Master of Computer Application (M.C.A.)€¦ · ASSESSMENT METHODS: THEORY Courses: SESSIONAL Courses: 1) Quiz (Three in number, as part of continuing evaluation). [Weightage: 30

Birla Institute of Technology, Mesra

Ranchi, Jharkhand – 835215

Master of Computer Application

(M.C.A.)

2011

Master of Computer Application, BIT Mesra

[Type here] 2 2011

Program Educational Objectives

1. To excel in software development skills coveted in

the IT industry.

2. To be well prepared for pursuing higher studies in

related fields of teaching and research.

3. To be aware of the requirements of being an ethical

and professional leader and inculcating team spirit.

4. To inculcate the ability to innovate and contribute

towards the growth of the nation.


[Type here] 3 2011

Program Outcomes

1. Attain problem solving attitude in systematic and timely manner.

2. Apply knowledge of mathematics, algorithm and computing

principles appropriately to solve real-world problems.

3. Identify modern tools and techniques through critical thinking for

solving complex problems.

4. Use the computational resources efficiently to develop software for

the industry need.

5. Understand and assess societal, environmental, safety, legal and

ethical norms for professional computing practices.

6. Function as an individual or as a member in team in the software

domain.

7. Recognize the need for self-motivation, learning and unlearning to

engage in life-long learning for continual development.

8. Excel in descriptive oral, written communication and presentation

skills required for documenting and delivering project artefacts

effectively.


[Type here] 4 2011

ASSESSMENT METHODS:

THEORY Courses:

SESSIONAL Courses:

1) Quiz (Three in number, as part of continuing evaluation). [Weightage: 30 out of 100]

2) End Semester Evaluation. [Weightage: 60 out of 100]

3) Assignment. [Weightage: 10 out of 100]

1) Continuing Evaluation. [Weightage 60 out of 100]

2) End Semester Evaluation. [Weightage: 40 out of 100]


[Type here] 5 2011


[Type here] 6 2011

Course Structure

Semester 1 (Total Credits: 20)

Theory Courses

Course Code Course Title Total Credit (L-T-P)

MCA 1001 Problem Solving and Program Design with C 3 (3-0-0)

MCA 1003 Numerical & Statistical Methods 4 (3-1-0)

MCA 1107 Discrete Mathematics 3 (3-0-0)

MCA 1009 Computer Organization & Architecture 3 (3-0-0)

Breadth Paper – I 3 (3-0-0)

Sessionals

MCA 1002 C programming Lab. 2 (0-0-2)

MCA 1004 Numerical & Statistical Methods Lab. 2 (0-0-2)


[Type here] 7 2011

Semester 2

Theory Courses


MCA 2001 Data Structures 3 (3-0-0)

MCA 2003 Object Oriented Design and Programming 3 (3-0-0)

MCA 2005 Database Management Systems 3 (3-0-0)

MCA 2007 Operating System 3 (3-0-0)

Sessionals

MCA 2002 Data Structures Lab 2 (0-0-2)

MCA 2004 C++ Programming Lab 2 (0-0-2)

MCA 2006 RDBMS Lab 2 (0-0-2)

MCA 2008 Operating System Lab 2 (0-0-2)


[Type here] 8 2011

Semester 3

Theory Courses


MCA 3001 Java Programming 3 (3-0-0)

MCA 3003 Software Engineering 3 (3-0-0)

MCA 3005 Fundamentals of Computer Algorithms 3 (3-0-0)

MCA 3007 Automata Theory 4 (3-1-0)

Elective – I 3 (3-0-0)

Sessionals

MCA 3002 Java Programming Lab. 2 (0-0-2)

MCA 3004 Software Engineering Lab. 2 (0-0-2)


[Type here] 9 2011

Semester 4

Theory Courses


MCA 4001 Compiler Design 4 (3-1-0)

MCA 4003 Data Communications and Computer

Networks

3 (3-0-0)

MCA 4007 Computerized Financial Accounting 3 (3-0-0)

Breadth Paper-II 3 (3-0-0)

Elective – II 3 (3-0-0)

Sessionals

MCA 4002 Compiler Design Lab. 2 (0-0-2)

MCA 4004 Computer Networks Lab 2 (0-0-2)


[Type here] 10 2011

Semester 5

Theory Courses


MCA 5001 Computer Graphics 3 (3-0-0)

MCA 5003 System Simulation and Modeling 4 (3-1-0)

MCA 5005 Optimization Theory 3 (3-0-0)

Breadth Paper – III 3 (3-0-0)

Elective – III 3 (3-0-0)

Sessionals

MCA 5002 Computer Graphics Lab 2 (0-0-2)

MCA 5004 System Simulation and Modeling Lab 2 (0-0-2)

Semester 6

Course Code Course Title Total Credit

MCA 6001 Project 20


[Type here] 11 2011

List of Electives

Students are required to choose at least two electives from the same group.

Group I: Database Technology

MCA 7101 Distributed Databases

MCA 7103 Decision Support Systems

MCA 7105 Enterprise Resource Planning

MCA 7107 Data Mining & Warehousing

MCA 7109 Multimedia Databases

Group II: Software Technology

MCA 7201 Advanced Java Programming

MCA 7203 Systems Programming

MCA 7205 Programming Language Design and Concepts

MCA 7207 Assembly Language Programming

MCA 7209 Web Programming

MCA 7211 Software Project Management

Group III : Cognitive Sciences and Intelligent Systems

MCA 7301 Natural Language Processing

MCA 7303 Genetic Algorithms and Swarm Intelligence


[Type here] 12 2011

MCA 7305 Artificial Intelligence

MCA 7307 Image Processing

MCA 7309 Soft Computing

Group IV: Networking and Distributed System

MCA 7401 Network Security and Cryptography

MCA 7403 Grid Computing

MCA 7405 Wireless Technology

MCA 7407 Parallel and Distributed Computing

MCA 7409 Mobile Computing

Group V : Application of Information Technology

MCA 7501 Bioinformatics

MCA7505 Multimedia and Animation

MCA 7507 Supply Chain Management

MCA 7311 Cloud Computing


[Type here] 13 2011

SYLLABUS


[Type here] 14 2011

Semester I


[Type here] 15 2011

MODULE- I & II

Problem Solving and Programming Concepts: Problem Solving in Everyday Life, Types

of Problem, Problem Solving with Computers, Constants and Variables, Data Types,

Functions, Operators, Expressions and Equations, Data Storage and Communication with

Computer, Organizing the Problem, Computer Software and Software Development

Method. .

MODULE - III

Overview of C: C Language Elements, Variable Declaration, Data Types, Expressions, Data

Files.

Top-Down Design with Functions: Top-Down Design and Structure Charts, Functions

without Arguments, Functions with Input Arguments.

