Master of Computer Applications Scheme of V-VI … of Computer Applications Scheme of V-VI Semester MCA (2013-2014) Department of PG-Studies in Computer Engineering and Application

NIE, Mysore – 8. Department of PG Studies in CE&A

THE NATIONAL INSTITUTE OF ENGINEERING, MYSORE – 8.

(Autonomous Institution under VTU)

Master of Computer Applications

Scheme of

V-VI Semester MCA

(2013-2014)

Department of PG-Studies in Computer Engineering and Application


SCHEME OF TEACHING AND EXAMINATION FIFTH SEMESTER MCA (AUTONOMOUS SCHEME)

Sl. No

Sub Code Subject Title Teaching

Dept.

Contact Hrs./Week Credits

Marks

Exam Duration

L T P CIE SEE Total (Hrs)

1 MCA0419

System Simulation and Modeling

PG Studies 4 0 0 4 50 50 100 3

2 MCA0420

Object Oriented Modeling and Design Patterns

PG Studies 4 0 0 4 50 50 100 3

3 MCA0421 .Net and C# PG

Studies 4 0 0 4 50 50 100 3

4 MCA04-- Elective – III PG

Studies 4 0 0 4 50 50 100 3

5 MCA04-- Elective – IV PG

Studies 4 0 0 4 50 50 100 3

6 MCA0112 Software Design Lab PG

Studies 0 0 3 1.5 50 – 50 --

7 MCA0113 .Net Lab PG

Studies 0 0 3 1.5 50 – 50 --

8 MCA0114 Mini Project PG

Studies - - 2 1.0 50 -- 50 --

9 MCA0115 Seminar – I PG

Studies - - 2 1.0 50 -- 50 --

TOTAL 20 0 10 25 450 250 700

SCHEME OF TEACHING AND EXAMINATION SIXTH SEMESTER MCA (AUTONOMOUS SCHEME)

Sl. No

Subject Cod

e Subject Title

Teaching

Dept.

Contact Hrs./Week Cred

its

Marks

Exam Durati

on L T P CIE SEE Total (Hrs)

1 MCA2801 Major Project PG

Studies - - - 28 150 75 225 3

2 MCA0201 Seminar - II PG

Studies - - - 2 - 50 50 -

TOTAL - - - 30 150 125 275

Pattern of course evaluation for both CIE and SEE will be mentioned in the abridged lesson plan and the Course Instructor (CI) will discuss the same with the students during the first/second session of the semester


System Simulation and Modeling (4:0:0)

Sub Code : MCA0419 CIE : 50%

Hrs/Week : 04 SEE : 50%

SEE Hours : 3 Hrs Max Marks : 100

Pre-requisite: N/A Course outcomes On successful completion of the course, the students will be able to:

1. Explain the benefits of simulation and modeling in a range of important application areas.

2. Demonstrate the ability to apply the techniques of modeling and simulation to a range of problem areas.

3. Evaluate a simulation, highlighting the benefits and the drawbacks. 4. To understand how to generate and evaluate pseudorandom numbers. 5. Understand the concepts of modeling and simulation of dynamic systems using

variety of formalisms. 6. Verify and validate various simulation models.

Unit 1: Introduction When simulation is the appropriate tool and when it is not appropriate; Advantages and disadvantages of Simulation; Systems and system environment; Components of a system; Discrete and continuous systems; Model of a system; Types of Models; Discrete-Event System Simulation; Steps in a Simulation Study. Simulation examples: Simulation of queuing systems. Self Learning Components: Areas of application. Unit 2: General Principles, Simulation Software Concepts in Discrete-Event Simulation: The Event-Scheduling / Time-Advance Algorithm, World Views, Manual simulation Using Event Scheduling. Self Learning Components: List processing, Simulation in Java. Unit 3: Statistical Models in Simulation and Queuing Models Review of terminology and concepts; Useful statistical models; Discrete distributions; Continuous distributions; Poisson process; Empirical distributions. Characteristics of queuing systems; Queuing notation; Long-run measures of performance of queuing systems; Steady-state behaviour of M/G/1 queue; Self Learning Components: Networks of queues. Unit 4: Random-Number Generation, Random-Variate Generation Properties of random numbers; Generation of pseudo-random numbers ; Techniques for generating random numbers; Tests for Random Numbers. Random-Variate Generation: Inverse transform technique ; Acceptance-Rejection technique;


Self Learning Components: Special properties. Unit 5: Input Modelling and Output Analysis for a Single Model Data Collection; Identifying the distribution with data; Parameter estimation; Goodness of Fit Tests; Fitting a non-stationary Poisson process; Selecting input models without data; Multivariate and Time-Series input models. Types of simulations with respect to output analysis; Stochastic nature of output data; Measures of performance and their estimation; Output analysis for terminating simulations; Self Learning Components: Output analysis for steady-state simulations. Unit 6: Verification and Validation of Simulation Models, Optimization Model building, verification and validation ; Verification of simulation models; Calibration and validation of models. Self Learning Components: Optimization via Simulation. Text Books:

1. Jerry Banks, John S. Carson II, Barry L. Nelson, David M. Nicol: Discrete-Event System Simulation, 4th Edition, Pearson Education / PHI, 2007.

Reference Books: 1. Lawrence M. Leemis, Stephen K. Park: Discrete – Event Simulation: A First Course, Pearson / Prentice-Hall, 2006. 1. Averill M. Law: Simulation Modeling and Analysis,4th Edition, Tata McGraw-

Hill, 2007.


Object-Oriented Modeling and Design Patterns (4:0:0)

Sub Code : MCA0420 CIE : 50%


SEE Hours : 3 Hrs Max Marks : 100 Pre-requisite: Concepts of OOPs. Course Outcomes: On successful completion of the course, the students will be able to:

1. Describe the concept of object-orientation methodologies 2. Create use case documents that capture requirements for a software system. 3. Create class diagrams that model both the domain model and design model of a

software system. 4. Design the interface between the classes and objects. 5. Create interaction diagrams that model the dynamic aspects of a software system. 6. Design communication and design patterns.

Unit – 1 Introduction, Modeling Concepts, class Modeling What is Object Orientation? What is OO development? OO themes; Evidence for usefulness of OO development; OO modeling history. Modeling as Design Technique: Modeling; abstraction; the three models. Class Modeling: Object and class concepts; Link and associations concepts; Generalization and inheritance; Self Learning Component: A sample class model; Navigation of class models; Practical tips. Unit – 2 Advanced Class Modeling, State Modeling Advanced object and class concepts; Association ends; N-array associations; Aggregation; Abstract classes; Multiple inheritance; Metadata; Reification; Constraints; Derived data; Packages; Practical tips. State Modeling: Events, States, Transitions and Conditions; State diagrams; State diagram behavior; Practical tips.Advanced State Modeling, Interaction Modeling: Advanced State Modeling: Nested state diagrams; Nested states; Signal generalization; Concurrency; Practical tips. Interaction Modeling: Use case models; Sequence models; Activity models. Use case relationships; Procedural sequence models; Special constructs for activity models. Self Learning Component: State diagram behavior, A Sample state model, Relation of class and state Models. Unit – 3 Process Overview, System Conception, Domain Analysis Process Overview: Development stages; Development life cycle. System Conception: Devising a system concept; Elaborating a concept; Domain Analysis: Overview of


analysis; Domain class model; Domain state model; Domain interaction model; Iterating the analysis. Self Learning Component: Preparing a problem statement. Unit – 4 Application Analysis, System Design Application Analysis: Application interaction model; Application class model; Application state model; adding operations. Overview of system design; Estimating performance; Making a reuse plan; Breaking a system in to sub-systems; Identifying concurrency; Allocation of sub-systems; Management of data storage; Handling global resources; Choosing a software control strategy; Handling boundary conditions; Setting the trade-off priorities; Common architectural styles; Self Learning Component: Architecture of the ATM system as the example. Unit – 5 Class Design, Implementation Modeling, Legacy Systems Class Design: Overview of class design; Bridging the gap; Realizing use cases; Designing algorithms; Recursing downwards, Refactoring; Design optimization; Reification of behavior; Adjustment of inheritance; Organizing a class design. Implementation Modeling: Overview of implementation; Fine-tuning classes; Fine-tuning generalizations; realizing associations; Testing. Legacy Systems: Reverse engineering; Building the class models; Reverse engineering tips; Wrapping; Maintenance. Self Learning Component: ATM example, Building the class, the interaction model and state model. Unit – 6 Design Patterns, Idioms What is a pattern and what makes a pattern? Pattern categories; Relationships between patterns; Pattern description; CommunicationPatterns:Forwarder-Receiver;Client-Dispatcher-Server;Publisher-Subscriber; Command processor; View Handler; Idioms: Introduction; What can idioms provide? Self Learning Component: Management Patterns, Idioms and style; Where to find idioms; Counted Pointer example. Text Books:

1. Michael Blaha, James Rumbaugh: Object-Oriented Modeling and Design with UML,

2nd Edition, Pearson Education / PHI, 2005. (Chapters 1 to 17, 23) 2. Frank Buschmann, Regine Meunier, Hans Rohnert, Peter Sommerlad, Michael Stal:

Pattern-Oriented Software Architecture, A System of Patterns, Volume 1, John Wiley and Sons, 2006. (Chapters 1, 3.5, 3.6, 4)

Reference Books:

1. Grady Booch et al: Object-Oriented Analysis and Design with Applications, 3rd Edition, Pearson, 2007. 2. Mark Priestley: Practical Object-Oriented Design with UML, 2nd Edition, Tata McGraw-Hill, 2003.


