Structure & Syllabus of Master of Computer …Use multilevel Inheritance. 7.Virtual base class concept Write a c++ program for display the result of the student as a class student

Vishwakarma Institute of Technology Issue 01 : Rev No. 1 : Dt. 01/07/18

Structure and syllabus of First Year MCA.Pattern B-19, A.Y. 2019-20 Page 1 of 75

Bansilal Ramnath Agarwal Charitable Trust’s

Vishwakarma Institute of Technology (An Autonomous Institute affiliated to University of Pune)

Structure & Syllabus of

Master of Computer Application

Pattern ‘B-19’

Effective from Academic Year 2019-20

Prepared by: - Board of Studies in Information Technology

Approved by: - Academic Board, Vishwakarma Institute of Technology, Pune

Signed by

Chairman – BOS Chairman – Academic Board



Content

Sr. No. Title Page no.

1 Course Structure - Module III 5

2 Course Syllabi for Courses - Module III 6

2.1 IT8001 Optimization techniques 7

2.2 IT8002 C++ and Core Java Programming 9

2.3 IT8003 Computer Networks 12

2.4 IT8004 Software Engineering 14

2.5 IT8005 Python programming 17

2.6 IT8106 Design and Inovation-1 69

3 Course Structure - Module IV

i

19

4 Course Syllabi for Courses - Module IV 20

4.1 IT8008 Advanced Java Programming 21

4.2 IT8009 Design and Analysis of Algorithms 23

4.3 IT8013 Software Testing and quality assurance 25

4.4 Elective 2

4.5 IT8007 Quantitative Techniques 27


5 List of Electives-2

5.1 IT8012 Software Project Management 28

5.2 IT8014 Organizational Behavior 30

5.3 IT8015 Foundation of management 32

5.4 IT8016 User interface design 34

12

Course Structure - Module V

i

6 Course Structure - Module V

36



7 Course Syllabi for Courses - Module V 37

7.1 IT9001 Network and Information Security 38

7.2 IT9102 Data Science 39

7.3 Elective 3

7.4 Elective 4

7.6 IT9005

Mobile Application Development

42



8.1 IT9009 Big data applications 44

8.2 IT9013 Advanced Web technology 45

8.3 IT9010 Advanced data structures 47

8.4 IT9008 Natural Language processing 49

8.5 IT9011 Software design and architecture 51

8.6 IT9012 Artificial intelligence 53


9.1 IT9004 Internet of Things 55

9.2 IT9014 Robotics 57

9.3 IT9015 Cloud Computing 59

9.4 IT9016 GPU computing and applications 61

9.5 IT9018 Image processing 63

9.6 IT9019 Data acquisition system 65

10 Course Structure - Module VI

67

11 Course Syllabi for Courses - Module VI 68



Assessment Pattern for all engineering courses with lab

In Semester Assessment End Semester Assess-

ment

Assignment

(%)

Lab As-

sessment

(%)

Mid Se-

mester Ex-

am

(%)

Group

Discussion

/ Ppt

Viva/Lab

Exam

(%)

End Se-

mester Ex-

am

(%)

10 30 15 10 20 15

Hands on Theory

Viva/Lab

Exam

(%)

Lab As-

sessment

(%)

GD

/ Ppt

(%)

Mid Se-

mester

Exam

(%)

Assignment

(%)

End Se-

mester

Exam

(%)

20 30 10 15 10 15

Assessment pattern for Mathematics 3, Mathematics 4 - direct grade Entry.

In Semester Assessment (%)

VIVA End Semester

Exam

(%)

50

Mid Semester

Exam

Assignment 20 30

30 20



DU

LE

III

MO



MCA Structure with effect from Academic Year 2018-19

Module III

Title : Course Structure FF No. 653

Branch MCA Year:

SY

Academic

Year:201

9-20

B19

Subj

ect

No.

Subject

Code

Subject Name Teaching Scheme Examination Scheme Total Credits

Theo

ry

Lab CA MS

E

ESA

H

A

LA

B

GD

/PP

T

ES

E

VIV

A

S1 IT8001

Optimization

techniques 3 0

20 30 30 20 100 3

S2 IT8002

C++ and Core

Java Program-

ming

3 2 10 30 10 15 15 20 100 4

S3 IT8003 Computer Net-

works

3 2

10 30 10 15 15 20 100 4

S4 IT8004

Software Engi-

neering 3 2

10 30 10 15 15 20 100 4

S5 IT8005

Python pro-

gramming 1 2

30 10 2

DAI IT8106

Design and In-

novation-1 1 4

10 30 10 15 15 20 100 3

Total 20



FF No. : 654

IT8001: Optimization techniques

Credits: 03 Teaching Scheme: 3 Hours / Week

Section 1:

Essentials of Linear Programming Model, Properties of Linear Programming Model,

Formulation of Linear Programming, General Linear Programming Model, Maximization &

Minimization Models, Graphical Method for Solving Linear Programming problems,

Unbounded LP Problem, Additional Variables Used In Solving LPP, Maximization Case,

Minimization Problems, Big M Method, Degeneracy in LP Problems, Unbounded Solutions in

LPP, Multiple Solutions in LPP. PERT/CPM Network Components, Rules in Constructing a

Network, Scheduling of Activities: Earliest Time and Latest Time, Determination of Float and

Slack Times, Critical Path method for project management, Project Evaluation Review

Technique – PERT, Gantt chart( time chart). Terminology, Types of Sequencing Problems,

Algorithm for Solving Sequencing Problems, Processing n jobs through 2, 3, m machines.

Processing 2 jobs through m machines, Characteristics of Queuing Systems, Poisson and

Exponential Distributions, Symbols and Notations, Single server Queuing Model, Two servers

Queuing Model.

Section2:

General Mathematical model of transportation problem, The transportation algorithm, Method of

finding initial solution: North west corner method, Least cost method, Vogel’s Approximation

method, Test for optimality: MODI method, Variation in transportation problems, Terminologies

of game theory, Two-person-zero-sum-game, Game with pure strategy, Methods of solving game

with mixed strategy, Dominance Property, Graphical method for 2xn and mx2 games. Linear

Programming approach for games theory, Inventory Model Building, Single item deterministic

Model, Inventory Control Models: Purchase model with instantaneous replenishment without

shortages, Manufacturing Model without shortages, Purchase model with instantaneous

replenishment with shortages, Manufacturing Model with shortages.

Text Books:

1. Kanti Swarup, Gupta P.K., Man Mohan, “Operations Research”, 12th Edition; Sultan Chand

& Sons, New Dehli.

2. R. Panneerselvam,“Operations Research”, 2nd Edition, PHI Learning Private Ltd New Dehli.

Reference Books:

1. Billy E. Gillett, “A Computer – Oriented Algorithmic Approach”, 1979 Edition, Tata McGraw

- Hill Publications Company Ltd., New Dehli.

2. Hiller Lieberman, “Introduction to Operations Research”, 7th Edition; Tata McGrew-hill

publishing Company Ltd., New Dehli.

Course Outcomes:

The student will be able to –

1: Develop linear programming models to solve real life problems.

2: Solve linear programming problems by applying optimization techniques.



3: Develop an optimal schedule chart for a given project by applying project management

techniques such as PERT, CPM.

4: Design Optimal time table for processing resources such as jobs, equipment, people, material

etc

5: Device the best inventory model for an organization by using Inventory control model.

6: Design a mathematical model for decision making and identify the optimal strategies for

bidding (business deal) by using game theory.



FF No. : 654

IT8002: C++ and Core Java Programming


Lab: 2 Hours / Week

Section 1:

Introduction to Object Oriented Programming :Procedural Vs Object Oriented Programming,

Basics and Application of C++, Functions: Inline Function, Default Arguments , Const

Arguments, Function Overloading, Friend Function. Classes: C++ Program with class, Arrays of

Objects, Object as Function Arguments, Friendly Functions, Returning Objects, Constructor:

Parameterized Constructor, Multiple Constructor in a Class, Constructors with Default

Arguments, Dynamic Initialization of Objects, types of Constructor. Operator Overloading,

Overloading Unary and Binary Operator. Static Data Members and static member Functions,

Manipulating of String Using Operators, overloading operator using friend.

Inheritance in C++: Single Inheritance, Hierarchical Inheritance, Multiple Inheritance , Virtual

Base Classes, Abstract Classes, Constructor in Derived Classes, Nesting of Classes. Multilevel

Inheritance, Hybrid Inheritance., Nested Namespaces, Unnamed Namespaces, Namespace

Aliases.. Namespace: Introducing Namespaces, Referring to Members of a Namespace, The

using namespace Statement, Defining A Namespaces.

Exception handling, STL in C++ :The try Block, the catch Exception Handler, The throw

Statements, The try/throw/catch sequence, Exception Specification, Unexpected Exception,

Catch – All Exception Handlers, Throwing an exception from handler, Uncaught Exception

.Introduction to Standard Template Library, STL Programming Model, Sequence, Container

Adapter, Integrator, Algorithms, Predicates, Allocators.

Section2:

Advance concepts of C++:Template: Generic Function, A function with Two Generic Data

Types, Explicitly Overloading a Generic Function, Overloading a Function Template, Using

Standard Parameter with Template, Functions, Generic Function Restriction, Generic Sort,

Generic Classes, An Example with Two Generic Data Types, Using Non-Type Arguments with

Generic, Class, Using Default Arguments With Template New-Style Casts, Runtime Type

Information(RTTI). Dynamic_cast , Static_cast ,Reinterpret_cast, Const_cast.

Introduction to core java :Difference between Java and C language, difference between Java and

C++.Object Oriented concepts with respect to Java-Data abstraction, encapsulation, Class and

Object, inheritance, polymorphism, Java Programming – Data types, variables, operators, control

statements, Arrays, Programs based on class, methods, constructor, Inheritance, Interfaces,

Packages. Exception Handling – Exception types, try, catch, throw, throws, finally, creating own

exceptions.

JAVA I/O, APPLET & AWT: Java I/O classes and interfaces, File, Byte Streams, Character

Streams, File handling exercise, Applets specific methods & Related HTML references, Creating

an Applet, Displaying it using Web Browser and with appletwiewer.exe, Advantages and

Disadvantages of Applet Vs Application, Abstract Windows Toolkit- Components and Graphics,

Containers, Frames and Panels, Layout Managers- Border layout, Flow layout, Grid layout, Card

layout, AWT all components, Event delegation Model - Event source and handler, Event



categories, Listeners, Interfaces, Anonymous classes.

List of Practicals: (For THL, TLP courses)

1.Program for calculate area of square & other function to calculate area of circle

overload these two function. Function parameter accept from user (Use function

Overloading concepts ).

2.Use Dynamic initializations of object concept Write a class cString having following

•Data Abstraction

•Length of string (int)

•Base address of the string (char *)

Procedural Abstraction

•Default constructor, Parameterized constructor having char * parameter

•Copy constructor

•AcceptString()

•DisplayString()

•Destructor()

3Operator overloading-I Write a class Complex containing members as m_real and

m_imag. Overload binary +, binary -, unary -, ++ and – operators

4.Operator overloading-II Write a class cString and overload assignment ,insertion and

extraction operators for it.

5.Design a C ++ class string to overload < and > operator

6.Single Inheritance Derive class cWageEmployee from cEmployee. Multiple Inheritance

Derive class cWageEmployee , cManager from cEmployee .Create two derived classes

called test-containing marks of two subjects & other derived class called result calculates

result of the student. Use multilevel Inheritance.

7.Virtual base class concept Write a c++ program for display the result of the student as a

class student accept roll no of the student, class test accept marks of the two subjects, in

class sports accept student’s sports marks. All the information of the above classes

display in the result class. Use virtual base class concept.Pure virtual base class Write a

c++ program for calculate area of circle & rectangle. Create class shape & two other

classes circle & rect. Use pure virtual class function concept

8.Program for unstructured Exception:

•divide by zero

•Array index out of bounds exception

•Null pointer Exception

•Using structured exception handlings catch these exceptions.

9.Template function & Namespace Write program for bubble sort using template and

namespace.Template class Write program for linked stack using template.

10.Display area and volume of different shapes( Use class, object, constructor,

overloading)using java

11.Display bank account information( Use interface and inheritance using java)

12.Read content of one file and write it into other file.

13.Display student mark sheet ( Use package in java)

14.Write a program to illustrate following exceptions

a) ArithmeticException b) ArrayIndexOutOfBoundsException

c) NullPointerException d) IllegalAccessException

15.Create one form to read student information( Use applet, layout managers and all

possible controls)



16.Write a program to illustrate card layout manager.

List of project areas :

The objective of this mini project is to understand practical applications of Object

oriented programming. Student will select individually a technical project using c++ or

core java. The students will be assessed based on demonstration.

Text Books:

1.Herbert Schildt, C++: The Complete Reference, Fourth Edition, Tata McGraw-Hill,

2003. ISBN 0-07-053246-X.

2.“Java 2 Complete Reference”, Patric Naughton, Herbert Schildt ISBN-0070495432.

Reference Books :

1.Robert Lafore, Object Oriented Programming in C++, Fourth Edition, Tech Media,

2002. ISBN 0-672-32308-7.

2.Core Java 2 Volume – I, Cay S Horstmann, Fary Cornell ,ISBN-0130894680.

3.E.Balguruswami , Programming with Java, A Primer, ISBN-0070617139.

4.Dustine R Callway , Inside Servlets, ISBN-9788131715451.

5.Core Java 2 Volume – II, Cay S Horstmann, Fary Cornell ,ISBN-0131118269.

Course Outcomes:

Upon completion of the course, post graduates will be able-

1.To implement polymorphism using c++.

2.To Apply the concepts of data encapsulation , inheritance, and polymorphism using

c++.

3.To incorporate exception handling in object-oriented programs.

4.Understand advanced concepts like template classes and RTTI .

5.To design a computer program to solve real world problems using java based on object-

oriented principles.

6.Develop Java based solution for real world problem.



FF No. : 654

IT8003: Computer Networks


Lab: 2 Hours / Week

Section 1: Topics/Contents

Modulation techniques: Principle of amplitude modulation, modulation index and percentage of

modulation, Single sideband communication, ISB modulation, frequency modulation principle,

phase modulation, AM vs FM, pulse code modulation, delta modulation, Multiplexing:

Introduction, FDM, TDM, WDM, Transmission media: guided, unguided Reference Models:

OSI and TCP/IP, Mathematical derivation for amplitude and frequency modulation, Design

Issues, Error Detection and correction, CRC, Examples on Checksum, Stop-and- Wait protocol,

Sliding Window protocols, HDLC, Point-to-Point-Access (PPP): Frame format, Transition states,

PPP Stack: LCP, NCP, Channel allocation: Static and Dynamic allocation, Multiple Access

Protocols: ALOHA, CSMA, Collision-free and limited- contention protocols, WDMA, Ethernet:

Cabling, MAC sub-layer protocol, Logical link control, Wireless LAN, Broad band wireless,

Bl,uetooth, . SLIP, SONET, MPLS, Switched, fast and Gigabit Ethernet, network device, Design

Issues, Packet switching, Connectionless and Connection-oriented Services, Virtual Circuit and

Datagram Subnets, IP addressing, Class-full, CIDR, Sub-netting, super-netting, IP protocol, ARP,

RARP protocol, Shortest path and widest path Routing algorithms: Bellman-Ford algorithm,

Dijkstras algorithm.