MCA 1001

PROBLEM SOLVING & PROGRAM DESIGN WITH C

Credits: 3

L-T-P: (3-0-0)

Expected number of classes: 45

Course Outcomes

1. Ability to develop efficient algorithms for solving a problem.

2. Understanding and the ability to use the basic C language for solving engineering or other real-life problems.

3. Ability to design an algorithmic solution for a given problem.

4. Ability to develop the use of the C-programming language to implement various algorithms and develop the basic concepts. and terminology of programming in general.

5. Ability to develop basic understanding of computers, the concept of algorithm and algorithmic thinking.


[Type here] 16 2011

MODULE - IV

Selection Structures: Problem Solving with Decisions, Control Structures, Conditions, All

kinds of if statements, Switch statement.

Repetition and Loop Statements: Problem Solving with Loops, Repetition in Programs,

while Statement, for Statement, Conditional Loops, Loop Design, Nested Loops, do-while

Statement and Flag Controlled Loops.

MODULE - V

Modular Programming: Functions with Simple Output Parameters, Multiple Calls to a

Function with Input/Output Parameters, Scope of Names, Formal Output Parameters as

Actual Arguments.

Arrays: Declaring and Referencing Arrays, Array Subscripts, Using for Loops for

Sequential Access, Using Array Elements as Function Arguments, Array Arguments,

Multidimensional Arrays.

MODULE - VI

Strings: String Basics, String Comparison, Arrays of Pointer, Character Operations, String-

to-Number and Number-to-String Conversions.

Recursion: The Nature of Recursion, Tracing a Recursive Function, Recursive

Mathematical Functions, Recursive Functions with Array and String Parameters, Problem

Solving with Recursion.

MODULE - VII

Structure and Union Types: User-Defined Structure types, Structure Type Data as Input

and Output Parameters, Functions Whose Result Values are Structured, Problem Solving

with Structure Types, Union types.

File Processing and Programming in the Large: Input and Output Files, Binary Files,

Using Abstraction to Manage Complexity, Header Files, Implementation Files, Storage

Classes, Macros.

Text Books

1. M.Sprankle- Problem Solving and Programming Concepts, 7th Edn, Pearson Education, New

Delhi-2006

2. J.R.Hanly & E.B. Koffman- Problem Solving and Program Design in C, 4th Edition, Pearson

Education, New Delhi-2004.

Reference Books:

1. E.Balagurusamy- Programs in ANSI C, 3rd Edn, TMH, New Delhi-2004

2. B.A.Forouzan & R.F. Gilberg- Computer Science: A structured Programming Approach Using

C, 2nd Edn, Brooks/Cole- Thomson Learning, Indian Reprint, 2003.


[Type here] 17 2011

MODULE- I

Errors in Numerical Calculations: Errors & their computation-absolute, relative & percentage.

Solution of algebraic & transcendental equations: Introduction, Bisection method, Iterative method,

False position method, Newton’s Raphson method, Lin Bairstows method. Error analysis &

convergence study.

MODULE - II

Interpolation with equal & unequal intervals: Introduction, finite differences-forward, backward &

central, difference tables, differences of polynomials, Newton’s formula for interpolation, Gauss’s

central difference interpolation formula, Divided difference & their properties- Newton’s divided

differences formula, Lagrange’s interpolation formula, Inverse interpolation.

Course Outcomes

1. Familiarise the student with different statistical methods and implementation.

2. Identify the strength and weakness of different numerical theories. 3. Able to use numerical methods in modern scientific computation. 4. Familiar with calculation and interpretation of errors in numerical methods. 5. Solve computing problems independently

MCA 1003

NUMERICAL AND STATISTICAL METHODS

Credits: 4

L-T-P: (3-1-0)



[Type here] 18 2011

MODULE - III & IV

Numerical differential & integration: Introduction, derivatives using forward & backward difference

formula, Numerical Integration-Trapezoidal rule, Simpson’s 1/3 & 3/8 rules Weddle’s rule.

Numerical solution of linear system of equations: Direct method-Gauss elimination, Gauss-Jordan,

LU decomposition methods. Iterative methods-Gauss-Jacobi & Gauss Seidel methods.

Numerical solution ordinary differential equations: Taylor Series method, Euler’s method, Modified

Euler’s method, Runga-Kutta methods of 2nd &4th order, Predictor-Corrector methods (Milne’s

method and Adam’s methods). Statistical Methods

MODULE - V

Concepts of Probability: Experiment and Sample Space,Events and Operations with Events,

Probability of an Event, Basic Probability Rules, Applications of Probability Rules, Conditional

Probability.

Random Variables: How Random Variable Arise, Probability Distribution of a Random Variable,

Mean or Expected Value of a Random Variable, Probability Histogram Value of a Random Variable,

Variance and Standard Deviation of a Random Variable.

MODULE - VI

Binomial Experiments: Structure of a Binomial Experiment, Binomial Probability Distribution, Use

of Binomial Probability Table.

Normal Curve and Normal Distribution: Motivation behind a Normal Curve, Properties of a Normal

Curve, Normal Probability Distribution, Areas Under a Normal Curve.

Applications of the Normal Distribution: Approximating a Binomial Probability, The Normal

Theorem and the Central Limit Theorem.

MODULE - VII

Estimation of Population Parameters: Parameter and Statistic, Point and Interval Estimation, Interval

Estimation of Three Common Parameters.

Hypothesis Testing for a Single Population: Concept of a Hypothesis, Tests Involving a Population

Mean, Tests Involving a Population Proportion, Tests Involving a Population Standard Deviation.

Hypothesis Testing to Compare Two Populations: Comparison of Two Populations, Tests for Two

Population Means, Tests for Two Population Means, Tests for Two Population Proportions, Tests

for Two Population Variance.

Bivariate Quantitative Data- Correlation and Regression: Concepts of a Bivariate Data Set,

Correlation Coefficient, Inferences on a Population Correlation Coefficient, The Regression line,

Inferences on the Population Regression Line.


[Type here] 19 2011

Text Books

1. S.S.Sastry-Introductory Methods of Numerical Analysis-PHI, Private Ltd., New Delhi.

2. N.Pal & S. Sarkar- Statistics: Concepts and Applications, PHI, New Delhi-2005.

Reference Books:

1 R.V.Hogg et.al- Probability and Statistical Inpane, 7th Edn, Pearson Education, New Delhi-2006.

2. R.L.Burden & J.D.Faires- Numerical Analysis, Thomson Learning-Brooks/Cole, Indian Reprint,

2005.


[Type here] 20 2011

Module-I

Relations and digraphs: Product sets and partitions, Relations and Digraphs, Paths in relations and

digraphs, equivalence relation, operations on relations, Transitive closure and Warshall’s algorithm

Module-II

Functions: Functions for Computer Science, Growth of functions, Permutation functions.

