Economics – Types of efficiency – Theory of Demand - Elasticity of demand-
Supply and law of Supply – Indifference Curves.
Demand Forecasting & Cost Estimation:
Meaning – Factors governing Demand Forecasting – Methods – Cost Concepts – Elements of Cost – Break
Even Analysis.
UNIT-II:
Investment Decisions & Market Structures: 17 Hrs
Time Value of Money – Capital Budgeting Techniques - Types of Markets – Features – Price Out-put
determination under Perfect Competition, Monopoly, Monopolistic and Oligopoly
Financial Statements & Ratio Analysis:
Introduction to Financial Accounting - Double-entry system – Journal – Ledger - Trail Balance – Final
Accounts (with simple adjustments) – Ratio Analysis (Simple problems).
UNIT-III:
Introduction to Management: 14 Hrs
Concepts of Management – Nature, Importance – Functions of Management, Levels - Evolution of
Management Thought – Decision Making Process - Methods of Production (Job, Batch and Mass
Production) - Inventory Control, Objectives, Functions – Analysis of Inventory – EOQ.
UNIT-IV:
Project Management: 16 Hrs
Introduction – Project Life Cycle – Role Project Manager - Project Selection – Technical Feasibility –
Project Financing – Project Control and Scheduling through Networks - Probabilistic Models – Time-Cost
Relationship (Crashing) – Human Aspects in Project Management.
Text Books:
1. Fundamentals of Engineering Economics by Pravin Kumar, Wiley India Pvt. Ltd. New Delhi, 2012.
2. Project Management by Rajeev M Gupta, PHI Learning Pvt. Ltd. New Delhi, 2011.
Reference Books:
1. Engineering economics by Panneer Selvam, R, Prentice Hall of India, New Delhi, 2013.
2. Engineering Economics and Financial Accounting (ASCENT Series) by A. Aryasri & Ramana Murthy,
McGraw Hill, 2004.
3. Project Management by R.B.Khanna, PHI Learning Pvt. Ltd. New Delhi, 2011.
4. Project Management by R. Panneer Selvam & P.Senthil Kumar, PHI Learning Pvt. Ltd. New Delhi,
2009.
5. Management Science by A.Aryasri, Tata McGraw Hill, 2013
6. Koontz & Weihrich: Essentials of Management, 6/e, TMH, 2007
Department of Computer Science & Engineering
B.Tech- 8th
Semester
SYLLABUS
(Applicable for 2012-13 admitted batch)
Course Title: INFORMATION RETRIEVAL SYSTEMS Course Code: IT 4423
L T P C
3 1 0 4
Course Objectives: The course content enables students to:
1. Understand the Functionalities of IRS
2. Create indices to extract data efficiently from Information Storage
3. Learn document management, retrieval and searching the web.
4. Apply Clustering for the data to be stored to IRS
5. Understand working of Search Engines and ways to improve them.
6. Know about hypermedia architectures, design and usability of IRS
Course outcomes: At the end of the course the students are able to:
1. Learn Classical and advanced techniques employed by Web Search engines
2. Know different ways of representation and retrieval of documents.
3. Apply techniques of preprocessing needed for IRS
4. Develop an IRS by using different user search techniques and text search algorithms
UNIT- I 14 Hrs
Introduction: Definition, Objectives, Functional Overview, Relationship to DBMS, Digital libraries and
Data Warehouses.
Information Retrieval System Capabilities: Search, Browse, Miscellaneous.
UNIT-II 16 Hrs
Cataloging and Indexing: Objectives, Indexing Process, Automatic Indexing, Information Extraction.
Data Structures: Introduction, Stemming Algorithms, Inverted file structures, N-gram data structure, PAT
data structure, Signature file structure, Hypertext data structure.
UNIT- III 15 Hrs
Automatic Indexing: Classes of automatic indexing, Statistical indexing, Natural language, Concept
indexing, Hypertext linkages
Document and Term Clustering: Introduction, Thesaurus generation, Item clustering, Hierarchy of
clusters.
UNIT IV 15 Hrs
User Search Techniques: Search statements and binding, Similarity measures and ranking, Relevance
feedback, Selective dissemination of information search, Searching the Internet and hypertext, Information
Visualization
Text Search Algorithms: Introduction, Software text search algorithms, Hardware text search systems.
Text Books:
1. Kowalski, Gerald, Mark T Maybury: Information Retrieval Systems: Theory and Implementation, Kluwer
Academic Press, 1997.