Section2: Topics/Contents

Distance vector routing, link state routing, routing loops, Counting to infinity problem, split

horizon, routing protocols, RIP, OSPF, BGP, IPv4, IPv6, ICMP, IGMP, Mobile IP, DHCP, Router

architecture, IP packet format, Multicast and broadcast routing, Congestion Control and QOS:

General Principles, Congestion prevention policies, Load shading, Jitter Control, Quality of

Service, Services and service primitives, Elements of Transport protocol: Addressing,

Connection establishment and release, flow control and buffering, Multiplexing, Crash recovery,

UDP: Introduction, TCP: Introduction, Model, protocol, header, connection establishment and

release, connection management, Transmission policy, congestion control, timer management,

RPC, Introduction to wireless TCP and UDP, Socket programming, Domain Name System

(DNS) and DNS servers, Electronic Mail: Architecture and services, MIME, SMTP, Mail

Gateways, Remote login, File Transfer Protocol. World Wide Web: Introduction, Architectural

overview, static and dynamic web pages, HTTP, LDAP, Browser Architecture, SNMP, wireless

web


1. Simulation of CRC.

2. Simulation of Checksum.

3. Implement stop & wait sliding window protocol.

4. Implement Go-Back-N sliding window protocol.

5. Implement selective repeat sliding window protocol.

6. Socket Programming using TCP.

7. Socket Programming using UDP.

8. Implement Dijkstra’s Shortest path routing algorithm.



9. Study any protocol analyzer software (eg. Wireshark) to learn and use its important features,

Study of network monitoring software like ETHREAL software. Assignment to examine TCP/IP

and non-TCP/IP protocols (IPX/SPX) and capture them using protocol analyzer Software.

10. Study of existing LAN and understand the design and various components. Set up a small

network of 3 to 4 computers and Hub/Switch as directed by the instructor. Use LAN Card, UTP

Cables and Connectors. Install LAN Cards and Crimp the connectors.

Text Books: (As per IEEE format)

1. Tanenbaum A. S., “Computer Networks”, 4th Edition, Pearson Education, ISBN 81 –

7808 – 785 – 5

2. Forouzan B. A, “Data Communications and Networking”, 4th edition, Tata McGraw- Hill

Publications, 2006, ISBN 0 – 07 – 063414 – 9

Reference Books: (As per IEEE format)

1. James F. Kurose, “Computer Networking- a top-down approach featuring the internet” ,

2nd Edition, Person Education, ISBN 81- 7808-787-1.

2. Comer D., “Computer Networks and Internet”, 2ND Edition, Pearson Education, ISBN

81 – 7808 – 086 – 9

Course Outcomes:


1. Estimate reliability issues based on error control, flow control and pipelining by using

bandwidth, latency, throughput and efficiency.

2. Build Design mechanisms to demonstrate LAN behavior utilizing network architecture,

protocols, and network components.

3. Analyze data flow between peer to peer in an IP network using Application, Transport

and Network Layer Protocols.

4. Illustrate applications of Computer Network capabilities, selection and usage for various

sectors of user community.

5. Demonstrate sustainable engineering practice indicating the scientific purpose and utility

of communication frameworks and standards.

6. Develop Client-Server architectures and prototypes by the means of correct standards and

technology.



FF No. : 654

IT8004: Software Engineering

Credits: 4 Teaching Scheme: 3 Hours/Week

Lab: 2 Hours / Week


Section I

INTRODUCTION TO SOFTWARE ENGINEERING

Nature of Software, Software Process, Software Engineering Practice, Software Myths, Generic

Process model, Analysis and comparison of Process Models: Waterfall Model, Incremental

Models, Evolutionary Models, Concurrent, Specialized Process Models, Personal and Team

Process Models, Introduction to Clean Room Software Engineering.

Software Quality Assurance (SQA): Verification and Validation, SQA Plans, Software Quality

Frameworks, ISO 9000 Models, CMM Models.

REQUIREMENT ANALYSIS Requirements Capturing: requirements engineering (elicitation,

specification, validation, negotiation, prioritizing requirements (Kano diagram) - real life

application case study. Requirements Analysis: basics, scenario based modeling, UML models:

use case diagram and class diagram, data modeling, data and control flow model, behavioral

modeling using state diagrams - real life application case study, software Requirement

Specification.

PROJECT PLANNING Project initiation, Planning Scope Management, Creating the Work

Breakdown Structure, Effort estimation and scheduling: Importance of Project Schedules,

Estimating Activity Resources, Estimating Activity Durations, Developing the Schedule using

Gantt Charts, Adding Milestones to Gantt Charts, Using Tracking Gantt Charts to Compare

Planned and Actual Dates, Critical Path Method, Program Evaluation and Review Technique

(PERT) with examples. Planning Cost Management, Estimating Costs, Types of Cost Estimates,

Cost Estimation Tools and Techniques, Typical Problems with IT Cost Estimates.

AGILE DEVELOPMENT PROCESS Agile Development: Agile manifesto, agility and cost of

change, agility principles, myth of planned development, toolset for the agile process. Extreme

Programming: XP values, process, industrial XP, SCRUM - process flow, scrum roles, scrum

cycle description, product backlog, sprint planning meeting, sprint backlog, sprint execution,

daily scrum meeting, maintaining sprint backlog and burn-down chart, sprint review and

retrospective. Agile Practices: test driven development, refactoring, pair programming,

continuous integration, exploratory testing versus scripted.Devops,Jenkins

Section II

PROJECT MANAGEMENT Project monitoring and control: tools for project management,

Software tools like Microsoft project management or any other open source tools. The

Importance of Project Quality Management: Planning Quality Management, Performing Quality

Assurance, Controlling Quality, Tools and Techniques for Quality Control (statistical control, six

sigma) The Importance of Project Risk Management, Planning Risk Management, Common

Sources of Risk in IT Projects.

RECENT TRENDS IN SOFTWARE ENGINEERING AND PROJECT MANAGEMENT



Software configuration management: SCM basics, SCM repository, SCM process, SCM tools

such as GitHub, CASE – taxonomy, tool-kits, workbenches, environments, components of

CASE, categories (upper, lower and integrated CASE tools). Emerging software engineering

trends: technology evolution, process trends, collaborative development, test-driven

development, global software development challenges Project Management trends: CRM, ERP:

Basic concepts, Advantages and limitations, SAP, Business process reengineering, International

Project Management, Case studies

SOFTWARE TESTING

Testing Concepts: Purpose of Software Testing, Testing Principles, Goals of Testing, Testing

aspects: Requirements, Test Scenarios, Test cases, Test scripts/procedures, Strategies for

Software Testing, Testing Activities, Mistakes, Faults & Failures, Planning Verification and

Validation, Software Inspections, Automated Static Analysis, Verification and Formal Methods,

Levels of Testing

White-Box Testing: Test Adequacy Criteria, Static Testing, Structural Testing, Code Complexity

Testing, Mutation Testing, Data Flow Testing

Black-Box Testing: Test Case Design Criteria, Requirement Based Testing, Positive and

Negative Testing, Boundary Value Analysis, Equivalence Partitioning State Based Testing,

Domain Testing

I List of Practical:

1. Study of different object oriented Methodologies and MDA and MOF

2. Problem Analysis and Project Planning -Thorough study of the problem – Identify Project

scope, Objectives and Infrastructure.

3. Software Requirement Analysis – Describe the individual Phases/modules of the project

and Identify deliverables. Identify functional and non-functional requirements.

4. Data Modeling – Use work products – data dictionary.

5. Software Designing – Develop use case diagrams and activity diagrams, build and

test class diagrams, sequence diagrams and add interface to class diagrams.

6. Prototype model – Develop the prototype of the product.

7. Introduction and use of github.

8. To perform various testing using the testing tool unit testing, integration testing for a

sample code of the suggested system.

9. Perform Estimation of effort using FP Estimation for chosen system.

10. To Prepare time line chart/Gantt Chart/PERT Chart for selected software project and

modern project management tools like JIRA.

11. Introduction to selenium and a toy project on it.

Project:

Students will select individually a technical project based on any area. Students need to complete

following phases to the selected project.

Phase 1. To narrate Requirement Definition Document for the target system with following areas:

- Problem Identification

- Problem Statement

- Proposed Solution

- Benefits



Phase 2. To narrate System Requirements Specification Document for target system with

reference to the IEEE 610.12.1990 std guidelines. The requirements collected need to fall into

Functional, Nonfunctional, Pseudo and inverse requirements categories. The User and

Stakeholder identification must be made.

Phase 3. To perform feasibility study and develop a project plan.

Phase 4. To develop analysis model of the target system by Context level DFD accompanied by

Problem decomposition and Data Store indicators. It is expected that up to Level 3 DFD analysis

must be included.

Phase 5. To develop design model of the target system by identifying the First cut program

structure. The modules identified need to bear processing narrative.

Phase 6. To implement the target system by selecting suitable programming language with well-

formed program structure.

Text Books:

1. “Software Engineering”, Ian Somerville Addison-Wesley, 7 th Edition, 2004. “Software En-

gineering: A Practitioner's Approach”, Roger S Pressman, McGraw Hill, 6/e,2005.

2. Software Engineering: A Practitioner's Approach, Roger S Pressman , 6/e, McGraw Hill,

ISBN: 0072853182,2005

Reference Books:

1. “Metrics and Models in Software Quality Engineering”, Stephen H. Kan Pearson Education.

Course Outcomes:


1. Compare different types of software models.

2. Collect requiems using different techniques and write SRS.

3. Analyze requirements and draw UML diagrams.

4. Describe various design approaches.

5. Write metric for the different levels and parts of software and identify maintenance strate-

gies.

6. Anticipate the software risks and suggest risk mitigation plan and summarize current trends

in software engineering.


Structure and syllabus of First Year MCA .Pattern B-19, A.Y. 2019-20 Page 17 of 75

FF No. : 654

IT8005: Python Programming

Credits: 2 Teaching Scheme:1Hours / Week

Lab: 2 Hours / Week

Section 1:

Introduction To Python Installation and Working with Python Understanding Python variables

Python basic Operators Understanding python blocks

Python Data Types Declaring and using Numeric data types: int, float, complex Using string

data type and string operations Defining list and list slicing Use of Tuple data type Python

Program Flow Control Conditional blocks using if, else and elif Simple for loops in python For

loop using ranges, string, list and dictionaries Use of while loops in python Loop manipulation

using pass, continue, break and else Programming using Python conditional and loops block

Section2:

Python Functions, Modules And Packages Organizing python codes using functions Organizing

python projects into modules Importing own module as well as external modules Understanding

Packages Powerful Lamda function in python Programming using functions, modules and

external packages

Python String, List And Dictionary Manipulations Building blocks of python programs

Understanding string in build methods List manipulation using in build methods Dictionary

manipulation Programming using string, list and dictionary in build functions Python File

Operation Reading config files in python Writing log files in python Understanding read

functions, read(), readline() and readlines() Understanding write functions, write() and

writelines() Manipulating file pointer using seek Programming using file operations


1. Python Program for factorial of a number

2. Python Program to find largest element in an array

3. Python program to find second largest number in a list

4. Generating random strings until a given string is generated

5. Program to create grade calculator in Python

6. Reverse each tuple in a list of tuples

7. Develop programs to learn concept of functions scoping, recursion and list mutability. 4.

Develop programs to understand working of exception handling and assertions.

8. Develop programs for data structure algorithms using python – searching, sorting and

hash tables.

9. Learn to plot different types of graphs using PyPlot.

10. Implement classical ciphers using python.

11. Develop chat room application using multithreading.

12. Demonstrate GUI Programming .

List of Projects:

1. Password Generator

2. Stop Watch

https://www.geeksforgeeks.org/python-program-for-factorial-of-a-number/

https://www.geeksforgeeks.org/python-program-to-find-largest-element-in-an-array/

https://www.geeksforgeeks.org/python-program-to-find-second-largest-number-in-a-list/

https://www.geeksforgeeks.org/python-program-match-string-random-strings-length/

https://www.geeksforgeeks.org/program-create-grade-calculator-in-python/

https://www.geeksforgeeks.org/python-reverse-each-tuple-in-a-list-of-tuples/



3. Shop Billing System

4. Notepad

5. Contact Management

6. Hotel Management

7. Web Scrapping of any website like BookMyShow

8. Game (Rock, Paper, Ceaser)

9. Tik Tak Toi Game

10. Music Player

11. Dice Rolling Simulator

12. Currency converter app using python

List of Project areas: (For THP, TLP courses)

1. Dice Rolling Simulator

2. Guess the Number

3. Text Based Adventure Game

4. Hangman


1. John V Guttag. “Introduction to Computation and Programming Using Python”, Prentice Hall

of India

2. R. Nageswara Rao, “Core Python Programming”, dreamtech

3. Wesley J. Chun. “Core Python Programming - Second Edition”, Prentice Hall

4. Michael T. Goodrich, Roberto Tamassia, Michael H. Goldwasser, “Data Structures and

Algorithms in Pyhon”, Wiley

5. Kenneth A. Lambert, “Fundamentals of Python – First Programs”, CENGAGE Publication

6. Luke Sneeringer, “Professional Python”, Wrox

7. “Hacking Secret Ciphers with Python”, Al Sweigart,

URLhttps://inventwithpython.com/hacking/chapters

Course Outcomes:


1. To develop proficiency in creating based applications using the Python Programming

Language.

2. To be able to understand the various data structures available in Python programming

language and apply them in solving computational problems.

3. To be able to do testing and debugging of code written in Python.

4. To be able to draw various kinds of plots using PyLab.

5. To be able to do text filtering with regular expressions in Python Plotting using



MO

DU

LE

IV




Module VI


Branch MCA Year:

SY

Academic

Year:201

9-20

B19

Subj

ect

No.