Module-III

Order Relations and Structures: Partially ordered sets, External elements of partially ordered sets,

Lattices, Finite Boolean Algebra, Functions on Boolean Algebra, Circuit design

Module-IV

Tree: Trees, Labelled trees, Tree searching, Undirected trees, Minimum Spanning trees

Module-V

Graph: Terminologies, connected graphs, Euler graph, Hamiltonian path and circuit Hamiltonian

path and circuits, Transport network, Matching problems, Graph colouring.

Course Outcomes

1. To know the use of mathematics and discrete structures in different domain of computer science.

2. To develop mathematical skills for writing good computer programs.

3. To develop the concepts/logic for writing mathematical proofs of the theorems/lemmas in the area of computer science.

4. To be exposed to the strategies to compare the relative efficiency of computer algorithms.

5. To understand basic properties of graphs and trees and be able to relate these to practical problems.

MCA 1107

Discrete Mathematics

Credits: 3

L-T-P: (3-0-0)



[Type here] 21 2011

Module-VI

Group: Properties and Operations, Semi group, Products and Quotients of Semigroups, Groups,

Products and Quotients of Groups, Other Mathematical structures,

Module-VII

Coding: Codewords and code, Encoding function, Hamming distance, Error detection and correction

codes, Pre-fix code

Text Books

1. Kolman, Busby, Ross, Rehmann: Discrete Matheamatical Structures, 5/e, Pearson Education,

2006.


[Type here] 22 2011

MODULE - I

Introduction: Organization and Architecture, Structure and Function, Why Study Computer Organization

and Architecture?

Computer Evolution and Performance: A Brief History of Computers, Designing for Performance,

Pentium and PowerPC Evolution.

MODULE - II

A Top-Level view of Computer Function and Interconnection: Computer Components, Computer

Function, Interconnection Structures, Bus Interconnection, PCI.

MODULE - III

Cache Memory: Computer Memory System Overview, Cache Memory Principles, Elements of Cache

Design, Pentium 4 and PowerPC Cache Organizations.

Internal Memory: Semiconductor Main Memory, Error Correction, Advanced DRAM Organization.

MODULE - IV

External Memory: Magnetic Disk, RAID, Optical Memory, Magnetic Tape.

Input/Output: External Devices, I/Os, Programmed I/O, Interrupt-Driven I/O, Direct Memory Access,

I/O Channels and Processors.

MODULE - V

Computer Arithmetic: The Arithmetic and Logic Unit, Integer Representation, Integer Arithmetic,

Floating-Point Representation, Floating-Point Arithmetic.

Course Outcomes

1. Describe performance evaluation of computers, computer architecture and organization, computer arithmetic, Memory and CPU design. 2. Describe I/O system and interconnection structures of computer. 3. Identify high performance architecture design, Pipelining and Multiprocessors. 4. Develop independent learning skills and be able to learn more about different computer architectures and hardware.

5. Familiar with the cost‐performance issues and design trade‐offs in designing and constructing a computer processor including memory.

MCA 1009

Computer Organization and Architecture

Credits: 3

L-T-P: (3-0-0)



[Type here] 23 2011

MODULE - VI

Instruction Sets- Characteristics and Functions: Machine Instruction Characteristics, Type of Operands,

Pentium and PowerPC Data Types, Types of Operations, Pentium and PowerPC Operation Types.

Instruction Sets- Addressing Modes and Formats: Addressing, Pentium and PowerPC Addressing Modes,

Instruction Formats, Pentium and PowerPC Instruction Formats.

MODULE - VII

Processor Structure and Function: Processor Organization, Register Organization, Instruction Cycle,

Instruction Pipelining, The Pentium Processor, The PowerPC Processor.

Reduced Instruction Set Computers: Instruction Execution Characteristics, The Use of a Large Register

File, Compiler-Based Register Optimization, Reduced Instruction Set Architecture, RISC Pipelining,

MIPS R4000, SPARC, RISC versus CISC Controversy.

Text Books

1. William Stallings- Computer Organization & Architecture: Designing for Performance, 7th Edn,

Pearson Education, New Delhi-2006.

Reference Books:

1. C. Hamacher- Computer Organization, 5th Edn, McGraw Hill, Internaional Education, New Delhi-

2002.

2. M.M.Mano- Computer System Architecture, 3rd Edn, PHI/Pearson Education, New Delhi-2006.

3. J.P.Hayes- Computer Architecture and Organization, 3rd Edn, McGraw Hill, Internal Edn, New Delhi-

1998.


[Type here] 24 2011

Semester II


[Type here] 25 2011

MODULE - I Introduction: Pseudocode, The Abstract Data Type, A Model for an Abstract Data, Algorithm Efficiency. Searching: List Searches, Hashed List Searches, Collision Resolution.

MODULE- II Linked Lists: Linear List Concepts, Linked List Concepts, Linked List Algorithms, Processing a Linked List, List Applications, Complex Linked List Structures, List Abstract Data Type-Linked List Implementation.

MODULE - III Stacks: Basic Stack Operations, Stack Linked List Implementation, Stack Applications, Stack Abstract Data Type Implementation, Stack ADT- Array Implementation. Queues: Queue Operations, Queue Linked List Design, Queuing Theory, Queue Applications, Queue ADT-Linked List Implementation, Queue ADT-Array Implementation.

MODULE - IV & V Recursion: Factorial – A Case Study, How Recursion Works, Designing Recursive Algorithms, Another Case Study- Fibonacci Numbers, The Towers of Hanoi. Introduction to Trees: Basic Tree Concepts, Binary Trees, Binary Tree Traversals, Expression Trees, General Trees, Huffman Code. Search Trees: Binary Search Trees, AVL Trees, AVL Tree Implementation, AVL Abstract Data Type.

MODULE - VI Heaps: Heap Definition, Heap Structure, Basic Heap Algorithms, Heap Data Structure, Heap Algorithms, Heap Applications. Multiway Trees: m-Way Search Trees, B-Trees, Simplified B-Trees.

Course Outcomes

1. Ability to choose appropriate data structure as applied to specified problem definition.

2. Ability to handle operations like searching, insertion, deletion, traversing mechanism etc. on various data structures.

3. Ability to apply concepts learned in various domains like DBMS, compiler construction etc.

4. Ability to use linear and non-linear data structures like stacks, queues, linked list, Trees etc.

5.Basic ability to analyse algorithms and to determine algorithm correctness and time efficiency class.

MCA 2001

Data Structures

Credits: 3

L-T-P: (3-0-0)



[Type here] 26 2011

MODULE - VII Advanced Sorting Concepts: General Sort Concepts, Insertion Sorts, Selection Sorts, Exchange Sorts, External Sorts.

Text Books

1. R.F.Gilberg & B.A. Forouzan- Data Structures: A Pseudocode Approach with C++, 2nd Edn,

Brooks/Cole- Thomson Learning, Indian Reprint, 2005.

