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Syllabus
M.Tech – Computer Science & Engg Page 1
Dr. K. N. Modi University, Newai Rajasthan
(Established by the Government of Rajasthan &
Recognized by UGC under section 2(F) of UGC Act, 1956.)
Department of Computer Science &
Engineering
Syllabus
M.Tech.
(Computer Science & Engineering)
(Session 2017-18)
Syllabus
M.Tech – Computer Science & Engg Page 3
Dr. K N Modi University, Newai Student Evaluation System
Continuous Assessment
All courses undertaken by students are evaluated during the semester using internal system of
continuous assessment. The students are evaluated on class /tutorial participation, assignment work, lab
work, class tests, mid-term tests, quizzes and end semester examinations, which contribute to the final
grade awarded for the subject. Students will be notified at the commencement of each courses about the
evaluation methods being used for the courses and weightages given to the different assignments and
evaluated activities.
In order to make the evaluation system as similar and transparent with any of the globally reputed
educational institutions like N.I.Ts, I.I.Ts etc. the Dr. K. N. Modi University Academic Council has
adopted the grading practices. Here marks obtained in the continuous assessment and end semester
examination are added together and a 10-point grading system will be used to award the student with
on overall letter grade for the course (subject).
Distribution of Marks
(i) Courses without Practical Components
10Marks -IITest Midterm(d)
Marks 10 -ITest Midterm(c)
10Marks -subject)each (for each marks 5 of sAssignment Two(b)
Marks 10 - etc.Seminar Projects, Quizzes, Tests, Class ion,participat Class Attendance(a)
40 Marks
End –Term Examination - 60
__________________________________________
Total : 100
(ii)Courses with Practical Components only
Internal Practical Examination and Continuous Progress- 50
End –Term Examination (Practical) - 50
___________________________________________
Total : 100
Syllabus
M.Tech – Computer Science & Engg Page 4
Letter Grading system
Final evaluation of course is carried out on a TEN POINT grading system. Performance Grade and
Grade Points are as shown below:
Table 1
Marks Grade Value Grade Description
91 to 100 10 AA Out Standing
81 to 90 9 A+ Excellent
71 to 80 8 A Very Good
61 to 70 7 B+ Good
51 to 60 6 B Above Average
41 to 50 5 C Satisfactory
Less than 41 0 F Exposed
Absent in the University
Final Examination
0 I Incomplete
Note: In order to convert the GPA and CGPA into percentile, multiply the same with the
Conversion factor of 10.
A student who earns a minimum of 5 grade Point (C grade) in a course (subject) is declared to have
successfully completed the course, and is deemed to have earned the credits assigned to that course. A
course successfully completed cannot be repeated.
A student should have appeared for the end semester examination of the prescribed course of study
(mere appearance in the continuous assessment test is not sufficient) to be eligible for the award of the
degree in the course.
If a student is eligible for but-fails to appeared in the end semester examination, he/she will be awarded
an ‘I grade (in complete) on the grade sheet. For all practical purposes an ‘I ‘Grade is treated as an ‘F’.
If a student is not eligible to appear in the end semester examination owing to his/her not fulfilling the
minimum attendance requirements, he may be permitted to re-register for those courses in which he/she
had attendance shortage, at the next available opportunity.
Grade Point Average (GPA) &Cumulative Grade Point Average (CGPA)
Each course grade will be converted into a specific number of points associated with the grade as
mentioned in above Table 1. Here points are weighted with the number of credits assigned to a course.
The Grade Point Average (GPA) is the weighted average of grade points awarded to a student. The
Grade Point Average for each semester will be calculated only for those students who have passed all
the courses of that semester. The weighted average of GPA’s of all semester that the student has
completed at any point of time is the Cumulative Grade Point Average (CGPA) at that point of time.
CGPA up to any semester will be calculated only for those students who have passed all the courses up
to that semester.
Syllabus
M.Tech – Computer Science & Engg Page 5
Calculation of GPA and CGPA :
Example:
Table 2
Courses Credits Letter
Grade
Grade
Value
Credit
Value
Grade
Points
Mathematics 3 B+ 7 3x7 21
Chemistry 3 A 8 3x8 24
Physics 3 A+ 9 3x9 27
Language Lab 2 A 8 2x8 16
TOTAL 11 TOTAL 88
In this case GPA = Total Grade Points 88
Credits 11
Suppose the GPAS in two successive semesters are 7.0 and 8.0 with 26 and 24 respective course
credits, then the
CGPA = 7x26+8x24 = 374
26+24 50
After the results are declared, grade cards will be issued to each student which will contain the list of
courses for that semester and the grades obtained by the student, as well as GPA of that semester.
However, a conversion factor of “10”, will be included, enabling students and future employers for
transforming CGPA into percentage of marks at par with the existing practices of I.I.Ts, N.I.Ts and
A.I.C.T.E.
Minimum Eligibility Requirements in Dr. K. N. Modi University for proceeding to the next
academic year of study.
A First year Student of Dr. K. N. Modi University satisfying the below mentioned requirements is
eligible to study in the 3rd Semester of next academic year.
“Pass with Minimum C Grade in Four Theory Papers & Pass in Four Laboratory Papers in the I & II
Semester ( Combined)”
A Second year Student of Dr. K. N. Modi University satisfying the below mentioned requirements is
eligible to study in the Vth Semester of the next academic year.
“Pass with Minimum C Grade in Four Theory Papers & Pass in Four Laboratory Papers in the IIIrd&
IV Semester (Combined)”
A Third year Student of Dr. K. N. Modi University satisfying the below mentioned requirements is
eligible to study in the VIIth Semester of the next academic year.