1. K. Barclay, J. Savage: Object-Oriented Design with UML and JAVA, Elsevier, 2008.

2. Booch, G., Rumbaugh, J., and Jacobson, I.: The Unified Modeling Language User Guide, 2nd Edition, Pearson, 2005.


.NET & C# (4:0:0) Sub Code : MCA0420 CIE : 50%



Pre-requisite: OOP concepts On successful completion of the course, the students will be able to:

1. Identify a solution in .NET environment after proper analysis of previous state of affairs.

2. Have a comparative study on C,C++,java and C# 3. Write/build various kinds of applications like exceptions in C# 4. Write/build various kinds of applications like interfaces 5. Devise an algorithm & formulate a solution in C# for the problems based on

object oriented programming principles 6. Working some of the delegates problems and getting an exposure to Visual Studio

.NET framework. Unit 1 The philosophy of .NET Understanding the previous State of Affairs, The .NET Solution, The Building Block of the .NET Platform (CLR,CTS, and CLS), The Role of the .NET Base Class Libraries, What C# Brings to the Table, An Overview of .NET Binaries ( aka Assemblies ), the Role of the Common Intermediate Language , The Role of .NET Type Metadata, The Role of the Assembly Manifast, Compiling CIL to Platform –Specific Instructions, Understanding the Common Type System, Intrinsic CTS Data Types, Understanding the Common Languages Specification, Understanding the Common Language Runtime A tour of the .NET Namespaces, Increasing Your Namespace Nomenclature, Deploying the .NET Runtime Building C# Applications The Role of the Command Line Complier (csc.exe), Building C # Application using csc.exe Working with csc.exe Response Files, Generating Bug Reports, C# Compiler Options, Command Line Debugger (cordbg.exe) Using the VisualStudio .NET IDE, Other Key Aspects of the VS.NET IDE, C# “Preprocessor:” Directives, An Interesting Aside: The System.Environment Class. Self learning component: execution of simple C# application programs

Unit 2 C# Language Fundamentals. The Anatomy of a Basic C# Class, Creating objects: Constructor Basics, The Composition of a C# Application, Default Assignment and Variable Scope, The C# Member Initialization Syntax, Understanding Value Types and Reference Types, The Master Node: System, Object, The System Data Types (and C# Aliases), Converting Between Value Types and Reference Types: Boxing and Unboxing, Defining Program Constants, C# Iteration Constructs, C# Controls Flow Constructs, The Complete Set of C# Operators, Defining Custom Class Methods, Understating Static Methods, Methods


Parameter Modifies, Array Manipulation in C #, String Manipulation in C#, C# Enumerations, Defining Structures in C#, Defining Custom Namespaces. Self learning component :Basic Input and Output with the Console Class Unit-3 Object- Oriented Programming with C# Forms Defining of the C# Class, Definition the “Default Public Interface” of a Type, Recapping the Pillars of OOP, The First Pillars: C#’s Encapsulation Services, Pseudo- Encapsulation: Creating Read-Only Fields, The Second Pillar:,keeping Family Secrets: The “ Protected” Keyword, Nested Type Definitions, The Third Pillar: C #’s Polymorphic Support, Casting Between . Self learning component :C#’s Inheritance Supports Unit4 Exceptions and Object Lifetime. Ode to Errors, Bugs, and Exceptions, The Role of .NET Exception Handing, the System. Exception Base Class, Throwing a Generic Exception, Catching Exception, CLR System–Level Exception, Custom Application-Level Exception Handling, Multiple Exceptions, The Finally Block; Dynamically Identifying Application and System Level Exceptions, Debugging System Exception Using VS .NET, Understanding Object Lifetime, the CIL of ‘new’, The Basics of Garbage Collection, Finalization of a Type, The Finalization Process, Building an Ad Hoc Destruction Method, Self learning component :Garbage Collection Optimizations, The System.GC Type. Unit 5 Interfaces and Collections Defining Interfaces Using C# Invoking Interface Members at the object Level, Exercising the Shapes Hierarchy, Understanding Explicit Interface Implementation, Interfaces As Polymorphic Agents, Building Interface Hierarchies, Implementing, Implementation, Interfaces Using VS .NET, understanding the IConvertible Interface, Building a Custom Enumerator(IEnumerable and Enumerator), building Cloneable objects(ICloneable), Building Comparable Objects(IComparable), Building a Custom Container Self learning component: Exploring the System.Collections Namespace

Unit 6 Callback Interfaces, Delegates & Advanced Techniques Understanding Callback Interfaces, Understanding the .NET Delegate Type, Members of System. Multicast Delegate, The Simplest Possible Delegate Example, Building More a Elaborate Delegate Example, Understanding Asynchronous Delegates, A Catalog of C# Keywords, Building a Custom Indexer, differentiating indexer from propertieDs,Creating Custom Conversion Routines, Defining Implicit Conversion Routines, The Internal Representations of Customs Conversion Routines. Self learning component Overloading of operator and Advanced Keywords of C# Text Books: 1. Andrew Troelsen: Pro C# with .NET 3.0, Special Edition, Dream tech Press, India, 2007. Chapters: 1 to 11 (up to pp.369).


2. E. Balagurusamy: Programming in C#, , 5th Reprint, Tata McGraw Hill, 2004. (Programming Examples 3.7, 3.10, 5.5, 6.1, 7.2, 7.4, 7.5, 7.6, 8.1, 8.2, 8.3, 8.5, 87, 8.8, 9.1, 9.2, 9.3, 9.4, 10.2, 10.4, 11.2, 11.4, 12.1, 12.4, 12.5, 12.6, 13.1, 13.2, 13.3, 13.6, 14.1, 14.2, 14.4, 15.2, 15.3, 16.1, 16.2, 16.3, 18.3, 18.5.18.6.)

Reference Books: 1. Tom Archer: Inside C#, WP Publishers, 2001. 2. Herbert Schildt: The Complete Reference C#, , Tata McGraw Hill, 2004.


Software Design Laboratory (0:0:3)

Sub Code : MCA0112 Hrs/Week : 03

Max Marks: 50

Pre-requisite: Concepts of OOPs. Course Outcomes: On successful completion of the course, the students will be able to:

1. Describe the concept of object-orientation methodologies 2. Create use case documents that capture requirements for a software system. 3. Create class diagrams that model both the domain model and design model of a

software system. 4. Design the interface between the classes and objects. 5. Create interaction diagrams that model the dynamic aspects of a software system. 6. Design communication and design patterns.

Objective: To design and develop various applications using IBM Rational Rose Experiments

The student has to draw the necessary UML diagrams using any suitable UML Drawing Tool and implement in Java OR C++ OR C# program to demonstrate the Design Patterns listed below:

1. Expert 2. Controller 3. Publisher-Subscriber 4. Command 5. Forward-Receive 6. Client-Dispatcher 7. Proxy 8. Façade 9. Polymorphism


.Net Laboratory (0:0:3)


Max Marks: 50

Pre-requisite: OOP concepts On successful completion of the course, the students will be able to:

1. Display proficiency in C# by building stand-alone applications in the .NET framework using C# that is completely event driven.

2. Create simple web applications and window application features of C# 3. Create distributed data-driven applications using the .NET Framework, C# 4. Create web-based distributed applications using C# 5. Debug an application using breakpoints and Try/Catch/Finally blocks 6. Debug an application using delegates and demonstration of inheritance support.

IDE: Microsoft Visual Studio8 Initially work with simple programs in runtime environment .NET framework i.e.SDK command prompt. Simple programs in C#, Programs on Array processing in C#, interfaces, use of Virtual and override key words, collections, abstract classes and methods, exception handling etc.


Mini Project 1 (0:0:2)


Max Marks: 50

Pre-requisite: NA Course Outcomes On successful completion of the course, the students will be able to:

1. Identification of real world problems 2. Understand different design methodologies. 3. Ability to select appropriate tools for solving a problem 4. Implementing advanced programming techniques/languages 5. Learn the art of verification and validation. 6. Ability to write technical reports

A team of TWO students must develop the mini project. However, during the final presentation, each student must demonstrate the project individually.

1. The team may implement a mini project of their choice. 2. The team must submit a Brief Project Report (25 to 30 Pages) that must include the

following:

• Introduction, Requirements • Software Development Process Model Adopted, Analysis and Design

Models of Implementation • Testing • The Report must be evaluated for 10 marks, Demonstration for 30 marks and

Viva for 10 marks.


Seminar I (0:0:2)


Max Marks: 50

Pre-requisite: NA On successful completion of the course, the students will be able to:

1. Awareness of current trends in specific area of interest 2. Ability to conduct literature survey the topics of interest 3. Ability to interpret the results of technical work 4. Ability to write technical reports 5. Ability prepare presentations of the technical contents 6. Ability to communicate effectively

A Seminar should be given by an individual student based on topics chosen from the emerging areas and technologies of Computer science & Computer Applications. References from journals such as IEEE, ACM etc., shall be used. A report on this seminar with 15-20 pages shall also be prepared.


VI Semester

Major Project

Sub Code : MCA2801 Credits : 28 Pre-requisite: NA Course Outcomes On successful completion of the course, the students will be able to:

1. Identification of real world problems 2. Understand different design methodologies. 3. Ability to select appropriate tools for solving a problem 4. Implementing advanced programming techniques/languages 5. Learn the art of verification and validation. 6. Ability to write technical reports

Major project must be carried out by individual student, one project per student. Student must submit a Detailed Project Report (60 to 80 Pages) in a format as specified by the department. Internal guides will evaluate the performance (Continuous Internal Evaluation) for 50 Marks. The Report will be evaluated for 125 marks by both internal and external evaluators. Final viva-voce which includes demonstration and presentation of project work will be evaluated jointly by internal and external examiners for 75 marks.


Seminar – II

Sub Code : MCA0201 Credits : 2 Pre-requisite: NA Course Outcomes: On successful completion of the course, the students will be able to:

7. Awareness of current trends in specific area of interest 8. Ability to conduct literature survey the topics of interest 9. Ability to interpret the results of technical work 10. Ability to write technical reports 11. Ability prepare presentations of the technical contents 12. Ability to communicate effectively

A Seminar should be given by an individual student based on topics chosen from the emerging areas and technologies of Computer science & Computer Applications. References from journals such as IEEE, ACM etc., shall be used. A report on this seminar with 15-20 pages shall also be prepared.