Reference Books:

1. E.Horowitz et.al-Fundamentals of Data Structures in C++, Galgotia Publication, New Delhi, 2006.

2. A.M.Berman- Data Structures vie C++, Oxford Univ. Press, Inc. Indian Reprint, 2002.

3. M.T.Goodrich et.al- Data Structures and Algorithms in C++, John Wiley, Inc. Indian Reprint, 2004.


[Type here] 27 2011

MODULE - I Computing and the Object-Oriented Design Methodology: Basic Computing Terminology, Software, Engineering Software, Object-Oriented Design. C++ -The Fundamentals: Program Organization, A First Program, A Second Program, Comments, Assigning a Value, Fundamental C++ Objects, Constants, Names, Definitions, Expressions, Output Statements, Computing Average Velocity.

Course Outcomes

1. Understand basic concepts of classes and objects. 2. Understand the concepts of polymorphism and techniques to implement it. 3. Familiarise the student with inheritance and its kinds 4. Understand concepts of cloning and its variants. 5. Learn how to perform systematic error handling in OOP systems.

MCA 2003

Object Oriented Design and Programming

Credits: 3

L-T-P: (3-0-0)



[Type here] 28 2011

MODULE - II Modifying Objects: Assignment, Const. Definitions, Input Statements, Computing the Number of Molecules in a Hydrocarbon, Compound Assignment, Increment and Decrement, Estimating Yearly Savings of Change, The String Class, EzWindows, Moving Lawns. Control Constructs: Boolean Algebra, A Boolean Type, Conditional Execution Using the if Statement, Conditional Execution Using the switch Statement, Computing a Requested Expression, Validating a Date, Iteration Using the while Statement, Simple String and Character Processing, Iteration Using the for Statement, Simple Data Visualization, Solving the Lazy Hobo Riddle, Iteration Using the do Construct.

MODULE - III Functions Usage Basics and Libraries: Function Basics, The Preprocessor, Using Software Libraries, The iostream Library, The iomanip Library, The fstream Library, The math Library, Library ctype, The assert macros.

MODULE – IV and V Programmer-Defined Functions: Basics, A Tasty Problem, Some Useful Functions, Integrating a Quadratic Polynomial, The Logic Scope, Displaying a Price-Interval Chart, Recursive Functions. Advanced Parameter Passing: Reference Parameters, Passing Objects by Reference, Validating Telephone Access Codes, Constant Parameters, Default Parameters, Casting of Function Parameters, Function Overloading, Random Numbers, A Factory Automation Trainer. The Class Construct and Object-Oriented Design: Introducing a Parameter-Defined Data Type, The Rectangle Shape Class, Using the Rectangle Shape Class, Constructors, Building a Kaleidoscope, Object-Oriented Analysis and Design.

MODULE - VI Pointers and Dynamic Memory: Lvalues and Rvalues, Pointer Basics, Constant Pointers and Pointers to Constants, Arrays and Pointers, Character String Processing, Program Command-line Parameters, Pointers to Functions, Dynamic Objects, A Simple ADT for Representing Lists of Integer Values.

MODULE - VII Inheritance: Object-Oriented Design Using Inheritance, Reuse via Inheritance, A Hierarchy of Shapes, Protected Members and Inheritance, Controlling Inheritance, Multiple Inheritance, A Prettier Kaleidoscope. Templates and Polymorphism: Generic actions and Types, Function Templates, Class Templates, A Simple List Class Using a Class Template, Sequential Lists, Polymorphism, Virtual Function Nuances, Abstract Base Classes, Virtual Multiple Inheritance.

Text Books

1. J.P.Cohoon & J.W.Davidson- C++ Program Design: An Introduction to Programming and Object-

Oriented Design, 2nd Edn, TMH Edn, New Delhi-2000.

Reference Books:

1. F.L.Friedman & E.B.Koffman- Problem Solving, Abstraction, and Design Using C++, 4th Edition, Pearson

Education, Inc. 2004.


[Type here] 29 2011

MODULE - I Introduction: Purpose of Database Systems, Data Models, Schemas and Instances, Three-Schema Architecture and Data Independence, Database languages, Database Architecture, Classification of DBMS, relational database, Database users and Administrators, Advantages of DBMS.

MODULE - II E-R-Model: Entities and Entity Sets, Relationships and Relationship Sets, Keys, Mapping, Constraints, ER Diagram, Reducing ER Diagram to tables, Generalization and Specialization, Aggregation.

MODULE - III Relational Model: Concepts, Constraints and Relational database Schemas, Relational Algebra, Relational Calculus, QUEL, QBE, SQL.

MODULE - IV Database Design: Pitfalls in relational database design, Normalization using functional, Multivalued and join dependencies, DKNF, Atomic values, alternative approaches to database design.

MODULE - V Security & Integrity :Security & Integrity violations, authorization and views, integrity constants, encryption, Statistical databases.

MCA 2005

Data Base Management System

Credits: 3

L-T-P: (3-0-0)


Course Outcomes

1. Evaluate and understand the role of database management systems in information technology applications within organizations. Generalize a physical design for a database from its logical design.

2. Illustrate the SQL data definition and SQL query languages and recognize the use of contemporary logical design methods and tools for databases

3. Formulate the operation of Transaction and concurrent task to ensure the results as quickly as possible.

4. Construct a distributed collections of data across multiple physical locations.

5. Develop sophisticated queries to extract information from large datasets. Prepare the system having data redundancy which improve data integrity.


[Type here] 30 2011

MODULE – VI & VII Transaction Processing and Concurrency Control : Transaction Processing, Schedules and Recovery, Locking and Timestamp Ordering for concurrency control. Distributed Databases : Concepts and Types of Distributed databases, data fragmentation, Replication and Allocation.

Text Books

1. Fundamentals of Database Systems "Ramez Elmasri", Pearson Education

Reference Books:

1. Database Systems Concepts "A. Silberschatz, Korth", McGraw Hill.


[Type here] 31 2011

MODULE – I Overview of Operating Systems: OS and the Computer System, Efficiency, System Performance and User Convenience, Classes of Operating Systems, Batch Processing Systems, Multiprogramming Systems, Time Sharing Systems, Real Time Operating Systems, Distributed Operating Systems, Modern Operating Systems.

MODULE – II Processes and Threads: Processes and Programs, Programmer view of Processes, OS view of Processes, Threads, Case studies of Processes and Threads.

MODULE – III Scheduling: Preliminaries, Non-preemptive Scheduling Policies, Preemptive Scheduling Policies, Scheduling in Practice, Real Time Scheduling, Scheduling in Unix, Scheduling in Linux, Scheduling in Windows, Performance Analysis of Scheduling Policies.