“Pass with Minimum C Grade in Four Theory Papers & Pass in Four Laboratory Papers in the Vth&
VI Semester (Combined)”
= = 8.0
= 7.48
Syllabus
M.Tech – Computer Science & Engg Page 6
Proficiencies:
Extra-curricular activities as listed below will be offered to students of all programs. These activities
will run in both semesters and evaluated. Activities will be graded as Outstanding/Excellent/
Very Good/Good/ Above Average/ Satisfactory/Exposedl/Incomplete.
The extracurricular activities are sports, cultural:
1. Tennis 2. Athletics 3. Table Tennis
4. Badminton 5. Gymnastics 6. Chess
7. Throw Ball 8. Gardening 9. Organization & Management
10. Football 11. Electronics 12. Fine Arts & Paintings
13. Cricket 14. Social Service Club 15. Rovers & Rangers
16. Volleyball 17. Music and Dramatics 18. Model and Sculptures
19. Basketball 20. Debate 21. Equestrian Race
22. Kho - Kho 23. Robotics 24. Yoga & Meditation
25. Art & Photography Club
26. Cultural Club 27. Any other activity with prior approval of the President.
Guideline for submission of assignment
A. Assignments (Theory)
Following are the guidelines of assignments, their evaluation.
Assignment means a set of work, tasks and/or numerical problems given to the student, on the basis
of topics recently covered in the class as homework to be solved and submitted, within the time
frame given by the faculty and the examination cell. Each assignment should require 5 – 6 hours work
to be done by the student. The Date of Submission (DOS) duly announced on the Date of Allotment
(DOA) to the student and duly mentioned in the Academic Calendar.
1. In a multiple-section course, the preparation, duplication and distribution is the responsibility of the Course Coordinator.
a. Allotment of an assignment should be made in the academic calendar of the semester. b. The Date of Submission (DOS) of an assignment should be the tutorial in the prescribed
week wherever applicable. Where tutorials are not scheduled, submission should be in the first lecture of the subsequent week.
2. Assignment should NOT have any descriptive questions (that can be directly copied from a book or from the internet). However, in those course(s) where only descriptive problems are feasible, prior approval for the same is to be sought from the President in writing mentioning the justification for the same.
Syllabus
M.Tech – Computer Science & Engg Page 7
3. The effective teaching for semester is generally of 14 weeks. The minimum number of assignments to be given throughout the semester is two. No assignment should be due in the last week of the semester.
4. The assignment is to be submitted on or before the Date of Submission (DOS) as announced. 5. The evaluation of numerical assignment will be done through a test based on the assignment.
The test would comprise of one of the questions from the assignment to be solved in the class. The following process may be adopted for the purpose:
a) Ask students to bring the assignment sheets to the class (along with calculators, if required).
b) Take 60 sheets of A4 sheets. On each sheet write the roll number of a student and the question number from the assignment that he/she has to solve. Different question for adjacent students. Make student sit roll-number-wise, so that no two adjacent students are given the same problem.
c) Give student just sufficient time to solve the problem assuming that they have done the assignment at home.
d) Make sure they have submitted the assignment before the start of the test and that they are not copying.
6. Marks to be awarded in these assignment-quizzes only if the assignment is submitted in time. 7. For non-numeric assignments the rest could have questions based on the assignment. Make sure
that there are multiple shuffled sets for these tests to prevent copying. The comments on the assignments are mandatory. The marks are to be allotted to submission and test separately.
8. Minimal time to be given to the students to attempt the said tests because they should not require any thinking for solving these as they have already solved these problems earlier.
9. The evaluated assignments/tests are to be shown to the student (as done in scrutiny of the End Term Examination answer sheets) and are to be retained by the instructor. The evaluated assignments/test should be retained till the next assignment is evaluated. This is to permit checking by designated authority at any instance.
10. The assignment-based tests should be given on the Date of Assignment (DOS). Only the students who have submitted the assignment on time should be allowed to take the test, otherwise, the student should be awarded ZERO marks for the same.
11. This procedure is to be announced and explained to the students in the very first class. The importance of timely submission of assignments should be explained.
12. No deviation from this policy is permitted except with a written prior approval from the president.
B. Laboratory Assessments
Following are the guidelines for the conduct and evaluation of practical in all courses with laboratory
components:
1. A practical is where a student is taken to a laboratory and is asked to perform a set of task on the given computer, equipment or on a setup comprising of devices or components. This includes on-the spot conduct of an activity to derive desired results and to report the findings.
Syllabus
M.Tech – Computer Science & Engg Page 8
2. A student will have to maintain record of the experiments performed in the labs in the bound lab notebook.
3. The lab notebook should be maintained in the format of a lab journal, where (in general) the aim of the experiment, the observations, calculations, results ad discussions are reported. These should not have any description like ‘method’ etc, unless the method itself is the aim of the experiment. Error analysis forms an essential part of the lab journal.
4. Each lab work performed is to be verified by the respective teachers in the next class. 5. A student will be evaluated on every experiment/lab performed. The components of practical
assessment are to be re-defined, notified to the student and to be strictly adhered to. 6. The records of the students attendance in the lab is to be maintained. The lab file record is
evaluated for 10 marks and the attendance weightage will be again 10 Marks.
Syllabus
M.Tech – Computer Science & Engg Page 9
DR. K. N. MODI UNIVERSITY
Syllabus and Evaluation Scheme
M.Tech. (Computer Science & Engg) - I Semester
Effective from session 2017-18
S.