Subject

Code


Theo

ry

Lab CA MS

E

ESA

H

A

LA

B

GD

/PP

T

ES

E

VIV

A

S1 IT8008

Advanced Java

Programming 3 4

10 30 10 15 15 20 100 5

S2 IT8009

Design and

Analysis of Al-

gorithms

3 2 10 30 10 15 15 20 100 4

S3 IT8108

Object Oriented

modelling &

Design

2 2

10 30 10 15 15 20 100 3

OE2

IT8012

Software Pro-

ject Manage-

ment

3 20 30 30 20 100 3

IT8014

Organizational

Behaviour 3

20 30 30 20 100

IT8015

Foundation of

Management 3

20 30 30 20 100

IT8016

User Interface

Design 3

20 30 30 20 100

IT8013

Software Test-

ing and Quality

Assurance

3 20 30 30 20 100

S5 IT8005

Quantitative

Techniques 2 2

10 30 10 15 15 20 100 3

DAI IT8111

Design and In-

novation-2 1 4

10 30 10 15 15 20 100 3

Total 21



FF No. : 654

IT8008: Advanced Java Programming

Credits: 5 Teaching Scheme:-Theory: 3 Hours / Week

Lab: 4 Hours / Week

Section 1: Swing Controls, JDBC, Multithreading & Java Collection

Swing controls, JPanel, JButton, JCheckbox, JCombobox, Jlist, JMenu,JradioButton, Slider,

JTextFIeld, JPasswordField, JFIleChooser, JTable, JTextArea, JTree, JLabel, JApplet,

JDialog, JFrame, JScrollPane, JTabbedPane, Event Handling , Java database connectivity, Types

of JDBC drivers, Writing first JDBC applications, Types of statement objects(Statement,

PreparedStatement and CallableStatement), Types of resultset , ResultSetMetadata, Inserting and

updating records, JDBC and Swing, Multithreading - Multithreading concepts, Thread Life

cycle, creating multithreaded application, Thread priorities, Thread synchronization, Interthread

Communication, Deadlock , Java Collection

Section2: Servlet , JSP & Hibernate

Introduction to servlets, Servlet API, Structure of web application, Creating web

application, Servlet interface, Generic Servlet, javax.servlet.http package, HTTPServlet,

HTTPServletRequest, HTTPServletResponse, Init Parameters, Session Management,

Cookies, Web security,, Introduction to JSP, JSP API, JSP life cycle, JSP scopes, JSP Tags,

Custom Tags, JSP directives, JSP implicit objects, JSP action elements, MVC in JSP ,

Introduction to groovy, Installation, Hibernate, NoSQL, Controllers


1. Design a java application to demonstrate file handling in Java.

2. Design a java application to demonstrate GUI using Swing.

3. Design a java application to demonstrate event handling using Java IDE.

4. Create an Application to display the table of different numbers using multithreading.

5. Create an Application to display even and odd numbers till number X input by user,

6. Using multithreading.

7. Implement Producer Consumer Problem using multithreading.

8. Design a java application to demonstrate use of ArrayList Collections.

9. Design a java application to demonstrate use of Hash map Collections.

10. Design a client-server application demonstrating the use of Java I/O using sockets with

11. GUI for configurations.

12. Design a java application using Grails and Groovy

13. Design a java application to demonstrate use of JSP/Servlet using database.

14. Develop a java application using hibernate.


1. eLibrary

2. Mall Guiding System

3. Educational Portal based System



4. Retail Shop Stock Management

5. Online Mobile Shop Management System

6. Online Student Performance Monitoring System

7. Online Movie Ticket Booking System

8. Online Student Feedback System

9. Online vegetable shopping system

10. Online faculty record keeping system

11. Online Food Shopping System

12. Online Property Enquiry System

Text Books:

1. Advanced Java 2: development for enterprise applications”, Clifford J. Berg, Sun ISBN:

0130848751, Microsystems Press, 2000.

2. “Advanced Java networking”, Dick Steflik, PrashantSridharan, ISBN: 0130844667, Prentice

Hall PTR, 2000.

Reference Books:

1.“Java: The Complete Reference”, , Herbert Schildt, McGraw Hill Publication, Seventh

Edition, ISBN: 007063677X, 2006.

2. “Java generics and collections”, Thomas Powell, O'Reilly Media, ISBN: 0596527756, 2006

3. “Java EE 7” for Beginners, Sharanam shah, Vaishali shah, SPD, ISBN: 13:978-93-5110-349-

Course Outcomes:


1. Analyze the nature of a problem to select appropriate advanced featureof Java towards

achieving at a problematic solution.

2. Develop Java based solution for real world problem.

3. Employ Integrated Development Environment (IDE) for implementing and testing of

software solution.

4. Work in well-formed teams with proper skill sets to achieve effective solutions.

5. Extend their knowledge in utilizing the appropriate advanced features of Java for using

emerging frameworks.

6. Construct software solutions by evaluating alternate architectural patterns.



FF No. : 654

IT8009: Design Analysis and Algorithm

Credits: 03 Teaching Scheme:-Theory:3 Hours / Week

Section 1:

Introduction To Analysis of Algorithm:Algorithm, analysis, Characteristics of an Algorithm, time

complexity and space complexity, Well Known Asymptotic Functions & Notations, Big O-

notation, Omega notation and theta notation, Sets and disjoint set, union and find algorithms,

Heaps. Sorting in linear time. Divide and Conquer:General Strategy, Exponentiation. ,Strassen’s

matrix multiplication. Convex hull, closest pair finding. Divide and conquer binary search, heap

sort, quick sort and merge sort, finding the median. Greedy Method:General Strategy,

Formalization of Greedy Technique, Knapsack problem, Job sequencing with Deadlines, Optimal

merge patterns, Minimal Spanning Trees Prim’s and Kruskal Algorithm and Dijkstra’s algorithm.

Section2:

Dynamic Programming: General Strategy, The Principle of Optimality, Multistage graphs,

OBST, 0/1 Knapsack, Traveling Salesperson Problem, Make change Problem. Dynamic

Programming: Flow Shop Scheduling, Chained Matrix Multiplication.

Backtracking And Branch And Bound:Backtracking: General Strategy, 8 Queen’s problem,

Graph Coloring, Hamiltonian Cycles, 0/1 Knapsack, sum of subset. Branch and Bound: General

Strategy, 0/1 Knapsack, Traveling Salesperson Problem , recourse allocation problem, Tile

Problem, Maze Problem.

NP hard and NP-Complete Problems :Basic concepts, non-deterministics algorithms: sorting,

,NP-HARD and NP-COMPLETE classes, COOKS theorem.

Introduction to parallel algoriyhms, Parallel sorting


1. Quick Sort/ Merge Sort implementations using divide and conquer approach.

Time complexity measure is to be obtained.

2. Minimal spanning Trees/ Job scheduling as an example of Greedy approach

3. Finding shortest path for multistage graph problem. (single source shortest path

and all pairs shortest path.)

4. 0/1 knapsack's problem using Greedy approach.

5. 0/1 knapsack's problem using Dynamic Programming/Branch & Bound

Strategies.

6. n-Queen problem using general backtracking method .

7. Algorithm implementation for `Traveling salesman' problem using Dynamic

programming approach.

8. Find a subset of a given set S = {s1,s2,.....,sn} of n positive integers . whose sum

is equal to a given positive integer d. For example, if S={1, 2, 5, 6, 8} and d = 9 there are

two solutions {1,2,6} and {1,8}.A suitable message is to be displayed if the given

problem instance doesn't have a solution.



Text Books

1. Horowitz/Sahani, “Fundamentals of Computer Algorithms”, Galgotia Publication.

2006

2. Sanjay Dasgupta,Chirostos Padadiminitriou, Umesh Vazirani “Algorithms” ,Tata

Mcgraw Hill, 2006

Reference Books

1. Bressard, “Fundamental of Algorithm.” PHI

2. Thomas H Cormen and Charles E.L Leiserson, “Introduction to Algorithm” PHI .

3. Aho And J.D. Ullman, “Design and Analysis of Algorithms”, Addison Wesley .

Course Outcomes:

Upon completion of the course, post graduates will be able to -

1. Analyze asymptotic time and space complexity of an algorithm for worst, average and

best cases using suitable mathematical tools.

2. Derive and solve recurrences describing the performance of divide and conquer

algorithms.

3. Synthesize and analyze greedy algorithms.

4. Describe the dynamic-programming paradigm and explain when an algorithmic design

situation calls for it.

5. Use backtracking and branch and bound technique for solving problems.

6. Differentiate polynomial and nonpolynomial problems.



FF No. : 654

IT8013: Software Testing and quality assurance


Lab:2 Hours/Week


Principles of Testing :Testing Concepts: Purpose of Software Testing, Testing Principles, Goals

of Testing, Testing aspects: Requirements, Test Scenarios, Test cases, Test scripts/procedures,

Strategies for Software Testing, Testing Activities, Mistakes, Faults & Failures, Planning

Verification and Validation, Software Inspections, Automated Static Analysis, Verification and

Formal Methods, Test Plan, White Box and Black Box Testing :White-Box Testing: Test

Adequacy Criteria, Static Testing, Structural Testing, Code Complexity Testing, Mutation

Testing, Data Flow Testing, Black-Box Testing: Test Case Design Criteria, Requirement Based

Testing, Positive and Negative Testing, Boundary Value Analysis, Equivalence Partitioning State

Based Testing, Domain Testing, Functional Testing :Test Plan, Test Management, Test Execution

and Reporting, Test Specialist Skills, Tester’s Workbench and Tool Categories, Test Maturity

Model and Test Process Assessment, Debugging & Root Cause Analysis, Software Items,

Component & Units, Test Bed, Traceability and Testability, Attributes of Testable Requirements,

Test Matrix, Benefits of Formal Test Documentation, Types of Testing Documentation,

Verification Testing, Validation Testing, Integration Testing, System and Acceptance Testing,

GUI Testing, , Regression Testing


Static & Dynamic Testing :Software Defects: Origins of Defects, Defect Classes, Defect

Repository / Test Design, Developer/Tester Support for Defect Repository, Need for Testing ,

Static Testing Techniques : Review types: Informal Review, Technical or peer review,

Walkthrough and Review Meeting , Review Reporting & Record keeping, Review guidelines,

Data flow analysis, Control flow analysis, Cyclometric Analysis

Higher Order Testing :Specification Based Testing, Performance Testing, Ad-hoc Testing,

Usability and Accessibility Testing, Risk-based Testing, Exploratory Testing, Scenario-based

Testing, Random Testing Compatibility Testing, User Documentation Testing, Client –Server

System Testing, RAD Testing, Configuration Testing, Testing internal Controls, Multiplatform

Environment Testing, Security Testing, Web-based System Testing, Testing VS Test Automation,

Tool evaluation and selection, Automation team roles,

Architectures, Planning and implementing test automation process

Standards and Documents :IEEE Standards Related to Testing, ISO 12207 & IEEE/EIA

Std12207on Testing, ISO 9000:2000 on Testing, ISO 9003, IEEE Std 1012, IEEE Std 1028, ISO

IEC 29119, IEEE 829 test documentation,

Text Books:

1. Fenton, Pfleeger, “Software Metrics: A Rigourous and practical Approach”, Thomson

Brooks/Cole, ISBN 981-240-385-X.



2. Desikan, Ramesh, “Software Testing: principles and Practices”, Pearson Education, ISBN

81-7758-121-X.

Reference Books :

1. Burnstein, “Practical Software Testing”, Springer International Edition, ISBN 81-8128-

089-X

2. William E. Perry, “ Effective Methods for Software Testing”, John Wiley and Sons, ISBN

9971-51-345-5

3. Yogesh Singh, ”Software Testing”, Cambridge University Press, ISBN 978-1-107-01296-

7

4. Nina Godbole, “Software Quality Assurance: Principles And Practice”,Alpha Science In-

ternational, Ltd (August 1, 2004) ISBN-10: 1842651765 ISBN-13: 978-1842651766

5. Ronald Radice, “Software Inspections”, Tata McGraw Hill, ISBN 0-07-048340-X

6. Capers Jones,” Software Assessments, Benchmarks, and Best Practices” ,Burlington,

Vermont Publisher: Addison-Wesley Professional 2000 ISBN-10: 0201485427 ,ISBN-

13: 9780201485424

Course Outcomes:


1. To understand Software Measurement Theory and Software Test Automation

2. To practice Software Testing Techniques and Strategies

3. Understand the fundamental concepts, approaches, and methodologies in software quality

management and assurance.

4. Understand the framework and general approach of several Quality System Standards and

Total Quality Management (TQM).



FF No. : 654

IT8007: Quantitative Techniques


Lab: 2 Hours / Week

Section 1:

Numbers, Average, Problem on ages, Problems on numbers, Logarithms, Surds and Indices, HCF

and LCM of Numbers. Time and distance, Problems on trains, Boats and Streams, Time and

Work , Pipes and Cisterns, Alligation or mixture. Percentage, Profit and loss, Ratio and

Proportion, Simple interest, Compound interest, Partnership, Chain Rule.

Section2:

Race and Games , Odd Man Out and Series, Number Series, Analogies, Logical Problems, Letter

and Symbol Series, Statement and Conclusion, Artificial Language. Area, Volume and Surface

Areas, Calendar, Clocks, Permutations and Combinations, Probability, Heights and Distances.

Tabulations: Tabulations of Imports and Exports of Data, Analysis of Tabulated Data, Bar

Graphs: Vertical or Horizontal Bars, Pie Charts: Pie Graphs, Central angle, Line Graphs.

Text Books:

1. Dr. R. S. Aggarwal, Quantitative Aptitude For Competitive Examinations”,twelth edition, S.

Chand.

2. Arun Sharma, “How to Prepare for Quantitative Aptitude”; fifth edition; Tata Mcgraw-Hill.

Reference Books:

1. Abhijit Guha, “Quantitative Aptitude for Competitive Examinations”, Fourth Quarter.

2. K. Sarvesh Verma ; Quantitative Aptitude Quantum Cat Common Admission Test”, Third

Edition; Arihant.

Course Outcomes:


1. Qualify all the company aptitude Test for placement.

2. Clear Most of the Banking test based on Quantitative aptitude and Reasoning.

3. Qualify most of the exam based on Quantitative aptitude and Reasoning like railways, public

services, etc.

4. Qualify the exam for higher study like GRE, GMAT.

5. Qualify the exam for higher study like NDA, CDS.

6. Develop overall aptitude ability.

http://www.indiabix.com/aptitude/odd-man-out-and-series/

http://www.indiabix.com/logical-reasoning/number-series/

http://www.indiabix.com/logical-reasoning/analogies/

http://www.indiabix.com/logical-reasoning/logical-problems/

http://www.indiabix.com/logical-reasoning/letter-and-symbol-series/

http://www.indiabix.com/logical-reasoning/letter-and-symbol-series/

http://www.indiabix.com/logical-reasoning/statement-and-conclusion/

http://www.indiabix.com/logical-reasoning/artificial-language/



FF No. : 654

IT8012: Software Project Management


Lab:2 Hours/Week


Project Management :What are “projects”? Why project management? The project life

cycle, Key stakeholders, Project management process groups , Project manager responsibilities ,

Understanding the role of senior management , Needs assessment , Project selection :

Benefit/cost ratio, Present value and net present value, Building SMART objectives, Project

charters, Project requirements document , Scope planning, The work breakdown structure

Risk Management Definition and characteristics of “risk”, Elements and factors of risk,

Types of risk, Components of risk management, Risk management planning, Risk identification,

Analysis Fundamentals, Prioritizing Risk, Risk-based financial tools and techniques , Expected-

value analysis, Decision trees, Planning For Risk, Risk documentation.