MODULE – IV Memory Management: Managing the Memory Hierarchy, Static and Dynamic Memory Allocation, Memory Allocation to a Process, Reuse of Memory, Contiguous Memory Allocation, Noncontiguous Memory Allocation, Paging, Segmentation, Segmentation with Paging, Kernel Memory Allocation, A Review of Relocation, Linking and Program Forms.

MODULE – V Virtual Memory: Virtual Memory Basics, Demand Paging, Page Replacement Policies, Memory Allocation to a Process, Shared Pages, Memory Mapped Files, Unix Virtual Memory, Linux Virtual Memory, Virtual Memory using Segmentation.

MCA 2007

Operating System

Credits: 3

L-T-P: (3-0-0)


Course Outcomes

1. Assess various operating systems and their functionalities. 2. Illustrate as well as design a CPU scheduler. 3. Analyze the resource management strategies of an OS. 4. Compile or extend memory management module of an OS. 5. Analyze and implement file system.


[Type here] 32 2011

MODULE – VI File Systems: File System and IOCS, Files and File Operations, Fundamental File Organizations, Directory Structures, File Protection, Interface between File System and IOCS, Allocation of Disk Space, Implementing File Access, File Sharing Semantics, File System Reliability, Virtual File System, Unix File System, Linux File System, Windows File System, Performance of File Systems.

MODULE – VII Security and Protection: Overview of Security and Protection, Goals of Security and Protection, Security Attacks, Formal and Practical aspects of Security, Encryption, Authentication and Password Security, Access Descriptors and the Access Control Matrix, Protection Structures, Capabilities, Unix Security, Linux Security, Windows Security.

Text Books

1. D.M. Dhamdhere- Operating Systems: A Concept-Based Approach, 2nd Edn, TMH, New Delhi – 2006.

Reference Books:

1. A. Silberschatz et.al-Operating System Concepts, 6th Edn, John Wiley, Indian Reprint, 2003.

2. C.Cronsley-Operating Systems: A Design-Oriented Approach, TMH, New Delhi, 2002.

3. H.M.Deitel-Operating Systems, 2nd Edn, Pearson Education, 2003.

4. A.S.Tanenbaum-Operating System:Design and Implementation, PHI, New Delhi, 2002.


[Type here] 33 2011

Semester III


[Type here] 34 2011

MODULE – I Fundamentals of Java Programming: Data in Java Programs, Arithmetic Operators and Expressions, Simple Program Input and Output.

MODULE – II Making Decisions with Java: Comparing Numbers in Java, Comparing Strings in Java, Logical (Boolean) Operators and Order of Precedence, Selection Structures in Java.

MODULE – III Repeating Program Statements: The while Statement, The for Statement, The do…while Statement, Nested Loops, break, and continue.

MODULE – IV Methods and Classes: Predefined Java Methods, Programmer-Defined Methods. Arrays: The One-Dimensional Array, Multidimensional Arrays, Other Array Topics.

MCA 3001

Java Programming

Credits: 3

L-T-P: (3-0-0)


Course Outcomes

1. Identify the need and power of Java programming language to develop robust and portable

applications.

2. Understand fundamentals of object-oriented programming using Java, including concepts of

object and classes, class members and relationship between them.

3. Demonstrate the ability of an object to take on many forms, code reusability and ability to

handle exceptions raised during execution of program.

4. Develop wide range of applications that includes; simple console based programs, Graphical

user interface and programs used in Internet environment.

5. Use and create professional looking java class libraries.


[Type here] 35 2011

MODULE – V Characters, Strings, and Formatting: Working with Characters, Working with Strings, Formatting Data for Output. Exceptions and Assertions: Exception Handling, Assertions.

MODULE – VI File Input and Output: Inputting Data from a Text File, Outputting Data to a Text file, Performing Input and Output with Binary Files.

MODULE – VII Graphical User Interfaces: Creating User Interfaces, Overview of a Java GUI, Developing a Java GUI, Adding Functionality to a GUI , Improving GUI Layout.

Text Books

1. Richard A. Johnson, “ An Introduction to Java Programming and Object-Oriented Application

Development”, 1st Edn.,Thomson Learning, New Delhi – 2007.

Reference Books:

1. 1. Dietel, Dietel - Java How to Program , 5th Edn, Pearson Education , New Delhi, 2006. 2. 2. E. Balagurusamy – JAVA Programming, TMH, New Delhi, 2005. 3. 3. James M. Sleek – Programming and Problem Solving with JAVA, Thomson Learning, Indian

Edition, 2007.


[Type here] 36 2011

MODULE - I Introduction to Software Engineering: Evolving Role of Software, Changing Nature of Software, Legacy Software, Software Engineering – A layered Technology.

MODULE - II Process Frame work, Process Patterns, Process Models, Waterfall Model, Incremental Process Models, Evolutionary Process Models, Specialized Process Models, Unified Process Model, Agile Process Model.

MODULE - III Requirement Engineering: A bridge to design and construction, Requirement Engineering Task, Initiating the Requirement Engineering Process, Eliciting Requirements, Developing Use case, Building the Analysis Model, Negotiating Requirements, Validating Requirements.

MODULE - IV Design Engineering: Design Process and Design Quality, Design Concepts, Design Models, Pattern Based Software Design.

MODULE – V Tasting Strategies and Testing Tactics: Strategic Approach to software Testing, Test Strategies for conventional and Object Oriented Software, Validation Testing System Testing, White Box

MCA 3003

Software Engineering

Credits: 3

L-T-P: (3-0-0)


Course Outcomes

1. Analytically apply ethical and general principles of software development lifecycle models for project development.

2. Identify and apply appropriate software architectures and patterns to carry out high-level design of a system as well as also be able to critically compare alternative choices.

3. Analyse and estimate critical factors related to project planning, scheduling and risk.

4. Develop and integrate strategies to ensure software quality through testing.

5. Summarize findings of the current business situation, business processes and models, for software evolution to ensure reliability and maintainability of the software.


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Testing, Basic Path Testing Control Structure Testing, Black Box Testing, Object Oriented Testing Methods.

MODULE – VI Metric for process and Estimation Techniques: Process metrics, Software Measurement, Software Project Estimation, Decomposition Techniques, Empirical Estimation Models, Estimation for Object Oriented Projects Specialized Estimation Techniques.

MODULE – VII Software Quality and Configuration Management: Quality Concepts, Software Quality Assurance, Software Reliability, Software Configuration Management, SCM Repository, SCM Process.

Text Books

1. Roger S. Pressiman – “Software Engineering – A Practitioner’s Approach”, 6th Edn., McGraw Hill. Reference Books:

1. John Wiley and Sons – “ Software Engineering – Principles and Practice –2nd Edn., Haus Van Vliet. 2. Ian Sommerville – “Software Engineering”, 7th Edn., Pearson Education.