N
O.
Sub Code Subject Name Period Evaluation Scheme Credit
Continuous
Assessment
Final
Exam
Total
L T P
1 01MTCS101 Advanced
computer
architecture
3 1 0 40 60 100 4
2 01MTCS102 Object oriented
software
engineering
3 1 0 40 60 100 4
3 01MTCS103 Data mining &
ware housing
3 1 0 40 60 100 4
4 01MTCS104 High performance
networks
3 1 0 40 60 100 4
LAB
1 01MPCS101 Computer
Network lab
0 0 2 50 50 100 1
2 01MPCS102 Unified
Modelling
Language Lab
0 0 2 50 50 100 1
3 01MP1010 Seamless
Learning
0 0 4 100 100 1
4 01MP1011 Co-Curricular
Activities
0 0 4 100 100 1
Total 12 4 12 460 340 800 20
Syllabus
M.Tech – Computer Science & Engg Page 10
DR. K. N. MODI UNIVERSITY
Syllabus and Evaluation Scheme
M.Tech. (Computer Science & Engg) - II Semester
Effective from session 2017-18
S.
NO.
Sub Code Subject Name Period Evaluation Scheme Credit
Continuous
Assessment
Final
Exam
Total
L T P
1 01MTCS201 Advance Java 3 1 0 40 60 100 4
2 01MTCS202 Digital Image
Processing 3
1 0 40 60 100 4
3 01MTCS203 Neural Network &
Fuzzy Logic
3 1 0 40 60 100 4
4 01MTCS204 Information Security 3 1 0 40 60 100 4
LAB
1 01MPCS201 Advance java 0 0 2 50 50 100 1
3 01MP2010 Seamless Learning 0 0 4 100 100 1
4 01MP2011 Co-Curricular
Activities
0 0 4 100 100 1
Total 12 4 10 410 290 700 19
Syllabus
M.Tech – Computer Science & Engg Page 11
DR. K. N. MODI UNIVERSITY
Syllabus and Evaluation Scheme
M.Tech. (Computer Science & Engg) - III Semester
Effective from session 2017-18
S.
NO.
Sub Code Subject Name Period Evaluation Scheme Credit
Continuous
Assessment
Final
Exam
Total
L T P
1 02MTCS301 Mobile Computing 3 1 0 40 60 100 4
2 02MTCS302 Software Testing &
Quality Management 3
1 0 40 60 100 4
LAB
1 02MPCS301 Software Testing Lab 0 0 2 50 50 100 1
2 02MPCS302 Seminar & Minor
Project
0 0 12 50 50 100 6
3 02MP3010 Seamless Learning 0 0 4 100 100 1
4 02MP3011 Co-Curricular
Activities
0 0 4 100 100 1
Total 9 3 12 380 220 600 17
Syllabus
M.Tech – Computer Science & Engg Page 12
DR. K. N. MODI UNIVERSITY
Syllabus and Evaluation Scheme
M.Tech. (Computer Science & Engg) - IV Semester
Effective from session 2017-18
S.
NO.
Sub Code Subject Name Period Evaluation Scheme Credit
Continuous
Assessment
Final
Exam
Total
L T P
1 02MPCS401 Dissertation 0 0 10 200 100 300 15
2 02MP4010 Seamless Learning 0 0 4 100 100 1
3 02MP4011 Discipline & Co-
Curricular Activities 0 0 4 100 100 1
Total 400 100 500 17
Syllabus
M.Tech – Computer Science & Engg Page 13
ADVANCED COMPUTER ARCHITECTURE
CODE: 01MTCS101
Course Objective:
The course is intended to understand the architecture of the computer, how the data is flowed in
the different parts of the computer and how it is processed by the computer. To understand the
different memory architectures used in the computer.
Unit – 1 : Review of Basic Organization and Architectural Techniques
RISC processors, Characteristics of RISC processors, RISC Vs CISC, Classification of
Instruction Set Architectures, Review of performance measurements, Basic parallel processing
techniques: instruction level, thread level and process level.
Unit – 2 : Parallelism
Classification of parallel architectures, Trends towards parallel processing, parallelism in Uni
processor systems, , parallel processing applications.
Bus structures and standards, Synchronous and asynchronous buses, Types and uses of storage
devices, Interfacing I/O to the rest of the system, Reliability and availability, I/O system design,
Platform architecture
Unit – 3 : Instruction Level Parallelism
Basic concepts of pipelining, Arithmetic pipelines, Instruction pipelines, Hazards in a pipeline:
structural, data, and control hazards, Overview of hazard resolution techniques, Dynamic
instruction scheduling, Classification of pipeline processors, nonlinear pipeline and reservation
table, Branch prediction techniques, Instruction-level parallelism using software approaches,
Superscalar techniques, Speculative execution
Unit – 4 : Processors & Memory Hierarchies
Pentium Processor: IA 32 and P6 micro architectures, ARM Processor, vector processing.
Basic concept of hierarchical memory organization, , memory hierarchy in parallel processing
systems, Main memories, Cache memory design and implementation, Virtual memory design
and implementation, Secondary memory technology, RAID
Reference Books:
1. Advanced Computer Architecture Book by Kai Hwang
2. Mano, M “Computer System and Architecture”, PHI.
3. Malvino “Digital Computer Electronics: An Introduction to Microcomputers, 3/e”,
McGraw Hill.