Reference Books:
1. Frakes, W.B., Ricardo Baeza-Yates: Information Retrieval Data Structures and Algorithms, Prentice Hall,
1992.
2. Modern Information Retrieval By Yates Pearson Education.
3. Information Storage & Retrieval By Robert Korfhage – John Wiley & Sons.
Department of Computer Science & Engineering
B.Tech- 8th
Semester
SYLLABUS
(Applicable for 2012-13 admitted batch)
Course Title: BIG DATA ANALYTICS Course Code: CSE 4424
L T P C
3 1 0 4
Course Objectives: The course content enables students to:
1. To introduce the fundamental concepts of BIG Data
2. To introduce various analytical techniques to crunch massive data
3. To have a knowhow about applications which uses Big Data
4. To know the Architectural components to handle Big Data.
5. To have a model to handle massive data using Hadoop Map Reduce.
Course Outcomes: At the end of the course students are able to:
1. Identify the need for big data analytics for a domain.
2. Apply big data analytics for a given problem.
3. Suggest areas to apply big data to increase business outcome.
4. Use Hadoop, Map Reduce Framework handle massive data
UNIT I 13 Hrs
Introduction to Big Data:
Analytics – Nuances of big data – Value – Issues – Case for Big data – Big data options Team challenge –
Big data sources – Acquisition – Nuts and Bolts of Big data. Features of Big Data -Security, Compliance,
auditing and protection - Evolution of Big data – Best Practices for Big data Analytics - Big data
characteristics - Volume, Veracity, Velocity, Variety.
UNIT II 15 Hrs
Applications of Big Data & Data Analysis:
Drivers for big data – Automation – Monetization- Applications of Big Data.- Social Media Command
Center-Product knowledge hub-infrastructure and knowledge hub-Product selection, Design and
Engineering- Location Based services- Online Advertizing- Improved Risk management. Analytic data sets –
Analytic methods –analytic tools – Cognos – Micro strategy - Pentaho.
UNIT-III 15 Hrs
Architectural components:
Massively Parallel Processing Platforms (MPP) - Unstructured data analytics and reporting-Context sensitive
and domain specific searches- categories and ontology-focus on specific time slice-big data and single view
of customer-Data privacy protection- Real time adaptive analytics and decision engine.
UNIT IV 17 Hrs
Hadoop Framework:
Big data implementation-Revolutionary, Evolutionary and Hybrid Approaches- Overview of Hadoop-
RDBMS (vs) HADOOP- IBM for Big Data – Map Reduce Framework and Architecture. Hadoop Distributed
file systems –Features of HDFS- Developing Map reduce – Analyzing big data with twitter.
Text Books:
1. Big Data Analytics: Disruptive Technologies for Changing the Game, Dr. Arvind Sathi, MC Press
online.
2. Hadoop: The Definitive Guide, Tom White, O'Reilly Media / Yahoo Press, 2012
Reference Books:
1. Bill Franks, “Taming the Big Data Tidal Wave: Finding Opportunities in Huge Data Streams with
Advanced Analytics”, Wiley and SAS Business Series, 2012.
2. Paul Zikopoulos, Chris Eaton, Paul Zikopoulos, “Understanding Big Data: Analytics for Enterprise Class
Hadoop and Streaming Data”, McGraw Hill, 2011.
Department of Computer Science & Engineering
B.Tech- 8th
Semester
SYLLABUS
(Applicable for 2012-13 admitted batch)
Course Title: BIO-INFORMATICS Course Code: CSE 4425
L T P C
3 1 0 4
Course Objectives: The course content enables students to:
1. Understand the theoretical basis behind bioinformatics.
2. Search databases accessible on the WWW for literature relating to molecular biology and biotechnology.
Retrieve protein structures from databases.
3. Find homologues, analyze sequences, construct and interpret evolutionary trees.
4. Understand homology modeling
Course Outcomes: At the end of the course students are able to:
1. Extract information from different types of bioinformatics data (gene, protein, disease, etc.), including
their biological characteristics and relationships
2. Analyze processed data with the support of analytical and visualization tools
3. Carry out bioinformatics research under advisement, including systems biology, structural bioinformatics
and proteomics
4. Manipulate DNA and protein sequences using stand-alone PC programs and programs available on the
WWW
UNIT –I 13 Hrs
Introduction:
Definitions, Sequencing, Biological sequence/structure, Genome Projects, Pattern recognition an prediction,
Folding problem, Sequence Analysis, Homology and Analogy.
Protein Information Resources:
Biological databases, Primary sequence databases, Protein Sequence databases, Secondary databases, Protein
pattern databases, and Structure classification databases.