Electives

Sub.Code Subjects L T P Credit MCA04XX Computer Graphics and Visualization 4 0 0 4

MCA04XX UNIX system Programming 4 0 0 4

MCA04XX Multimedia Systems 4 0 0 4

MCA04XX Principles of User Interface Design 4 0 0 4

MCA04XX Advanced Computer Networks 4 0 0 4

MCA04XX Information Retrieval 4 0 0 4

MCA04XX Data Mining 4 0 0 4

MCA04XX Network Management 4 0 0 4

MCA04XX Software Architectures 4 0 0 4 MCA04XX Information and Network Security 4 0 0 4 MCA04XX Software Testing 4 0 0 4

MCA04XX Services Oriented Architectures 4 0 0 4

MCA04XX Mobile Computing 4 0 0 4

MCA04XX Artificial Intelligence 4 0 0 4

MCA04XX Web 2.0 and rich internet applications 4 0 0 4

MCA04XX Digital Image Processing 4 0 0 4

MCA04XX Introduction to Android Programming 4 0 0 4

MCA04XX Cloud Computing 4 0 0 4


Computer Graphics and Visualization (4:0:0)

Sub Code : 12MCA671 CIE : 50%



Course Outcomes:

On successful completion of the course, the students will be able to:

1. Understand and identify the different applications of computer graphics. 2. Recognize the potential and benefits of using openGL in field of computer graphics 3. Understand the working of various animated interactive programs by using suitable

input and output devices. 4. Understand the different aspects of modeling and transforming using homogeneous

coordinates. 5. Able to design and implement various three dimensional Line clipping algorithms. 6. Have the ability to use modeling and transformation in order to visualize various

models.

Unit – 1 Introduction - Applications of computer graphics; A graphics system; Images: Physical and synthetic; The human visual system; The pinhole camera; The synthetic camera model; The programmer’s interface; Graphics architectures. Self Learning Component:Graphics Programming: The Sierpinski gasket. Unit-2 The OpenGL - The OpenGL API; Primitives and attributes; Color; Viewing; Control functions; The Gasket program; Polygons and recursion. Self Learning Component: The three dimensional gasket. Unit – 3 Input and Interaction - Interaction; Input devices; Clients and servers; Display lists; Programming event-driven input; Menus; Picking; A simple paint program; Animating interactive programs. Self Learning Component:Design of interactive programs. Unit – 4 Geometric Objects and Transformations - Scalars, points, and vectors; Three-dimensional primitives; Coordinate systems and frames; Modeling a colored cube; Affine transformations; Rotation, translation and scaling; Transformation in homogeneous coordinates.


Viewing Classical and computer viewing; Positioning of the camera; Simple projections; Projections in OpenGL; Hidden-surface removal; Walking through a scene; Parallel-projection matrices. Self Learning Component: OpenGL transformation matrices; Interfaces to three dimensional applications, Perspective-projection matrices; Projections and shadows. Unit – 5 Shading Light and matter; Light sources; The Phong reflection model; Computation of vectors; Polygonal shading; Approximation of a sphere by recursive subdivisions; Light surfaces in OpenGL; Specification of materials in OpenGL. Implementation - The major tasks; Implementation of transformations; Line-segment clipping; Polygon clipping; Clipping of other primitives; Clipping in three dimensions; Hidden-surface removal; Scan conversion; Bresenham’s algorithm. Self Learning Component:Shading of the sphere model; Global rendering, Scan conversion of polygons; Antialiasing; Display considerations. Unit – 6 Visualization Data + Geometry; Height field and contours; Visualizing surfaces and scalar fields; Isosurfaces and marching cubes; Direct volume rendering; Vector-field visualization. Self Learning Component:Tensor-visualization. Text Books: 1. Edward Angel: Interactive Computer Graphics A Top-Down Approach with OpenGL, 2nd Edition, Addison-Wesley, 2000. (Chapters 1, 2, 3, 4, 5, 6, 7, 12) Reference Books: 1. F.S. Hill,Jr.: Computer Graphics Using OpenGL, 2nd Edition, Pearson education / PHI, 2001. 2. James D Foley, Andries Van Dam, Steven K Feiner, John F Hughes: Computer Graphics, Addison Wesley, 1997. 3. Donald Hearn and Pauline Baker: Computer Graphics- C Version, 2nd Edition, Pearson Education / PHI, 2003.


UNIX Systems Programming (4:0:0)




Pre-requisite:- Introduction to UNIX Course Outcomes On successful completion of the course, the students will be able to:

1. Understand the role of standards for programming with respect to compatibility of code and also portability of code.

2. They master in the usage of makefiles, linking, object files, loading, symbol resolution, shared and static libraries, debugging, and execution of system programs.

3. Become familiar with basic UNIX OS concepts such as: process, program, process groups, signals, running programs, process control, address space, user and kernel modes, system calls, and context switching.

4. Learn the usage of thread execution models (e.g. Posix threads). 5. Understand and handle signals and exceptions within a process and to control

processes. 6. Learn different approaches of concurrent programming.

Unit 1 Introduction UNIX and ANSI Standards: The ANSI C Standard, The ANSI/ISO C++ Standards, Difference between ANSI C and C++, The POSIX Standards, The POSIX.1 FIPS Standard, The X/Open Standards. UNIX and POSIX APIs: The POSIX APIs, The UNIX and POSIX Development Environment, API Common Characteristics. UNIX Files File Types, The UNIX and POSIX File System, The UNIX and POSIX File Attributes, Inodes in UNIX System V, Application Program Interface to Files, UNIX Kernel Support for Files, , Directory Files, Hard and Symbolic Links. Self learning component: Relationship of C Stream Pointers and File Descriptors Unit 2 UNIX File APIs General File APIs, File and Record Locking, Directory File APIs, Device File APIs, FIFO File APIs, Symbolic Link File APIs, General File Class, regfile Class for Regular Files, dirfile Class for Directory Files, FIFO File Class, Device File Class, Symbolic Link File Class. Self learning component: File Listing Program


Unit 3 UNIX Processes The Environment of a UNIX Process: Introduction, main function, Process Termination, Command-Line Arguments, Environment List, Memory Layout of a C Program, , Environment Variables, setjmp and longjmp Functions, getrlimit, setrlimit Functions, UNIX Kernel Support for Processes. Self learning component: Shared Libraries, Memory Allocation Unit 4 Process Control Introduction, Process Identifiers, fork, vfork, exit, wait, waitpid, waited, wait3, wait4 Functions, Race Conditions, exec Functions, Changing User IDs and Group IDs, Interpreter Files, system Function, Process Accounting, User Identification, Process Times. Process Relationships: Introduction, Terminal Logins, Network Logins, Controlling Terminal, tcgetpgrp, tcsetpgrp, and tcgetsid Functions, Job Control, Shell Execution of Programs, Orphaned Process Groups. Self learning component: Process Groups, Sessions Unit 5 Signals and Daemon Processes Signals: The UNIX Kernel Support for Signals, signal, Signal Mask, sigaction, The SIGCHLD Signal and the waitpid Function, The sigsetjmp and siglongjmp Functions, Kill, Alarm, Interval Timers, POSIX.lb Timers. Daemon Processes: Introduction, Daemon Characteristics, Coding Rules, Error Logging, Single instance daemons; Daemon conventions; Self learning component: Client-Server Model. Unit 6 Interprocess Communication Introduction; Pipes, popen, pclose Functions; Coprocesses; FIFOs;; Message Queues; Semaphores. Network IPC: Sockets Introduction; Socket Descriptors; Addressing; Connection establishment; Data transfer; Socket options; Out-of-band data; Self learning component: XSI IPC and Nonblocking and asynchronous I/O. Text Books: 1 Terrence Chan: Unix System Programming Using C++, Prentice-Hall of India / Pearson Education, 1999.. (Chapters 1, 5, 6, 7, 8, 9) 2 W.Richard Stevens, Stephen A. Rago: Advanced Programming in the UNIX Environment, 2nd Edition, Pearson Education / Prentice-Hall of India, 2005. (Chapters 7, 8, 9, 13, 15, 16) Reference Books: 1. Marc J. Rochkind: Advanced UNIX Programming, 2nd Edition, Pearson Education, 2005.


2. Maurice.J.Bach: The Design of the UNIX Operating System, Pearson Education / PHI, 1987. 3. Uresh Vahalia: UNIX Internals, Pearson Education, 2001.


Multimedia Systems (4:0:0)




Course Outcomes: On successful completion of the course, the students will be able to:

1. Understand various elements of multimedia and its applications. 2. Able to design and implement graphics, digitized videos and animation using

Computer Assisted Graphics and Image Processing; 3. Analyze the different data compression techniques for both audio and video. 4. Understand the need for different type of storage media and its applications. 5. Understand to design and implement different data file formats 6. Able to understand and appreciate different applications of multimedia.

Unit – 1 Introduction, Media and Data Streams, Audio Technology Multimedia Elements; Multimedia Applications; Multimedia Systems Architecture; Evolving Technologies for Multimedia Systems; Defining Objects for Multimedia Systems; Multimedia Data Interface Standards; The need for Data Compression; Multimedia Databases. Media: Perception Media, Representation Media, Presentation Media, Storage Media; Characterizing Continuous Media Data Streams. Sound: Frequency, Amplitude, Sound Perception and Psychoacoustics; Audio Representation on Computers. Self Learning Component: Three Dimensional Sound Projection; Music and MIDI Standards; Speech Signals; Speech Output; Speech Input; Speech Transmission. Unit – 2 Graphics and Images, Video Technology, Computer-Based Animation Capturing Graphics and Images Computer Assisted Graphics and Image Processing; Reconstructing Images; Graphics and Image Output Options. Basics; Television Systems; Digitalization of Video Signals; Digital Television; Basic Concepts; Specification of Animations; Methods of Controlling Animation; Display of Animation. Self Learning Component: Transmission of Animation; Virtual Reality Modeling Language. Unit – 3 Data Compression - Storage Space; Coding Requirements; Source, Entropy, and Hybrid Coding; Basic Compression Techniques; JPEG: Image Preparation, Lossy Sequential DCT-based Mode. Data Compression - H.261 (Px64) and H.263: Image Preparation, Coding Algorithms, Data Stream, H.263+ and H.263L; MPEG: Video Encoding, Audio Coding, Data Stream, MPEG-2.