4. Pal Chaudhuri, P. “Computer Organization & Design”, PHI.
Syllabus
M.Tech – Computer Science & Engg Page 14
OBJECT ORIENTED SOFTWARE ENGINEERING
CODE: 01MTCS102
Course Objective:
To understand the software development requirements, life cycles, risks, testing and the
maintenance of the software. Software development is contain many phases with the UML
building blocks.
Unit I:
Software Engineering Development, Software processes and characteristics, Software Life Cycle
Models, Standards for developing life cycle models like ISO 9001, Introduction to Object
Oriented Methodology. Size estimation (line of code), cost estimation models.
Unit II:
Model Architecture, Requirements Model, Requirement Engineering Analysis Model, Design
Model, Implementation Model, Test Model, Requirement documentation, nature of SRS,
Characteristic and organization of SRS. Cohesion and Coupling
Unit III:
Object oriented design, Basic Building Blocks of UML, Use case approach, requirement using
DFD, A Conceptual Model of UML, Basic Structural Modelling, UML Diagrams
Unit IV:
Risk Management, Testing process, Design of test cases ,unit testing , Integration testing and
system testing, functional testing , structural testing, Regression testing ,testing tools and
standards.
Unit V:
Management of maintenance, maintenance process, maintenance models, reverse engineering,
software re-engineering documentation.
Reference Books:
1. Stephen R. Scach, “Classical & Object Oriented Software Engineering with UML and
Java”, McGraw Hill, 1999.
2. R.Fairley , ”Software Engineering Concepts”, Tata McGraw Hill,1977.
3. P.Jalote, “An Integrated approach to Software Engineering “ , Narosa,1991.
4. James Peter ,W.Pedrycz,:”software Engineering “,John Wiley & sons.
DATA MINING & DATA WAREHOUSING
CODE: 01MTCS103
Course Objective: The course is concerned to analysis of database used for reporting and
finding out the useful data and result from that database. The data stored in the warehouse
is uploaded from the operational systems. Data Mining is the analysis step of the Knowledge
Discovery in Databases process.
Unit I: Data Mining
Basics of data mining, Data mining techniques, KDD (Knowledge Discovery in Database
Process), Application and Challenges of Data Mining, Data Preprocessing, Data Integration and
Syllabus
M.Tech – Computer Science & Engg Page 15
Transformation, Data Reduction, Discretization and Concept Hierarchy Generation, Introduction
of Web Structure Mining, Web Usage Mining, Spatial Mining, Text Mining, Security Issue,
Privacy Issue, Ethical Issue.
Unit II: Mining Association Rules in Large Databases
Association Rule Mining, Single-Dimensional Boolean Association Rules, Multi-Level
Association Rule, Apriori Algorithm, Time series mining association rules, latest trends in
association rules mining, Constraint based association rule mining.
Unit III: Classification and Prediction
Classification, Supervised & Unsupervised approaches, Measuring central tendency, Clustering
Distance Measures, Types of Clustering, K-Means Algorithm, Decision Tree Induction,
Bayesian Classification, Association Rule Based, Other Classification Methods, Prediction,
Classifier Accuracy, Categorization of methods, Partitioning methods, Cluster Analysis: Data
types in cluster analysis, Categories of clustering methods, Partitioning methods, Parallel
approaches to clustering and outlier analysis, Hierarchical Clustering- CURE and Chameleon,
Density Based Methods-DBSCAN, OPTICS, Grid Based Methods- STING, CLIQUE, Model
Based Method –Statistical Approach, Neural Network approach.
Unit IV: Data Warehousing
Concept and Introduction, Need for data warehousing, Basic elements of data warehousing, Data
Mart, Data Warehouse Architecture, extract and load Process, Clean and Transform data, Star
,Snowflake and Galaxy Schemas for Multidimensional databases, Fact constellation and
dimension data, Partitioning Strategy-Horizontal and Vertical Partitioning.
Unit V: OLAP
Data Warehouse and OLAP, Multidimensional data models and different OLAP Operations,
OLAP Server: ROLAP, MOLAP, Data Warehouse implementation, Data Cubes constructions,
Efficient Computation of Data Cubes, Processing of OLAP queries, Indexing Data, Data Cube
Computation and Data Generalization.
Reference Books:
1. M.H.Dunham,”Data Mining: Introductory and Advanced Topics” Pearson Education
2. Jiawei Han, Micheline Kamber,”Data Mining Concepts & Techniques” Elsevier
3. Sam Anahory, Dennis Murray, “Data Warehousing in the Real World: A Practical Guide
for Building Decision Support Systems, Pearson Education
4. Mallach,”Data Warehousing System”, McGraw –Hill
Syllabus
M.Tech – Computer Science & Engg Page 16
HIGH PERFORMANCE NETWORKS
CODE: 01MTCS104
Course Objective:
This course provides knowledge about various types of Network, Network Topologies, and
protocols.
UNIT – I : Introduction The Motivation for Internetworking; Need for Speed and Quality of Service; History of
Networking and Internet; Advanced TCP/IP and ATM Networks; Internet Services; Internet
Architecture; Interconnection through IP Routers; Standards; TCP Services; TCP format and
connection management; Encapsulation in IP; UDP Services, Format and Encapsulation in IP; IP
Services; Header format and addressing; Fragmentation and reassembly; classless and subnet
address extensions; sub netting and super netting; CIDR; IPV4 & IPv6.