Unit-II 15 Hrs
Genome Information Resources:
DNA sequence databases, specialized genomic resources
DNA Sequence analysis:
Importance of DNA analysis, Gene structure and DNA sequences, Features of DNA sequence analysis, EST
(Expressed Sequence Tag) searches, Gene hunting, Profile of a cell, EST analysis, Effects of EST data on
DNA databases
Unit-III 16 Hrs
Pair wise alignment techniques:
Database searching, Alphabets and complexity, Algorithm and programs, Comparing two sequences, sub-
sequences, Identity and similarity, The Dotplot, Local and global similarity, different alignment techniques,
Dynamic Programming, Pair wise database searching.
Multiple sequence alignment :
Definition and Goal, The consensus, computational complexity, Manual methods,
Simultaneous methods, Progressive methods, Databases of Multiple alignments and searching
Unit-IV 16 Hrs
Secondary database searching:
Importance and need of secondary database searches, secondary database structure and building a sequence
search protocol
Analysis packages:
Analysis package structure, commercial databases, commercial software, comprehensive packages, packages
specializing in DNA analysis, Intranet Packages, Internet Packages.
Text Books:
1. Introduction to Bioinformatics, by T K Attwood & D J Parry-Smith Addison Wesley Longman
2. Bioinformatics- A Beginner’s Guide by Jean-Michel Claveriw, Cerdric Notredame, WILEY dreamlech
India Pvt. Ltd
Reference Books:
1. Introduction to Bioinformatics by M.Lesk OXFORD publishers (Indian Edition)
Department of Computer Science & Engineering
B.Tech- 8th
Semester
SYLLABUS
(Applicable for 2012-13 admitted batch)
Course Title: E – COMMERCE Course Code: CSE 4426
L T P C
3 1 0 4
Course Objectives: The course content enables students to:
1. Acquaint with fundamental terms and concepts of e-commerce.
2. Compare and contrast the types of business models and e-commerce models
3. Analyze important strategic planning factors when implementing e-commerce initiatives.
4. Recommend appropriate technical resources for e-commerce projects.
Course Outcomes: At the end of the course students are able to:
1. Examine some typical distributed applications.
2. Detail some of the problems that are encountered when developing distributed applications.
3. Understand some of the technologies that are used to support distributed applications.
4. Illustrate some of the business models used in the internet.
UNIT - I 14 Hrs
Electronic Commerce-Frame work, anatomy of E-Commerce applications, E-Commerce Consumer
applications, E-Commerce organization applications.
Consumer Oriented Electronic commerce - Mercantile Process models.
UNIT - II 15 Hrs
Electronic payment systems - Digital Token-Based, Smart Cards, Credit Cards, Risks in Electronic Payment
systems.
Inter Organizational Commerce - EDI, EDI Implementation, Value added networks
UNIT - III 16 Hrs
Intra Organizational Commerce - work Flow, Automation Customization and internal
Commerce, Supply chain Management
Corporate Digital Library - Document Library, digital Document types, corporate Data Warehouses.
Advertising and Marketing - Information based marketing, Advertising on Internet, on-line marketing
process, market research.
UNIT-IV 15 Hrs
Consumer Search and Resource Discovery - Information search and Retrieval, Commerce
Catalogues, Information Filtering
Multimedia - key multimedia concepts, Digital Video and electronic Commerce, Desktop video processing,
Desktop video conferencing.
TEXT BOOK:
1. Frontiers of electronic commerce – Kalakata, Whinston, Pearson.
REFERENCES:
1. E-Commerce fundamentals and applications Hendry Chan, Raymond Lee, Tharam Dillon,
Ellizabeth Chang, John Wiley.
2. E-Commerce, S.Jaiswal – Galgotia.
Department of Computer Science & Engineering
B. Tech - 8th
Semester
SYLLABUS
(Applicable for 2012-13 admitted batch)
Course Title: OBJECT ORIENTED SOFTWARE ENGINEERING Course Code: CSE 4427
L T P C
3 1 0 4
Course Objectives: The course content enables students to:
1. Understand about software process models, planning, and estimation of projects.
2. Learn software project development CASE tools using object oriented design concept.
3. Know the projects under the requirement engineering process and use case models.
4. Study and experiment with alternative design models of the software development process.
Course Outcomes: At the end of the course students are able to:
1. Relate the object oriented methodology and implementation of software and the management of the
software project.
2. Apply the knowledge of object oriented design tools including use cases, UML, Java and the JDK.
3. Study and experiment with alternative models of the software development process from the
Prototyping method to dynamic modeling.