Cost Control and Scheduling :Using estimates for scheduling and cost control, The basic

rules of estimating, Levels of estimating and estimate types , Estimation methodologies, Time-

controlled estimates, Resource-limited estimates, Scheduling: Network scheduling, Validating

schedules, Arrow diagrams and precedence diagrams, Basic scheduling and network

calculations, Advanced precedence relationships and the critical path, Alternative constraints,

Gantt and milestone charts, Establishing baselines, Understanding types of baselines, Managing

Change Within The Project


Project Progress Monitoring, Control and Report :What to monitor and why, Where and when to

monitor, Project control through monitoring, Use of plans in project control, Reasons for reports:

whom to report to and how to report. Types of report: exception, progress, management.

Monitoring and control of project finances and quality. Assessment of implications and impact

on the project of deviations and changes to project plan

Planning Project Quality :Quality planning (QP) introduction, QP inputs and tools and

techniques, Stakeholders and customers : Types, Importance of identification, Prioritization,

Project quality requirements, Project quality Standards, Benchmarking, Quality function

deployment (QFD), QP outputs, quality assurance, QA activities and the project quality

management plan, Quality audits, Quality path vs. critical path, QA and change control, QA

outputs , Quality control , QC inputs and tools and techniques, Plan-do-check-act (PDCA) cycle

Project Close-out, Termination and Follow-up: Introduction, Project Close-out, Steps for Closing

the Project, Project Termination, Project Follow-up. Case studies on Work Breakdown Structure,

Cost Estimation, Scheduling, Risk Management. Implementation of documentation guidelines of

PMBOK.


Students will select individually a technical project based on any area. Students need to

complete following phases to the selected project.

Phase 1. To narrate Requirement Definition Document for the target system with following areas:

- Problem Identification - Problem Statement - Proposed Solution - Benefits



Phase 2. To narrate System Requirements Specification Document for target system with

reference to the IEEE 610.12.1990 std guidelines. The requirements collected need to fall into

Functional, Nonfunctional, Pseudo and inverse requirements categories. The User and

Stakeholder identification must be made.

Phase 3. To perform feasibility study and develop a project plan. Phase 4. To develop analysis

model of the target system by Context level DFD accompanied by Problem decomposition and

Data Store indicators. It is expected that up to Level 3 DFD analysis must be included. Phase 5.

To develop design model of the target system by identifying the First cut program structure. The

modules identified need to bear processing narrative. Phase 6. To implement the target system by

selecting suitable programming language with well-formed program structure.

Text Books:

1 Richard Bechtold, “Essentials of Software Project Management”, Management Concepts;

second edition

2 Bob Hughes, Mike Cotterell, “Software Project Management”, McGraw-Hill Publishing

Reference Books:

1. Robert T. Futrell, Donald F. Shafer, Linda I. Shafer, “Quality Software Project Management”,

Prentice Hall

2. Edward Yourdon, Richard H. Thayer, “Software Engineering Project Management”, Wiley-

IEEE Computer Society

Course Outcomes:


1. Understand and practice the process of project management and its application in deliver-

ing successful IT projects

2. Use risk management analysis techniques that identify the factors that put a project at risk

and to quantify the likely effect of risk on project timescales

3. Evaluate a project to develop the scope of work, provide cost estimates and to plan the

activities viz. identifying the resources required for a project, produce a work plan and re-

source schedule

4. Implement monitoring mechanism of progress of a project and to assess the risk of slip-

page, revising targets

5. Apply quality principles of software project.

6. Distinguish between the different types of project and follow the stages needed to

negotiate an appropriate contract



FF No. : 654

IT8014:: Organizational Behavior


Lab:2 Hours/Week


Introduction: A review of the Manager’s Job Management Functions, Management Roles,

Management Skills, Effective versus Successful Managerial Activities. Definition, Importance,

Scope, Fundamental Concepts of OB, Challenges and Opportunities of OB Different models of

OB - autocratic, custodial, supportive, collegial and SOBC. Disciplines That Contribute to the

OB Field - Psychology, Social Psychology, Sociology, Anthropology. Responding to Economic

Pressures, Responding to Globalization, Managing Workforce Diversity, Improving Customer

Service.

Types of changes: Dilemma of change, Pressure of change, Resistance to change Force field

analysis, Change process, Overcoming the resistance to change, Approaches to Managing

Organizational Change: Lewin’s Three-Step Model, Creating a Culture for Change: Stimulating a

Culture of Innovation, Creating a Learning Organization, Work Stress and Its Management:

What Is Stress? Potential Sources of Stress, Individual Differences, Cultural Differences,

temporariness, Consequences of Stress, Managing Stress, balance Work–Life Conflicts.

Definition, Importance, Motives – Characteristics, Classification of motives - Primary &

Secondary motives. Theories of Motivation - Maslow’s Theory of need hierarchy - Herzberg's

theory, Goal-Setting, Self-Efficacy Theory , Reinforcement Theory , Equity Theory, Expectancy

Theory , Motivating by Job Design: How Can Jobs BeRedesigned? Alternative Work

Arrangements, Employee Involvement Programs, Using Rewards to Motivate Employees


Concept of Group & Team, Differences Between Groups and Team, Theories of Group

Formation - Formal and Informal Groups. Importance of Team building, Stages of Group

Development - The Five-Stage Model, Group Decision Making, Groups versus the Individual,

Problem-Solving Teams, Self-Managed Work Teams, Creating Effective Teams, Leadership,

Quality Circle.

Concept of MBO technique and details, phases, Concept of personality: Development of

personality – Attributes of personality, perception, values, and attitudes. Learning Behavior -

Emotional Intelligence in organization. Johari window - Nature and dimensions of attitude –

Developing the right attitude. Concept of Organizational Culture, Culture’s Functions, Creating

an Ethical. Organizational Culture, Creating a Positive Organizational Culture, What Is

Spirituality? Spirituality and Organizational Culture, Why Spirituality Now? Characteristics of a

Spiritual Organization, Achieving a Spiritual Organization, Criticisms of Spirituality, How a

Culture Begins, Creating and Sustaining Culture, Keeping a Culture Alive.



Text Books:

1. Fundamentals of Organizational Behavior by Nancy Langton , Stephen P.Robbins

2. Organizational Behavior : Stephen Robbins, Timothy Judge : Pearson Publications : 13th

Edition

Reference Books:

1. Essentials of Organizational Behavior : Laurie J. Mullins : Pearson Education : 2nd Edition

2. Organizational Behavior : Individuals, Groups and Organisation, 3rd Edition : Ian Brooks :

Pearson Publication

3. Organizations: Structures, Processes, and Outcomes: Richard H. Hall.

4. Organizational Behavior: Concepts, Controversies and Applications : Stephen Robbins

5. The Fundamentals of Organizational Behavior : Henry Tosi And Neal P. Mero : Black Well

Publishing

Course Outcomes:


1. Describe the concepts of organizational behavior and management practices.

2. Summarize the problems occurring due to organizational change and Analyze how the theo-

ries and empirical evidence can help to solve contemporary organizational issues.

3. Apply theories of motivation to practical problems in organizations in a critical manner.

4. Justify the role of leadership qualities.

5. Apply MBO technique to achieve the organizational objectives .

6. Develop the skills that are necessary for making ethical decisions in Professional life



FF No. : 654

IT8015: Foundation of management

Credits:4 Teaching Scheme: 3 Hours / Week

Lab: 2 Hours / Week

Section 1:

Management Concepts And Theory: What is Management? Is Management a science or an

Art? Importance of Management, Challenges and Tasks of Management; Contributions of

Taylor and Henry Fayol. Various approaches to Management; Functions of a Manager,

introduction to Planning Process Nature of Plans; Types of Plans; Importance of Planning;

McGregor’s Theory ‘X’ and ‘Y’. Steps in Planning. Why people fail in Planning; Limits of

Planning; Establishing an Environment for Effective Planning; Creativity. Case studies based

on planning

Organizing : Introduction; Organizational Roles; Formal and informal Organization;

Organizational, Customer Departmentalization: Market Oriented Departmentalization Process,

Service Departments, Matrix Organization. Case studies based on organizing

Staffing : Staffing: Recruitment; Selection; Sources of New Employees; Kinds of Tests;

Purpose of Employment Interview; Education and Training; An Introduction; Methods of

Training. Leadership-Definition and Concepts; Leadership Styles; The Managerial Grid;

Leadership and Managing,

Section 2:

Motivation: Introduction to Motivation, Concept of Motivation and Motivators; The theory of

‘Hierarchy of Needs’; Hertzberg’s Theory on Motivation; The Porter and Lawler Model on

Motivation; Special Motivational Techniques, The Porter and Lawler Model on Motivation;

Special Motivational Techniques. Case studies based on Staffing and Motivation

Communication: Communication, Purpose and Importance; The Communication Process;

Need for Different Types of Communication in a Business Enterprise; Barriers and Breakdowns

in Communication; Towards Effective Communication Controlling Methods: The Control

Process; Control as a Feedback System; Common types of standards used in Control Process;

Control Technique; The Budget; Return on Investment Contents of Unit

Case studies based on Communication

Decision Making: Introduction and Definition; Aids to Decision Making; Theories of Decision

Making; Decision Making; Under Certainty; Decision Making; Under Uncertainty. Key issues

in Modern Management: MBO; Quality Circles- A Review; Total Quantity Management;

Review and Concepts Case studies based on decision making



Text Books

1. P.C. Tripathi and P.N. Reddy, ‘Principles of Management’ 4th Edition TMH

2. “Essential of Management”, Koontz H &Weitrich H

Reference Books

1. “Fundamentals of Management”,Griffin Houghton Mifflin Company, 3rd Edi-

tion,2003

2. “Management Today Principles And Practices”, Burton & Thakur



FF No. : 654

IT8016: User interface design


Lab:2 Hours/Week

Section 1:

Introduction:Importance of good design, defining user interface, graphical user interface, web

user interface,graphical business systems, principles of user interface design, measurable human

factors, humancomputer interaction (HCI), usability and design team

User, Client and Business:Understanding people’s interaction with computers, users and cli-

ents, human characteristics in design, human considerations in design, specialized users, human

interaction speeds, human performance and preference, understanding users, business and re-

quirement analysis, basicbusiness functions, design standards, style guide, system training, user

persona, user survey and documentation.

User Interaction Design. Human consideration in screen design, test for good design, bad de-

signs, organization and structural guidelines, statistical graphics, technological considerations,

cognitive models - GOMS, LUCID, task analysis, structures, usability evaluation methods, win-

dow management and multi-modal interaction

Section 2:

User Interface and Controls: Input and output devices, characteristics of device-based controls,

selecting proper device-based control, interaction styles, operational controls, buttons, text entry

/ read-only controls, selection controls, check boxes, combo boxes, combination entry, other con-

trols, sliders, tabs, scroll bars custom controls, presentation controls and selecting proper controls

Visual Interface Design: Words, sentences, text, text design in web pages, error messages, in-

structions, providing proper feedback, blinking for attention, guidance and assistance, help, wiz-

ards, tips, international considerations, localization, accessibility, disabilities, icons, images, an-

imation, multimedia, color – RGB, HSV, color uses, problems with color, cross-disciplinary and

cross-cultural differences, color and human vision, choice of colors, discrimination and harmony,

accessibility considerations and selection of colors in design.

Types of Applications and Interfaces: Groupware, shared applications and artifacts, computer–

supported cooperative work, social issues, social acceptability and organizational change, ubiqui-

tous computing, information kiosk, digital library, virtual and augmented realities, mobile inter-

faces, hypertext and hypermedia, interfaces that give and take advice, natural interfaces, eye-free

interfaces, context-aware computing, roomware, tangible user interfaces.

Text Books:

1. Wilbert Galitz, ‘The Essential Guide to User Interface Design’, Wiley Dreamtech, 2005.

2. Ben Shneiderman, ‘Designing the User Interface’, Pearson Education, Third edition, 2002.



Reference Books:

1. Alan Dix, Janet Finlay, Gregory Abowd, Russell Beale, ‘Human Computer Interaction’, Third

Edition, 2004.

2. Donald Norman, ‘The Design of Everyday Things’, Basic Books, USA, 2002.

3. Donald Norman, ‘The Design of Future Things’, Basic Books, USA, 2007.

Course Outcomes:

Students will be able to:

1. Analyze types of user interfaces

2. Design user interfaces for various applications

3. Distinguish between good and bad user interaction designs

4. Follow required processes and standards while designing user interfaces.

5. Integrate ethno-cultural and accessibility computing aspects into the user interface design

6. Describe the types of interfaces and their applications.



MO

DU

LE

V




Module V


Branch MCA Year:

SY

Academic

Year:2019

-20

A19

Subj

ect

No.

Subject

Code


Theo

ry

Lab CA MS

E

ESA

H

A

LAB GD/

PP

T

ES

E

VIV

A

S1 IT9001

Network & In-

formation Securi-

ty

3 2 10 30 10 15 15 20 100 4

S2 IT9102 Data Science 3 2 10 30 10 15 15 20 100 4

OE3 IT9009

Big Data Appli-

cations 3 2

10 30 10 15 15 20 100 4

IT9013 Advanced Web

Technology 3 2

10 30 10 15 15 20 100

IT9010 Advanced Data

Structure 3 2

10 30 10 15 15 20 100

IT9008 Natural Lan-

guage Processing 3 2

10 30 10 15 15 20 100

IT9011 Software Design

& Architecture 3 2

10 30 10 15 15 20 100

IT9012 Artificial Intelli-

gence 3 2

10 30 10 15 15 20 100

S4 IT9004

Internet of

Things 3 2

10 30 10 15 15 20 100 4

IT9014 Robotics 3 2 10 30 10 15 15 20 100

IT9015

Cloud Compu-

ting 3 2

10 30 10 15 15 20 100

IT9016

GPU Computing

& Applications 3 2

10 30 10 15 15 20 100

IT9018 Image Processing 3 2 10 30 10 15 15 20 100

IT9019

Data Acquisition

System 3 2

10 30 10 15 15 20 100

S5 IT9005

Mobile Applica-

tion Develop-

ment

1 2 10 30 10 15 15 20 100 2

DAI IT9106

Design and In-

novation -3 1 4

10 30 10 15 15 20 100 3

Total 21



FF No. : 654

IT9001: Network and Information Security


Lab:2 Hours/Week


Worms, viruses, Trojans, Bots, Types of Attacks: DoS, IP spoofing, replay, DNS poisoning,

Phishing, Need of security, attributes of security, authentication, confidentiality, integrity and

cryptography, Vulnerabilities in OSI model, layers, Bioinformatics security, Mathematical

background for security, Substitution Techniques: Ceaser cipher, Playfair cipher, Hill cipher,

Vigener cipher, One time pad, Transposition Techniques, Product Cipher, Steganography, Block

Cipher Principle, S-DES, DES, Double DES, Triple DES, Man in the middle attack, RC4, AES,

S-AES, RSA Algorithm, Elliptic Curve Arithmetic, Elliptic curve Cryptography, El Gamal

Cryptosystem, Knapsack public key algorithm


Diffie-Hellman Key Exchange Technique, ECC Diffie-Hellman Key Exchange Technique,

Symmetric Key Distribution using symmetric encryption, Symmetric Key Distribution using

asymmetric encryption, Distribution of public keys, X.509 Certificates, Public key infrastructure,

Remote user authentication principles, Remote user authentication principles using symmetric

encryption, Kerberos, Remote user authentication principles using asymmetric encryption,

Applications of cryptography, Hash Functions, SHA, Whirlpool, Message Authentication, MAC,

HMAC, CMAC, Digital Signature, EL Gamal Digital Signature Scheme, Digital Signature

Standard, Transport Layer Security, Secure Socket Layer, HTTPS, Secure Shell(SSH), Wireless

network security, Wireless transport layer security, Wireless application layer protocol(WAP) end

to end security, E-mail Security, PGP, S/MIME, IP security, Firewall security


1. Implement Caesar Cipher & perform brute force attack on it.

2. Implementation of Playfair cipher.

3. Implement Vigenere Cipher

4. Implementation of Hill cipher.

5. Implementation of RC4 algorithm.

6. Implementation of S-DES.

7. Implementation of S-AES

8. Implementation of RSA.

9. Implementation of Diffie-Hellman key exchange technique.

10. Implementation of ECC.

11. Implement Hash algorithm.

12. Implementation of packet sniffer.

13. Kerberos simulation




The objective of this project is to understand practical applications of network and information

security. Student will select individually a technical project based on

networks and information security. Any one or many network security concepts can be chosen as

project area. The students will be assessed based on demonstration.