UNIT –II : Error & Control Messages
ICMP; Error reporting vs Error Correction; ICMP message format and Delivery; Types of
messages; Address Resolution (ARP); BOOTP; DHCP; Remote Logging; File Transfer and
Access; Network Management and SNMP; Comparison of SMTP and HTTP; Proxy Server; The
Socket Interface.
UNIT – III : High Speed Networks Packet Switching Networks; Frame Relay Networks; Asynchronous Transfer Mode (ATM);
ATM protocol Architecture; ATM logical connections; ATM cells; ATM Service categories;
ATM Adaptation Layer; Optical Networks: SONET networks; SONET architecture; High-Speed
LANs: The Emergence of High-Speed LANs; Bridged and Switched Ethernet; Fast Ethernet;
Gigabit Ethernet; Wireless LANs: IEEE 802.11, Bluetooth; Connecting LANs: Devices,
Backbone networks, Virtual LANs.
UNIT – IV: Congestion Control and Quality of Service Congestion Control : Data traffic; Network performance; Effects of Congestion; Congestion
Control; Congestion control in TCP and Frame Relay; Link-Level Flow and Error Control; TCP
flow control.
Quality of Service: Flow Characteristics, Flow Classes; Techniques to improve QoS; Traffic
Engineering; Integrated Services; Differentiated Services; QoS in Frame Relay and
ATM;Protocols for QoS Support: Resource Reservation-RSVP; Multiprotocol Label Switching;
Real-Time Transport Protocol
UNIT – V : Wireless Telephony & Routing
Cellular Telephony; Generations; Cellular Technologies in different generations; Satellite
Networks.
Reference Books:
1. William Stallings, “High-Speed Networks and Internets, Performance and Quality of
Syllabus
M.Tech – Computer Science & Engg Page 17
Service”, Pearson Education;
2. B. Muthukumaran, “Introduction to High Performance Networks”, Vijay Nicole Imprints.
3. James F. Kurose, Keith W. Ross, “Computer Networking, A Top-Down Approach Featuring
the Internet”, Pearson Education.
4. Andrew S. Tanenbaum, “Computer Networks”, Pearson Education.
5. Behrouz A. Forouzan, “Data Communications and Networking”, Fourth Edition, McGraw
Hill.
6. Mahbub Hassan, Raj Jain, “High Performance TCP/IP Networking, Concepts, Issues, and
Solutions”, Pearson Education.
Network lab
CODE: 01MPCS101
1. Implementation of network between two or more computer using star topology
2. Implementation of the Data Link Layer framing method such as character stuffing and bit
stuffing in C.
3. Write a program for bit staffing.
4. Implementation of CRC algorithm in C.
5. Write a program for substitution method.
6. Write a program for transposition method.
7. Write a program for find out the self IP address.
8. Write program for find out the IP address of server.
9. Implementation of a Hamming code. We have to code the 4 bit data in to 7 bit data by adding
10. Parity bits. Implementation will be in C.
11. Write a socket program in C to implement a listener and a talker.
Syllabus
M.Tech – Computer Science & Engg Page 18
UML Lab
CODE: 01MPCS102
Students are required to prepare various UML diagrams for any case study.
Following diagrams should be prepared:
Use case static structure diagram
Object and Class diagram
Sequence Diagram
Collaboration Diagram
State Chart Diagram
Activity Diagram
Component Diagram
Deployment Diagram
Reference Books:
1. Object Oriented Analysis and Design using UML, Mahesh P. Matha, PHI, New Delhi
Syllabus
M.Tech – Computer Science & Engg Page 19
SECOND SEMESTER
ADVANCE JAVA CODE: 01MTCS201
Course Objective:
Understand the concepts of applet swing jdbc connectivity Serve let jsp.Write client-side Java
applications using Swing jsp servlet Work with Java Web Services.
UNIT – I : Introduction to GUI
AWT: Working with Windows, Graphics, and Text, Using AWT Controls, Layout Managers
and Menus
Swing : Frames, Panels and layouts, Swing Applets
Event Handling : Event Classes, Sources of Events, Event Listeners and Handlers, Handling
Mouse Events, Handling Keyboard events
UNIT – II : Java Database Connectivity and HTML
JDBC : Fundamentals, Establishing Connectivity and working with connection interface,
working with statements, Creating and Executing SQL statements, working with Result Set
Object & Result Set Meta Data, Merging Data from Multiple Tables: Joining, Manipulating
Databases with JDBC, Prepared Statements, Transaction Processing
HTML : Introduction to HTML, HTML Tags, Creating Forms, Creating tables, Managing home
page
UNIT – III : Servlets Introduction to Servlets, Life cycle of servlets, Java Servlets Development Kit, Creating,
Compiling and running servlet, Servlet API, Reading the servlet Parameters, Reading
Initialization parameter, Request Dispatcher, HTTP Request and Response, GET and POST
methods, Using Cookies, Session Tracking, URL Rewriting, Servlet Collaboration, Deployment
Descriptor, Servlet Input Stream and Servlet Output Stream
UNIT – IV : Java Server Pages
JSP, Advantage of JSP technology, JSP Architecture, JSP Access Model, JSP Syntax Basic,
Scripting Elements, Implicit Objects, Directive Elements, Action Elements, Custom tags,
Project Development in JSP, Java Beans, Use Bean in JSP.
UNIT – V : MVC Architecture and Struts
Introduction to MVC architecture, Struts architecture, Struts Components, Controller, Actions,
Interceptors, Result and View Components, Understanding Action Context and Action
Invocation.