Self Learning Component:Expanded Lossy DCT-based Mode, Lossless Mode, Hierarchical Mode, MPEG-4, MPEG-7; Fractal Compression. Unit – 4 Optical Storage Media History of Optical Storage; Basic Technology; Video Discs and Other Worms; Compact Disc Digital Audio; Compact Disc Read Only Memory; CD-ROM Extended Architecture; Further CD-ROM-Based Developments; Compact Disc Recordable. Content Analysis Simple Vs. Complex Features; Analysis of Individual Images; Analysis of Image Sequences. Self Learning Component:Compact Disc Magneto- Optical; Compact Disc Read/Write; Digital Versatile Disc, Audio Analysis; Applications. Unit – 5 Data and File Format Standards Rich-Text Format; TIFF File Format; Resource Interchange File Format (RIFF); MIDI File Format; JPEG DIB File Format for Still and Motion Images; AVI Indeo File Format; Self Learning Component:MPEG Standards; TWAIN. Unit – 6 Multimedia Application Design Multimedia Application Classes; Types of Multimedia Systems; Virtual Reality Design; Components of Multimedia Systems; Organizing Multimedia Databases. Self Learning Component: Application Work flow Design Issues; Distributed Application Design Issues. Text Books: 1. Ralf Steinmetz, Klara Narstedt: Multimedia Fundamentals: Vol 1-Media Coding and Content Processing, 2nd Edition, Pearson Education / PHI, 2003. (Chapters 2, 3, 4, 5, 6, 7, 8, 9) 2. Prabhat K. Andleigh, Kiran Thakrar: Multimedia Systems Design, PHI, 2003. (Chapters 1,3,7) Reference Books: 1. K.R Rao, Zoran S. Bojkovic and Dragorad A. Milovanovic: Multimedia Communication Systems: Techniques, Standards, and Networks, Pearson Education, 2002. 2. Nalin K Sharad: Multimedia information Networking, PHI, 2002.


Principles of User Interface Design (4:0:0)




Prerequisite: Nil Course Outcomes: The students on successful completion of this course should be able to:

1. Knowledge and understanding: be able to give an account of the historic development of user interfaces.

2. Demonstrate knowledge about some interaction design patterns and their applicability

3. Able to analyse a user interface from a communication perspective 4. Able to discuss a user interface from a historical perspective 5. Understand the Values and demonstrate an awareness of the relation between

interaction design and users expectations 6. Demonstrate knowledge about the specific needs of professional users with respect

to Management & tools' environment Unit – 1 Human Factors of Interactive Software, Theories, Principles and Guidelines Introduction, Goals of Systems Engineering, Goals of Interface Design, Motivation for Human Factors in Design, Accommodation of Human Diversity, Goals for the Profession, High Level Theories, Object-Action Interface Model, Principle 1: Recognize the Diversity, Principle 2: Use the Eight Golden Rules of Interface Design, Principle 3. Management Issue Introduction, Organizational Design to Support Usability, The Three Pillars of Design, Development Methodologies, Ethnographic Observation, Participatory Design, Scenario Development, Social Impact Statement for Early Design Review, Legal Issues. Self Learning Component:Prevent Errors, Guidelines for Date Display, Guidelines for Data Entry, Balance of Automation and Human Control, Expert Reviews, Usability Testing and Laboratories, Surveys, Acceptance Tests, Evaluation During Active Use, Controlled Psychologically Oriented Experiments. Unit – 2 Tools and Environments Introduction, Specification Methods, Interface-Building Tools, Evaluation and Critiquing Tools. Introduction, Examples of Direct-Manipulation Systems, Explanations of Direct Manipulation, Visual Thinking and Icons.


Self Learning Component: Direct Manipulation Programming, Home Automation, Remote Direct Manipulation Virtual Environments. Unit – 3 Menus, Forms, Dialog Boxes and Commands Task Related Organization, Item Presentation Sequence, Response Time and Display Rate, Fast Movement through Menus, Menu Layout, Form Fillin, Dialog Boxes. Functionality to support. The Benefits of Structure, Naming and Abbreviations, Command Menus, Natural Language in Computing. Self Learning Component:Users Tasks, Command-Organization Strategies. Unit – 4 Interaction Devices and Response Time Interaction Devices, Introduction, Keyboards and Function Keys, Pointing Devices, Speech Recognition, Digitization, and Generation, Image and Video Displays, Printers. Presentation Styles, Manuals, Help, and Tutorials - Error Messages, Non-anthropomorphic Design, Display Design, Color. Self Learning Component:Theoretical Foundations, Expectations and Attitudes, Reading from Paper Versus from Displays. Unit – 5 Presentation Styles, Manuals, Help, and Tutorials – 2, Multiple-Window Strategies, Hypermedia and the World Wide Web – Preparation of Printed Manuals, Preparation of On line Facilities. Multiple-Window Strategies: Introduction, Individual-Window Design, Multiple- window Design, Co-ordination by Tightly Coupled Windows, Image Browsing and Tightly Coupled Windows. Self Learning Component:Personal Role Management an Elastic Windows. Unit – 6 Multiple-Window Strategies, Hypermedia and the World Wide Web– Genres and Goals and Designers, Users and Their Tasks. Self Learning Component:Object-Action Interface Model for Web Site Design. Text Books: 1. Ben Shneiderman: Designing the User Interface, 3rd Edition, Addison-Wesley, 1998. (Chapters 1 to 13, and 16) Reference Books: 1. Alan J Dix et. al.: Human-Computer Interaction, II Edition, Prentice- Hall, India,1998 2. Eberts: User Interface Design, Prentice-Hall, 1994. 3. Wilber O Galitz: The Essential Guide to User Interface Design – An Introduction to GUI Design, Principles and Techniques, Wiley-Dreamtech India Pvt. Ltd, 1998.


Advanced Computer Networks(4:0:0)




Pre-requisites: Computer Networks Course Outcomes: On successful completion of the course, the students will be able to:

1. Understand the fundamentals of layering using OSI model and principles of network layering.

2. Analyze the behavior of physical layer and their topology with the help of particular technologies.

3. To understand the need for use of IPV6,and various address translation mechanisms in computer networks.

4. Understand the different Unicast,multicast and broadcast routing protocols and also learn the working of SCTP protocol.

5. Understand why and how congestion occurs in a network and different techniques to improve QOS.

6. Prepare and lead simple courses targeted in particular areas of computer networks and their applications.

Unit – 1 Review of Network Models Layered tasks; The OSI model and layers in the OSI model; TCP / IP protocol suite. SONET / SDH Architecture; SONET layers; SONET frames; STS multiplexing; SONET networks. Self Learning Component: Addressing,Virtual tributaries. Unit – 2 Frame Relay and ATM Frame relay; ATM. Self Learning Component: ATM LANs Unit – 3 IPv6, Address Mapping and Error Reporting IPv6: Advantages, Packet format, and Extension headers,Dual stack, Tunneling, and Header translation; Address mapping: ARP, RARP, BOOTP, and DHCP; Error reporting: ICMP. Self Learning Component: Transition from IPv4 to IPv6: Unit – 4 Multi-cast Routing Protocols


Unicast, multicast and broadcast,Multicasting routing; Routing protocols. SCTP SCTP services; SCTP features; Packet format; An SCTP association; Flow control; Error control; Congestion control. Self Learning Component:Applications Multicast and broadcast. Unit – 5 Congestion Control and Quality of Service Data traffic; Congestion and congestion control; Congestion control in TCP, Frame relay; Quality of Service; Techniques to improve QoS; Integrated services. Self Learning Component: Differentiated services, Unit – 6 Multimedia Digitizing audio and video; Audio and video compression; Streaming stored audio / video; Real-time interactive audio / video; RTP; RTCP; VoIP. Self Learning Component: Streaming live audio / video; Text Books: 1. Behrouz A. Forouzan, Data Communications and Networking, 4th Edition, Tata McGraw-Hill, 2006. (Chapters 2, 17, 18, 20.3, 20.4, 21.1, 21.2, 22.4, 23.4, 24, 29) 2. Nader F. Mir: Computer and Communication Networks, Pearson, 2007. (Chapters 19, 20 excluding 20.5) References: 1. William Stallings , Data and Computer Communication, 5th Edition, Prentice Hall India. 2. William A. Shay, Understanding Data Communications and Networks, 2nd Edition, Thomson. 3. Godbole, Data Communications and Networks, Tata McGraw-Hill 2002. 4. Micael A. Gallo & William M. Handcock, Computer 5. Communications and Networking Technologies, 2003 Edition, Thomson.


Information Retrieval (4:0:0)




Pre-requisite: Nil Course Outcomes: The students on successful completion of this course should be able to: 1. Use different information retrieval techniques in various application areas 2. Apply IR principles to locate relevant information large collections of data 3. Analyse performance of retrieval systems when dealing with unmanaged data sources 4. Implement retrieval systems for web search tasks. 5. Understand the concepts of parallel and distributed information retrieval 6. Understand the usage of Multimedia IR systems. Unit – 1 Introduction, Retrieval Strategies - 1 Introduction; Retrieval Strategies: Vector Space Model; Probabilistic Retrieval strategies Retrieval Strategies – 2 Some More Retrieval Strategies: Language Models; Inference Networks; Extended Boolean Retrieval; Latent Semantic Indexing; Self Learning Component: Neural Networks; Genetic Algorithms; Fuzzy Set Retrieval. Unit – 2 Retrieval Utilities Relevance feedback; Clustering; Passage-Based Retrieval; N-Grams; Regression Analysis; Thesauri; Self Learning Component:Semantic Networks; Parsing. Unit – 3 Indexing and Searching Introduction; Inverted Files; Other indices for text; Boolean queries; Sequential searching; Self Learning Component:Pattern matching; Structural queries; Compression. Unit – 4 Cross-Language Information Retrieval and Efficiency Introduction; Crossing the language barrier; Cross-Language retrieval strategies; Cross language utilities. Duplicate Document Detection. Integrating Structured Data and Text Review of the relational model; A historical progression; Information retrieval as a relational application; Self Learning Component: Semi-structured search using a relational schema; Multi-dimensional data model.


Unit – 5 Parallel Information Retrieval, Distributed Information Retrieval Parallel text scanning; Parallel indexing; Clustering and classification; Large parallel systems; A theoretic model of distributed information retrieval; Self Learning Component:Web search; Result fusion; Peer-to-Peer information systems; Other architectures. Unit – 6 Multimedia IR Introduction; data modeling; Query languages; Spatial access methods; A general multimedia indexing approach; Self Learning Component:One-dimensional time series; Two-dimensional color images; Automatic picture extraction. Text Books:

1. David A. Grossman, Ophir Frieder: Information Retrieval Algorithms and Heuristics, 2nd Edition, Springer, 2004. (Chapters 1, 2, 3, 4, 5, 6, 7, 8)

2. Ricardo Baeza-Yates, Berthier Ribeiro-Neto: Modern Information Retrieval, Pearson Education, 1999 (Chapters 8, 11, 12)

Reference Books :

1. William B. Frakes, Ricardo Baeza-Yates (Editors):Information Retrieval Data Structures & Algorithms, Prentice Hall PTR, 1992.