1. “Network Security and Cryptography”, by Bernard Menezes, Cengage Lerning, 2010, ISBN

81-315-1349-1, 1st Edition.

2. “Cryptography and Network Security-Principles and Practices” by William Stallings, Pearson

Education, 2006, ISBN 81-7758-774-9, 4th Edition.


1. “Computer Security: Art and Science”, by Matt Bishop, Pearson Education, 2002, ISBN

0201440997, 1st Edition.

2. “Network security, private communication in a public world”, by Charlie Kaufman, Radia

Perlman and mike speciner, Prentice Hall, 2002, ISBN 9780130460196, 2nd Edition.

Course Outcomes:


1. Identify the various types of attacks by analyzing the behaviour of data in the networks

2. Design a secure system for protection from the various attacks for 7 layer model by de-

termining the need of security from various departments of an organization

3. Investigate the vulnerabilities in the existing system for the development of new system

by following laws of security.

4. Perform authentication of individuals or groups with cost effective Engineering solutions.

5. Examine the importance of network security applications for current and future needs of

organizations.

6. Estimate future needs of security for a system by researching current environment on a

continuous basis for the benefit of society.



FF No. : 654

IT9012: DATA SCIENCE

Credits: 4 Teaching Scheme : 3 Hours/Week

Lab :- 2Hours/Week

Section 1:

Introduction : Introduction to data science, role of data scientist ,Data mining Techniques, Data

pre processing: Data cleaning, Data summarization, Data integration, Data transformation ,Data

reduction.

Classification: classification and prediction ,Decision tree classifier, baysian classification, rule

based classification, classifier accuracy, introduction to other classification methods like neural

network classification, back propagation, KNN classifier, Support Vector Machines.

Clustering: What is cluster analysis, types of cluster analysis ,a categorization of major clustering

method ,partition ,hierarchical ,density based, grid based method,

Mining Frequent Pattern: Basic concept, market basket analysis ,frequent pattern mining, Mining

frequent itemset using candidate generation and without candidate generation methods, mining

various kind of association rules.

Section2:

Predictive analytics: linear and multiple regression.

Outlier analysis: Global outlier, Local outlier, Outlier detection various methods.

Data cube and OLAP, Concept hierarchies, OLAP operations. Multi dimensional modeling: star,

snowflake ,fact constellation. MDM case studies. ETL Overview.

Data Mining Application: Mining various databases, multimedia databases, spatial database, text

databases.

Text Mining: Text preprocessing, text mining operations, Categorization, Text mining

Applications,


Perform following practical on given dataset.

1. Gain experience using Weka, a software package for machine learning, and R, a software

package for statistics;

2. Implementing Data cleansing method for a given problem.

3. Generating different types of classification Trees using WEKA:Decision Trees

4. Applying various classification methods on a given data set.

5. Implementing K-means clustering algorithm using a data set.

6. Using clustering algorithm build a partitional model

7. Using clustering algorithm build A Hierarchical Model

8. Using clustering algorithm build Probabilistic Model.

9. Multi dimensional modeling .

10. Concept hierarchy, OLAP operations and KPI.

11. ETL operations using kettle software. Implementing data transformation for a given prob-

lem domain.



12. Advance ETL operations using Kettle

List of Project Areas :

1. Take a real world data analysis problem and solve it using data mining concepts Gain ex-

perience using Weka, a software package for machine learning, and R, a software pack-

age for statistics.

2. Take a real world data analysis problem and Implementing Data cleansing method for a

given problem.

3. Take a real world data analysis problem and Generating different types of classification

Trees using WEKA:Decision Trees

4. Take a real world data analysis problem and Applying various classification methods on a

given data set.

5. Take a real world data analysis problem and Implementing K-means clustering algorithm

using a data set.

6. Take a real world data analysis problem and Using clustering algorithm build A Hierar-

chical Model/Probabilistic Model.

7. Designing Multi dimensional modeling for a real world scenario and design

8. identify Concept hierarchy, apply OLAP operations and KPI for a real world scenario.

9. ETL operations using kettle software. Implementing data transformation on real world

scenario.

10. Advance ETL operations using Kettle on real world scenario.

11. Apply text mining methods on real world problems.

12. Sentiment analysis using text mining.

Text Books:

1.Jiawei Han and Micheline Kamber “Data mining: concepts and techniques”, the

Morghan Kaufman, 2001.

2. T. Mitchell. “Machine Learning”, McGraw-Hill, 1997.

Reference Books:

1.Hand, Smyth, Mannila “Principles of Data mining”, MIT press,2001

2.Gagendra Sharma, “Data mining, Data warehousing and OLAP”, S.K. Kataria and

sons.

Course Outcomes:

Upon completion of the course, post graduates will be able to –

1.Understand the process of data mining and the key steps involved well enough to

lead/manage a real-life data mining project

2.Derive useful facts from data using different data mining algorithms

3.Apply suitable data mining technique to predict useful patterns

4. Apply predictive analytics and various mining techniques for real life problems.

5.Construct a multi-dimensional modellingsolution involving various data sources, ETL,

and OLAP.

6.Illustrate use of appropriate Data analysis technique/s given the data Specifications.

Solve real life problems using data analysis techniques



FF No. : 654

IT9005: Mobile Application and Development

Credits: 02 Teaching Scheme:-Theory: 1 Hour/Week

Lab: 2 Hours/Week

Section 1: Android UI Components & Multimedia

Basics-Fundamentals of Java for Android Application Development, Introduction to Mobility,

Mobile Platform, App development approaches, Android Platform Architecture, Development

Environment for Android, Android app project structure, Logical components of Android app,

Android Tool Repository, Introduction of Apple and Window mobile OS Architecture

UI Components-Activity life cycle, UI resources, String resources, Image resources, Common

attributes of View, Event handling associated with Button, EditText, CheckBox, ListView,

ImageView, AlertDialog, Navigation between Activities, Fragments, Life cycle of Fragment,

Interaction between Fragments, ActionBar, Menu, Introduction to Material Design Pattern,

Layouts, Recycler View, Fragments, Intents

Multimedia-Graphics and Animation, Multimedia, Audio, Video, Camera

Section2: Data Storage, Services & Advanced Functionalities

Data Storage-Internal and External File storage Operation, Shared Preference, SQLite database,

Remote database operations, Notification, Thread, AsynTask, JSON data access.

Services-Service, Broadcast Receivers, SMS and Telephony API, Threads & Services, Invading

the home screen

Advanced Functionalities-Location services and Maps, Geocoding, Sensor, Emailing &

Networking in android, Bluetooth, NFC, Wifi, Publishing, monetizing and distributing android

application, Paranoid Android, Cloud to device messaging

I. List of Practical:

1. Design an android Application for calculator.

2. Design an android Application student registration form.

3. Design an android Application for Phone Call.

4. Design an android application for audio player.

5. Design an android application for video player.

6. Design an android Application for SMS Manager.

7. Design an android Application to store and retrieve student data from database

8. Design an android Application using Google Map To Trace The Location of Device.

9. Design an android Application for jumping ball animation using graphics library.

10. Design an android Application for study room using Unity 3D



11. Design an android Application for library using Unity 3D

12. Design an android Application for office using unity 3D

II. List of Projects: (Any1)

1. Chatting application

2. Student registration system

3. Hospital management system

4. Office search helper

5. Library management system

6. Simulation of Car driving

7. Simulation of molecule structure

8. City road map

9. Transport alert system

10. Toll plaza management system

11. Path finder

12. Image clipper or photo editor

Text Books:

1. “Head First Android Development”, Jonathan Simon, O’Reilly Media, Inc., 1005 Gravenstein

Highway North, Sebastopol, CA 95472, ISBN: 978-1-449-39330-4, 2011

2. “Beginning Android™ Application Development”, Published by Wiley Publishing, Inc.10475

Crosspoint Boulevard Indianapolis, IN 46256. ISBN: 978-1-118-01711-1, 2011

Reference Books:

1. “Professional Android™ Application Development”, Published by Wiley publishing,

Inc.10475 Crosspoint Boulevard Indianapolis, IN 46256, ISBN: 978-0-470-34471-2, 20.

2. “Pro Android 4”, Published by Apress,Satya Komatineni, Dave MacLean, ISBN 978-1-4302-

3930-7, 2012.

Course Outcomes:


1. Simplify the data manipulation using Content Providers, Shared Preferences, embedded

database SQLite, Flat files and Multi Media files.

2. Design UI-rich apps using all the major UI components

3. Choose suitable software tools, IDE and APIs for the development of Mobile Application.

4. Trace and identify the location of specific/ specialized handheld or mobile devices using

Google map and other alternative techniques.

5. Develop android social media applications using HTTP and Socket communication protocol.

6. Package and prepare real world apps for deploying on mobile device.



FF No. : 654

IT9009: Big data Applications

Credits: 04 Teaching Scheme:-Theory: 3 Hours/Week

Lab: 2 Hours/Week

Section I

Digital data types: Structured, semi-structured, unstructured data, sources, ease of use, handling

issues, Why not RDBMS? What is big data? Why big data? Other characteristics of data but not

definitional for big data, Challenges with big data, Big data stack, Big Data Anayltics, Analytics

1.0, Analytics 2.0, Analytics 3.0, Traditional Business Intelligence vs. Big Data Envirnoment,

Big Data technology Landscape

Hadoop Architecture: Distributed Computing Challenges, A Brief History of Hadoop, Hadoop

Overview, Hadoop Components

Hadoop Distributed File System, HDFS Architecture, Daemons Related to HDFS, Working with

HDFS Command, Special Features of Hadoop

Limitation of Hadoop 1.0, Hadoop 2: HDFS, Hadoop 2: YARN

Map Reduce Programming: Processing Data With Hadoop, How Map Reduce Works, Map

Reduce Examples

Introduction to HBASE, Sqoop, Spark

Section II

PigLatin: Primitive Data Types , Colletion Types and NULL, Common Operators in Pig, Pig

Statements - LOAD, STORE, DUMP, Interactive Shell – GRUNT, FILTER, SORT, GROUP BY,

ORDER BY, JOIN, LIMIT, Pig Latin Script - Local Mode, Map Reduce Mode, Running Pig

Script, Working with Field, Tuple, Bag, User Defined Function

Hive: Hive Features, Hive Integration and Work Flow, Hive Data Units, Hive Query Language –

Statements, DDL, DML, Hive User Defined Function, Sub Query, join, Aggregations in Hive,

Hive Analytic Functions

NOSQL database: Comparative study of RDBMS and NOSQL, Databases types, NOSQL Data

Modeling, Benefits of NOSQL, NOSQL using MongoDB- mongoDB shell, data types,

manipulation(insert, update, delete documents), querying, aggregation, indexing, croud-sourcing,

Cassandra, NewSQL

Lab Assignments

1. Installation of Hadoop with single node and/or multiple node cluster

2. Manipulation of data on HDFS

3. Word count problem using Map Reduce Programming

4. Data handling using Spark

5. Result analysis using Pig

6. Student database analysis using Hive

7. Data maniputlation using MongoDB

8. User defined functions for data analysis in Pig, Hive



FF No. : 654

IT9013: Advanced Web Technology


Lab: 2 Hours/Week

Section 1: Introduction to HTML 5: New elements, New input types, New attributes, Local

Storage, Session Storage, Server sent events, CSS3, Bootstrap

JQuery: Introduction to JQuery, loading JQuery, selecting elements, changing styles, creating

elements, appending elements, removing elements, handling events, JQuery AJAX

Server side technology and TOMCAT, introduction to servlet, need and advantages, servlet

lifecycle, creating and testing of sample servlet, session management.

JSP: introduction, advantages of JSP over Servlet, elements of JSP page: directives, comments,

scripting elements, actions and templates, JDBC,

MongoDB: Introduction, Environment, Create Database, Drop Database, Create Collection,

Drop Collection, Read Operations, Write Operations, Data Modelling, Administration

Section 2: Web Technology Frameworks: Express Framework: Introduction to Express

Framework, Introduction to Nodejs, , What is Nodejs, Getting Started with Express, First

Express App, Express Routing, Implementing MVC in Express, Middleware, Using Template

Engines, Error Handling , API Handling , Debugging, Developing Template Engines, Using

Process Managers, Security & Deployment

Angular JS: Overview, MVC architecture, Directives, Expression, Controllers, Filters, Tables,

Modules, Forms, Includes, Views, Scopes, Services, Dependency injection, Custom directives,

Internationalization,

NodeJS: Getting started, Node Core, Node Modules,File System,Debugger, Automation and

Deployment

List of Practicals (Any 6 statements):

1. Design a web page to demonstrate the use of different HTML5 tags.

2. Design a web page to demonstrate the use of CSS3 tags.

3. Design CRUD (Create, Read, Update, Delete) application using HTML and JQuery

4. Design application using JQuery to process a simple quiz, checking if the user entered the

correct answer and messaging the result.

5. Design a web page using JQuery AJAX methods.

6. Write a program to demonstrate the use of servlet request and response as well as doGet

( ) and doPost( ) methods.

7. Design Registration form with following fields: First Name, Last Name, Username, Password,

Address, Contact Number with JSP and using MVC architecture.