Reference Books:
1. Head First Servlets and JSP By Bert Bates, Kathy Sierra, Bryan Basham, O Reilly
Syllabus
M.Tech – Computer Science & Engg Page 20
2. Java Programming Advanced Topics, Joe Wigglesworth ‘And Paula Lumby,
Course Technology (Thomson Learning), (2000).
3. The Complete Reference 3/e, Patrick Naughton and Herbert Schildt, TMH).
4. Beginning Java EE 5 From Novice to Professional by Kevin Mukhar and Chris
Zelenak with James L. Weaver and Jim Crume
5. Programming Jakarta Struts by Chuck Cavaness, Publisher: O'Reilly Media
DIGITAL IMAGE PROCESSING
CODE: 01MTCS202 Course Objective:
To understand the concepts of the digital image, image transformation, compression of a image
without affecting the image quality and representation and decryption of the digital image.
Unit I Introduction and Fundamentals
Motivation and Perspective, Applications, Components of Image Processing System, Element of
Visual Perception, A Simple Image Model, Sampling and Quantization. Image Enhancement in
Frequency Domain Fourier Transform and the Frequency Domain, Basis of Filtering in
Frequency Domain, Filters – Lowpass, High-pass; Correspondence Between Filtering in Spatial
and Frequency Domain; Smoothing Frequency Domain Filters – Gaussian Lowpass Filters;
Sharpening Frequency Domain Filters – Gaussian Highpass Filters; Homomorphic Filtering.
Unit II
Image Enhancement in Spatial Domain Introduction; Basic Gray Level Functions – Piecewise-
Linear Transformation Functions: Contrast Stretching; Histogram Specification; Histogram
Equalization; Local Enhancement; Enhancement using Arithmetic/Logic Operations – Image
Subtraction, Image Averaging; Basics of Spatial Filtering; Smoothing - Mean filter, Ordered
Statistic Filter; Sharpening – The Laplacian.
Unit III Image Restoration
A Model of Restoration Process, Noise Models, Restoration in the presence of Noise only-
Spatial Filtering – Mean Filters: Arithmetic Mean filter, Geometric Mean Filter, Order Statistic
Filters – Median Filter, Max and Min filters; Periodic Noise Reduction by Frequency Domain
Filtering – Bandpass Filters; Minimum Mean-square Error Restoration.
Unit IV
Syllabus
M.Tech – Computer Science & Engg Page 21
Morphological Image Processing Introduction, Logic Operations involving Binary Images,
Dilation and Erosion, Opening and Closing, Morphological Algorithms – Boundary Extraction,
Region Filling, Extraction of Connected Components, Convex Hull, Thinning, Thickening
Unit V Registration
Introduction, Geometric Transformation – Plane to Plane transformation, Mapping, Stereo
Imaging – Algorithms to Establish Correspondence, Algorithms to Recover Depth Segmentation
Introduction, Region Extraction, Pixel-Based Approach, Multi-level Thresholding, Local
Thresholding, Region-based Approach, Edge and Line Detection: Edge Detection, Edge
Operators, Pattern Fitting Approach, Edge Linking and Edge Following, Edge Elements
Extraction by Thresholding, Edge Detector Performance, Line Detection, Corner Detection.
References:
1. Digital Image Processing 2nd Edition, Rafael C. Gonzalvez and Richard E. Woods.
Published by: Pearson Education.
2. Digital Image Processing and Computer Vision, R.J. Schalkoff. Published by: John Wiley
and Sons, NY.
3. Fundamentals of Digital Image Processing, A.K. Jain. Published by Prentice Hall, Upper
Saddle River, NJ.
4. Sonka, Digital Image Processing and Computer Vision, Cengage Learning
5. Gonzalez and Woods, Digital Image Processing, Addison Wesley.
NEURAL NETWORKS AND FUZZY LOGIC
CODE: 01MTCS203
Course Objective:
To understand the networking concept and the parts and working of the each used in the
network. Understanding the fuzzy logics ,how it is used in the computer. and to understand the
probability theory.
UNIT – I : Introduction
Fundamentals of ANN, Biological prototype, Neural Network Concepts, Definitions Activation,
Functions, single layer and multilayer networks, Training ANNs, perceptrons, Exclusive OR
problem, Linear seperability, storage efficiency, perceptron learning - perceptron training
algorithms, Hebbian learning rule - Delta rule, Kohonen learning law, problem with the
perceptron training algorithm.Back propagation neural network, Training algorithm, network
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M.Tech – Computer Science & Engg Page 22
configurations, Back propagation error surfaces, Back propagation learning laws, Network
paralysis - Local minima, and temporal instability
UNIT – II : Networks Counter propagation Networks, Kohonen layer, Training the Kohonen layer, preprocessing the
input vectors, initializing the weight vectors.
Statistical properties, Training the Grossberg layer- Feed forward counter propagation Neural
Networks, Applications. Statistical methods simulated annealing, Bloltzman Training, Cauchy
training - artificial specific heat methods, Application to general non-linear optimization
problems, back propagation and cauchy training. Hopfield network
UNIT – III : Fuzzy Logic Classical and Fuzzy Sets, Overview of Classical Sets, Membership Function, a-cuts, Properties
of a-cuts, Decomposition Theorems, Extension Principle, fuzzy operations, fuzziness in neural
networks, neural trained fuzzy system, Bidirectional Associative Memory (BAM), Fuzzy
Associative Memory (FAM), Operations on Fuzzy Sets: Complement, Intersections, Unions,
Combinations of Operations, Aggregation Operations, Fuzzy Arithmetic: Fuzzy Numbers,
Linguistic Variables, Arithmetic Operations on intervals & Numbers, Lattice of Fuzzy Numbers,
Fuzzy Equations.