Data Mining (4:0:0)




Pre-requisite: DBMS Course Outcomes: On successful completion of the course, the students will be able to:

1. State the necessity of data mining. 2. Identify different tasks of data mining. 3. Identify the different methods in association analysis 4. Demonstrate decision tree induction algorithm 5. Demonstrate the importance of cluster analysis. 6. Understand the importance of advanced data mining topics like spatial data

mining, text mining, mining the web. Unit - 1 Introduction, Data - 1 What is Data Mining? Motivating Challenges; The origins of data mining; Data Mining Tasks. Types of Data; Self Learning Component: Data Quality. Unit - 2 Data – 2 Data Preprocessing; Measures of Similarity and Dissimilarity Classification Preliminaries; General approach to solving a classification problem; Decision tree induction; Rule-based classifier; Self Learning Component: Nearest-neighbor classifier. Unit - 3 Association Analysis - 1 Problem Definition; Frequent Itemset generation; Rule Generation; Compact representation of frequent itemsets; Self Learning Component: Alternative methods for generating frequent itemsets. Unit - 4 Association Analysis - 2 FP-Growth algorithm, Evaluation of association patterns; Effect of skewed support distribution; Self Learning Component: Sequential patterns.


Unit - 5 Cluster Analysis Overview, K-means, Agglomerative hierarchical clustering, DBSCAN, Self Learning Component: Overview of Cluster Evaluation. Unit - 6 Further Topics in Data Mining Multidimensional analysis and descriptive mining of complex data objects; Spatial data mining; Multimedia data mining; Text mining; Mining the WWW. Outlier analysis. Applications Data mining system products and research prototypes; Additional themes on Data mining; Social impact of Data mining; Trends in Data mining. Self Learning Component: Data mining applications Text Books: 1.Pang-Ning Tan, Michael Steinbach, Vipin Kumar: Introduction to Data Mining, Pearson Education, 2007. (Chapter 1, 2, 4.1 to 4.3, 5.1, 5.2, 6, 8.1 to 8.4, 8.5.1) 2. Jiawei Han and Micheline Kamber: Data Mining – Concepts and Techniques, 2nd Edition, Morgan Kaufmann, 2006. (Chapters 7.11, 10, 11) Reference Books: 1. K.P.Soman, Shyam Diwakar, V.Ajay: Insight into Data Mining – Theory and Practice, PHI,


Network Management (4:0:0)




Course Outcomes: On successful completion of the course, the students will be able to: 1. Able to define the basic components of a Network system, and define the goal of

network managements. 2. Knowing and Applying various standards, models and languages for network

management, with the help of SNMPV1. 3. Differentiating the various types of network configurations, architectures,operations

of SNMP. 4. Defining the different protocols, software, and network architectures. Using SNMP. 5. Understanding the concepts and technologies of broadband network management in

ATM and other related technologies. 6. Understanding the various applications of network management.

Unit – 1 Introduction Analogy of Telephone Network Management, Data and Telecommunication Network Distributed computing Environments, TCP/IP-Based Networks: The Internet and Intra-nets, Communications Protocols and Standards- Communication Architectures, Protocol Layers and Services; Case Histories of Networking and Management – The Importance of topology , Filtering Does Not Reduce Load on Node, Some Common Network Problems; Challenges of Information Technology Managers, Network Management: Goals, Organization, and Functions- Goal of Network Management, Network Provisioning, Network Operations and the NOC, Network Installation and Maintenance. Self Learning Component: Network and System Management, Network Management System platform, Current Status and Future of Network Management. Unit – 2 Basic Foundations: Standards, Models, and Language Network Management Standards, Network Management Model, Organization Model, Information Model – Management Information Trees, Managed Object Perspectives, Communication Model; ASN.1- Terminology, Symbols, and Conventions, Objects and Data Types, Object Names. SNMPv1 Network Management - 1 Managed Network: The History of SNMP Management, Internet Organizations and standards, Internet Documents, The SNMP Model. Self Learning Component : An Example of ASN.1 from ISO 8824; Encoding Structure; Macros, Functional Model,The Organization Model, System Overview.


Unit – 3 SNMPv1 Network Management – 2 The Information Model – Introduction, The Structure of Management Information, Managed Objects, Management Information Base. The SNMP Communication Model – The SNMP Architecture, Administrative Model. Self Learning Component :SNMP Specifications, SNMP Operations, SNMP MIB Group, Functional Model. Unit – 4 SNMP Management – RMON Remote Monitoring, RMON SMI and MIB, RMONI1- RMON1 Textual Conventions, RMON1 Groups and Functions, Relationship Between Control and Data Tables, RMON1 Common and Ethernet Groups, RMON Token Ring Extension Groups, RMON2 – The RMON2 Management Information Base, RMON2 Conformance Specifications. Self Learning Component :ATM Remote Monitoring, A Case Study of Internet Traffic Using RMON. Unit – 5 Broadband Network Management: ATM Networks Broadband Networks and Services, ATM Technology – Virtual Path-Virtual Circuit, TM Packet Size, Integrated Service, SONET, ATM LAN Emulation, Virtual LAN; ATM Network Management – The ATM Network Reference Model, The Integrated Local Management Interface, The ATM Management Information Base, The Role of SNMP and ILMI in ATM Management, M1 Interface: Management of ATM Network Element, M2 Interface: Management of Private Networks, M3 Interface. Self Learning Component : Customer Network Management of Public Networks, M4 Interface: Public Network Management, Management of LAN Emulation, ATM Digital Exchange Interface Management. Unit – 6 Broadband Network Management Broadband Access Networks and Technologies – Broadband Access Networks, roadband Access Technology; HFCT Technology – The Broadband LAN, The Cable Modem, The Cable Modem Termination System, The HFC Plant, The RF Spectrum for Cable Modem; Data Over Cable Reference Architecture; HFC Management – Cable Modem and CMTS Management, HFC Link Management, RF Spectrum Management, DSL Technology; Asymmetric Digital Subscriber Line Technology – Role of the ADSL Access Network in an Overall Network, ADSL Architecture, ADSL Channeling Schemes, ADSL Encoding Schemes; ADSL Management – ADSL Network Management Elements, ADSL Configuration Network Management Applications Configuration Management- Network Provisioning, Inventory Management, Network Topology, Fault Management- Fault Detection, Fault Location and Isolation Techniques, Performance Management – Performance Metrics, Data Monitoring, Problem Isolation, Performance Statistics; Event Correlation Techniques – Rule-Based Reasoning, Model- Based Reasoning, Case-Based Reasoning, Codebook


correlation Model, State Transition Graph Model, Finite State Machine Model, Security Management – Policies and Procedures, Security Breaches and the Resources Needed to Prevent Them, Firewalls, Cryptography, Authentication and Authorization, Client/Server Authentication Systems, Messages Transfer Security, Protection of Networks from Virus Attacks. Self Learning Component : Management,.ADSL Fault Management, ADSL Performance Management, SNMP-Based ADSL Line MIB, MIB Integration with Interfaces Groups in MIB-2, ADSL Configuration Profiles,Accounting Management, Report Management, Policy-Based Management, Service Level Management.

Text Books: 1. Mani Subramanian: Network Management- Principles and Practice, Pearson Education

Publication, 2003. Reference Books: 1. J. Richard Burke: Network management Concepts and Practices: a Hands- On

Approach, PHI, 2008.


Software Architectures (4:0:0)




Course outcomes: On successful completion of this course the students should be able to:

1. Understand the architecture business cycle. 2. Study the different architectural styles with case study 3. Understand the quality attributes in the architecture. 4. Study the different architectural patterns. 5. Understand the different design patterns. 6. Understanding the design and documentation of the architecture.

Unit – 1 1. Introduction The Architecture Business Cycle: Where do architectures come from? Software processes and the architecture business cycle; What makes a “good” architecture? What software architecture is and what it is not; Other points of view; Architectural patterns, reference models and reference architectures; Importance of software architecture; Self learning component:- Architectural structures and views. Unit – 2 Architectural Styles and Case Studies Architectural styles; Pipes and filters; Data abstraction and object-oriented organization; Event-based, implicit invocation; Layered systems; Repositories; Interpreters; Process control; Other familiar architectures; Heterogeneous architectures. Case Studies: Keyword in Context; Instrumentation software; Self learning component:- Mobile robotics; Cruise control; Three vignettes in mixed style. Unit – 3 Quality Functionality and architecture; Architecture and quality attributes; System quality attributes; Business qualities; Architecture qualities. Achieving Quality: Introducing tactics; Availability tactics; modifiability tactics; Performance tactics; Security tactics; Testability tactics; Usability tactics; Relationship of tactics to architectural patterns; Architectural patterns and styles. Self learning component:- Quality attribute scenarios in practice; Other system quality attributes;


Unit – 4 Architectural Patterns Introduction; From mud to structure: Layers, Pipes and Filters, Blackboard. Distributed Systems: Broker; Interactive Systems: MVC, Presentation-Abstraction-Control: Microkernel; Reflection. Self learning component:- Adaptable Systems Unit – 5 Some Design Patterns Structural decomposition: Whole – Part: Master –Slave; Access Control: Proxy. Self learning component:- Organization of work Unit – 6 Designing and Documenting Software Architecture Architecture in the life cycle; Designing the architecture; Forming the team structure; Creating a skeletal system. Uses of architectural documentation; Documenting a view; Documentation across views. Self learning component:- Views; Choosing the relevant views Text Books:

1. Len Bass, Paul Clements, Rick Kazman: Software Architecture in Practice, 2nd Edition, Pearson Education, 2003. (Chapters 1, 2, 4, 5, 7, 9)

2. Frank Buschmann, Regine Meunier, Hans Rohnert, Peter Sommerlad, Michael Stal: Pattern-Oriented Software Architecture, A System of Patterns, Volume 1, John Wiley and Sons, 2006. (Chapters 2, 3.1 to 3.4)

3. Mary Shaw and David Garlan: Software Architecture- Perspectives on an Emerging Discipline, Prentice-Hall of India / Pearson Education, 2007. (Chapters 1.1, 2, 3)

Reference Books: 1. E. Gamma, R. Helm, R. Johnson, J. Vlissides: Design Patterns- Elements of Reusable

Object-Oriented Software, Addison-Wesley, 1995.