8. Create a new database and perform all the basic CRUD operations on it using MongoDB.

9. Design a simple application using Express framework.

10. Design a Login form using AngularJS

11. Build a web app where users can type in a city name and get real-time weather data instantly

displayed on their screen using NodeJS and Express.

12. Build a navigation menu that highlights the selected entry using AngularJS



List of Project areas (Any 1 project):

Design and deploy web based application using HTML5, CSS, Bootstrap,

JQuery,MobgoDB,AngularJS,Nodejs and Express framework.

1. Student Registration System

2. Library Management System

3. Tours and Travel System

4. Online Examination System

5. Online Hotel Management System

6. E-book shop

7. Online Reservation System

8. Online recruitment System

9. Movies management

10. E healthcare system

11. Chat application

12.U Tube search engine

Text Books: 1. Thomas Black Book; “ JDBC 4.2, Servlet 3.1 & JSP 2.3”; Dreamtech Press, 2016.

2. Adam Bretz & Colin J Ihrig; “Full Stack Javascript Development with MEAN”;SPD, 1st Edition,

Indian Reprint September 2015.

Reference Books: 1. Giulio Zambon; “ Beginning JSP, JSF and Tomcat”; 2nd Edition, Apress Publication.

2. Sandeep Panda; “Angular JS: Novice To Ninja”; SPD, 1st Edition, Indian Reprint 2015.

3. Black book; “Web Technologies:HTML,JS,PHP,Java,JSP,ASP.NET,XML and AJAX” ; Dreamtech

Press, 2016.

4. Robin Nixon; “Learning PHP, MySQL, JavaScript, CSS and HTML 5”;4th Edition, O’Reilly pub-

lication.

Course Outcomes:


1. Design reliable, efficient, scalable front end view of web pages with HTML5,CSS3

and Bootstrap .

2. Apply JQuery concepts for responsive web frontend development.

3. Refine dynamic web pages with JSP, Servlet.

4. Implement frontend and backend scenarios to read, write and update data stored in

MongoDB.

5. Build responsive web application using Express framework.

6. Develop front end application using Angular JS.



FF No. : 654

IT9010: Advanced Data Structures


Lab: 2 Hours/Week

Section 1:

Priority queue and heaps:Double Ended Priority queues, Leftist Trees: Height Biased, Weight

Biased. Binomial Heaps: Cost Amortization, Definition of Binomial Heaps, Insertion, Melding

two Binomial Heaps, deletion of min element. Fibonacci Heaps: Definition, Deletion from an F-

heap, Decrease key, Cascading Cut.

Advanced Binary Search Trees: Red-Black Trees: Definition, Representation, Searching,

Insertion, Deletion. Splay Trees: Bottom-up, top-down. Insertion and Deletion in B Trees and B+

Trees

Digital Search Structures:Introduction to digital search tree,various operations for digital search

tree like Search, Insert and Delete. Binary Tries, Compressed Binary Tries.

Section2:

Tries: Multiway Tries: Definition, searching a Trie, sampling strategies, Insertion, Deletion,

Height of a Trie. Prefix Search and applications. Suffix Trees.

Dynamic Hashing: Motivation for Dynamic Hashing, Dynamic Hashing using Directories,

directory less Dynamic Hashing. Bloom Filters: An application-differential files, Bloom Filter

Design

linear programming : Overview, Applications, Algorithms, Standard and Slack forms,

Formulating problems as linear programs, Simplex Algorithm.

List of practical

1. Assignment based on Leftist Trees.

2. Assignment based on Fibonacci Heaps.

3. Assignment based on Binomial heap (insert, delete, display).

4. Assignment based on Red black tree (insert, delete, display).

5. Assignment based on B/B+ tree.

6. Assignment based on Assignment based on Suffix Trees. (insert, delete, display).

7. Assignment based on tries (insert, delete, display).

8. Assignment based on prefix search.

9. Assignment based on Directory based Dynamic Hashing (insert, delete, display).

10. Assignment based on Directory less Dynamic Hashing (insert, delete, display).

11. Assignment based on Bloom Filter.

12. Assignment based on Linear programming.

II: List of Project: ( Any 1)

1. Priority based patient management

2. Priority data storage and retrieval.

3. Job Scheduling

4. String processing

5. Dictionary

6. Search engines

7. Modeling the real world problems using RB trees



8. B trees and B+ trees in Database management system

9. Geographical maps

10. Image processing.

11. Internet routing

12. Server access management

Text books:

1.“Advanced Data structures”, Peter Brass, Cambridge Publication, 1st Edition, 2008 ,

ISBN – 978-0-521-88037-4.

2.“Fundamentals of Data Structures in C”, E. Horwitz , S. Sahani, Anderson-Freed,

Universities Press, Second Edition, 2008, ISBN 978-81-7371-605-8.

Reference books :

1.“Data structure and program design in c”, R.L.Kruse, B.P.Leung, C.L.Tondo,Prentice

Hall Of India, latest edition , ISBN 0 -13-725649-3

2.“Data Structures using C & c++”, Y. Langsam, M. Augenstin and A. Tannenbaum ,

Prentice Hall India, Second edition,ISBN-978-81-203-1177-0,

Course Outcomes:


1.Demonstrate memory efficient solution in order to apply basic principle of

programming perspective.

2.Infer memory utilization with modularization useful for programming pragmatics.

3.Verify and narrate test condition in employing debugging technique to assist problem

solving.

4.Elaborate on unrecognizable well organized problems based on realizable solutions.

5.Implement and demonstrate different data structures with operations like insertion,

deletion, traversing.

6.Contribute breadth of modularization in order to understand and implement realistic

solution.



FF No. : 654

IT9008: Natural Language Process


Lab: 2 Hours/Week

Section 1:

Introduction : NLP tasks in syntax, semantics, and pragmatics. Applications such as information

extraction, question answering, and machine translation. The problem of ambiguity. The role of

machine learning. Brief history of the field.

N-gram Language Models :The role of language models. Simple N-gram models. Estimating

parameters and smoothing. Evaluating language models.

Part Of Speech Tagging and Sequence Labeling : Lexical syntax. Hidden Markov Models

(Forward and Viterbi algorithms and EM training).

Basic Neural Networks,LSTM Recurrent Neural Networks

Section2:

Syntactic parsing :Grammar formalisms and treebanks. Efficient parsing for context-free

grammars (CFGs). Statistical parsing and probabilistic CFGs (PCFGs). Lexicalized PCFGs.

Neural shift-reduce dependency parsing .

Semantic Analysis : Lexical semantics and word-sense disambiguation. Compositional

semantics. Semantic Role Labeling and Semantic Parsing.

Information Extraction (IE) :Named entity recognition and relation extraction. IE using

sequence labeling.

Machine Translation :Basic issues in MT. Statistical translation, word alignment, phrase-based

translation, and synchronous grammars..


1. Basic natural language processing task using Python.

2. Implementation of language model.

3. Perform latent semantic analysis or latent semantic indexing in Python.

4. perform semantic analysis given a real life problem statement.

Text Books:

1. Steven Bird, Ewan Klein, Edward Loper ,”Natural Language Processing with Python:

Analyzing Text with the Natural language processing”, oreilly. ISBN-13: 978-

0596516499,ISBN-10: 0596516495

2. Benjamin Bengfort , Rebecca Bilbro , Tony Ojeda, “Applied Text Analysis with

Python: Enabling Language-Aware Data Products with Machine Learning 1st Edition”.

ISBN-13: 978-1491963043,ISBN-10: 1491963042

Reference books

1. Christopher Manning and Hinrich Schütze. “Foundations of Statistical Natural

Language Processing”, MIT Press (MA), ISBN: 9780262133609, 0262133601

2. Daniel jurafskyand james martin “speech and language processing an introduction to

natural language processing, computational linguistics and speech”.

3. Allen, James, Natural Language Understanding, Second Edition, Benjamin/Cumming,



1995.

Course Outcomes:


1. Illustrate use of appropriate NLP technique/s given the problem statement.

2. Construct and evaluate language model

3. Understand the process of part of speech tagging and its application to manage

a real-life NLP project

4. Derive useful facts from syntactic parsing data using different data mining

algorithms

5.Apply semantic learning technique to predict useful patterns

6.Solve real life problems using machine translation.



FF No. : 654

IT9011: Software Design and Architecture


Lab: 2 Hours/Week


Software Architecture Vs Software Design, Software Architecture Relationships to Other

Disciplines, Foundations of Software Architecture, Software architecture in the context of the

overall software life cycle ,Role of Software Architect, Architectural Styles, Architectural

Frameworks, Designing, Describing, and Using Software Architecture, IS2000: The Advanced

Imaging Solution, Global Analysis, Conceptual Architecture View, Module Architecture View,

Execution Architecture View, Code Architecture View. Introduction to software Patterns:

Architectural Patterns, Design Patterns and Idioms. Architectural Patterns: Blackboard, Pipe and

filter, Design Patterns proposed by GoF: Creational Patterns, Structural Patterns, and Behavioral

Patterns. Design Patterns proposed by Buchman: Object Management Patterns Adaptation

Patterns, Communication Patterns, Patterns for Distribution, Patterns for Interactive Systems,

Adaptable Systems, Analysis Patterns.


Layering, Organizing Domain Logic, Mapping to Relational Databases, Web Presentation,

Domain Logic Patterns, Data Source Architectural Patterns, Object- Relational Behavioral

Patterns, Object-Relational Structural Patterns, Object-Relational Metadata Mapping Patterns,

Web Presentation Patterns, Distribution Patterns, Offline Concurrency Patterns Defining EAI,

Data-Level EAI, Application Interface-Level EAI, Method-Level EAI, User Interface-Level

EAI, The EAI Process, An Introduction to EAI and Middleware, Transactional Middleware and

EAI, RPCs, Messaging, and EAI, Distributed Objects and EAI, Database-Oriented Middleware

and EAI, Java Middleware and EAI, Implementing and Integrating Packaged Applications, XML

and EAI, Message Brokers, Process Automation and EAI. Archetypes and Archetype Patterns,

Model Driven Architecture with Archetype Patterns. Literate Modeling, Archetype Pattern,

Customer Relationship Management (CRM) Archetype Pattern, Product Archetype Pattern,

Quantity Archetype Pattern, Rule Archetype Pattern

List of Practicles:

1. Select a moderately complex system and narrate concise specification for the same. Im-

plement the system features using Abstract Factory and Composite design patterns. State

the complete pattern specification and note the difference between the patterns.


plement the system features using Facade and Proxy design patterns. State the complete

pattern specification and note the difference between the patterns.


plement the system features using Flyweight and Iterator design patterns. State the com-

plete pattern specification and note the difference between the patterns.




plement the system features using Template and Command design patterns. State the

complete pattern specification and note the difference between the patterns.


plement the system features using Mediator and Observer design patterns. State the com-

plete pattern specification and note the difference between the patterns.

6. Select a complex system and narrate concise specification for the same. Develop archi-

tecture specification and use archetypes to recognize the architectural elements.

Text Books

Erich Gamma, Richard Helm, Ralph Johnson,“Design Patterns: Elements of Reusable

Object-Oriented Software” (Addison-Wesley Professional Computing Series)

,John Vlissides, Publisher: Addison-Wesley Professional, 1st edition (January 15,

1995) , ISBN-10: 0201633612 ISBN-13: 978-0201633610

Martin Fowler ,“Patterns of Enterprise Application Architecture”, Addison-Wesley

Professional, 2003, ISBN-10: 0321127420 ISBN-13: 9780321127426

Reference Books

Paul Clements, Felix Bachmann, Len Bass, David Garlan,Documenting Software

Architectures: Views and Beyond Addison-Wesley Professional 2003, ISBN-10:

0201703726, ISBN-13: 9780201703726

Frank Buschmann, Hans Rohnert, Kevin Henney, Douglas C. Schmidt ,”Pattern-

Oriented Software Architecture Volume 1, 2, 3, 4, 5”, Publisher: Wiley, 1 edition

(August 8, 1996-2004), ISBN-10: 0471958697, ISBN-13: 978-0471958697

Additional Reading

Fred A. Cummins ,“Enterprise Integration: An Architecture for Enterprise Application and

Systems Integration”, Wiley; 2002 ISBN-10: 0471400106 ISBN-13: 978-0471400103

David S. Linthicum, Enterprise Application Integration Addison-Wesley Professional 2003,

ISBN-10: 1402052626

Course Outcomes:

1. To describe what patterns are, how to use them, and why they are important.

2. To understand contribution of patterns towards the design process efficiency

3. To trace the relationship between patterns and traditional methods

4. To learn the relationship among patterns, frameworks, object-oriented languages, and

software architecture

5. To identify fundamental and advanced concepts of design and architectural patterns

6. To Structure systems by applying architectural patterns

7. To focus on Archetypes and Architecture Documentation

http://www.amazon.com/David-S.-Linthicum/e/B001IU4QAQ/ref=ntt_athr_dp_pel_1



FF No. : 654

IT9012: Artificial Intelligence


Lab: 2 Hours/Week


Fundamentals of Artificial Intelligence (6 Hours )

Introduction, A.I. Representation, Non-AI &AI Techniques, Representation of Knowledge,

Knowledge Base Systems, State Space Search, Production Systems, Problem

Characteristics, types of production systems, Intelligent Agents and Environments, concept of

rationality, the nature of environments, structure of agents, problem solving agents, problem

formulation

Uninformed Search Strategies (7Hours )

Formulation of real world problems, Breadth First Search, Depth First Search, Depth Limited

Search, Iterative Deepening Depth First Search, Bidirectional Search, Comparison of

Uninformed search Strategies, Searching with partial information, Sensor-less problems,

Contingency problems

Informed Search Strategies (8 Hours )

Generate & test, Hill Climbing, Best First Search, A* and AO* Algorithm, Constraint

satisfaction, Game playing: Minimax Search, Alpha-Beta Cutoffs, Waiting for Quiescence,

Applications of search strategies:- Tic-tac-Toe, 8-Puzzle,


Knowledge Representation (7 Hours )

Knowledge based agents, Wumpus world. Propositional Logic: Representation, Inference,

Reasoning Patterns, Resolution, Forward and Backward Chaining.First order

Logic: Representation, Inference, Reasoning Patterns, Resolution, Forward and Backward

Chaining. Basics of PROLOG: Representation, Structure, Backtracking.

Expert System: Case study of Expert System in PROLOG

Introduction to Planning and ANN (5 Hours )

Blocks world, STRIPS, Implementation using goal stack, Introduction to Neural networks:-

basic, comparison of human brain and machine, biological neuron, general neuron model,

activation functions, Perceptron learning rule, applications and advantages of neural networks.

Brief introduction to single layer and multiplayer networks.

Uncertainty and Expert system

(7 Hours )

Non Monotonic Reasoning, Logics for Non Monotonic Reasoning, semantic Nets, Statistical

Reasoning, Fuzzy logic: fuzzy set definition and types, membership function, designing a fuzzy

set for a given application. Probability and Bays theorem.