UNIT – IV : Fuzzy Relations
Crisp & Fuzzy Relations, Projections & Cylindric Extensions, Binary Fuzzy Relations, Binary
Relations on single set, Equivalence, Compatibility & Ordering Relations, Morphisms, Fuzzy
Relation Equations.
UNIT – V : Possibility Theory
Fuzzy Measures, Evidence & Possibility Theory, Possibility versus Probability Theory. Fuzzy
Logic: Classical Logic, Multivalued Logics, Fuzzy Propositions, Fuzzy Qualifiers, Linguistic
Hedges. Uncertainty based Information: Information & Uncertainty, Non-specificity of Fuzzy &
Crisp sets, Fuzziness of Fuzzy Sets.
Reference Books:
1. James A. Freeman and David M. Skapura, Neural Network Algorithms, Application and
Programming Techniques, Addison – Wesley publishing company.
2. Freeman A. James, Skapura M. David, Neural networks algorithms, applications and
programming Techniques, Pearson Education.
3. Philip D. Wasserman, Neural Computing – Theory and Practice, Van Nostrand and Reinhold,
Syllabus
M.Tech – Computer Science & Engg Page 23
INFORMATION SECURITY
CODE: 01MTCS204
Course Objective:
The course is intended to practice and study of techniques for securing the communication from
unauthorized users. And the policies adopted by the network administrator to prevent and
monitor unauthorized access, misuse, modification, or denial of the computer network and
network-accessible resources.
Unit I : Introduction and Objectives
Basic objectives of cryptography, secret-key and public-key cryptography, one-way and trapdoor
one-way functions, cryptanalysis, attack models, Block ciphers: Modes of operation, DES and its
variants, AES, linear and differential cryptanalysis. Stream ciphers: Stream ciphers based on
linear feedback shift registers.
Unit II : Message Digest
Properties of hash functions, attacks on hash functions. Public-key parameters: Modular
arithmetic, gcd, primality testing, Chinese remainder theorem, modular square roots, finite fields.
Unit III : Intractable problems
RSA problem, modular square root problem, Diffie-Hellman problem, known algorithms for
solving the intractable problems.
Unit IV : Public-key encryption
RSA, side channel attacks. Key exchange: Diffie-Hellman and Digital signatures: RSA, signature
schemes, blind and undeniable signatures. Entity authentication: Passwords, challenge-response
algorithms, zero-knowledge protocols. Standards: IEEE, RSA and ISO standards
Unit V : Network issues
Certification, public-key infrastructure (PKI), secured socket layer (SSL), Kerberos. Advanced
topics: Elliptic and hyper-elliptic curve cryptography, number field sieve, lattices and their
applications in cryptography, hidden monomial cryptosystems, cryptographically secure random
number generators.
Reference Books:
1. William Stallings, Cryptography and Network Security, PHI
2. Atul Kahate, “Cryptography and Network Security”, TMH
3. Calabrese, Info security intelligence-cryptography principles appl., Cengage Learn
4. Krawetz, Intro to network security, Cengage Learning.
Syllabus
M.Tech – Computer Science & Engg Page 24
ADVANCED JAVA LAB
CODE: 01MPCS201
Write programs to carry out:
1. Write an Application program /Applet to make connectivity with Database using JDBC
API
2. Write an Application program/Applet to send queries through JDBC Bridge& handle
result.
3. Write a program to design a form using basic swing components.
4. Write a program to demonstrate the use of scroll panes in Swing.
5. Write a servlet for demonstrating the generic servlet class.
6. Write a servlet for demonstrating the generic servlet class.
7. Write a servlet to demonstrate the Http Servlet class using do Get ().
8. Write a servlet to demonstrate the Http Servlet class using do Post ().
9. Write a servlet to demonstrate the cookie
10. Write a servlet for demonstrating the generic jsp class.
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M.Tech – Computer Science & Engg Page 25
THIRD SEMESTER
MOBILE COMPUTING
CODE: 02MTCS301
Course Objective:
This course is intended to understand cellular network concepts, multiple access techniques,
GSM and CDMA architectures, wireless networks, and mobile Ad-hoc network.
UNIT – I : Introduction Overview of Mobile Computing and its applications; Radio Communication; Mobile Computing
Architecture; Mobile System Networks; Data Dissemination; Mobility Management;
Introduction to Cellular network: components, Architecture, Call set-up, Frequency Reuse and
Co-channel cell, Cell Design, Interference, Channel assignment, Hand Off;
UNIT – II : Cellular Networks and Techniques Cellular Network Standards; Digital cellular communication; Multiple Access Techniques:
FDMA, TDMA, CDMA;
GSM: System Architecture, Mobile services & features, Protocols, Radio interface, Handover,
GSM Channels, Localization and calling, User validation; General Packet Radio Service;
Introduction to CDMA based systems; Spread spectrum in CDMA systems; coding methods in
CDMA; IS-95
UNIT – III : Wireless and Bluetooth Wireless LAN, Wireless LAN (Wi-Fi) Architecture and protocol layers, WAP Architecture,
Bluetooth Architecture, Layers, Security in Bluetooth.