Web site for Patterns: http://www.hillside.net/patterns/


Information and Network Security (4:0:0)




Course Outcome On successful completion of the course, the students will be able to:

1. Plan to provide security for the information by designing models and also familiarize with the security technologies

2. Apply cryptographic techniques using various tools 3. Learn about authentication applications 4. Analyse the email security formats 5. Learn about the key management techniques and design of IP security 6. Analyse the web security

Unit – 1 Planning for Security Introduction; Information Security Policy, Standards, and Practices; The Information Security Blue Print; Contingency plan and a model for contingency plan. Security Technology Introduction; Physical design; Firewalls; Protecting Remote Connections. introduction; Intrusion Detection Systems (IDS); Honey Pots, Honey Nets, and Padded cell systems; Scanning and Analysis Tools. Unit – 2 Cryptography Introduction; A short History of Cryptography; Principles of Cryptography; Cryptography Tools; Attacks on Cryptosystems. Unit – 3 Introduction to Network Security, Authentication Applications Attacks , services, and Mechanisms; Security Attacks; Security Services; A model for Internetwork Security; Internet Standards and RFCs. Kerberos, X.509 Directory Authentication Service. Unit – 4 Electronic Mail Security Pretty Good Privacy (PGP); S/MIME. Unit – 5 IP Security IP Security Overview; IP Security Architecture; Authentication Header; Encapsulating


Security Payload; Combining Security Associations; Key Management. Unit – 6 Web Security Web security requirements; Secure Socket layer (SSL) and Transport layer Security (TLS); Secure Electronic Transaction (SET). Text Books:

1. Michael E. Whitman and Herbert J. Mattord: Principles of Information Security, 2nd Edition, Thomson, 2005. (Chapters 5, 6, 7, 8; Exclude the topics not mentioned in the syllabus)

2. William Stallings: Network Security Essentials: Applications and Standards, Pearson Education, 2000. (Chapters: 1, 4, 5, 6, 7, 8)

Reference Book:

1. Behrouz A. Forouzan: Cryptography and Network Security, Special Indian Edition, Tata McGraw-Hill, 2007.


Software Testing (4:0:0)




Course outcomes The students on successful completion of this course should be able to:

1 Understand the testing and test generation strategies. 2 Generation of test cases from the requirement. 3 Distinguish advantages and disadvantages of dataflow model and data flow

testing. 4 Distinguish which type of test case to be selected and when the testing has to be

stopped. 5 Understand the quality process in testing. 6 Distinguish which type of interaction and regression testing has to be performed

and when to release the software. Unit – 1 Basics of Software Testing Human Errors and Testing; Software Quality; Requirements, Behavior and Correctness; Correctness versus Reliability; Testing and Debugging; Test Metrics; Software and Hardware Testing; Testing and Verification; Defect Management; Execution History; Test-generation Strategies, Static Testing. Model-Based Testing and Model Checking; Control-Flow Graph;. Self learning component:- Types of Testing; The Saturation Effect Unit – 2 Test Generation from Requirements, Structural Testing Introduction; The Test-Selection Problem; Equivalence Partitioning; Boundary Value Analysis; Category-Partition Method. Cause-Effect Graphing, Test Generation from Predicates. Structural Testing: Overview; Statement testing; Path testing; Procedure call testing; Comparing structural testing criteria; The infeasibility problem. Self learning component:- Branch testing; Condition testing Unit – 3 Dependence, Data Flow Models, and Data Flow Testing Definition-Use pairs; Data flow analysis; Classic analyses; From execution to conservative flow analysis; Data flow analysis with arrays and pointers; Inter-procedural analysis; Overview of data flow testing; Definition-Use associations; Data flow testing criteria; Data flow coverage with complex structures. Self learning component:- The infeasibility problem


Unit – 4 Test Case Selection and Adequacy, Test Execution Overview; Test specification and cases; Adequacy criteria; Comparing criteria; Overview of test execution; From test case specification to test cases; Scaffolding; Generic versus specific scaffolding; Capture and replay. Self learning component:- Test oracles; Self-checks as oracles Unit – 5 Process Test and analysis activities within a software process: The quality process; Planning and monitoring; Quality goals; Analysis; Testing; Improving the process; Organizational factors. Self learning component:- Dependability properties Unit – 6 Integration and component-based software testing Overview; Integration testing strategies; Testing components and assemblies. System, Acceptance and Regression Testing: Overview; System testing; Acceptance testing; Usability; Regression testing; Test case prioritization and selective execution. Self learning component:- Regression test selection techniques Text Books: 1. Aditya P Mathur: Foundations of Software Testing, Pearson Education, 2008.

(Chapters 1 excluding 1.15, 1.16, 1.17, 2, 6) 2. Mauro Pezze, Michal Young: Software Testing and Analysis – Process, Principles and

Techniques, John Wiley & Sons, 2008. (Chapters 4, 6, 9, 12, 13, 17, 21, 22)

Reference Books:

1. Srinivasan Desikan, Gopalaswamy Ramesh: Software testing Principles and Practices, 2nd Edition, Pearson, 2007.

2. Ron Patton: Software Testing, 2nd edition, Pearson, 2004. 3. Brian Marrick:The Craft of Software Testing, Pearson, 1995.


Services Oriented Architecture (4:0:0)




Course outcome:- The students on successful completion of this course should be able to:

1. Understand the Service oriented architecture. 2. Understand the web services primitives with the SOA 3. Distinguish the different principles of SOA 4. Distinguish the different service layers in SOA 5. Understand web service design process. 6. Distinguish different SOA platforms.

Unit – 1 Introduction o SOA, Evolution of SOA Fundamental SOA; Common Characteristics of contemporary SOA; Common tangible benefits of SOA; An SOA timeline (from XML to Web services to SOA); The continuing evolution of SOA (Standards organizations and Contributing vendors); Self learning component:- The roots of SOA (comparing SOA to Past architectures). Unit – 2 Web Services and Primitive SOA The Web services framework; Services (as Web services); Service descriptions (with WSDL); Self learning component:- Messaging (with SOAP). Unit – 3 Web Services and Contemporary SOA Message exchange patterns; Service activity; Coordination; Atomic Transactions; Business activities; Orchestration; Choreography. Addressing; Reliable messaging; Correlation; Polices; Metadata exchange; Security; Notification and eventing Principles of Service – Orientation Services-orientation and the enterprise; Anatomy of a service-oriented architecture; Common Principles of Service-orientation; How service orientation principles inter-relate; . Self learning component:- Service-orientation and object-orientation; Native Web service support for service-orientation principles


Unit – 4 Service Layers Business service layer, Orchestration service layer; Agnostic services; Self learning component:- Service layer configuration scenarios Unit – 5 Business Process Design WS-BPEL language basics; WS-Coordination overview; Service-oriented business process design; WS-addresing language basics; Self learning component:- WS-ReliableMessaging language basics Unit – 6 SOA Platforms SOA platform basics; SOA support in J2EE; SOA support in .NET; Service-orientation and contemporary SOA; Service layer abstraction; Self learning component:- Application service layer, Text Books: 1. Thomas Erl: Service-Oriented Architecture – Concepts, Technology, and Design,

Pearson Education, 2005. Reference Books:

1. Eric Newcomer, Greg Lomow: Understanding SOA with Web Services, Pearson Education, 2005.


Mobile Computing (4:0:0)




Course Outcomes:

On successful completion of the course, the students will be able to: 1. Know the classification mobile systems. 2. Differentiate various access methods 3. Analyze mobile Network and transport layer and database requirements 4. Explain the broad casting methods involved. 5. Know about synchronization among mobile devices 6. Analyze the Internet connectivity requirement in mobile devices.

Unit – 1 Mobile Devices and Systems, Architectures Mobile phones, Digital Music Players, Handheld Pocket Computers, Handheld Devices, Operating Systems, Smart Systems, Limitations of Mobile Devices, Automotive Systems GSM – Services and System Architectures, Radio Interfaces, Protocols, Localization, Calling, Handover, Self Learning Component : General Packet Radio Service Unit – 2 Wireless Medium Access Control and CDMA – based Communication Medium Access Control, Introduction to CDMA – based Systems, Self Learning Component: OFDM

Unit – 3 Mobile IP Network Layer, Mobile Transport Layer IP and Mobile IP Network Layers Packet Delivery and Handover Management, Registration, Tunneling and Encapsulation, Route Optimization, Dynamic Host Configuration Protocol Indirect TCP, Snooping TCP, Mobile TCP, Other Methods of TCP – layer Transmission for Mobile Networks. Databases Database Hoarding Techniques, Data Caching, Client – Server Computing and Adaptation, Transactional Models, Query Processing, Data Recovery Process Self Learning Component: Issues relating to Quality of Service Unit – 4 Data Dissemination and Broadcasting Systems Communication Asymmetry, Classification of Data – Delivery Mechanisms, Data Dissemination Broadcast Models, Selective Tuning and Indexing Techniques, Digital Audio Broadcasting


Self Learning Component: Digital video Broadcasting.

Unit – 5 Data Synchronization in Mobile Computing Systems Synchronization, Synchronization Protocols, SyncML – Synchronization Language for Mobile Computing Self Learning Component: Synchronized Multimedia Markup Language (SMIL). Unit – 6 Mobile Devices, Server and Management, Wireless LAN, Mobile Internet Connectivity and Personal Area Network Mobile agent, Application Server, Gateways, Portals, Service Discovery, Device Management, Mobile File Systems. Wireless LAN (WiFi) Architecture and Protocol Layers, WAP 1.1 and WAP 2.0 Architectures, Bluetooth – enabled Devices Network, Zigbee. Mobile Application languages – XML, Java, J2ME and JavaCard, Mobile Operating Systems Introduction, XML, JAVA, Java 2 Micro Edition (J2ME), JavaCard Operating System, PalmOS, Windows CE, Symbian OS, Self Learning Component: Linux for Mobile Devices Text Book: 1. Raj Kamal: Mobile Computing, Oxford University Press, 2007. Reference Books:

1 Asoke Talkukder, Roopa R Yavagal: Mobile Computing – Technology, Applications and Service Creation, Tata McGraw Hill, 2005.