Introduction to Expert Systems, Architecture of Expert Systems; Expert System Shells;

Knowledge Acquisition; Case Studies; MYCIN, Learning, Rote Learning; Learning by

Induction; explanation based learning.



List of Practical

1. Implement Non-AI and AI Techniques

2. Implement any one Technique from the following

a. Best First Search & A* algorithm

b. AO* algorithm

c. Hill Climbing

3. Implement Perceptron learning algorithm

4. Implement real time applications in Prolog.

5. Expert System in Prolog- new application

6. Implement any two Player game using min-max search algorithm.

7. Design a fuzzy set for shape matching of handwritten character

Text Books

1. Elaine Rich and Kevin Knight: "Artificial Intelligence." Tata McGraw Hill

2. Stuart Russell & Peter Norvig : "Artificial Intelligence : A Modern Approach",

Pearson Education, 2nd Edition.

3. Dan W.Patterson, Introduction to Artificial Intelligence and Expert Systems – Prentice

Hal of India.

Reference Books

1. Ivan Bratko : "Prolog Programming For Artificial Intelligence" , 2nd Edition Addison

Wesley, 1990.

2. Eugene, Charniak, Drew Mcdermott: "Introduction to Artificial Intelligence.", Addison

Wesley

3. Nilsson : ―Principles of Artificial Intelligence‖, Morgan Kaufmann.

4. Carl Townsend, ―Introduction to turbo Prolog‖, Paperback, 1987

5. Jacek M. Zurada, Introduction to artificial neural systems, Jaico Publication

Course Outcomes:

Upon completion of the course, graduates will be able to -

1. Understand the basics of the theory and practice of Artificial Intelligence as a

discipline and about intelligent agents capable of problem formulation.

2. Evaluation of different uninformed search algorithms on well formulated

problems along with stating valid conclusions that the evaluation supports.

3. Design and Analysis of informed search algorithms on well formulated problems.

4. Formulate and solve given problem using Propositional and First order logic.

5. Apply planning and neural network learning for solving AI problems

6. Design a small expert system using PROLOG.



FF No. : 654

IT9013: Internet of Things


Lab: 2 Hours/Week

Section 1:

Introduction of Internet of Things , Things in IoT, Characteristics of IoT, IoT Enabling

technologies: WSN, Cloud Computing, Big Data Analytics, Communication protocols ,

Embedded systems, IoT vs M2M. IoT Smart-X applications: Home Automation, Cities,

Environment, Energy, Logistics, Agriculture, Industry, Health & Lifestyle.

Introduction to sensors, Transducers, Classification, Roles of sensors in IOT, Various types of

sensors, Design of sensors, sensor architecture, special requirements for IOT sensors, Role of

actuators, types of actuators.

Physical device – Arduino Interfaces, Hardware requirement for Arduino, Connecting remotely

over the network using VNC, GPIO Basics, Controlling GPIO Outputs Using a Web Interface, –

Programming, APIs / Packages, Introduction to Raspberry Pi Interfaces, Beagle bone Interfaces

Section2:

Protocol Standardization for IoT , M2M and WSN Protocols, RFID Protocols & NFC protocols,

Issues with IoT Standardization ,Unified Data Standards ,Protocols – IEEE 802.15.4, Zigbee,

IPv6 technologies for the IoT, IPv6 over low-power WPAN (6LoWPAN)

Hardwire the sensors with different protocols such as HART, MODBUS-Serial & Parallel,

Ethernet, BACNet , Current, M2M etc.

IOT Analytics : Role of Analytics in IOT, Data visualization Techniques, Introduction to R

Programming, Statistical Methods.

Internet of things Challenges: Vulnerabilities of IoT, Security, Privacy & Trust

for IoT, Security requirements, Threat analysis, Use cases and misuse cases.

Internet of Things Applications : Smart Metering, e-Health Body Area Networks, City

Automation, Automotive Applications, Home Automation, Smart Cards, Plant Automation,

Real life examples of IOT in Manufacturing Sector


1. Interfacing LED, Push button, Traffic light, Automatic Street light

2. Interfacing IR sensors and Buzzer, Intrusion Detection, Music Player

3. Interfacing Temperature sensor, Ethernet shield. Tweet Sensor data

4. Weather monitoring system to things speak

5. Connecting Arduino and Android Application development.

6. Smart home monitoring Humidity, Gas, Temp

7. Health Monitoring using IoT

8. Automotive security Application - Vehicle Anti theft detection.

9. Analytics using R.




1.

2.

Text Books:

1. Arshdeep Bahga, Vijay Madisetti, “Internet of Things – A hands-on approach”, Universities

Press, 2015.

2. Dr. Ovidiu Vermesan, Dr. Peter Friess, “Internet of Things: Converging Technologies for

Smart Environments and Integrated Ecosystems”, River Publishers, ISBN-10: 8792982735

Reference Books:

1. Marco Schwartz, “Internet of Things with the Arduino Yun”, Packt Publishing, 2014.

2. Daniel Minoli John Wiley & Sons ,Building the internet of things with ipv6 and mipv6, The

Evolving World of M2M Communications, ISBN: 978-1-118-47347-4

3. Cassimally, Hakim, “Designing the Internet of Things”, Wiley Publications, ISBN

10: 111843062X

Course Outcomes:


1. Learn the terminology, technology and its applications of IoT

2. Analyze Embedded suite widely used in IoT.

3 . Describe the concept of M2M with necessary protocols

4. Uunderstand the cloud storage for IoT applications.

5. Optimize resources for different IoT applications

6. Understand Real world IoT Design constraint

https://www.abebooks.com/servlet/SearchResults?an=Cassimally%2C+Hakim&cm_sp=det-_-bdp-_-author

https://www.abebooks.com/products/isbn/9781118430620?cm_sp=bdp-_-9781118430620-_-isbn10



FF No. : 654

IT9014: Robotics


Lab: 2 Hours/Week

Section 1:

Specification of a Robot, Classification of Robots, Advantage and Disadvantages of Robots,

Robot Components, Robot Sensing, Robot Degree of Freedom, Robot Joints, Robot Coordinates,

Robot Reference Frames, Programming Modes, Robot Programming Language, Robot

Applications Position and orientation representations, homogeneous transformations, frames, D-

H convention, forward kinematics, inverse kinematics Classes of tactile and non-tactile sensors,

working principles, mathematical modelling of sensors, multi-sensor integration, control issues

Section 2:

Classes of robot actuators, working principles, mathematical modelling of actuators, mechanical

construction and control issues Hardware and software architectures of robot controllers, robot

programming paradigms, robot programming languages Path types, point-to-point-motion,

continuous path motion, spline interpolation


1. Build robot arms using mechanical components and motor drive.

2. Build robot for given configuration and degrees of freedom.

3. Design a pick and place robot for given operation

4. Robot path planning and path tracking using GPS local map dictionary.

5. Develop a wall Follower robot

6. Implement a coffee maker configuration

7. Controls for a Pneumatic Robot.

8. 2D simulation of a 3 DOF robot arm. (C / C++ OR MATLAB)


Text Books

1. Introduction to robotics: Mechanics and Control, John J. Craig, Prentice Hall, 2004

2. Introduction to robotics. Phillip John McKerrow. Addison-Wesley Publishing Company, 1991

3. Robot Dynamics and Control. Mark W. Spong and M. Vidyasagar.John Wiley and Sons, 1996

4. Robot Motion and Control (Recent Developments) by M.Thoma& M. Morari

Reference Books

1. Robotics: Control, Sensing, Vision and Intelligence, K.S. Fu, R.C. Gonzalez, C.S.G. Lee,

McGraw Hill Education (India Ed.)

2. Robotics and Automation Handbook, Thomas R. Kurfess, CRC Press



Course Outcomes:

The student will be able to-

1. Translate specifications to the components of robots such as arms, linkages, drive systems

and end effectors.

2. Understand mechanics and kinematics of robots.

3. Select sensors and design their signal conditioning circuit.

4. Demonstrate use of engineering methods and problem solving towards design

of the specified robot.

5. Use robot operating system for application development

6. Apply prerequisite knowledge of programming, Microcontrollers, sensor

interfacing, and operating systems for development of robot.



FF No. : 654

IT9015: Cloud Computing


Lab: 2 Hours/Week


Introduction to Cloud Computing, Definition, Characteristics, Components, Cloud Service

Models: SaaS, PaaS, IaaS, Cloud provider, benefits and limitations, Deploy application over

cloud, Cloud computing vs. Cluster computing vs. Grid computing. Open Stack vs Cloud Stack,

Role of Open Standards,Infrastructure as a Service (IaaS): Virtualization Technology: Different

approaches to virtualization, Hypervisors, Machine Image, Virtual Machine (VM).

Virtualization: Server, Storage, Network. Virtual Machine (resource) provisioning and

manageability, storage as a service, Data storage in cloud computing(storage as a

service),Multitenant software: Multi-entity support, Multi-schema approach, Multitenance using

cloud data stores, Data access control for enterprise applications,Cloud file-systems: GFS and

HDFS, BigTable, Features and comparisons among GFS, HDFS etc.,Databases on Cloud:

NoSQL, MogoDB, HBase, Hive, Dynamo, Graph databases


Map-Reduce and extensions: Parallel computing, The map-Reduce model, Parallel efficiency of

Map-Reduce, Relational operations using Map-Reduce, Example/Application of Map-

reduce,PaaS: Introduction to PaaS - What is PaaS, Service Oriented Architecture (SOA). Cloud

Platform and Management - computation, storage

SaaS: Introduction to SaaS, Web services, Web 2.0, Web OS, Case Study on SaaS Service

Management in Cloud Computing: Service Level Agreements(SLAs), Billing & Accounting,

Comparing Scaling Hardware: Traditional vs. Cloud, Economics of scaling: Benefitting

enormously, Managing Data - Looking at Data, Scalability & Cloud Services, Database & Data

Stores in Cloud, Large Scale Data Processing

Cloud Security: Infrastructure Security - Network level security, Host level security, Application

level security. Data security and Storage - Data privacy and security Issues, Jurisdictional issues

raised by Data location: Identity & Access Management, Access Control, Trust, Reputation,

Risk, Authentication in cloud computing, Client access in cloud, Cloud contracting Model,

Commercial and business considerations


1. Implement application using NoSQL

2. Implement application using Map-Reduce

3. Implement SaaS application and host it on Cloud Platform


1. Judith Hurwitz, R.Bloor, M.Kanfman, F.Halper, “Cloud Computing for Dummies”, Wiley

India.

2. Ronald Krutz and Russell Dean Vines, “Cloud Security”, Wiley-India


1. Barrie Sosinsky, “Cloud Computing Bible”, Wiley India



2. Antohy T Velte, et.al, “Cloud Computing : A Practical Approach”, McGraw Hill.

3. McGraw Hill, “Cloud Computing”, Que Publishing.

Course Outcomes:


1. Illustrate the architecture and infrastructure of cloud computing, including SaaS, PaaS, IaaS,

public cloud, private cloud, hybrid cloud, etc.

2. Investigate the resource virtualization technique for a given business case

3. Choose the appropriate file system and database for a given business case

4. Develop a algorithm for a given business case using Map-Reduce model

5. Build a SaaS solution for a real world problem with collaborative efforts

6. Identify the challenges in Cloud Management and Cloud Security



FF No. : 654

IT9016: GPU Computing and Applications


Lab: 2 Hours/Week


Fundamentals of Parallel computing and architectures (8 Hours)

Parallel programming definition, motivation, Types and levels of parallelism, Different grains of

parallelism, data dependence graph, data parallelism, functional parallelism, Flynn’s

classification of multi-processors, Definition of thread and process, programming parallel

computers, Parallel computing architectures (multi-core CPUs, GPUs, traditional multi-processor

system, Xeon-Phi, Jetson Kit, Kilocore processor), multiprocessor and multicomputer systems,

interconnection networks, Modern GPU architecture (in brief), Performance comparison:

Speedup, Gain in time and scalability.

Introduction to GPU architecture and parallel algorithms (8 Hours)

Introduction to Modern GPU Tesla architecture, Types of GPU memories: global, shared, texture

memory and their properties and uses, Streaming processor (SP), Streaming multiprocessor

(SM), Special Functional unit (SFU), SM instruction types

Fosters Parallel algorithm design, Designing GPU parallel algorithm for pattern clustering.

Introduction to CUDA (8 Hours)

Introduction to CUDA programming model: threads, blocks, grid, Kernel, Kernel definition and

kernel launch configuration, Use of GPU memories: global, shared, texture and constant

memories, shared memory: organization, bank conflicts, global memory coalesced accesses,

CUDA APIs: for memory allocation, synchronization, Execution of a CUDA kernel on GPU:

concept of warp, warp divergence, CUDA example programs (Vector dot product, Vector-Matrix

multiplication and etc). Atomic operations in CUDA and their use.


Scientific Computing and problem solving on GPU-Part1 (6 Hours)

Parallel computation of binomial coefficients, Multi-variate polnomials in power form and their

GPU parallel evaluation, Polynomials in Bernstein form and parallel computation of Bernstein

coefficients: conventional method and using matrix method.

Applications:- image processing, HCR, processing of large images, Data mining:- Clustering

Scientific Computing and problem solving on GPU-Part2 (5 Hours)

Parallel reduction on GPU and its applications. Compute intensive research oriented

problems decided by instructor and their GPU parallelization. GPU Parallel implementation of

nearest neighbor classifier for large data sets.

Applications:- Accelerating RDBMS queries on GPU in parallel.



CUDA code optimization and Performance improvement (5 Hours)

CUDA code optimization: Memory optimization, Control flow optimization, Execution

configuration optimization and Instruction optimization, Concept and application of page locked

host memory, Single vss double precision computing on GPU: precision vss speed of

computation, choosing correct precision for a real GPU application, memory leaks and

associated problems, CUDA tools: cuda-memcheck and profiler.

List of Practical’s

1. Parallel GPU implementation of vector-vector operations

2. Parallel GPU implementation of vector-Matrix operations

3. Parallel computation of binomial coefficient matrix

4. Parallel GPU implementation of Matrix-Matrix operations

5. Assignment focusing on optimization of data transfer between CPU and

GPU:using page locked host memory and to avoid the data transfer

6. Assignment focusing on memory optimization: use of GPU shared, constant and

texture memory.

7. Parallel GPU implementation involving kernel looping.

8.Working of CUDA tools MemCheck and & Visual Profiler

9. A small application development using CUDA

Text Books:

1. David Kirk, Wen-mei Hwu, Programming Massively Parallel Processors: A Hands-On

Approach, 2 nd Edition, ELSEVIER Inc.