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MODULE - I Elementary Algorithmic: Introduction, Problems and instances, The efficiency of algorithms, Average and worst-case analyses, What is an elementary operation, why look for efficiency Asymptotic Notation : Introduction, A notation for “the order of”, Other asymptotic notation, Conditional asymptotic notation, Conditional asymptotic notation, Asymptotic notation with several parameters, Operations on asymptotic notation

MODULE - II Analysis of Algorithm: Introduction, Analyzing control structures, Using a barometer, Supplementary examples, Average-case analysis, Amortized analysis, Solving recurrences

MODULE - III Greedy Algorithms: General characteristics of greedy algorithms, Graphs: Minimum spanning trees, Shortest paths, The knapsack problem, scheduling.

MODULE - IV Divide-and-conquer: Introduction: Multiplying large integers, The general template, Binary search, Sorting, Finding the median, Matrix Multiplication, Exponentiation.

MCA 3005

Fundamentals of Computer Algorithms

Credits: 3

L-T-P: (3-0-0)


Course Outcomes

1. Analyze different running times of algorithms using asymptotic analysis.

2. Knowledge of algorithm design strategies like divide and conquer approach, greedy and dynamic programming etc.

3. Apply important algorithmic design paradigms and methods of analysis to given problem.

4. Demonstrate a familiarity with major graphs algorithms and probabilistic algorithms.

5. Learn how to apply their theoretical knowledge in real life problems.


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MODULE - V Dynamic Programming: Calculation the binomial coefficient, The World Series, Making change, The principle of optimality, The knapsack problem, Shortest paths, Chained matrix multiplication

MODULE - VI Exploring Graphs : Graphs and games: An introduction, Traversing trees, Depth-first search: Undirected graphs, Depth-first search: directed graphs, Breadth-first search, Backtracking, Branch-and-bound, the minimax principle.

MODULE – VII Probabilistic Algorithms: Introduction, Probabilistic does not imply uncertain, Expected versus average time, Pseudorandom generation, Numerical probabilistic algorithms, Monte Carlo algorithms, Las Vegas algorithms

Text Books

1. G Brassard & P Bratley - Fundamentals of Algorithmics PHI, New Delhi, 2005. Reference Books:

1. E.Horowitz. et.al.- Fundamentals of Computer Algorithms, Galgotia Publication Pvt. Ltd., New Delhi, 2004.

2. J.Kleinberg & E. Tardos – Algorithm Design, Pearson Education, New Delhi, 2006 3. T.H. Cormen et.al. – Introduction to Algorithms – PHI, New Delhi, 2005 4. S. Dasgupta et.al. – Algorithm, TMH, New Delhi – 2007 5. S. Sahani – Data Structures, Algorithms and Applications in C++ 2nd Edition, Universities Press

(India) Pvt. Ltd., 2005


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MODULE – I & II Basic Mathematical Objects and Mathematical Induction: Sets, logic, Functions, Relations, Alphabets, Strings, Languages, Principle of mathematical induction, Recursive definition. Regular Expressions and Finite Automata: Regular languages and Regular Expressions, Memory required to recognize a language, Finite Automata, capability & limitations of FSM, Deterministic Finite Automata , Non-Deterministic Finite Automata, NFA with e-moves, regular sets & regular expressions, Equivalence of DFA and NDFA, NFA from regular expressions, regular expressions from DFA, Moore versus Mealy m/c, two way finite automata equivalence with one way , Kleen’s Theorem, applications of finite automata.

MODULE - III Regular and Non-regular languages: Criterion for Regularity, Minimal Finite Automata, Pumping Lemma for Regular Languages, Decision problems, Regular Languages and Computers.

MODULE - IV Context Free Grammars : Introduction, definition, Regular Grammar, Derivation trees, Ambiguity, Simplified forms and Normal Forms, Applications.

MCA 3007

Automata Theory

Credits: 4

L-T-P: (3-1-0)


Course Outcomes

1. Understand the basic concepts of various types of formal languages and their corresponding

grammars.

2. Differentiate the powers of various Automata types.

3. Design Automata for various formal languages.

4. Optimize a given automaton.

5. Implement the machines for real life situations.


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MODULE - V Pushdown Automata : Definition, Moves, Instantaneous Descriptions, Language recognised by PDA, Deterministic PDA, Acceptance by final state & empty stack, Equivalence of PDA , Pumping lemma for CFL, Interaction and Complements of CFL,Decision algorithms.

MODULE - VI Turing Machines: Definition and examples, Computing Partial Functions with Turing Machine(TM), Combining TMs, Variations of TMs, Multi-tape TMs, Non-deterministic TM, Universal TM, Church Thesis.

MODULE - VII Recursively Enumerable Languages: Recursively Enumerable and Recursive, Enumerating Language, Context Sensitive and Chomosky Hierarchy. Unsolvable Problems and Computable Functions: Nonrecursive Language and unsolvable Problems, Halting Problem, Rice Theorem, Post Correspondence Problem. Computational Complexity: Discussion on P, NP, NPC and NP-Hard Problems.

Text Books

1. John Martin -“Introduction to Languages and the Theory of Computation”, 3rd edition, TMH. Reference Books:

1. K.L.P Mishra & N. Chandrasekharan - Theory of Computer Science, PHI .

2. Hopcroft JE. And Ullman JD - Introduction to Automata Theory, Languages & Computation, Narosa.

3. Lewis H. R. and Papadimitrou C. H - Elements of the theory of Computation, PHI.


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Semester IV


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MODULE – I Introduction to Compiler: Compilers, Analysis of the source program, The phases of the compiler, Major data structures in a Compiler, Issues in a Compiler Structure, Bootstrapping and Porting .

MODULE - II Scanning : Scanning Process, Regular Expression(R.E.), Finite Automata(F.A.), R.E. to DFA , Implementation of Scanner, Use of Lex to generate a Scanner. Context Free Grammar and Parsing: Parsing Process, The role of a parser, Context Free Grammar, Parse trees and Abstract Syntax trees, Ambiguity, EBNF, Formal properties of Context Free Languages.

MODULE - III Top-down Parsing: Top down Parsing by Recursive Descent, LL(1), First and Follow sets, Recursive Descent Parser for a Tiny language, Error Recovery in Top-down Parser.

MODULE – IV & V Bottom-up Parsing : Overview of Bottom-up Parsing, LR(0) items and LR( 0 ) Parsing, SLR(1), General LR(1) and LALR(1) Parsing, YACC , Error Recovery in Bottom-up Parser. Semantic Analysis: Attributes and Attributes Grammars, Algorithms for Attribute Computation, Symbol Table, Data types and Data type Checking, Semantic Analyzer for Tiny language.