4. Practice the principles and techniques by developing a “real world” software system.
Unit I: 14 Hrs
Introduction to Classical software Engineering - Historical, Economic and Maintenance aspects.
Introduction to Object Oriented Paradigm. Different phases in structured paradigm and Objective Oriented
Paradigm. Software Process and different life cycle models and corresponding strengths and weaknesses.
Planning and Estimation -Estimation of Duration and Cost, COCOMO components of software. Project
Management plan.
Unit II: 15 Hrs
Tools for step wise refinement - Cost - Benefit analysis, Introduction to software metrics and CASE
tools. Taxonomy and scope of CASE tools. Introduction to testing, with focus on Utility, Reliability,
Robustness, Performance, Correctness.
Modules to objects-Cohesion and Coupling, Data Encapsulation and Information hiding aspects of objects.
Inheritance, polymorphism and Dynamic Binding aspects. Cohesion and coupling of objects. Reusability,
Portability and Interoperability aspects.
Unit III: 17 Hrs
Requirement phase - Rapid Prototyping method, Specification phase, Specification Document, Formal
methods of developing specification document, Examples of other semi - formal methods of using Finite-
State- Machines, Petri nets.
Analysis phase - Use case Modeling, Class Modeling, Dynamic Modeling.
Unit IV: 14 Hrs
Design phase - Formal techniques for detailed design.
IIM Phases - Implementation, Integration and maintenance phases.
Software Testing Tools: selenium, QTP, Winrunner, Silktest, LoadRunner
TEXT BOOKS:
1. Object oriented and Classical Software Engineering, 7/e, Stephen R. Schach, TMH
2. Object oriented and classical software Engineering, Timothy Lethbridge, Robert Laganiere, TMH
REFERENCE BOOKS:
1. Component-based software engineering: 7thinternational symposium, CBSE 2004, Ivica Crnkovic,
Springer
2. Software Testing Tools by Dr KVKK Prasad,dreamtech press
Department of Computer Science & Engineering
B. Tech- 8th
Semester
SYLLABUS
(Applicable for 2012-13 admitted batch)
Course Title: PATTERN RECOGNITION Course Code: CSE 4428
L T P C
3 1 0 4
Course Objectives: The course content enables students to:
1. Understand the possibilities and limitations of pattern recognition
2. Apply decision functions suitable for given problem
3. Validate different clustering algorithms
4. Learn Bayesian approach to pattern recognition
5. Analyze various dimensionality reduction techniques
Course Outcomes: At the end of the course students are able to:
1. Implement decision functions
2. Analyze tradeoffs involved in various classification techniques
3. Apply various dimensionality reduction methods whether through feature selection or feature
extraction
4. Develop model for solving problems in more specialized areas such as speech
5. Recognition, optical character recognition etc.,
UNIT – I 15 Hrs
Introduction:
Fundamental problems in pattern recognition system design, Design concepts and methodologies, Simple
pattern recognition model.
Decisions and Distance Functions:
Linear and generalized decision functions, Pattern space and weight space, Geometrical properties,
implementations of decision functions, Minimum-distance pattern classifications.
UNIT – II 20 Hrs
Statistical Pattern Recognition:
Bayes Decision Theory, Minimum Error and Minimum Risk Classifiers, Discriminate Function and Decision
Boundary ,Normal Density ,Discriminate Function for Discrete Features
Non Parametric Decision Making:
Histogram, kernel and window estimation, nearest neighbor classification techniques. Minimum squared
error discriminant functions, choosing a decision making techniques.
UNIT-III 12 Hrs
Hierarchical Clustering:
Introduction, agglomerative clustering algorithm, the single-linkage, complete-linkage and average-linkage
algorithm. Ward’s method Partition clustering-Forg’s algorithm, K-means’s algorithm, Iso data algorithm.
UNIT-IV 13 Hrs
Dimensionality Problem:
Dimension and Accuracy, Computational complexity, Dimensionality Reduction, Fisher Linear and Multiple
discriminant Analysis. Application of pattern recognition techniques in bio-metric, facial recognition, IRIS,
Finger prints, etc.,
Text Books:
1. Pattern recognition and Image Analysis, Gose. Johnsonbaugh Jost, PHI.
2. Pattern Recognition Principle, Tou. Rafael. Gonzalez, Pea.
Reference Books:
1. Bishop, C. M. Pattern Recognition and Machine Learning. Springer. 2007
2. Pattern Classification, Richard duda, Hart., David Strok, Wiley.