2 Reza B’Far: Mobile Computing Principles – Designing and Developing Mobile Applications with UML and XML, 5th Edition, Cambridge University press, 2006.

3 Uwe Hansmann, Lothat Merk, Martin S Nicklous and Thomas Stober: Principles of Mobile Computing, 2nd Edition, Springer International Edition, 2003.

4 Schiller: Mobile Communication, Pearson Publication, 2004.


Artificial Intelligence (4:0:0)

Sub Code : 12MCA04-- CIE : 50%



Pre-requisites: Nil Course Outcomes: On successful completion of the course, the students will be able to:

1 Know the fundamentals of Artificial Intelligence. 2 Explain the search techniques and knowledge representation. 3 Describe the Rules for knowledge representation. 4 Usage of reasoning and planning. 5 Explore the ways of Learning and Common Sense. 6 Analyze the requirements of Network Security and Robot.

UNIT-1 Introduction , Problems, Problem Spaces & Search What is Artificial Intelligence? What is an AI Technique, The Level of the Model; Problems, Problem Spaces & Search Defining the problem as a state space search, Production Systems: Control strategies, Heuristic Search, Problem Characteristics: Is the problem decomposable? Can solution steps be ignored or undone? Is the Universe Predicate? Is a good solution Absolute or Relative? Is the solution a State or a Path? What is the role of knowledge? Does the task Require Interaction with a Person? Problem Classification, Production System Characteristics; Self Learning Component: Issues in the design of search programs UNIT- 2 Search Techniques and Knowledge Representation Heuristic Search Techniques: Generate-and-Test, Hill-Climbing: Simple Hill climbing, Steepest Ascent Hill Climbing , Best-First search: OR Graphs, The A* Algorithm, Problem reduction: AND-OR Graphs, The AO* Algorithm. Constraint satisfaction, Means-ends analysis; Knowledge Representation: Representations and Mappings, Approaches to knowledge representation, Issues in Knowledge Representation: attributes, relationships among attributes, choosing granularity of Representation; Self Learning Component: Representing set of objects, Finding right structures as needed UNIT-3 Representing knowledge using Rules Representing knowledge using Rules: Procedural Vs Declarative Knowledge, Logic Programming, Backward Reasoning: Backward chaining rule systems, Forward chaining Rule systems, Combining Forward and Backward Reasoning, Matching: Indexing, Matching with variables, Complex and Appropriate Matching;


Self Learning Component: conflict resolution UNIT-4 Statistical Reasoning and Planning Statistical Reasoning: Probability and Bayes’ Theorem, Certainty and Rule-Based System, Bayesian Networks, Dempster-Shafer Theory, Fuzzy Logic; Planning: Components of Planning system, Hierarchical Planning; Self Learning Component:Reactive Systems UNIT-5 Learning and Common Sense What is Learning? Rote Learning, Learning by taking advice, Learning in Problem-solving, Learning from Examples: Wintson Learning Program; Common Sense: Common Sense Ontologies: Time, Space, Materials, Memory Organization, Case Based Reasoning Self Learning Component: Explanation based learning UNIT-6 Artificial Immune Systems The phenomenon of Immunity, Immunity and Infection, The Innate Immune system, Adaptive Immune system, Clonal Selection, Learning, Immune Network Theory, Mapping Immune systems to practical Applications: Modeling affinities, Case studies: Case-1 Network Security, Case-2 AIS for Robot control and Navigation; Self Learning Component: Other applications Text Book: 1. Elaine Rich, Kelvin Knight, Shivashankar B Nair: Artificial Intelligence, 3rd Edition, Tata McGraw Hill, 2009. Reference Books: 1. Stuart Russel, Peter Norvig: Artificial Intelligence: A Modern Approach, 2nd Edition,

Pearson Education, 2003. 2. Nils J. Nilsson: Principles of Artificial Intelligence, Elsevier, 1980.


Web 2.0 and Rich Internet Applications (4:0:0)




Course Outcomes:

On successful completion of the course, the students will be able to: 1. Understanding the basics of web services 2. Design and implement Rich Internet Applications using AJAX 3. Understand the usage of basics of XML and HTTP 4. Able to work with FLEX 5. Design and implement User Interface techniques 6. Understand the concepts of web 2.0 technology.

Unit – 1 Introduction, Web Services What is Web 2.0?, Folksonomies and Web 2.0, Software As a Service (SaaS), Data and Web 2.0, Convergence, Iterative development, Rich User experience, Multiple Delivery Channels, Social Networking. Web Services: SOAP, RPC Style SOAP, Document style SOAP, WSDL, REST services, JSON format, What is JSON?, Array literals, Object literals, Mixing literals. Self Learning Component : JSON Syntax, JSON Encoding and Decoding, JSON versus XML.

Unit – 2 Building Rich Internet Applications with AJAX Building Rich Internet Applications with AJAX: Limitations of Classic Web application model, AJAX principles, Technologies behind AJAX, Examples of usage of AJAX, Dynamic web applications through Hidden frames for both GET and POST methods. IFrames, Asynchronous communication Self Learning Component : AJAX application model,

Unit – 3 XMLHTTP Object – properties and methods, handling different browser implementations of XMLHTTP, The same origin policy, Cache control, AJAX Patterns (Only algorithms – examples not required): Predictive fetch pattern, Submission throttling pattern, Periodic refresh, Multi stage download, Self Learning Component : Fall back patterns.


Unit – 4 Building Rich Internet Applications with Flex Flash player, Flex framework, MXML and Actionscript, Working with Data services, Understanding differences between HTML and Flex applications, Understanding how Flex applications work, Understanding Flex and Flash authoring, MXML language, a simple example. Using Actionscript, MXML and Actionscript correlations. Understanding Actionscript 3.0 language syntax: Language overview, Objects and Classes, Packages and namespaces, Variables & scope of variables, case sensitivity and general syntax rules, Operators, Conditional, Looping, Functions, Nested functions, Functions as Objects, Function scope, OO Programming in Actionscript: Classes, Interfaces, Inheritance, Working with String objects, Working with Arrays, Error handling in Actionscript: Try/Catch, Working with XML Framework fundamentals, Understanding application life cycle, Differentiating between Flash player and Framework, Bootstrapping Flex applications, Loading one flex application in to another, Understanding application domains, Understanding the preloader. Self Learning Component : Managing layout, Flex layout overview, Working with children, Container types, Layout rules, Padding, Borders and gaps, Nesting containers, Making fluid interfaces.

Unit – 5 Working with UI components: Understanding UI Components, Creating component instances, Common UI Component properties, Handling events, Button, Value selectors, Text components, List based controls, Data models and Model View Controller, Creating collection objects, Setting the data provider, Using Data grids, Using Tree controls, Working with selected values and items, Pop up controls, Navigators, Control bars Working with data: Using data models, Using XML, Self Learning Component : Using Actionscript classes, Data Binding. Unit – 6 Building Advanced Web 2.0 applications Definition of mash up applications, Mash up Techniques, Building a simple mash up application with AJAX, Remote data communication, strategies for data communication, Simple HTTPServices, URLLoader in Flex, Web Services in Flex, Examples: Building an RSS reader with AJAX Self Learning Component : , Building an RSS reader with Flex. Text Books:

1 .Nicholas C Zakas et al: Professional AJAX, Wrox publications, 2006. (Chapters 1 to 4, Chapter 6 pp157-166, Chapter 7 pp191-196)

2 Chafic Kazoun: Programming Flex 2, O’Reilly publications, 2007.

(Chapters 1, Chapters 3 to 7, Chapter 12, Chapter 16 pp380-403)

3 Francis Shanahan: Mashups, Wrox, 2007. (Chapters 1,6)


Reference Books:

1 Thomas A. Powel: Ajax The Complete reference, McGraw Hill, 2008. 2 Gottfried Vossen, Stephan Hagemann: Unleashing Web 2.0 From Concepts to

Creativity, Elsevier, 2007. 3 Colin Moock: Essential Actionscript 3.0, O’Reilly Publications, 2007. 4 Steven Holzner : Ajax Bible Wiley India , 2007. 5 Justin Gehtland et al: A Web 2.0 primer Pragmatic Ajax, SPD Publications,

2006. 6 Eric Van derVlist et al: Professional Web 2.0 Programming, Wiley India, 2007.


DIGITAL IMAGE PROCESSING (4:0:0)




Pre-requisites: NA Course Outcomes:

1. Understand digital image fundamentals 2. Learn the concepts of image digitization 3. Analyze the image display’s hardware and software 4. Ability to understand and apply image enhancement and restoration techniques 5. Appreciate some of the image encoding techniques

Unit – 1 Introduction: Origins of Digital Image Processing, Fundamental Steps in Digital Image Processing, Components of an Image Processing System Self Learning Component: Digital Image Processing, Application examples Unit – 2 Digital Image Fundamentals: Elements of Visual Perception, A Simple Image Formation Model, Basic Concepts in Sampling and Quantization, Representing Digital Images, Zooming and Shrinking Digital Images, Some Basic Relationships Between Pixels. Self Learning Component: Linear and Nonlinear Operations Unit – 3 Image Enhancement in the Spatial Domain: Some Basic Gray Level Transformations, Histogram Processing, Enhancement Using Arithmetic/Logic Operations, Basics of Spatial Filtering, Smoothing Spatial Filters, Sharpening Spatial Filters. Self Learning Component: Combining Spatial Enhancement Methods Unit – 4 Image Restoration: A Model of the Image degradation/Restoration process, Noise Models, Properties of Noise, Some important Noise PDFs, Periodic Noise, Estimation of Noise Parameters, Restoration in the Presence of Noise Only–Spatial Filtering, Mean Filters, Order Statistics Filters, Adaptive filters. Self Learning Component: Geometric Transformations Unit – 5 Color Fundamentals:


Color Models, Pseudocolor Image Processing, Basics of Full-Color Image Processing, Color Transformations, Smoothing and Sharpening, Color Segmentation. Self Learning Component: Noise in Color Images Unit – 6 Image Compression: Fundamentals, Image Compression Models, Error-Free Compression, Lossy Compression, Image Compression Standards. Self Learning Component: Video Compression Standards Text Book