MCA 4001

Compiler Design

Credits: 4

L-T-P: (3-1-0)


Course Outcomes

1. Understand the need of compiler for interfacing between users and machine.

2. Perceive the role of several phases of compilation process.

3. Create an awareness of the function and complexity of modern compilers.

4. Trace the major concept areas of language translation and compiler design.

5. Develop a comprehensive Compiler for a given language and enhance knowledge for developing tool for natural language processing.


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MODULE - VI Run-time Environments : Memory organization during program execution, Fully static run-time environment, Stack-based run-time environments, Dynamic memory, Parameter passing mechanism, Run-time environment for Tiny language.

MODULE - VII Code Generation: Intermediate code and data structures for code generation, Basic code generation techniques, Code generation of Control statements and Logical expressions, Code generation of Procedure and Function calls, Code generation for a tiny language, A survey of code optimization techniques.

Text Books

1. Kenneth C. Louden -“Compiler Construction – Principle and Practice”, Thomson 2007.

Reference Books: 1. Aho, Sethi, Ullman -“Compiler Principles, Techniques and Tools”, Pearson Education, 2007.


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MODULE – I Data Communications and Networking Overview: A Communications Model, Data Communications, Data Communication Networking. Protocol Architecture: The Need for a Protocol Architecture, A Simple Protocol Architecture, OSI, The TCP/IP Protocol Architecture.

MODULE - II Data Transmission: Concepts and Terminology, Analog and Digital Data Transmission, Transmission Impairments, Channel Capacity. Guided and Wireless Transmission: Guided Transmission Media, Wireless Transmission, Wireless Propagation, Line-of-Sight Transmission.

MODULE - III Signal Encoding Techniques: Digital Data Digital Signals, Digital Data Analog Signals, Analog Data Digital Signals, Analog Data Analog Signals.

MODULE – IV Digital Data Communication Techniques: Asynchronous and Synchronous Transmission, Types of Errors, Error Detection, Error Correction, Line Configurations, Interfacing.

MCA 4003

Data Communication and Computer Networks

Credits: 3

L-T-P: (3-0-0)


Course Outcomes

1. Analyse and understand the components, characteristics and structure of the networks.

2. Interpret the characteristics of the theory of communication signals through different mediums.

3. Compare and identify different network protocols and able to apply in different applications.

4. Ability to devise innovative networking protocols using existing ideas.

5. Develop knowledge in contemporary problems and solve the related issues.


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MODULE - V Data Link Control: Flow Control, Error Control, High-Level Data Link Control (HDLC). Multiplexing: Frequency Division Multiplexing, Synchronous Time Division Multiplexing, Statistical Time Division Multiplexing.

MODULE - VI Circuit Switching and Packet Switching: Switching Networks, Circuit-Switching Networks, Circuit-Switching Concepts, Control Signaling, Softswitch Architecture, Packet-Switching Principles, X.25, Frame Relay.

MODULE – VII Asynchronous Transfer Model: Protocol Architecture, ATM Logical Connections, ATM Cells, Transmission of ATM Cells, ATM Service Categories, ATM Adaptation Layer. Routing in Switched Networks: Routing in Circuit-Switching Networks, Routing in Packet-Switching Networks, Least-Cost Algorithms

Text Books

1. W. Stallings - Data and Computer Communications, 7th Edn., Pearson Edn./ PHI, New Delhi, 2006

Reference Books:

1. B. A. Forouzan - Data Communications and Networking, 4th Edn. TMH, New Delhi 2006

2. P.C. Gupta – Data Communications and Computer Networks, PHI, New Delhi 2006


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MODULE – I Origin, People Interested in Accounts, Concepts & Conventions System of Accounting, Accounting Standards Book-Keeping, Double Entry, Classification of Business Accounts, “Golden Rules”, Journal, Subsidiary Books, Ledger Posting & Balancing, Concept of Trial Balance, Errors and Omission, Commission, Principle and Compensating, Final Accounts with Adjustments, Introduction to Financial Accounting, (Tally 7.2), Creating Company Master, Modification & Deletion.

MODULE - II Definition, Aims, Traditional vs. Innovative Management Accounting Practices, Development of Throughput Accounting, An Alternative view of Management Accounting, Lean Accounting(Accounting for Lean), Related Qualifications, Concept of Financial Budgeting, Fund Flow, Cash Flow Statement, C-V-P Analysis, MIS in Report Preparation, SFC and DFD, Working of FM Module of SAP Transaction.

MODULE - III Voucher Entry: Receipt Voucher, Payments Voucher, Contra Voucher, Journal Voucher, Physical Stock Voucher, Stores Ledger Book Keeping Through MM Module of SAP Transaction.

MODULE – IV Inventory Information: Stock Groups, Unit of Memo, Go Down Items, Warehousing, Displaying and Altering and Stock Keeping.

MODULE - V Invoice: Preparation of Invoice, Entry, Inco-Terms, Tax Implication, CENVAT and Concept of CVED, Printing & Display.

MCA 4007

Computerized Financial Accounting

Credits: 3

L-T-P: (3-0-0)


Course Outcomes

1. Gain knowledge of basic concepts of CFA practices in complex management decision making.

2. Students will be able to analyse financial position of any business entity through application of different tools like, financial ratio.

3. Students will be able to compare various financial ratios.


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MODULE - VI Report Generation: Balance Sheet, Profit and Loss Accounts, Stock Summary, Day Book, Accounts Books.

MODULE – VII Report Generation: Cash Book, Bank Book, Ledger, Outstanding Register.

Text Books

1. S.N. Maheshwari- Advance Accountancy, Vikas Publication

2. Amitabh Mukherjee & Md Hanif- Modern Accountancy, TMH Publication


[Type here] 49 2011

Semester V


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MODULE – I Introduction: Image Processing as Picture Analysis, The Advantages of Interactive Graphics, Representative Uses of Computer Graphics, Classification of Applications, Development of Hardware and Software for Computer Graphics, Conceptual Framework for Interactive Graphics. Basic Raster Graphics Algorithms for Drawing 2D Primitives: Overview, Scan Converting Lines, Scan Converting Circles, Scan Converting Ellipses, Filling Rectangles, Filling Polygons, Filling Ellipse Arcs, Pattern Filling, Thick Primitives, Line Style and Pen Style, Clipping in a Raster World, Clipping Lines, Clipping Circles and Ellipses, Clipping Polygons, Generating Characters, SRGP_copy Pixel, Antialising.

MODULE – II & III Graphics Hardware: Hardcopy Technologies, Display Technologies, Raster-Scan Display Systems, The Video Controller, Random-Scan Display Processor, Input Devices for Operator Interaction, Image Scanners. Geometrical Transformations: 2D Transformations, Homogeneous Coordinates and Matrix Representation of 2D Transformations, Composition of 2D Transformations, The Window-to-View port Transformation, Efficiency, Matrix Representation of 3D Transformations, Composition of 3D Transformations, Transformations as a Change in Coordinate System. Viewing in 3D: Projections, Specifying an Arbitrary 3D View, Examples of 3D Viewing, The Mathematics of Planar geometric Projections, Implementing Planar Geometric Projections, Coordinate Systems.