UNIT – IV : Mobile Ad-hoc and Sensor Networks Introduction, MANET, Routing in MANET’s Wireless Sensor Networks, Applications; Mobile
Devices: Mobile Agent, Application Server, Gateways, Portals, Service Discovery, Device
Management,
Unit –V : Network System and Protocols
Mobile File Systems; Mobile IP: Architecture, Packet delivery and Hand over Management,
Location Management, Registration, Tunneling and Encapsulation, Route optimization, DHCP.
Mobile Transport Layer: Conventional TCP/IP transport protocols, Indirect TCP, Snooping TCP,
Mobile TCP
Reference Books:
1. Jochen Schiller, “Mobile Communications”, Second Edition, Pearson Education, 2004.
2. Raj Kamal, “Mobile Computing”, Oxford Higher Education, 2008.
3. Sipra DasBit, Biplab K. Sikdar, “Mobile Computing”, PHI, 2009.
4. William C.Y.Lee, “Mobile Cellular Telecommunications”, Second Edition, (Tata
McGraw-Hill), 2006.
Syllabus
M.Tech – Computer Science & Engg Page 26
SOFTWARE TESTING & QUALITY MANAGEMENT
Code: 02MTCS302
Course Objective:
This course is intended to understand the concepts of software testing, automation, software
quality, quality assurance, errors occurred in the software their quality and actions to be taken
for removing the errors.
Unit – 1 : Introduction
Software, Software Development Life Cycle, V-Model, Error, Fault, Failure, Software Testing
Life cycle, Limitations of the testing, Need of the software testing, Types of testing, Test
Documentation, Test Environment Set Up, Test Data, Test Cases, Entire Flow/Test Execution,
Test Reporting – Metrices.
Unit – 2 : Levels of Testing
Functional Testing, Boundary Value Analysis, Equivalence Class Testing, Decision Table Based
Testing, Cause Effect Graphing Technique.
Structural Testing, Path testing, DD-Paths, Cyclomatic Complexity, Graph Metrics, Data Flow
Testing, Mutation testing, Risk Analysis, Regression Testing, Slice based testing, Integration
Testing, System Testing, Debugging, Domain Testing.
Unit – 3 : Object Oriented Testing Issues and Automation
Object Oriented Testing, Testing issues, Class Testing, GUI Testing, Object Oriented Integration
and System Testing, Manual & Automation Teting, Testing Stand Alone Applications, Project
based Automation, Product based Automation Testing Tools, Static Testing Tools, Dynamic
Testing Tools, Characteristics of Modern Tools.
Unit – 4 : Software Quality and SQA
Software Quality: Concepts of software quality, quality attributes, software quality control,
Hierarchical models of Boehm and McCall, Quality measurement – Metrics measurement and
analysis.
Software Quality Assurance: Quality tasks, SQA plan, Teams, Characteristics,
Implementation, Documentation, Reviews and Audits
Unit – 5 : Quality Control and Management System
Tools for Quality, CASE tools, Reliability growth models for quality assessment
Elements of Quality Management System, Rayleigh model framework, Reliability Growth
models for QMS, Complexity metrics and models, Customer satisfaction analysis.
Quality Standards, Need for standards, ISO 9000 Series, ISO 9000-3 for software development,
CMM and CMMI, Six Sigma concepts.
Syllabus
M.Tech – Computer Science & Engg Page 27
Reference Books:
1. Boris Beizer, “Software Testing Techniques”, Second Volume, Second Edition,Van
Nostrand Reinhold, New York, 1990.
2. Louise Tamres, “Software Testing”, Pearson Education Asia, 2002.
3. Roger S. Pressman, “Software Engineering – A Practitioner’s Approach”, Fifth Edition,
McGraw-Hill International Edition, New Delhi, 2001.
4. Robert Dunn,”Software Quality Concepts and Plans”, Prentice-Hall,1990.
5. Alan Gillies,”Software Quality, Theory and management”, Chapman and Hall,1992.
6. Michael Dyer, “The Cleanroom approch to Quality Software Engineering “,Wiley &
Sons.1992.
7. Tom Gilb, ” Prnciples of Software Engineering Management”, Addison-Wesley,1988.
SOFTWARE TESTING LAB
CODE : 02MPCS301
1. Hands on Software Engineering principles Infrastructure.
2. Usage of Front-end and Back-end technologies and packages
3. Prepare the following documents for three of the experiments listed below Using
software engineering methodology.
a. Program Analysis and Project Planning.
b. Thorough study of the problem – Identify project scope, Objectives,
c. Software requirement Analysis
4. Describe the individual Phases / Modules of the project, Identify deliverables
5. Software Design
a. Use work products – Data dictionary, Use case diagrams and activity diagrams,
Build and test class diagrams,
b. Sequence diagrams and add interface to class diagrams, DFD, ER diagrams
c. Software Development and Debugging using any Front end and Back end tool
d. Software Verification and Validation procedures
SEMINAR AND MINOR PROJECT
CODE : 02MPCS302
Students have to select one topic given by the department .He \She has to first submit the
synopsis, and then carry out detailed study on the subject. He has to submit his progress to the
guide assigned. He has to give presentation of near about 15 minutes duration on the topic
assigned.
A team consisting of Dean, HOD and External examiner appointed by University shall carry out
the evaluation of the student for his/her major project and evaluation for his/her professional
branch
Syllabus
M.Tech – Computer Science & Engg Page 28
FOURTH SEMESTER
DISSERTATION
CODE: 02MPCS401
The students have to submit a synopsis in a specified format at the beginning of the semester for
the approval by the university project committee. The students have to present the progress
report of the work through seminars and progress reports. A report must be submitted to the
university for the evaluation purpose at the end of the semester in a specific format.