Download Scheme-2013

G. PULLA REDDY ENGINEERING COLLEGE (Autonomous): KURNOOL
Accredited by NBA of AICTE and NAAC of UGC
An ISO 9001:2008 Certified Institution
Affiliated to JNTUA, Anantapur
M.Tech Syllabus- Scheme 2013
(Computer Science & Engineering)
Two year M.Tech Course (Scheme – 13)
Scheme of instruction and Examination
(Effective from 2013-14)
S No
Course
No
Scheme of
Instruction
periods/week
Course Title
Scheme of Examination
L
T
P
End Exam
Marks
Internal
Assessment
Marks
Total
Marks
Credits
1.
CS801
Advanced Data Structures
3
3
-
-
70
30
100
2.
CS802
Software Engineering
3
3
-
-
70
30
100
3.
CS803
Web Technologies
3
3
-
-
70
30
100
4.
CS804
Advanced Database Management Systems
3
3
-
-
70
30
100
Elective-I
3
3
-
-
70
30
100
5.
6.
CS805
Software Lab – I
2
-
-
3
50
50
100
7
CS806
Seminar-I
1
-
-
-
-
100
100
18
15
-
3
400
300
700
M.Tech I Semester
COMPUTER SCIENCE AND ENGINEERING
M.Tech II Semester
S No
Course No
1.
CS807
Software Quality and Testing
3
3
-
-
70
30
100
2.
CS808
Advanced Computer Networks
3
3
-
-
70
30
100
3.
CS809
Cloud Computing
3
3
-
-
70
30
100
4.
CS810
OOAD and Design Patterns
3
3
-
-
70
30
100
Elective-II
3
3
-
-
70
30
100
5.
Course Title
COMPUTER SCIENCE AND ENGINEERING
Scheme of
Instruction
Scheme of Examination
periods/week
Internal
End Exam
Total
Credits
L
T
P
Assessment
Marks
Marks
Marks
6.
CS811
Software Lab – II
2
-
-
3
50
50
100
7.
CS812
Seminar-II
1
-
-
-
-
100
100
18
15
-
3
400
300
700
M.Tech III Semester
S No
Course No
COMPUTER SCIENCE AND ENGINEERING
Scheme of
Instruction
periods/week
Course Title
Scheme of Examination
Credits
L
T
P
End Exam
Marks
Internal
Assessment
Marks
Total
Marks
Mobile Computing
3
3
-
-
70
30
100
2.
Elective-III
3
3
-
-
70
30
100
3.
Elective-IV
3
3
-
-
70
30
100
Dissertation Phase-I
6
-
-
-
50
50
100
15
9
-
-
260
140
400
1.
5.
CS901
CS902
M.Tech IV Semester
S No
1.
Course No
CS903
COMPUTER SCIENCE AND ENGINEERING
Course Title
Dissertation Phase-II
Description
Credits
12
Subject title
1. C# & .Net Framework
2. Embedded System
Elective-I
Elective II
Elective III
Elective IV
Scheme of
Instruction
periods/week
3. Advanced Computer Architecture
4. Design and Analysis of Algorithms
5. Language Processors
1.Artificial Intelligence
2.Parallel and Distributed Algorithms
3. Client Server Computing
4. Pattern Recognition
5. Distributed Operating System
1. Soft Computing
2. Information Retrieval System
3. Software Project Management
4. Neural Networks
1. Distributed Database
2. Network Security & Cryptography
3. Data Mining and Business Analytics
4. Data warehousing and Mining
Scheme of Examination
L
T
P
End Exam
Marks
Internal
Assessment
Marks
Total
Marks
-
-
-
50
50
100
Code
CS813
CS814
CS815
CS816
CS817
CS818
CS819
CS820
CS821
CS822
CS904
CS905
CS906
CS907
CS908
CS909
CS910
CS911
CS801: ADVANCED DATA STRUCTURES(ADS)
(M.Tech CSE-I Semester)
Scheme
Internal Assessment
End Exam
End Exam Duration
: 2013
: 30
: 70
: 3 Hrs
L
2
T/D
P
1
-
C
Course Objectives:

To develop proficiency in the specification, storage representation and implementation of data types and
data structures and to get a good understanding of applications of data structures like stacks, queues, trees,
hash tables etc.
Course Outcomes:

Students are able to choose the appropriate data structure and implement it to store data for a given
problem by considering various problem characteristics such as data size, type of operations etc.
Introduction to C++: Concepts of Object Oriented Programming, Parts of C++ program, data types, pointers,
operators and their precedence, Scope Access Operator, Memory Management Operators, Control Structures,
functions in C++, introducing Classes, constructor and destructor functions, parameterized constructors.
Linear Data Structures and Applications: Arrays: Array operations, Representation of Arrays in Memory,
Applications. Linked Lists: Single, Double and Circular Linked Lists, Applications. Stacks: Stack operations,
Applications. Queues: Operations on Queues, Circular Queues, Other Types of Queues, Applications.
Trees and Applications: Definition and Basic Terminologies, Representation of Trees, Binary Trees:
Representation of Binary Trees, Binary Tree Traversals, Threaded Binary Trees, Application. Binary Search Trees,
AVL Trees: Definition and Operations, B Trees: Definition and Operations Applications. Red-Black Trees and
Splay Trees, Applications.
Priority Queues (Heaps): Model, Simple Implementation, Binary Heap, applications of priority queues, d-heaps,
leftist heaps, skew heaps, Binomial queues.
Hash tables and Sorting techniques: Definition, Hash function, Open hashing (separate chaining), Closed hashing
(open addressing) – linear probing, quadratic probing, double hashing, Rehashing, Extendible hashing. Bubble Sort,
Insertion Sort, Selection Sort, Quick Sort, Heap Sort.
Text Books:
1. G.A.V.Pai, Data Structures and Algorithms, Tata McGraw Hill Edition.
2. Mark Allenweiss, Data Structures and Algorithms Analysis, Pearson Education.
Reference Books:
1. Jean Paul Tremblay, Paul G.Sorenson, An Introduction to Data Structures with Applications, TMH.
2. E.Balaguru Swamy, Object Oriented Programming with C++.TMH.
NOTE: The question paper shall consist of Eight questions out of which the student shall answer any Five
questions.
3
CS802: SOFTWARE ENGINEERING(SE)
(M.Tech CSE-I Semester)
Scheme
Internal Assessment
End Exam
End Exam Duration
: 2013
: 30
: 70
: 3 Hrs
L
3
T/D
P
C
-
-
3
Course Objectives:


To gain a broad understanding of software engineering discipline and its application to the
development and management of software systems.
To learn the complete software life cycle, software process models and design approaches, risk
quality management.
and
Course Outcomes:

Students will be able to apply software engineering principles and techniques and to produce efficient,
reliable , robust and cost-effective software solutions.
Software Process: Introduction
To
Software Engineering,Generic view of process-A Process
Framework,CMM,Process Patterns,Process Assessment,Personal Models-Prescriptive Models,The waterfall model,
Incremental process models, Evolutionary process models, The Unified process,An Agile View of ProcessIntroduction ,Agile Process Models.
Software Engineering Practice: Introduction, Communicationpractices, Modeling. Practices,Construction
Practice,Deployment,System Engineering,Requirements Engineering- Requirements Engineering Tasks,Initiating
the Requirements Engineering Process ,Eliciting Requirements,Developing Use Cases,,Negotiating
Requirements,Validating Requirements, Building the Analysis Model-Requirement Analysis and Analysis Modeling
approaches,Data Modeling Concepts,Object oriented Analysis,Scenario based Modeling,Flow Oriented
Modeling,Class Based Modeling,Creating a Behavioral Model.
Design Engineering: Introduction ,Design process and Design Quality,Design Concepts,The Design Model,Pattern
Based Software Design,Testing Strategies-Strategic approach of Software Testing ,Strategic issues,Test strategies
for Conventional Software,Test Strategies for Object-Oriented Software,Validation Testing,System
Testing,Debugging ,Testing Tactics.
Managing Software Projects: Project Management –Management Spectrum,The people,The Product,The
Process,The Project,W5HH Principle,Metrics and Process and Projects-Metrics in the Process and Project
Domains,Software Measurement,Metrics for Software Quality,Integrating Metrics within the Software
Process,Metrics for Small Organizations,Establishing a Software Metrics Program,Estimation.
Project Scheduling: Risk Management-Reactive vs Proactive Risk Strategies,Software Risks,Risk
Identification,Risk
Projection,Risk
Refinement,RMMM
Plan,Quality
ManagementQualityConcepts,SoftwareQualityAssurance,SoftwareReviews,FormalTechnical Reviews,Formal Approaches to
SQA,Statistical Software Quality Assurance,Software Reliability,Change Management-Software Configuaration
Management,The SCM Repository,The SCM Process ,Configuration Management for Web Engineering.
Text Books:
1.Roger S.Pressman [2005], [6th Edition], Software Engineering, A Practitioner’s Approach, Mc GrawHill
International Edition.
Reference Books:
1. Sommerville [2008], [7th Edition], Software Engineering ,Pearson education.
NOTE: The question paper shall consist of Eight questions out of which the student shall answer any Five
questions.
CS803: WEB TECHNOLOGIES(WT)
(M.Tech CSE-I Semester)
Scheme
Internal Assessment
End Exam
End Exam Duration
: 2013
: 30
: 70
: 3 Hrs
L
T/D
P
C
-
-
3
3
Course Objectives:


To introduce the students to some of the basic concepts of Markup languages, develop programming skills
in java using Beans, Swings, Servlets and Java Server Pages.
To enable the students in Web development.
Course Outcomes:

Students are able to design, develop web applications.
HTML & XML: HTML Common tags- List, Tables, images, forms, Frames; Introduction to Java Scripts, Objects
in Java Script, Dynamic HTML with Java Script.XML - Document type definition, XML Schemas, Document
Object model, Presenting XML.
JAVA BEANS: Introduction to Java Beans, Advantages of Java Beans, BDK Introspection, Developing a simple
Bean Using the BDK, Using Bound properties, Using Bean Info Interface.
SWINGS: JApplet, Icons, Labels, Buttons, Checkboxes, Text Boxes, Combo Boxes, Tabbed Panes – Scroll Panes.
Trees, Tables.
JAVA SERVLETS: Lifecycle of a Servlet, Simple Servlet, The Servlet API, The javax. servlet Package, Reading
servlet parameters, Handling Http Request & Responses, Using Cookies- Session Tracking.
JSP: Introduction, Problem with Servlets. The Anatomy of a JSP Page, JSP Processing. JSP Application Design
with MVC architecture. Database Access: Accessing a Database from a JSP Reading and storing information in a
Database.
Text Books:
1. Chris Bates [2008], [Second Edition], Web Programming Building Internet Applications, WILEY.
2. Herbert Schildt , [5th Edition], The Complete Reference Java2, TMH.
3. Hans Bergsten, Java Server Pages, O’Reilly.
Reference Books:
1. Programming world wide web-Sebesta, Pearson.
2. Core SERVLETS ANDJAVASERVER PAGES VOLUME 1: CORE TECHNOLOGIES , Marty Hall and Larry
Brown Pearson.
3. Internet and World Wide Web – How to program, Dietel and Nieto PHI/Pearson.
4. An Introduction to web Design and Programming –Wang-Thomson
5. Beginning Web Programming-Jon Duckett WROX.
6. Java Server Pages, Pekowsky, Pearson.
NOTE: The question paper shall consist of Eight questions out of which the student shall answer anyFive
questions.
CS804: ADVANCED DATABASE MANAGEMENT SYSTEMS(ADBMS)
(M.Tech CSE-I Semester)
Scheme
Internal Assessment
End Exam
End Exam Duration
: 2013
: 30
: 70
: 3 Hrs
L
T/D
P
C
-
-
3
3
Course Objectives:

To understand query processing and query optimization, database system architecture, data analysis and
mining
Course Outcomes:

Students will be able to use persistent programming, information retrieval and advanced transaction
processing in various database applications.
Query processing and Query Optimization: Measures of Query cost, Selection operation, sorting, join operation,
other operations Evaluation of expressions, Transformation of relational expressions, Estimating statistics of
expression, choice of evaluation plans.
Object Based Databases and XML: Complex Data types, Structured types and Inheritance in SQL. Table
inheritance, Array and Multi set types in SQL, Object identity and reference types in SQL, Implementing O-R
features .Persistent Programming Languages, Object-Oriented v/s Object relational.
Database System Architecture: Centralized and Client–server Architectures, server system architectures Parallel and
Distributed systems.
Parallel Databases : Introduction, I/O Parallelism, Inter query Parallelism, Intra query Parallelism, Intra operation
parallelism, Inter operation parallelism, Design of Parallel Systems.
Distributed Databases : Homogeneous and Heterogeneous databases, Distributed data storage, Distributed
Transactions, Commit protocols, concurrency control in Distributed databases, Availability, Distribu ted query
processing, Heterogeneous Distributed Databases.
Advanced Data types and New Applications: Motivation, Time in databases, Spatial and Geographic Databases,
Multimedia Databases, Mobility and personal Databases.
Advanced Transaction processing: Transaction processing Monitors ,Transactional Workflows, Main memory
databases, Real time transaction systems, Long Duration Transactions, Transaction Management in Multi databases.
Text Books:
1. Henry F. Korth & Abraham Silberschatz [2006], Database System Concepts.
Reference Books:
1. Ramez Elmasri , Navathe [2009], Fundamentals of Database systems
NOTE: The question paper shall consist of Eight questions out of which the student shall answer any
questions.
Five
CS813: C # & . NET FRAMEWORK
(Professional Elective-I for M.Tech CSE)
Scheme
Internal Assessment
End Exam
End Exam Duration
: 2013
: 30
: 70
: 3 Hrs
L
T/D
3
-
P
C
-
3
Course Objectives:

The student will gain knowledge in the concepts of the .NET framework as a whole and the technologies
that constitute the framework.
Course Outcomes:


The student will gain programming skills in C# both in basic and advanced levels.
By building sample applications, the student will get experience and be ready for large-scale projects.
Introduction To C#: Introducing C#, Understanding .NET, Overview of C#, Literals, Variables, Data Types,
Operators, Expressions, Branching, Looping, Methods, Arrays, Strings, Structures, Enumerations.
Object Oriented Aspects Of C#: Classes, Objects, Inheritance, Polymorphism, Interfaces, Operator Overloading,
Delegates, Events, Errors and Exceptions.
Application Development On .Net: Building Windows Applications, Accessing Data with ADO.NET.
Web Based Application Development On .Net: Programming Web Applications with Web Forms, Programming
Web Services.
The Clr And The .Net Framework: Assemblies, Versioning, Attributes, Reflection, Viewing MetaData, Type
Discovery, Reflecting on a Type, Marshaling, Remoting, Understanding Server Object Types, Specifying a Server
with an Interface, Building a Server, Building the Client, Using SingleCall, Threads.
Text Books:
1. E. Balagurusamy, "Programming in C#", Tata McGraw-Hill, 2004. (Unit I, II)
2. J. Liberty, "Programming C#", 2nd ed., O'Reilly, 2002. (Unit III, IV, V)
Reference Books:
1. Herbert Schildt, "The Complete Reference: C#", Tata McGraw-Hill, 2004.
2. Robinson et al, "Professional C#", 2nd ed., Wrox Press, 2002.
3. Andrew Troelsen, "C# and the .NET Platform", A! Press, 2003.
4. S. Thamarai Selvi, R. Murugesan, "A Textbook on C#", Pearson Education, 2003.
NOTE: The question paper shall consist of Eight questions out of which the student shall answer any Five
questions.
CS814: EMBEDDED SYSTEMS(ES)
(Professional Elective-I for M.Tech CSE)
Scheme
Internal Assessment
End Exam
End Exam Duration
: 2013
: 30
: 70
: 3 Hrs
L
T/D
3
-
P
C
-
3
Course Objectives:


To learn fundamentals concepts of Embeded Systems and softwares.
To enable the students to learn the advanced processor architecture and microcontrollers.
Course Outcomes:

Students will be able to apply the embedded software development process and tools.
Introduction to Embedded Systems: Embedded Systems, Processor Embedded into a System, Embedded
Hardware Units and Devices in a System, Embedded Software, Complex System Design, Design Process in
Embedded System, Formalization of System Design, Classification of Embedded Systems
8051 and Advanced Processor Architecture: 8051 Architecture, 8051 Micro controller Hardware, Input/Output
Ports and Circuits, External Memory, Counter and Timers, Serial data Input/Output, Interrupts (To be referred from
The 8051 Microcontroller, Third Edition, Kenneth J.Ayala, Thomson), Introduction to Advanced Architectures,
Real World Interfacing, Processor and Memory organization - Devices and Communication Buses for Devices
Network: Serial and parallel Devices & ports, Wireless Devices, Timer and Counting Devices, Watchdog Timer,
Real Time Clock, Networked Embedded Systems, Internet Enabled Systems, Wireless and Mobile System protocols
Embedded Programming Concepts: Software programming in Assembly language and High Level Language,
Data types, Structures, Modifiers, Loops and Pointers, Macros and Functions, object oriented Programming,
Embedded Programming in C++ & JAVA.(refer IV, V and VI chapters of The 8051 Microcontroller, Third Edition,
Kenneth J.Ayala, Thomson)
Real – Time Operating Systems: OS Services, Process and Memory Management, Real – Time Operating
Systems, Basic Design Using an RTOS, Task Scheduling Models, Interrupt Latency, Response of Task as
Performance Metrics - RTOS Programming: Basic functions and Types of RTOSES, RTOS VxWorks, Windows
CE
Embedded Software Development Process and Tools: Introduction to Embedded Software Development Process
and Tools, Host and Target Machines, Linking and Locating Software, Getting Embedded Software into the Target
System, Issues in Hardware-Software Design and Co-Design - Testing, Simulation and Debugging Techniques
and Tools: Testing on Host Machine, Simulators, Laboratory Tools
Text Books:
1. Embedded Systems, Raj Kamal, Second Edition TMH.
2. The 8051 Microcontroller, Third Edition, Kenneth J.Ayala, Thomson.
Reference Books:
1. Embedded/Real-Time Systems, Dr.K.V.K.K.Prasad, dreamTech press
2. The 8051 Microcontroller and Embedded Systems, Muhammad Ali Mazidi, Pearson.
3. An Embedded Software Primer, David E. Simon, Pearson Education.
4. Micro Controllers, Ajay V Deshmukhi, TMH.
NOTE: The question paper shall consist of Eight questions out of which the student shall answer any Five
questions.
CS815: ADVANCED COMPUTER ARCHITECHTURE (ACA)
(Professional Elective-I for M.Tech CSE)
Scheme
Internal Assessment
End Exam
End Exam Duration
: 2013
: 30
: 70
: 3 Hrs
L
T/D
3
-
P
C
-
3
Course Objectives:


To make the students to learn and analyze fundamental issues in architecture design and their impact on
performance.
To familiarize the students with parallel processing and pipelining concepts, Array processor and its
interconnection networks, multi-processor and dataflow computer architectures.
Course Outcomes:

Students will be able to identify the factors affecting performance in superscalar processors and the key
components, options and tradeoffs that a designer has to consider when designing such processors.
.
Introduction to parallel processing: Trends towards parallel processing, Parallelism in uniprocessor systems,
Parallel computer structures, Architectural classification schemes, Memory hierarchy in parallel processing systems,
Addressing schemes.
Pipelining: Pipeline concept, linear pipelining and space time diagram, Classification of pipeline processors,
nonlinear pipeline and reservation table, Instruction and arithmetic pipelines. Principles of designing pipeline
processors. Instruction level parallelism (ILP), overcoming data hazards, reducing branch costs, high performance
instruction delivery, hardware based speculation- limitations of ILP.
SIMD Array processors: SIMD structures and algorithms for array processors, Organization, Masking and routing
mechanisms, Inter processor communication, Parallel algorithms for array processors (matrix multiplication and
parallel sorting).SIMD interconnection networks.
Multiprocessor Architecture: Loosely coupled and Tightly coupled multiprocessor systems, Processor
characteristics, Interconnection network, Timeshared or common busses, Crossbar switch and multi port memories,
Multistage network, Banyan and Delta networks.
Data flow computers: Control flow Vs Data flow, data flow computer architectures, static and dynamic data flow
computers, data flow graphs and languages, data flow and design alternatives-dependency driven approach and
multi level driven approaches.
Text Books:
1. Kai Hwang, Faye Briggs [1993], Computer architecture and parallel processing, TMH edition.
2. John L. Hennessy & David A. Patterson Morgan Kufmann, [3 rd Edition], Computer Architecture A quantitative
approach (An Imprint of Elsevier).
Reference Books:
1. Kai Hwang [1993], Advanced computer architecture, TMH edition.
2. Parallel Computer Architecture, A Hardware / Software Approach, David E. Culler, Jaswinder Pal
singh with Anoop Gupta, Elsevier
NOTE: The question paper shall consist of Eight questions out of which the student shall answer any Five
questions.
CS816: DESIGN AND ANALYSIS OF ALGORITHMS (DAA)
(Professional Elective-I for M.Tech CSE)
Scheme
Internal Assessment
End Exam
End Exam Duration
: 2013
: 30
: 70
: 3 Hrs
L
T/D
3
-
P
C
-
3
Course Objectives:


To study paradigms and approaches used to analyze and design algorithms and to appreciate the impact of
algorithm design in practice.
To understand how a number of algorithms for fundamental problems in computer science and engineering
work and compare with one another, and to make the students design efficient algorithms
Course Outcomes:


Students will be able to prove the correctness and analyze the running time of the algorithms for the classic
problems in various domains.
Students can apply these algorithms and design techniques to solve problems.
Introduction: What is an Algorithm? Analysis, Asymptotic notation.
Divide and Conquer :- General method, Binary search, Finding Maximum and Minimum, Merge sort, Quick sort,
Strassen’s Matrix Multiplication.
Greedy Method : The General Method, Knapsack Problem,Job Sequencing with Deadlines, Minimum-Cost
Spanning Tree, Optimal Storage on Tapes, Optimal Merge Patterns, Single Source Shortest Path.
Basic Traversal and Search Techniques :- Techniques for Binary Trees, Techniques for Graphs, Biconnected
Components and DFS.
Dynamic Programming : The General Method, Multistage Graphs, All Pairs Shortest Paths, Optimal Binary
Search Trees, 0/1-Knapsack, Reliability Design, The Travelling Salesperson Problem .
Backtracking : The General Method, The 8-Queens Problem, Sum of Subsets, Graph Coloring, Hamiltonian cycles.
Branch and Bound : The Method, Travelling Salesperson, 15 Puzzle problem
Lower Bound Theory : Comparison Trees, Oracles and Adversary arguments, Techniques for Algebraic problems.
Text Books:
1. Ellis Horowitz, Sartaz Sahni & Sanguthevar Rajasekaran, Fundamentals of Computer Algorithms, Galgotia
Publications.
Reference Books:
1.
Jon Kleinberg, Eva Tardos, Algorithm Design, Pearson Education.
NOTE: The question paper shall consist of Eight questions out of which the student shall answer any Five
questions.
CS817: LANGUAGE PROCESSORS(LP)
(Professional Elective-I for M.Tech CSE)
Scheme
Internal Assessment
End Exam
End Exam Duration
: 2013
: 30
: 70
: 3 Hrs
L
T/D
3
-
P
C
-
3
Course Objectives:


To introduce the major concept areas of language translation and compiler design
To develop an awareness of the function and complexity of modern compilers
Course Outcomes:

Students will be able to understand the phases of the compilation process and be able to describe the
purpose and implementation approach of each phase.
Assemblers, Compilers and lexical Analysis: General Design Procedure, Design of Assembler,
Basic function of Language translator, differences between compiler and interpreter, bootstrapping, logical phase of
a compiler, difference between pass and phase, grouping the phases into passes, compiler construction tools. The
role of lexical analyser input buffering, specifications of tokens, recognition of tokens, a language for specifying
lexical analysers, design of a lexical analyser generators.
Syntax analysis: Top-Down Approach: Role of parser, parsing, top down parsing – recursive decent parsing,
predictive parsers, non recursive predictive parsing. Bottom-Up Approach: bottom up parsing, operator precedence
parsing, LR parsers, using ambiguous grammars, parser generators.
Semantic Analysis: Typical semantic errors, type checking, type conversions, specification of a simple type
checker, equivalence of type expressions, overloading of functions and operators, polymorphic functions, storage
allocations, strategies of storage allocation, static, dynamic and heap.
Intermediate Code Generation: Intermediate code languages - three address code, types of three address code,
syntax directed translation into three address code, implementations of three address statements - quadruples, triples,
indirect triples, declarations, Boolean expressions back patching.
Code Generation And Code Optimization: Issues in the design of code generator, the target machine, run-time
storage management, basic blocks and flow graphs, next use information, a simple code generator, DAG
representation of basic blocks, generating code from dags. Introduction to code optimization, principles sources of
optimization, optimization of basic blocks, peephole optimization.
Text Books:
1. Alfred V.Aho, Ravi Sethi, Jeffrey and D.Ullman [2008], Compilers Principles, Techniques and
tools, Pearson edition.
2. Alfred V. Aho, Jeffrey D. Ullman [2002], Principles of Compiler Design Naroba Publications.
Reference Books:
1. Trembly & Sorenson [2007], Theory & practice of compiler writing , MCGrawHill.
NOTE: The question paper shall consist of Eight questions out of which the student shall answer any Five
questions.
CS805:SOFTWARE LAB-I
(M.Tech CSE-I Semester)
Scheme
Internal Assessment
End Exam
End Exam Duration
: 2013
: 50
: 50
: 3 Hrs
L
T/D
P
C
-
-
3
2
3
Course Objectives:
 To enable the students to understand the implementation of data structures.
 To make the students understand various object oriented concepts and web Technologies
Course Outcomes:
 Students will be able to apply various concepts of data structures, Java and Web Technologies in
different applications
List of experiments:
DATA STRUCTURES:
1.a) Merging of two sorted arrays.
b) Polynomial manipulation using Linked Lists.
2. a) Operations on Stack using Linked Lists.
b) Operations on Circular Queue using Arrays.
3. Postfix Expression Evaluation.
4. Operations on Binary Search Trees.
5. Heap Sort.
JAVA & WEB TECHNOLOGIES :
1.
2.
3.
4.
5.
6.
7.
8.
9.
Implementing classes and objects.
Constructors.
Inheritance.
Packages.
Interfaces.
Exception Handling.
Multithreading.
AWT and AWT Controls.
a) Webpage design using Text formatting Tags, images.
b) Webpage design using Links and Lists.
10. Static webpage design of GPREC
11. HTML Forms and Controls
CS807: SOFTWARE QUALITY AND TESTING(SQT)
(M.Tech CSE-II Semester)
Scheme
Internal Assessment
End Exam
End Exam Duration
: 2013
: 30
: 70
: 3 Hrs
L
3
T/D
-
P
C
-
3
Course Objectives:
 To understand the quality metrics, system testing and maintaining software.
Course Outcomes:
 Students will learn software quality metrics and different testing methods.
Software Quality: What is Software quality, Total Quality management.
Software quality metrics, product quality metrics, In-process quality metrics, metrics for software quality
maintenance, Examples.
Software Testing : Introduction, Purpose of testing, Some Dichotomies, Model for testing,
Consequences of bugs, Taxonomy for bugs
Flow Graphs and Path Testing: Path testing basics, Path Predicates and Achievable paths, Path
Sensitizing, Path Instrumentation
Transaction Flow Testing: Transaction Flows, Transaction Flow Testing Techniques
Data Flow Testing : Basics and Testing Strategies
Domain Testing : Domains and paths, Domain Testing, Domains and Interface Testing,
Domains and Testability.
Metrics : Linguistic, Structural and Hybrid Metrics
Text Books:
1. Stephen H. Kan [2008], Metrics and Models in Software Quality Engineering, Pearson
Education
2. Boris Beizer, Software Tesing Techniques, Dreamtech Press
NOTE: The question paper shall consist of Eight questions out of which the student shall answer any
questions.
Five
CS808: ADVANCED COMPUTER NETWORKS(ACN)
(M.Tech CSE-II Semester)
Scheme
Internal Assessment
End Exam
End Exam Duration
: 2013
: 30
: 70
: 3 Hrs
L
3
T/D
-
P
C
-
3
Course Objectives:

To make the students understand the structured environment to develop critical understanding of relevant,
modern theories associated with practical expertise in networking technologies and applications in a wide
range of contexts.
Course Outcomes:
 Students will be able to understand major functions of each layer of the OSI and TCP/IP Protocol suites,
congestion control algorithms, Internetworking, QoS, TCP and UDP and network security
Review of Computer Networks and the Internet: What is the Internet. ISPs and Internet Backbones, History of
Computer Networking and the Internet.
Foundation of Networking Protocols: 5-layer TCP/IP Model, 7-Layer OSI Model.
Logical Addressing: IPv4 Addresses, IPv6 Addresses
Internet Protocol: Internetworking, IPv4, IPv6, Transition from IPv4 to IPv6
Transport and End-to-End Protocols: Transport Layer, Transmission Control Protocol (TCP), User Datagram
Protocol (UDP), TCP Congestion Control and Mobile TCP.
Application Layer: Principles of Network Applications, HTTP, FTP, SMTP and DNS
Wireless Network and Mobile IP: Infrastructure of Wireless Networks, Wireless LAN Technologies, IEEE 802.11
Wireless Standard, Cellular Networks, Mobile IP.
Network Security: Cryptography, Firewalls, Secure Socket Layer (SSL) and Virtual Private
Networks (VPN).
Case study: Study of various network simulators, Network performance analysis using NS2.
Text Books:
1. Behrouz A.Forouzan, [4th Edition], Data Communications and Networking, Tata McGraw Hill, 2007
2. Jochen Schiller, [2011], Mobile Communications, Pearson Education
Reference Books:
1. Computer Networks, AndrewS. Tanenbaum, Fourth Edition, Prentice Hall.
2.
An Engineering Approach to Computer Networks, S.Keshar, II Edition, Pearson Ed.
NOTE: The question paper shall consist of Eight questions out of which the student shall answer any
questions.
Five
CS809: CLOUD COMPUTING (CC)
(M.Tech CSE-II Semester)
Scheme
Internal Assessment
End Exam
End Exam Duration
: 2013
: 30
: 70
: 3 Hrs
L
T/D
3
-
P
C
-
3
Course Objectives:



To understand the basic concepts of cloud computing and its architecture.
To enable the students learn the implementation of clouds using Aneka tool.
To make the students understand the cloud applications and its advanced concepts
Course Outcomes:


Students will be able to understand the basic and advanced concepts of cloud computing.
Students will be capable of understanding the implementation of clouds using Aneka tool.
Introduction : Cloud Computing - Introduction , Historical Developments, Building Cloud Computing
Environments, Computing Platforms and Technologies, Parallel vs. Distributed Computing
Virtualization Introduction , Characteristics of Virtualized Environments, Virtualization and Cloud Computing,
Pros and Cons of Virtualization, Technology Examples
Cloud Computing Architecture Introduction, Cloud Reference Model , Types of clouds, Economics of the Cloud
Aneka: Cloud Application Platform - Framework Overview, Anatomy of the Aneka Container, Building Aneka
Clouds, Cloud Programming and Management
Concurrent Computing Programming Applications with Threads, Multithreading with Aneka, Programming
Applications with Aneka Threads
Cloud Applications : Scientific Applications ,Business and Consumer Applications
Advanced Topics in Cloud Computing : Energy Efficiency in Clouds , Market Based Management of Clouds,
Federated Clouds / InterCloud, Third Party Cloud Services
Text Books:
1. Rajkumar Buyya, Christian Vecchiola, S.Thamarai Selvi, "Mastering Cloud Computing", 1st Edition,
McGraw Hill Publications.
Reference Books:
1. RajKumar Buyya, James Broberg, "Cloud Computing Principles and Paradigms", John Wiley & Sons
Publications.
2. Judith Hurwitz, R Bloor, M Kanfman, F Halper, "Cloud Computing for Dummies", 1st Edition,
WileyPublishers, 2009.
NOTE: The question paper shall consist of Eight questions out of which the student shall answer any
questions.
Five
CS810: OOAD AND DESIGN PATTERNS(OOADDP)
(M.Tech CSE-II Semester)
Scheme
Internal Assessment
End Exam
End Exam Duration
: 2013
: 30
: 70
: 3 Hrs
L
T/D
3
-
P
C
-
3
Course Objectives:


.
To make the students use UML throughout the project lifecycle to capture and communicate analysis
and design decisions.
To provide the graduate the better understanding of the usage of design patterns.
Course Outcomes:


Students will understand Object Oriented Analysis and Design concepts, learn to represent it with UML
and document it using UML modeling tool.
Graduates are able to understand the design pattern for given scenario.
Introduction : Introducing UML, Conceptual Model of UML
Basic Structural Modeling : Classes, Relationships, Common Mechanisms, Diagrams, Class Diagrams
Basic Structural Modeling : Advanced Classes, Advanced Relationships, Interfaces, Types and Roles, Packages
, Instances and Object Diagrams
Basic Behavioral Modeling : Usecase Diagrams, Interaction Diagrams, Activity Diagrams
Advanced Behavioral Modeling : Events and Signals, State Machines, Processes and threads, Time and Space,
Statechart Diagrams
Design Pattern : Introduction, Design Patterns in Smalltalk MVC, Describing Design Patterns, The Catalog of
Design Patterns, Organizing the Catalog, How Design Patterns Solve Design Problems, How to Select a Design
Pattern, How to Use a Design Pattern.
A Case Study : Designing a Document Editor: Design Problems, Document Structure, Formatting, Embellishing
the User Interface, Supporting Multiple Look-and-Feel Standards, Supporting Multiple Window Systems, User
Operations Spelling Checking and Hyphenation, Summary.
Text Books:
1. Grady Booch, James Rumbaugh, Ivar Jacobson, The Unified Modeling Language User Guide,
Pearson Education.
2. Ali Bahrami – Irwin [1999], Object Oriented Systems Development, McGraw Hill.
3. Erich Gamma [2008], Design Patterns elements of reusable object oriented software, Pearson
Education.
NOTE: The question paper shall consist of Eight questions out of which the student shall answer any
questions.
Five
CS818: ARTIFICIAL INTELLIGENCE (AI)
(Professional Elective-II for M.Tech CSE)
Scheme
Internal Assessment
End Exam
End Exam Duration
: 2013
: 30
: 70
: 3 Hrs
L
T/D
3
-
P
C
-
3
Course Objectives:

To make the stent familiarize
about the subject of the brain and its development potentially which not only unifies all the subareas of AI
but also leads to wide-front breakthroughs.
Course Outcomes:

The graduates will pay own role
as professionals efficiently and effectively in Robotics and medicines.
What is Artificial Intelligence? - The AI problems, the underlying Assumption, What is an AI Technique? The
level of the model, Criteria for success, Problems, problem spaces, and search - defining the problem as a state space
search, production systems
Problem characteristics, production system characteristics, issues in the design of search programs.
Heuristic Search Techniques - Generate and test- travelling sales man problem, Hill climbing, Best first search,
problem reduction, constraint satisfaction, Mean ends analysis
Knowledge Representation - Representations and mappings, approaches to knowledge representation, The Frame
Problem. Using Predicate logic - Representing simple facts in logic, Representing Instance and Isa relationships,
Resolution.
Representing Knowledge Using Rules - Procedural versus declarative knowledge, logic programming, forward
versus backward reasoning, matching.
Weak Slot And Filler Structures - Semantic nets, Frames.
Strong Slot And Filler Structures - Conceptual dependency, scripts, CYC
Game Playing - MIN MAX search procedure, Adding Alpha Beta cutoffs.
Learning – Learning from Observations – Forms – inductive - Learning Decision Trees, Essemble Learning,
Knowledge in Learning – A Logical Formulation of Learning, Knowledge in Learning, EBL, Learning Using
Relevance information, Inductive Logic Learning, Passive Active and Generalization in Reinforcement Learning.
case studies : MYCIN, PROSPECTOR, XCON.
Text Books:
1. Elaine Richie Kevin Knight [2008], [2nd Edition], Artificial Intelligence, TMH.
Reference Books:
1. Stuart Russell, Peter Norvig [2008], [2nd Edition], Artificial Intelligence A Modern Approach,
Pearson Education.
NOTE: The question paper shall consist of Eight questions out of which the student shall answer any Five
questions.
CS819: PARALLEL AND DISTRIBUTED ALGORITHMS (PDA)
(Professional Elective-II for M.Tech CSE)
Scheme
Internal Assessment
End Exam
End Exam Duration
: 2013
: 30
: 70
: 3 Hrs
L
T/D
3
-
P
C
-
3
Course Objectives:



To learn parallel and distributed algorithms development techniques for shared memory and message
passing models.
To study the main classes of parallel algorithms.
To study the complexity and correctness models for parallel algorithms.
Course Outcomes:

Students will be able to apply the parallel and distributed algorithms in a specific applications or problems.
Introduction: Basic Techniques, Parallel Computers for increase Computation speed, Parallel & Cluster Computing
Message Passing Technique- Evaluating Parallel programs and debugging, Portioning and Divide and Conquer
strategies examples
Pipelining- Techniques computing platform, pipeline programs examples
Synchronous Computations -load balancing, distributed termination examples, programming with shared memory,
shared memory multiprocessor constructs for specifying parallelist sharing data parallel programming languages and
constructs, open MP
Distributed shared memory- systems and programming achieving constant memory distributed shared memory
programming primitives, algorithms – sorting and numerical algorithms.
Text Books:
1. Parallel Programming, Barry Wilkinson, Michael Allen, Pearson Education, 2 nd Edition.
Reference Books:
1.
algorithms by Jaja from Pearson, 1992.
Introduction to Parallel
NOTE: The question paper shall consist of Eight questions out of which the student shall answer any Five
questions.
CS820: CLIENT SERVER COMPUTING (CSC)
(Professional Elective-II for M.Tech CSE)
Scheme
Internal Assessment
End Exam
End Exam Duration
: 2013
: 30
: 70
: 3 Hrs
L
T/D
3
-
P
C
-
3
Course Objectives:

To learn client-server requirements, hardware and software requirements.

Students will be able to understand the client-server technologies ,requirements ,layers and developments.
 To enable the students to learn layers in client/server architecture.
Course Outcomes:
Introduction: Basics, Benefits of client/server computing, Evolution of client/server computing. Trends, Overview
of client/server applications- components, classes, categories. Understanding of client/server computing : Dispelling
the Myths, Obstacles – Upfront and hidden, open systems and standards – settings, organizations, factors for
success.
Client Hardware & Software: Client components, Client operating systems, What is GUI?, X-Windows versus
Windowing, Database access, Application logic, Client software products: GUI environments, converting 3270/5250
screens, Database access tools. Client Requirements : GUI design standard, open GUI standards, Interface
independence, Testing interfaces, Development aids.
Server Hardware: Bench marks, Categories of servers, Features of server machines, Classes of server machines,
Eight layers of software , Network management environment, Network computing environment, Extensions,
Network operating system, Loadable modules, Server operating systems: OS/2 2.0, Windows new technology, Unix
based operating systems.
Server Requirements: Platform independence, Transaction processing, Collectivity, Intelligent database, Stored
procedures, Triggers, Load levelling, Optimizer, Testing and diagnostic tools, Reliability, Backup and recovery
mechanisms. Server data management and access tools: Data manager features. Data management software,
Database gateways, Overview of networking, LAN hardware, Network operating systems.
Development & Deployment Methodology:Convert existing screen interfaces, COBOL to COBOL migration,
Reengineering existing applications, Business reengineering, Methodology tools, Application development
environments, Distributed transaction management, Integrating multi vendor environments, Production
requirements. Mobile computing, More Robust servers, Integration of network and server operating systems, Use
of object technologies, ATM switching.
Text Books:
1. Dawna Travis Dewire ,James Martin [2003], Client/Server computing, McGraw-HILL
PRODUCTIVITY SERIES.
Reference Books:
1.
Robert Orfali,Dan Harken,Jeri Edwards,Client/Server Survival Guide,Wiley India III Edition
NOTE: The question paper shall consist of Eight questions out of which the student shall answer any Five
questions.
CS821: PATTERN RECOGNITION (PR)
(Professional Elective-II for M.Tech CSE)
Scheme
Internal Assessment
End Exam
End Exam Duration
: 2013
: 30
: 70
: 3 Hrs
L
3
T/D
P
-
-
C
Course Objectives:


To implement pattern recognition and machine learning theories
To design and implement certain important pattern recognition techniques
Course Outcomes:


Students will be able to apply the pattern recognition theories to applications of interest
Students will be able to implement the entropy minimization, clustering transformation and feature
ordering
Introduction - Basic concepts, Applications, Fundamental problems in pattern Recognition system design, Design
concepts and methodologies, Examples of Automatic Pattern recognition systems, Simple pattern recognition model.
Decision And Distance Functions - Linear and generalized decision functions, Pattern space and weight space,
Geometrical properties, implementations of decision functions, Minimum-distance pattern classifications.
Statistical Decision Making - Introduction, Baye’s theorem, Multiple features, Conditionally independent features,
Decision boundaries, Unequal cost of error, estimation of error rates, the leaving-one-out-techniques, characteristic
curves, estimating the composition of populations. Baye’s classifier for normal patterns. Non Parametric Decision
Making - Introduction, histogram, kernel and window estimation, nearest neighbour classification techniques.
Adaptive decision boundaries, adaptive discriminate functions, Minimum squared error discriminate functions,
choosing a decision making techniques.
Clustering And Partitioning - Hierarchical Clustering: Introduction, agglomerative clustering algorithm, the
single-linkage, complete-linkage and average-linkage algorithm. Ward’s method Partition clustering-Forg’s
algorithm, K-means’s algorithm, Isodata algorithm.
Pattern Pre-processing And Feature Selection-Introduction, distance measures, clustering transformation and
feature ordering, clustering in feature selection through entropy minimization, features selection through orthogonal
expansion, binary feature selection.
Syntactic Pattern Recognition & Application Of Pattern Recognition :Introduction, concepts from formal
language theory, formulation of syntactic pattern recognition problem, syntactic pattern description, recognition
grammars, automata as pattern recognizers, Application of pattern recognition techniques in bio-metric, facial
recognition, IRIS scon, Finger prints, etc.,
Text Books:
1. Gose. Johnsonbaugh. Jost. “Pattern recognition and Image Analysis”, PHI.
2. Tou. Rafael. Gonzalez. “Pattern Recognition Principle”, Pearson Education
Reference Books:
1. Richard duda, Hart, David Strok, “Pattern Classification”, John Wiley.
NOTE: The question paper shall consist of Eight questions out of which the students shell any Five questions.
3
CS822: DISTRIBUTED OPERATING SYSTEM (DOS)
(Professional Elective-II For M.Tech CSE)
Scheme
Internal Assessment
End Exam
End Exam Duration
: 2013
: 30
: 70
: 3 Hrs
L
3
T/D
P
-
-
C
Course Objectives:

Students will learn the fundamental principles of distributed systems, emphasizing on communication,
process, naming, synchronization, consistency and replication, and fault tolerance in distributed systems.
Course Outcomes:

Students will be able to learn the goals and fundamental concepts of distributed operating system,
communication models, synchronization algorithms, threads, implementation issues for process allocation.
Distributed Operating System: Goals, Hardware Concepts-Bus Based Multiprocessors, Switched
Multiprocessors, Bus Based MultiComputers, Switched MultiComputers, Software Concepts, Design Issues,
Communication in Distributed Systems, Remote Procedure Call, Group Communication
Synchronization in Distributed Systems: Clock Synchronization-Logical Clocks, Physical Clocks, Clock
Synchronization Algorithms, Use of Synchronized Clocks, Mutual Exclusion, Election Algorithms, Atomic
Transactions, Dead Locks.
Processes And Processors in Distributed Systems: Threads-Introduction, Threads Usage, Design Issues,
Implementing a Threads Package, Threads and RPC ,System Models-Workstation Model, Using Idle Workstations,
Processor Pool Model, Hybrid Model.
Processor allocation-Allocation Models, Design Issues for Process Allocation Algorithms, Implementation Issues for
Process Allocation Algorithms, Example Process Allocation Algorithms, Scheduling in Distributed Systems.
Distributed File System: Distributed File System Design-File Service Interface, Directory Service Interface,
Semantics of File Sharing, Implementation-File Usage, System Structure, Caching,Replication, Trends in Distributed
File System.Introduction to Database Operating Systems, Concurrency Control-Introduction,Database Systems
Problem of Concurrency Control,Serializability Theory,Concurrency Control Algorithms-Introduction,Basic
Synchronization
Primitives,Lock
Based
Algorithms,TimeStamp
Based
Algorithms,Optimistic
Algorithms,Concurrency Control Algorithms:Data Replication
Case Study Amoeba: Introduction, Objects and Capabilities-Capabilities, Object Protection, Standard Operations,
Memory Management-Segments, Mapped Segments.
Communication in AMOEBA-Remote Procedure Call, Group Communication, Fast Local Internet Protocol,
AMOEBA Servers-Bullet Server, Directory Server, Replication Server, Run Server, Boot Server,TCP/IP Server.
Text Books:
1.
Andrew S. Tanenbaum [2008] Distributed Operating System, PE.
Reference Books:
1.
Mukesh Singhal, Niranjan G. Shivaratri [1994], Advanced Concepts in Operating Systems.[VII UNIT]
NOTE: The question paper shall consist of Eight questions with ONE question from each unit. The student shall
answer any Five questions.
3
CS811:SOFTWARE LAB-2
(M.Tech CSE-II Semester)
Scheme
Internal Assessment
End Exam
End Exam Duration
: 2013
: 50
: 50
: 3 Hrs
L
T/D
P
C
-
-
3
2
3
Course Objectives:


To enable the students to understand the implementation of Object Oriented Analysis and design.
To enable the students to create the OO Design of a system from the requirements model in terms of a high
level architecture description and low level models.
Course Outcomes:

Students will be able to make the application of an Unified Modelling Language(UML) towards analysis
and design.
List of experiments:
UML:
1. Introduction to unified modeling language(UML)
2. Implementation of Case Studies
3. Mini Project1: Elevator problem.
4. Mini Project2: on line book shop.
5. Mini Project3: library system.
6. Mini Project4: ATM system.
7. Mini Project5: Student Information System.
8. Mini Project6: Vending Machine.
9. Mini Project7: Graphics Editor.
10. Mini Projects: Payroll System
CS901: MOBILE COMPUTING (MCP)
(M.Tech CSE III Semester)
Scheme
Internal Assessment
End Exam
End Exam Duration
: 2013
: 30
: 70
: 3 Hrs
L
3
T/D
P
-
-
C
Course Objectives:



To expose the students to the concepts of wireless devices and mobile computing.
To understand characteristics of local and wide area technologies such as Bluetooth, 802.11 and GSM.
To understand network and transport layer protocols for wireless networks, including mobile IP and
variants of TCP.
Course Outcomes:

Students will understand the concept of mobile computing and the architecture of mobile communications.

Students understand wireless access and core networks and mobility in cellular and wireless networks using
the important standards like GSM, CDMA, GPRS and IEEE 802.11.
Wireless transmission: Frequencies for radio transmission, Signals, Antennas, Signal propagation, Multiplexing,
Modulation, Spread spectrum, Cellular systems Medium access control: Motivation for a Specialized MAC, SDMA,
FDMA, TDMA, CDMA, Comparison of S/T/F/CDMA.
GSM: Mobile services, System Architecture, Radio interface, Protocols, Localization and calling, Handover,
Security DECT System architecture, Protocol architecture, TETRA
Wireless LAN: Infrared Vs Radio Transmission, Infra Red and ad-hoc network IEEE 802.11: System architecture,
Protocol architecture, Physical layer, Medium access control layer, MAC management, 802.11b, 802.11a, Newer
developments.
Mobile IP: Goals & requirements, Entities and terminology, IP Packet delivery, Agent discovery, Registration,
Tunneling & encapsulation, Optimizations, Reverse tunneling, IPv6, IP micro- mobility support, Dynamic host
Configuration protocol.
Traditional TCP: Congestion control, Slow start, Fast retransmit/fast recovery, implications of mobility, Classical
TCP improvements.
Text Books:
1. Jochen Schiller, Mobile Communications, [Second Edition], Low price edition Pearson Education.
Reference Books:
1. Talukder, Mobile Computing: Technology, Applications & service creation, TMH.
NOTE: The Question paper shall consists of Eight questions out of which the student shall answer any Five
questions.
3
CS904: SOFT COMPUTING (SC)
(Professional Elective-III for M.Tech CSE)
Scheme
Internal Assessment
End Exam
End Exam Duration
: 2013
: 30
: 70
: 3 Hrs
L
3
T/D
P
-
-
C
Course Objectives:

To give students knowledge of soft computing theories fundamentals, ie. Fundamentals of artificial and
neural networks, fuzzy sets and fuzzy logic and genetic algorithms.
Course Outcomes:

Students will be able to understand the Soft computing theories and fundamentals of Artificial and Neural
Networks
AI Problems and Search: AI problems, Techniques, Problem Spaces and Search, Heuristic Search TechniquesGenerate and Test, Hill Climbing, Best First Search Problem reduction, Constraint Satisfaction and Means End
Analysis. Approaches to Knowledge Representation- Using Predicate Logic and Rules.
Artificial Neural Networks: Introduction, Basic models of ANN, important terminologies, Supervised Learning
Networks, Perceptron Networks, Adaptive Linear Neuron, Back propagation Network. Associative Memory
Networks. Training Algorithms for pattern association, BAM and Hopfield Networks.
Unsupervised Learning Network- Introduction, Fixed Weight Competitive Nets, Maxnet, Hamming Network,
Kohonen Self-Organizing Feature Maps, Learning Vector Quantization, Counter Propagation Networks, Adaptive
Resonance Theory Networks. Special Networks-Introduction to various networks.
Introduction to Classical Sets ( crisp Sets)and Fuzzy Sets- operations and Fuzzy sets. Classical Relations -and
Fuzzy Relations- Cardinality, Operations, Properties and composition. Tolerance and equivalence
relations.Membership functions- Features, Fuzzification, membership value assignments, Defuzzification.
Fuzzy Arithmetic and Fuzzy Measures, Fuzzy Rule Base and Approximate Reasoning Fuzzy Decision making.
Fuzzy Logic Control Systems. Genetic Algorithm- Introduction and basic operators and terminology. Applications:
Optimization of TSP, Internet Search Technique
Text Books:
1.Principles of Soft Computing- S N Sivanandam, S N Deepa, Wiley India, 2007.
2.Soft Computing and Intelligent System Design -Fakhreddine O Karray, Clarence D Silva, Pearson Edition,
2004.
Reference Books:
1.Artificial Intelligence and SoftComputing- Behavioural and Cognitive Modelling of the Human Brain- Amit
Konar, CRC press, Taylor and Francis Group.
2. Artificial Intelligence – Elaine Rich and Kevin Knight, TMH, 1991, rp2008.
NOTE: The question paper shall consist of Eight questions with ONE question from each unit. The student shall
answer any FIVE questions.
3
CS905: INFORMATION RETRIEVAL SYSTEM (IRS)
(Professional Elective-III for M.Tech CSE)
Scheme
Internal Assessment
End Exam
End Exam Duration
: 2013
: 30
: 70
: 3 Hrs
L
3
T/D
P
-
-
C
Course Objectives:




To understand the dimensions and functions of the information retrieval system
To analyze the components of an information retrieval system;
To consider the factors which optimize the information retrieval process;
To examine current issues in information retrieva
Course Outcomes:



Students will be able to Learn history and development of information retrieval systems
Students will be able to explain core concepts and terms, retrieval models and basic algorithms involved in
processing and retrieval of information
Students will identify the essential components and functions of an information retrieval system
Introduction: Basic concepts, Past present and Future of IRS, Retrieval Process. Modeling: Introduction, A
Taxonomy of JR Models, Retrieval: Adhocand Filtering, A formal characterization of IR Models, Classic IR, Set
Theoretic Models, Algebraic Models.
Retrieval Evaluation: Introduction, Reference Collections. Query languages: Introduction, Keyword-based
querying, pattern Matching, Structural Queries, Query Protocols.
Document and Term Clustering: Introduction, Thesaurus generation, Item clustering, Hierarchy of clusters– User
Search Techniques: Search statements and binding, Similarity measures and ranking, Relevance feedback,
Selective dissemination of information search, Weighted searches of Boolean systems, Searching the Internet and
hypertext- Information Visualization: Introduction, Cognition and perception, Information visualization
technologies.
Text Search Algorithms: Introduction, Software text search algorithms, Hardware text search systems. Information
System Evaluation: Introduction, Measures used in system evaluation, Measurement example–TREC results.
Multimedia Information Retrieval – Models and Languages – Data Modeling, Indexing and Searching - Libraries
and Bibliographical Systems – Online IR Systems, OPACs, Digital Libraries.
Text Books:
1. Modern Information Retrieval By Ricardo Baeza-Yates, Pearson Education, 2007.
2. Information Storage and Retrieval Systems: Theory and Implementation By Kowalski,
Gerald, Mark T Maybury Kluwer Academic Press, 2000.
Reference Books:
1.
Information Retrieval Data Structures and Algorithms By William B Frakes, Ricardo Baeza-Yates, Pearson
Education, 1992.
2. Information Storage & Retieval By Robert Korfhage – John Wiley & Sons.
3. Introduction to Information Retrieval By Christopher D. Manning and Prabhakar Raghavan, Cambridge
University Press, 2008.
NOTE: The question paper shall consist of Eight questions with ONE question from each unit. The student
shall answer any Five questions.
3
CS906: SOFTWARE PROJECT MANAGEMENT (SPM)
(Professional Elective-III for M.Tech CSE)
Scheme
Internal Assessment
End Exam
End Exam Duration
: 2013
: 30
: 70
: 3 Hrs
L
3
T/D
P
-
-
C
Course Objectives:


To be able to estimate, effectively monitor progress, risk assessment of the software project under
development.
To understand how software development is integrated with other business activities and how social and
environmental factors impact development.
Course Outcomes:

Students will be able to describe and determine the purpose and importance of project management from
the Perspectives of planning, tracking and completion of project.
Managing Software Projects: Process and Project Management, Project management and the CMM.Project
Planning Infrastructure: The Process Database, Process Capability Baseline, Process Assets and the Body of
Knowledge System.
Process Planning: Development Process, Requirement Change Management, Process Planning. Effort Estimation
and Scheduling: Estimation and Scheduling Concepts, Effort Estimation, Scheduling.Quality Planning: Concepts,
Quantitative Quality Management Planning, Defect Prevention Planning
Risk Management: Concepts, Risk Assessment, Risk Control. Measurement and Tracking Planning: Concepts,
Measurement, Project Tracking.
Project Management Plan: Team Management, Communication and Issue Resolution, Structure.Configuration
Management: Concepts, Process – Planning – Control – Status Monitoring and Audits.
Project Execution and Closure: Review Process, Data Collection, Monitoring.Project Monitoring and Control:
Project Tracking Milestone Analysis – Actual versus Estimated Analysis, Monitoring Quality, Risk-Related
Monitoring.
Text Books:
1. Pankaj Jalote [2002], Software Project Management in Practice, Pearson Education
Reference Books:
1. Sommerville [2008], [7th Edition], Software Engineering ,Pearson education.
2. Roger S.Pressman [2005], [6th Edition], Software Engineering, A Practitioner’s Approach,
Mc GrawHill International Edition.
NOTE: The question paper shall consist of Eight questions with ONE question from each unit. The student shall
answer any FIVE questions.
3
CS907: NEURAL NETWORKS (NN)
(Professional Elective-III for M.Tech CSE)
Scheme
Internal Assessment
End Exam
End Exam Duration
: 2013
: 30
: 70
: 3 Hrs
L
3
T/D
P
-
-
C
3
Course Objectives:


To Understand the mathematical foundations of neural network models.
To Design and implement neural network systems to solve real-world problems
Course Outcomes:

Students will be able to learn
basic neural network architecture and learning algorithms

Students
will
be
able
to
understand data pre and post processing.
Introduction - what is a neural network? Human Brain, Models of a Neuron, Neural networks viewed as Directed
Graphs, Network Architectures, Knowledge Representation, Artificial Intelligence and Neural Networks.
Learning Process – Error Correction learning, Memory based learning, Hebbian learning, Competitive, Boltzmann
learning, Credit Assignment Problem, Memory, Adaption, Statistical nature of the learning process,
Single Layer Perceptrons – Adaptive filtering problem, Unconstrained Organization Techniques, Linear least
square filters, least mean square algorithm, learning curves, Learning rate annealing techniques, perceptron –
convergence theorem, Relation between perceptron and Bayes classifier for a Gaussian Environment
Multilayer Perceptron – Back propagation algorithm XOR problem, Heuristics, Output representation and decision
rule, Computer experiment, feature detection,
Back Propagation - back propagation and differentiation, Hessian matrix, Generalization, Cross validation,
Network pruning Techniques, Virtues and limitations of back propagation learning, Accelerated convergence,
supervised learning.
Text Books:
1. Simon Hhaykin,[2nd edition], [2004] Neural networks A comprehensive foundations, Pearson Education.
Reference Books:
1. Neural networks in Computer intelligence, Li Min Fu TMH 2003
2. Neural networks James A Freeman David M.Skapura pearson education 2004
3. Artifical neural networks - B.Vegnanarayana Prentice Halll of India P Ltd 2005
NOTE: The question paper shall consist of Eight questions out of which the student shall answer any Five
questions.
CS908: DISTRIBUTED DATABASE (DD)
(Professional Elective-IV for M.Tech CSE)
Scheme
Internal Assessment
End Exam
End Exam Duration
: 2013
: 30
: 70
: 3 Hrs
L
3
T/D
P
-
-
C
Course Objectives:

To understand the management of
Distributed Transactions, reliability concepts and architectural issues of Distributed databases.
Course Outcomes:

Students will be able to
understand persistent programming, information retrieval and advanced transaction processing.
Features of Distributed versus Centralized Data Bases, Principles of Distributed Databases, Levels of
Distribution Transparency, Reference Architecture for Distributed Databases, Types of Data Fragmentation.
Integrity Constraints in Distributed Databases, Distributed Database Design
Translation of Global Queries to Fragment Queries, Equivalence Transformation for Queries, Transforming
Global Queries into Fragment Queries, Distributed Grouping and Aggregate, Function Evolution, Parametric
Queries
Optimization of Access, Strategies, A Frame work foe Query Optimization Join Queries, General Queries
The Management of Distributed Transactions, A Framework for Transaction management, Supporting Atomicity
of Distributed Transactions, Concurrency Control for Distributed Transactions, Architectural Aspects of Distributed
Transactions
Concurrency Control, Foundation of Distributed Concurrency Control, Distributed Deadlocks, Concurrency Control
based on Timestamps, Optimistic Methods for Distributed Concurrency Control.
Reliability, Basic Concepts, Nonblocking Commitment Protocols, Reliability and Concurrency Control.
Determining a Consistent View of the Network, Detection and Resolution of Inconsistency, Checkpoints and Cold
Restart, Distributed Database Administration, Catalog Management in Distributed Databases, Authorization and
Protection
Architectural Issues, Alternative Client/Server Architectures, Cache Consistency, Object Management, Object
Identifier Management, Pointer Swizzling, Object Migration, Distributed Object Storage, Object Query Processing
and Architecture, Query Processing Issues, Query Execution, Transaction Management, Database Integration,
Scheme Translation, Scheme Integration, Query Processing Layers in Distributed Multi DBMSs, Query
Optimization, Issues Transactions Management Transactions and Computation Model, Multi Database Concurrency
Control, Multi Database recovery, Object Orientation and Interoperability, Object Management Architecture
CORBA and Database interoperability, Distributed Component Object Model, COM/ OLE and Database
Interoperability, PUSH –Based Technologies
Text Books:
1.
Distributed Databases Principles & Systems ,Stefano Ceri,Giuseppe Pelagatti, TMH.
Reference Books:
1.
Principles of Distributed Database Systems. M. Temer Ozsu, Patrick Valduriez, pearson
Education,2nd Edition.
3
NOTE: The question paper shall consist of Eight questions out of which the student shall answer any Five
questions
CS909: NETWORK SECURITY & CRYPTOGRAPHY (NSC)
(Professional Elective-IV for M.Tech CSE)
Scheme
Internal Assessment
End Exam
End Exam Duration
: 2013
: 30
: 70
: 3 Hrs
L
3
T/D
P
-
-
C
Course Objectives:

To understand the principles of
encryption algorithms, Conventional and public key cryptography, and to have a detailed knowledge on
authentication, hash functions and application level security mechanisms.
Course Outcomes:

Students are able to understand
encryption algorithms like DES, IDEA, AES, RSA, Diffie Hellman key exchange etc., authentication
systems, IP and web security.
Overview: Services, Mechanisms and Attack, The OSI Security Architecture: Security Services, Availability
Services, Security Mechanisms and Security Attacks, A model for Network Security.
Classical Encryption Techniques : Symmetric Cipher Model, Substitution Techniques : Caesar Cipher,
Monoalphabetic Cipher, Playfair Cipher, Hill Cipher, Monoalphabetic cipher, One-Time Pad, Transposition
Techniques. Block Ciphers and the Data Encryption Standard: Simplified DES, Block Cipher Principles, The DES,
The Strength of DES, Differential and Linear Cryptanalysis, Block Cipher Design Principles, Block Cipher modes
of Operation
Public Key Cryptography and RSA: Principles of Public Key Cryptosystems, The RSA Algorithm. Key
Management: Key Management, Diffie – Hellman Key Exchange
Message Authentication and Hash Functions : Authentication Requirements, Authenticaion Functions, Message
Authentication Codes, Hash Functions, Security of Hash Fuctions and MACs. Hash Algorithms : MD5 Message
Digest Algorithm: MD5 Logic, MD5 Compression function, MD4, Strength of MD5, Secure Hash algorithm: SHA1 Logic, Compression function, Comparison of SHA-1 and MD5, Revised Secure Hash Standard.
Digital Signatures and Authentication Protocols: Digital Signatures, Authentication Protocols: Mutual
Authentication, Symmetric Authentication approaches, Public-key Encryption approaches and One-Way
Authentication, Digital Signature Standard.
Authentication Applications: Kerberos: Motivation, Kerberos Version 4, Kerberos Version 5, X.509 Authentication
Service: Certificates, Authentication Procedures, X.509 Version 3.
Text Books:
William Stallings [2008], [4th Edition], Cryptography and Network Security: Principles and Practices,
Pearson Education.
Reference Books:
William Stallings [2008], [3rd Edition], Network Security Essentials (Applications and Standards),
PearsonEducation.
3
NOTE: The question paper shall consist of Eight questions with ONE question from each unit. The student shall
answer any FIVE questions.
CS910: DATA MINING AND BUSSINESS ANALYTICS (DMBA)
(Professional Elective-IV for M.Tech CSE)
Scheme
Internal Assessment
End Exam
End Exam Duration
: 2013
: 30
: 70
: 3 Hrs
L
3
T/D
P
-
-
C
Course Objectives:

To make the students learn algorithms, data mining, sensing and cluster analysis.
Course Outcomes:

Able to understand the cluster analysis, visual time series analysis.
Introduction to Data mining : What is Data Mining, Integration of Data Mining system with a Database or a
Data Warehouse System, Major issues in Data Mining, Applications and Trends in Data Mining.
Algorithms & Data mining: Mining Frequent Patterns, Associations, Basic Concepts, Efficient and Scalable
Frequent Itemset Mining methods Mining various kinds of association rules, from association analysis to
Correlation analysis, constraint-based association mining
Classification and Prediction: What is classification, What is Prediction, Classification by Decision tree
Induction, Bayesian classification, Rule based classification, Prediction: Linear Regression, non-linear regression
Cluster Analysis: Types of data in cluster analysis, classical Partitioning methods : k-Means and k-Medoids.
Interactive Visual Data Analysis: Challenges faced by everyday data analysts, A brief history of interactive
visual data analysis, Differences between statics graphics and interactive graphics.
Text Books:
1.
2.
3.
4.
Jiawei Han and Micheline Kamber, Data Mining: Concepts and Techniques, Second Edition, Elsevier
Michael Berry and Gordon Linoff, Data Mining Techniques, Wiley Publishing, 2004.
Kimball and Ross, The Data Warehouse Toolkit, Second Edition, John Wiley & Sons, 2002.
T. Davenport, “Competing on Analytics,” Harvard Business Review (Decision Making), January 2006.
NOTE: The question paper shall consist of Eight questions with ONE question from each unit. The student
shall answer any FIVE questions.
3
CS911: DATA WAREHOUSING AND MINING (DWM)
(Professional Elective-IV for M.Tech CSE)
Scheme
Internal Assessment
End Exam
End Exam Duration
: 2013
: 30
: 70
: 3 Hrs
L
3
T/D
P
-
-
C
Course Objectives:

Students can learn the knowledge
that is held in enterprise data warehouses and other data stores by examining the data to reveal untapped
patterns that suggest better ways to improve quality of product, customer satisfaction and retention, and
profit potentials.
Course Outcomes:

Understand the conceptual steps involved in data mining and learn how to apply it for solving business
problems
Introduction, Delivery Process, System Process – Process flow, Extraction and Loading of Data, Clean and
Transform Data, Backup and Query Management process.Process Architecture – Various types of Managers and
information.
Data Warehousing Components: Overall Architecture, Datawarehouse database, Sourcing, Acquisition Cleanup and
Transformation Tools,Meta Data, Access tools, Data Marts, Data warehouse Administration and Management.
Building a Data Warehouse: Business considerations, Design considerations, Technical considerations,
Implementation considerations, Integrated solutions, Benefits of data warehousing. Mapping Datawarehouse to
Multiprocessor Architecture.
DBMS Schemas for Decision Support: Data layout for best access,Multidimentional data model, Star schema, Star
Join and StarIndex,Bitmapped Indexing, Column Local storage, Complex Data types. Data Extraction, Cleanup and
Transformation Tools: Tool Requirements, Vendor Approaches, Access to Legacy data, Vendor Solutions,
Transformation Engines, Metadata: Metadata Defined, Metadata Interchange Initiative, Metadata Repository,
Metadata Management, Implementation Examples, Metadata Trends.
Reporting and Query Tools: Reporting Tools, Managed Query Tools, Executive Information system Tools, OLAP
Tools, Data Mining Tools. OLAP – Need for OLAP, Guidelines, Categorization. Patterns and Models – Where and
What of a Model, Sampling, Experimental Design
Data Mining: Introduction, Decision Trees – What and where How of Decision Trees, Nearest Neighbour and
Clustering, General Idea. Case Studies.
Text Books:
1.
2.
Sam Anahory and Dennis Murray [2008], Data Warehousing in the Real World, Pearson Education.
Alex Berson, Stephen J. Smith [2008], Data Warehousing, Data Mining & OLAP, TMH
Reference Books:
3
1.
2.
Jiawei Han, Micheline Kamber, Elsevier [2008], Data Mining concepts and techniques.
Margaret H. Dunham, S. Sridhar [2003], Data Mining Introductory and Advanced Topics ,Pearson Education.
NOTE:The question paper shall consist of Eight questions with ONE question from each unit. The student shall
answer any FIVE questions.