2. Jason Sanders and Edward Kandrot, CUDA by Example: An Introduction to General-Purpose

GPU Programming, Addison Wesley

Reference Books:

1. Michael J. Quinn, Parallel Programming in C with MPI and OpenMP , Tata McGraw-Hill

Edition

2. Kai Hwong, Advanced computer architecture, Tata McGraw-Hill Edition

Course Outcomes:


1. Recognize fundamentals of parallel computing and architectures available

2. Design parallel algorithms that better maps on GPU architecture

3. Write CUDA applications for execution on GPU

4. Apply parallel computing methods to scientific and engineering problems

5. Apply parallel computing methods to research problems and real applications

6. Optimize CUDA code using tools for performance improvements



FF No. : 654

IT9018: Image Processing


Lab: 2 Hours/Week

Section 1:

Introduction, Elements of image processing system, Scenes and Images, Vector Algebra, Human

Visual System, color vision color model: RGB, HVS, YUV, CMYK, YCbCr and some basic

relationships between pixels, linear and nonlinear operations. Image types (optical and

microwave), Image file formats (BMP, tiff, jpeg, ico, ceos, GIF, png, raster image format). Image

sampling and quantization. Thresholding, Spatial domain techniques { Image Negative, Contrast

stretching, gray level slicing, bit plane slicing, histogram and histogram equalization, local

enhancement technique, image subtraction and image average, Image Smoothening: low-pass

spatial filters, median filtering, Image Sharpening: high-pass spatial filter, derivative filters and

its application.

Image segmentation- Classification of image segmentation techniques: Watershed Segmentation,

Edge-based Segmentation, region approach, clustering techniques, edge-based, classification of

edges and edge detection, watershed transformation.

Section2:

Introduction to Image compression and its need, Coding redundancy, classification of

compression techniques (Lossy and lossless- JPEG, RLE, Huffman, Shannon fano), Object

Recognition { Need, Automated object recognition system, pattern and pattern class, relationship

between image processing and object recognition, approaches to object recognition. Introduction

to two dimensional orthogonal and unitary transforms, properties of unitary transforms. One-two

dimensional discrete Fourier Transform (DFT). Cosine. Singular Value Decomposition,

Applications of transforms in Image processing. Sub band coding, Haar Transform – it’s

application as a Wavelet, multi resolution expansions, Other Applications of Wavelet in image

processing.

List of Practical(THL)

1. Write matlab code to display following binary images

Square

Triangle

Circle

Write matlab code to perform following operations on images

Flip Image along horizontal and vertical direction.

Enhance quality of a given image by changing brightness of image.

Image negation operation.

Change contrast of a given Image.

2. Write Matlab code to implement pseudo colouring operation of a given image.

Write Matlab Code for Pseudo Colour of Image by using Gray to colour

transform.

3. Study of different file formats e.g. BMP, TIFF and extraction of attributes of

BMP.

4. Write matlab code to find following statistical properties of an image.

Mean



Median

Variance

Standard deviation

Covariance.

5. Write matlab code to enhance image quality by using following techniques

Logarithmic transformation

Histogram Equalization

Gray level slicing with and without background.

Inverse transformation.

6. Read an Image and Perform singular value decomposition. Retain only k largest

singular values and reconstruct the image. Also Compute the Compression ratio.

7. Write matlab code to enhance image quality by using following techniques

Low pass and weighted low pass filter.

Median filter.

Laplacian mask.

8. Write matlab code for edge detection using Sobel, Prewitt and Roberts operators.

9. Write C-language code to find out Huffman code for the following word

COMMITTEE.

10. Write matlab code to design encoder and decoder by using Arithmetic coding for

the following word MUMMY. (Probabilities of symbols M-0.4, U-0.2, X-0.3,Y-

0.1 ).

11. Write matlab code to find out Fourier spectrum, phase angle and power spectrum

of binary image and gray scale image.

Text Books:

1. Rafael Gonzalez & Richard Woods, “Digital Image Processing,” 3rd Edition, Pearson publi-

cations, ISBN 0132345633.

2. Anil K. Jain, “Fundamental of Digital Image Processing,” 5th Edition, PHI publication, ISBN

13: 9780133361650.

Reference Books:

1. Pratt, “Digital Image Processing,” Wiley Publication, 3rd Edition , ISBN 0-471-37407-5.

2. K.R. Castleman, “Digital Image Processing,” 3rd Edition, Prentice Hall: Upper Saddle River,

NJ, 3, ISBN 0-13-211467 -4.

3. K. D. Soman and K. I. Ramchandran, “Insight into wavelets - From theory to practice,” 2nd

Edition PHI, 2005.

Course Outcomes:

The student will be able to

1. Describe image model

2. Perform spatial filtering on image

3. Identify Image Segmentation techniques.

4. Apply lossless and lossy compression techniques for image compression.

5. Use various image transforms to analyze and modify image.

6. Understand Wavelet transform for Image Processing Applications.



FF No. : 654

IT9019: Data Acquisition System


Lab: 2 Hours/Week

Section 1:

Systems and Measurements

Introduction to data acquisition system(DAS), Block Diagram of DAS, Multichannel DAS,

Generalized measurement system, Characteristics of measuring devices, accuracy, precision,

errors, linearity, hysteresis, threshold, repeatability, reliability calibration., Basic concepts of

feedback control system:- open loop and closed loop.

Sensors and Signal Conditioning circuits

Introduction to the sensors, Types of sensors: Temperature sensor (LM35,RTD, Thermocouple),

Light sensor(photodiode, optocoupler), Distance and range sensor (IR,LVDT), Accelerometer

sensor, Touch screen sensor. Signal conditioning circuits: Analog and Digital, Opamp in signal

conditioning circuits as amplifier.

ARM Microcontroller

Architecture, Block diagram, Features, Data / Programme Memory, Reg set, Reg Bank, Special

Function Registers, Data Memory, Programme Memory, Interrupt Structure , Timer Prog ,Serial

Port Prog , Misc Features.

Section 2:

I/O interfacing & Bus Systems

Introduction to the BUS System, Bus design issues, Synchronous Bus, Asynchronous Bus, Bus

Allocation, Bus Priority. Interfacing Buses:I2C, SPI ,CAN , SCADA and RS 232C .

Relay Sequencer and Ladder diagrams

Introduction to the relay sequencer. Elements of Ladder Diagrams (limit, pressure, level,

thermal, mechanical switch) and examples based on ladder diagrams. Data Loggers.

Programmable Logic Controls

PLC : PLC block diagram and its function, PLC Operation: I/O scan mode, execution mode,

PLC Software Functions: Timer, accumulated timer, counters. Advantages of PLC over Relay

sequencer.



List of Project Domains:

1. Project based on signal conditioning circuit for sensors.

2. Project based on temperature controller using LM35

3. Project based on IR sensor.

4. Project based on ARM controller and any sensor

5. Case study on PLC systems

Text Books:

1. “Process control instrumentation”, C.D. Johnson, Pearson education, ISBN-81-7758-

410-3, seventh edition.

2. “Opamp and linear integrated circuits”, Ramakant Gaikwad, PHI publication, ISBN-

9780132808682, 4th edition.

Reference Books :

1. “Instrumentation Devices and System”, Rangan, G .R. Sarma, V.S.V. Mani, Tata

McGraw-Hill, ISBN-0-07-463350-3, 2nd Edition.

2. Microcontroller Handbook

Course Outcomes:


1. Define the characteristics of measuring devices for an instrument.

2. Identify the functioning of measuring devices in an industrial process.

3. Design elements of signal conditioning circuit that are necessary for sensors.

4. Describe the structural units of Microcontroller.

5. Interconnect devices using communication buses.

6. Develop programs for the process control systems using sensors.



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Design and Development

This course emphasizes project life cycle phase’s requirement, system analysis and system

design. A further aim is for students to heighten personal awareness of the importance of

developing strategies for themselves and working with peers to create desired outcomes. The

project requires the students to conceive, design, implement and operate a mechanism (the

design problem). The mechanism may be entirely of the student’s own design, or it may

incorporate off-the-shelf parts.

Various domains under which multiple projects can be implemented are defined at each semester

for creating or developing new innovative projects.

Course Outcomes:


1. Identify Real World Problems

2. Apply Computing Solutions to Real World Problems

3. Construct a Solution Model to Real World Problem

4. Select Design Pattern to Best approach the Solution.

5. Lay Down rules to Minimise Adverse Impact of Design Implementation

6. Adapt to changing Technological and Human resource advances.



DD1: Web Designing application

Topi

c 1:

Introduction to web technology and research areas:

WWW means World Wide Web is a simple word with the world inside it, all communication

protocols like http, file transfer protocols and programming paradigm comes under web technology.

Semantic Web, Web mining, Web Services and RDF, Web Information retrieval are the some research

area under Web technology.

2 hrs

Topi

c 2:

Design a website using HTML and CSS for any system:

Client-side (i.e. frontend) web development involves everything users see on their screens. HTML

tells a browser how to display the content of web pages, while CSS styles that content. Bootstrap is a

helpful framework for managing HTML and CSS.

2 hrs

Topi

c 3:

Design interactive web pages using JavaScript, JQuery:

Client-side (i.e. frontend) web development involves everything users see on their screens. JS makes

web pages interactive. There are many JavaScript libraries and frameworks for faster and easier web

development.

2 hrs

Topi

c 4:

Develop a dynamic web application using PHP & MySQL/MongoDB:

For server-side programming languages, they are used to create the logic of websites and

applications. Web application needs a place to store its data, and that’s what a database is used for.

2 hrs

Topi

c 5:

Design a website using Content management system of WordPress:

WordPress is an open source Content Management System (CMS), which allows the users to build

dynamic websites and blogs.

2 hrs

DD1: Pattern Recognition Application

Topic

1:

Introduction to (Pattern recognition Application) and description of research areas under the same

domain.

-What is pattern recognition application? Why it is necessary? Research, designand development

problems in pattern recognition.

-

2 hrs

Topic

2:

Design/ Develop Application

Of overall pattern recognition system for visual pattern recognition e.g. handwritten character

recognition

Definition of a pattern, features, types of features, representation of pattern in computer memory,

Feature extraction problems: - How many features? What features to extract?

-Extracting spatial features from a handwritten digit image, Representing such images in memory

along with class label. Matching on the basis of features using Euclidean distance

2 hrs



Top

ic3:

Design/Develop application

Of overall pattern recognition system for samples from a large database

- Database rows and patterns

- Computational complexity when dealing with large samples

- Available architectures for HPC

2 hrs

Top

ic4:

Design/Develop Application for

Pattern Classification system for multi-class problems e.g. Using Fisher Iris Data for plant

classification and using K-NN classifier/ other classifiers

2 hrs

Top

ic5:

Design/Develop Application for

Pattern Clustering system using c-means clustering. Use of clustering and classification for

measuring the performance of the system. Confusion matrix, %classification, %Recognition and

recall ti--*-*--me per pattern.

2 hrs

DD1: Network Applications

Topic

1:

Transport Layer and Sockets and Socket Programming 2 hrs

Topic

2:

Application Development

TCP Echo Server, TCP Echo Client

2 hrs

Topic

3:

Socket Option and Elementary UDP Socket

Getsocket and setsocket functions – generic socket options, IP socket options, ICMP socket

options, Elementary UDP sockets: UDP echo Server, UDP echo Client, Multiplexing TCP and

UDP sockets.

2 hrs

Topic

4:

Advanced Sockets

IPv4 and IPv6 Interoperability: IPv4 Client, IPv6 Server, IPv6 Client, IPv4 Server, IPv6 Address

Testing Macros, IPV6_ADDRFORM Socket Option ICMPv4 and ICMPv6.

2 hrs

Topic

5:

Routing Sockets

Data link Socket, Address Structure, Reading and Writing, Interface Name and Index Functions,

data link access, raw socket (creation input, output)

2 hrs



DD1: Microcontroller Applications

Topic 1: Introduction to microcontrollers , 8051, PIC, ARM, Block Diagram of Microcontroller

Research area using Microcontrollers: Smart Agriculture, Waste Management, Medicine etc.

2 hrs

Topic 2: Design/Develop a system using Microcontrollers for Smart Agriculture. 2 hrs

Topic 3: Design/Develop a system using Microcontrollers for home automation and Smart cities

.

2 hrs

Topic 4: Design/Develop a system using Microcontroller for Waste Management which will contribute to

Swachh Bharat Mission.

2 hrs

Topic 5: Design/Develop a system using Microcontroller for in medicine and Health Care, Aid to

Physically Handicap.

2 hrs

DD1: Client Server Application

Topic 1: Introduction to Client Server Computing

Discussion of research areas such as

Cloud computing (Architecture,Security,Services)

Grid Computing,

Distributed computing.

Web Application and Web Services development.

Mobile Application development(Opportunities,Challenges )

2 hrs

Topic 2: Design and Develop Web Application by using technologies such as Java /.NET/Grails .etc

(E.x.Online Exam or Reservation /Registration system)

2 hrs



Topic 3: Design and develop application based on RMI/RPC

(E.g Multiplayer Game in LAN environment)

2 hrs

Topic 4: Design and Develop Mobile application using Android Technology to solve day to day problems

(E.g. Finding Near by Places or order and delivery applications)

2 hrs

Topic 5: Design and develop Grid Computing environment for solving complex scientific computing

tasks.

(Example : development of Grid of GPUs )

2 hrs

DD1: Data Applications

Topic 1: Introduction to Data Modeling and Business Modeling using ER Diagrams and UML. 2 hrs

Topic 2: Design/ Develop a system in which you can practice Create

programming language APIs for open and close a

"connection" (in a db context, initialize your library, open

your db file, and create an access handle for other API calls),

creating a table, insert, delete, update, and select with a simple

where clause.

2 hrs

Topic 3: Design/Develop a project which helps Storing the data using a simple format to begin with,

possibly something like JSON.Encoding variable-sized Rows and standard-sized Pages.

Comparing persistent metadata (ie, table definitions) versus transient metadata (which is

actually used in small devices where storage of persistent metadata can be problematic).

2 hrs



Topic 4: Design/Develop Data Intensive systems like health care systems, Hotel management

system,School Management System,Gym management System,Student record system,Library

management System

Inventory Management System.

2 hrs

Topic 5: Design/Develop projects on Mongo DB 2 hrs

DD1: Parallel Computing

Topic

1:

Introduction to (Parallel Computing area) and description of research areas under the same

domain.

Need og HPC, What is HPC ? What is parallel computing? Serial vss parallel processing,

Advantages, General computing architectures, speedup and scale up

Introduction to CUDA

2 hrs

Topic

2:

Design/ Development of

Parallel computing systems using GPU and CUDA.

Scientific computing systems involving large matrices, vectors and polynomials

GPU memories

2 hrs

Topic

3:

Design/Development of

Parallel computing systems using GPU and CUDA to accelerate long running RDBMS queries.

2 hrs

Topic

4:

Design/Development of

Parallel computing systems using GPU and CUDA to accelerate

Pattern recognition system

-CUDA code optimization tricks

2 hrs

Topic

5:

Design/Develop of

Parallel computing systems using GPU and CUDA to acceleratePattern clustering Comparison of

serial and parallel executions

2 hrs