1. Rafel C Gonzalez and Richard E. Woods, "Digital Image Processing", PHI 2nd Edition 2005


Introduction to Android Programming




Pre-requisite: DBMS , Java Programming Course Outcomes: The student on completion of this course will 1. Able to understand the basic versions, the evolution of Android as a Mobile OS, create simple apps and apply different styles. 2. Learn the User Interface of Android. 3. Manipulate the UI with different common elements. 4. Apply the knowledge to a real time Internet download app. 5. Able to learn how to persist data using preferences. 6. Apply the knowledge of DBMS to persist data. Unit – 1 GETTING STARTED WITH ANDROID PROGRAMMING: What Is Android? Android Versions, Features of Android, Architecture of Android, Android Devices in the Market, The Android Market, The Android Developer Community, Obtaining the Required Tools,Android SDK, Installing the Android SDK Tools, Configuring the Android SDK Manager, Eclipse, Android Development Tools (ADT), Creating Android Virtual Devices (AVDs), Creating Your First Android Application, Anatomy of an Android Application ACTIVITIES, FRAGMENTS AND INTENTS: Understanding Activities, Applying Styles and Themes to an Activity, Hiding the Activity Title, Displaying a Dialog Window, Displaying a Progress Dialog, Displaying a More Sophisticated Progress Dialog, Linking Activities Using Intents, Resolving Intent Filter, Collision, Returning Results from an Intent, Passing Data Using an Intent Object, Fragments, Adding Fragments Dynamically, Life Cycle of a Fragment, Interactions between Fragments, Calling Built-In Applications Using Intents, Self Learning Component: Understanding the Intent Object, Using Intent Filters, Adding Categories, Displaying Notifications Unit – 2 GETTING TO KNOW THE ANDROID USER INTERFACE: Understanding the Components of a Screen, Views and ViewGroups, LinearLayout, AbsoluteLayout, TableLayout, RelativeLayout, FrameLayout, ScrollView, Adapting to Display Orientation, Anchoring Views, Resizing and Repositioning, Managing Changes


to Screen Orientation, Persisting State Information during Changes in Confi guration, Detecting Orientation Changes, Controlling the Orientation of the Activity, Utilizing the Action Bar, Adding Action Items to the Action Bar, Customizing the Action Items and Application Icon, Creating the User Interface Programmatically, Listening for UI Notifications, DESIGNING YOUR USER INTERFACE WITH VIEWS: Using Basic Views, TextView, View, Button, ImageButton, EditText, CheckBox, ToggleButton, RadioButton, and RadioGroup Views, ProgressBar View, AutoCompleteTextView, View Using Picker Views, TimePicker View, DatePicker View, Using List Views to Display Long List, ListView View, Using the Spinner View, Understanding Specialized Fragments, Using a ListFragment, Using a DialogFragment Self Learning Component: Overriding Methods Defined in an Activity, Registering Events for Views, Using a PreferenceFragment Unit – 3 DISPLAYING PICTURES AND MENUS WITH VIEWS: Using Image Views to Display Pictures, Gallery and ImageView Views, ImageSwitcher, GridView, Using Menus with Views, Creating the Helper Methods, Options Menu, Context Menu, Self Learning Component:Some Additional Views, AnalogClock and DigitalClock Views, WebView Unit – 4 USING INTERNET RESOURCES: Downloading and Parsing Internet Resources, Connecting to an Internet Resource, Parsing XML Using the XML Pull Parser, Creating an Earthquake Viewer, Using the Download Manager, Downloading Files, Customizing Download Manager Notifications, Specifying a Download Location, Cancelling and Removing Downloads, Querying the Download Manager, Using Internet Services, Self Learning Component: Connecting to Google App Engine, Best Practices for Downloading Data Without Draining the Battery Unit – 5 FILES, SAVING STATE, AND PREFERENCES: Saving Simple Application Data, Creating and Saving Shared Preferences, Retrieving Shared Preferences, Creating a Settings Activity for the Earthquake Viewer,Introducing the Preference Framework and the Preference Activity, Defining a Preference Screen Layout in XML, Native Preference Controls, Using Intents to Import System Preferences into Preference Screens, Introducing the Preference Fragment, Defi ning the Preference Fragment Hierarchy, Using Preference Headers, Introducing the Preference Activity, Backward Compatibility and Preference Screens, Finding and Using the Shared Preferences Set by Preference Screens, Introducing On Shared Preference Change Listeners, Creating a Standard Preference Activity for the Earthquake Viewer, Persisting the Application Instance State, Saving Activity State Using Shared Preferences, Saving and Restoring Activity Instance State, Using the Lifecycle Handlers, Saving and


Restoring Fragment Instance State, Using the Lifecycle Handlers, Including Static Files as Resources, Working with the File System, File-Management Tools Using Application-Specific Folders to Store Files, Creating Private Application Files, Self Learning Component: Using the Application File Cache, Storing Publicly Readable File Unit – 6 DATABASES AND CONTENT PROVIDERS: Introducing Android Databases, SQLite Databases, Content Providers, Introducing SQLite, Content Values and Cursors, Working with SQLite Databases, Introducing the SQLiteOpenHelper, Opening and Creating Databases Without the SQLite Open Helper, Android Database Design Considerations, Querying a Database, Extracting Values from a Cursor, Adding, Updating, and Removing Rows, Inserting Rows, Updating Rows, Deleting Rows, Creating Content Providers, Registering Content Providers, Publishing Your Content Provider’s URI Address, Creating the Content Provider’s Database, Implementing Content Provider Queries, Content Provider Transactions, Storing Files in a Content Provider, A Skeleton Content Provider Implementation, Using Content Providers, Introducing the Content Resolver, Querying Content Providers, Querying for Content Asynchronously Using the Cursor Loader, Introducing Loaders, Using the Cursor Loader, Adding, Deleting, and Updating Content, Inserting Content, Deleting Content, Updating Content, Accessing Files Stored in Content Providers, Self Learning Component: Creating a To-Do List Database and Content Provider Text Books:

1. Wei-Meng Lee, Beginning Android 4 Application Development, Wrox, Wiley India Edition. (Chapters: 1, 2, 3, 4, 5)

2. Reto Meier, Professional Android 4 Application Development, Wrox, Wiley India Edition(Chapters: 6, 7, 8)

Reference Books:

1. Mark Murphy, The Busy Coder's Guide to Android Development, version 4.2. 2. Android Programming: The Big Nerd Ranch Guide (Big Nerd Ranch Guides) 3. Paul Deitel, Harvey Deitel, Abbey Deitel, and Michael Morgano, Android for

Programmers: An App-Driven Approach 4. Anubhav Pradhan, Anil V Deshpande, Composing Mobile Apps: Learn / Explore

/ Apply using Android 1st Edition.


Cloud Computing (4:0:0)




Course Outcomes: On successful completion of the course, the students will be able to: 1. Analyse what is cloud computing and what is not. 2. Develop an insight into the basic cloud architecture and cloud services. 3. Use the concepts of abstraction and virtualization and cloud services. 4. Explain clear sight into the working of a cloud with special reference to google cloud

services. 5. Take decisions on cloud deployment with special reference to cloud security issues. 6. Acquire the working knowledge of service oriented architectures and cloud based

storages. UNIT 1 : Introduction Defining Cloud Computing, Cloud Types: NIST Model, Cloud Cube Model, Deployment models, Service Models. Characteristics of Cloud Computing: Paradigm shift, Benefits of Cloud computing, Disadvantages of cloud computing, Role of Open Standards,Assesing the value proposition:Measuring the cloud’s value, Self Learning Component: Avoiding Capital Expenditures,Computing the total cost of ownership,Specifying service level agreement,Defining licensing models UNIT 2 : Understanding Cloud Architecture Exploring the Cloud Computing Stack: Composability, Infrastructure, Platforms, Virtual Appliances, Communication Protocols, Applications, Connecting to the cloud: Jolicloud Netbook OS, Self Learning Component: Chromium OS : The Browser as an Operating System. UNIT 3 : Understanding Services, Applications, Abstraction and Virtualization Defining Infrastructure as Service (IaaS), Defining Platform as a Service (PaaS), Defining Software as a Service (SaaS), Defining Identity as a Service (IDaaS), Defining Compliance as a Service (CaaS), Using Virtualization Technologies, Load Balancing and Virtualization, Self Learning Component: Understanding Hypervisors, Understanding Machine Imaging, Porting Applications. UNIT 4 : Using Google Web Services and Managing the Cloud Exploring Google Applications, Surveying the Google Application Portfolio: Indexed Search, The dark Web, Aggregation and disintermediation, Productivity applications and services, Enterprise offerings, Google Analytics, Google Translate, Exploring the Google Toolkit,


Self Learning Component: Working with Google App Engine, Administrating the Clouds, Cloud Management Products, Emerging Cloud Management Standards. UNIT 5 : Understanding Cloud Security Securing the Cloud: The security boundary, Security service boundary, Security mapping. Security Data: Brokered cloud storage access, Storage location and tenancy, Encryption, Auditing and compliance. Self Learning Component: Establishing Identity and Presence: Identity protocol standards, Windows Azure identity standards, Presence. UNIT 6 : Understanding Service Oriented Architecture Introducing Service Oriented Architecture: Event-driven SOA or SOA 2.0, Enterprise Service Bus, Service catalogs. Defining SOA Communications : Business Process Execution Language, Business Process modeling. Managing and Monitoring SOA : SOA Management tools, SOA security, Self Learning Component: The Open Cloud Consortium. Relating SOA and Cloud Computing,Moving applications to the cloud:Applications in the cloud’s,Applications and cloud API’s:Case Study-Aneka. Text Book: Cloud Computing Bible by Barrie Sosinsky, Wiley India Reference Books :

1) Cloud Computing for Dummies by Judith Hurwitz, R. Bloor, M. Kanfman, F. Halper (Wiley India Edition).

2) Cloud Security by Ronald Krutz and Russell Dean Vines, Wiley-India. 3) Cloud Computing : A Practical Approach, Anthony T Velte. 4) Google Apps by Scott Granneman,Pearson 5) A Brief Guide to Cloud Computing: An Essential Introduction to the Next

Revolution in Computing, Christopher Barnatt.