MCA 5001

Computer Graphics

Credits: 3

L-T-P: (3-0-0)


Course Outcomes

1. Understand the concept of image formation, digitization and the role human visual system plays in perception of image data.

2. Acquire an appreciation for spatial and frequency based techniques for enhancing the appearance of an image duly applying them in different applications.

3. Discern the difference between noise models, gain an insight into assessing the degradation function and realize different spatial and frequency based filtering techniques for reduction and removal of noise.

4. Synthesize a solution to image compression using the concept of information theory and lossless and lossy compression techniques.

5. Design and create practical solutions using morphological operators for common image processing problems and assess the results.


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MODULE - IV Input Devices, Interaction Techniques, and Interaction Tasks: Interaction Hardware, Basic Interaction Tasks, Composite Interaction Tasks. Representation Curves and Surfaces : Polygon Meshes, Parametric Cubic Curves, Parametric Bicubic Surfaces, Quadric Surfaces.

MODULE - V Achromatic and Colored Light: Achromatic Light, Chromatic Color, Color Models for Raster Graphics, Reproducing Color, Using Color in Computer Graphics. The Quest for Visual Realism: Why Realism?, Fundamental Difficulties, Rendering Techniques for Line Drawings, Rendering Techniques for Shaded Images, Improved Object Models, Dynamics, Stereosis, Improved Displays, Interacting with Our Other Senses, Aliasing and Antialiasing.

MODULE - VI Visible-Surface Determination: Functions of Two Variables, Techniques for Efficient Visible-Surface Algorithms, Algorithms for Visible-Line Determination, The z-Buffer Algorithms, List-Priority Algorithms, Area-Subdivision Algorithms, Algorithms for Octress, Algorithms for Curved Surfaces, Visible-Surface Ray Tracing. Illumination and Shading: Illumination Models, Shading Models for Polygons, Surface Detail, Shadows, Transparency, Interobject Reflections, Physically Based Illumination Models, Extended Light Sources, Spectral Sampling.

MODULE – VII Advanced Raster Graphics Architecture: Simple Raster-Display System, Display-Processor Systems, Standard Graphics Pipeline, Introduction to Multiprocessing, Pipeline Front-End Architectures, Parallel Front-End Architectures, Multiprocessor Rasterization Architectures. Advanced Geometric and Raster Algorithms: Clipping, Scan-Converting Primitives, Antialiasing, The Special Problems of Text, Filling Algorithms, Making copyPixel Fast, The Shape Data Structure and Shape Algebra.

Text Books

1. Foley, Van Dam, Feiner, Hughes- Computer Graphics Principles & Practice, 11th edn., Pearson Education, New Delhi, 2004. Reference Books: 1. D. Hearn & M.P.Baker- Computer Graphics, PHI, New Delhi, 2006


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MODULE – I & II Introduction to Discrete-Event System Simulation Introduction to Simulation: When Simulation is the Appropriate Tool, When Simulation is not Appropriate, Advantages and Disadvantages of Simulation, Areas of Application, Systems and System Environment, Components of a System, Discrete and Continuous Systems, Model of a System, Types of Models, Discrete-Event System Simulation. Simulation Examples: Simulation of Queuing Systems, Simulation of Inventory Systems, Other Examples of Simulation.

MODULE – III General Principles: Concepts in Discrete-Event Simulation, List Processing. Simulation Software: History of Simulation Software, Selection of Simulation Software, An Example of Simulation, Simulation in Java, Simulation in GPSS, Simulation in SSF, Simulation Software, Experimentation and Statistical-Analysis Tools.

MODULE - IV

Mathematical and Statistical Models Statistical Models in Simulation: Review of Terminology and Concepts, Useful Statistical Models, Discrete Distributions, Continuous Distributions, Poisson Process, Empirical Distributions.

MODULE - V Queuing Models: Characteristics of Queuing Systems, Queuing Notation, Long-Run Measures of Performance of Queuing Systems, Steady-State Behavior of Infinite-Population Markovian Models, Steady-State Behavior of Finite-Population Models(M/M/c/K/K), Networks of Queues.

MCA 5003

System Simulation and Modelling

Credits: 4

L-T-P: (3-1-0)


Course Outcomes

1. Define the basics of simulation modelling and replicating the practical examples of an organizations.

2. To familiarize the students the concepts in Discrete-event simulation and queuing theory.

3. To familiarize the simulation software and programming languages.

4. To familiarize the students role of random number generation and variates.

5. To Explain Verification and Validation of simulation model .


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MODULE - VI Random-Number Generation: Properties of Random Numbers, Generation of Psedo-Random Numbers, Techniques for Generating Random Numbers, Tests for Random Numbers. Random-Variate Generation: Inverse-Transform Technique, Acceptance-Rejection Technique, Special Properties.

MODULE – VII

Analysis of Simulation Data Input Modeling: Data Collection, Identifying the Distribution with Data, Parameter Estimation, Goodness-of-fit Tests, Fitting a Nonstationary Poisson Process, selecting Input Models without Data, Multivariate and Time-Series Input Models. Verification and Validation of Simulation Models: Model Building, Verification, and Validation, Verification of Simulation Models, Calibration and Validation of Models.

Text Books

1. J. Banks, J. S. Carson , B.L. Nelson, D.M. Nicol- Discrete-Event System Simulation, 4th Edn, Pearson

Education, 2007.

Reference Books:

1. A.M. Law & W.D. Kelton – Simulation Modeling and Analysis, 3rd Edn. TMH, 2003


[Type here] 54 2011

MODULE – I Operation Research – An overview, Organ and Development of OR, Nature and Features of OR, Modeling in OR, General Solution Methods for OR models, Scientific method in OR, Methodology of OR, Application, Opportunities and Shortcomings of OR.

MODULE – II Linear Programming Problem : Introduction, Mathematical Formulation of the Problem, Graphical Solution Method, Some Exceptional Cases, General LPP, Canonical and Standard forms of LPP, Simplex Method: Introduction, Fundamental properties of solutions, the Computational Procedure, Use of Artificial variables, Solution to simulation Linear Equations, Investing a Matrix using Simplex Method.

MODULE - III Duality in LPP: Introduction, General Primal – Dual pair, Formulating a Dual Problem, Primal Dual pair in Matrix form, Dhaliting theorems, Dual simplex method, Post optical Analysis, Introduction: Variation in cost vector, Requirement Vector, Coefficient Matrix, Structural Variation.

MODULE - IV Integer Programming and Advance LPP techniques: Introduction, Gomory’s Method, Courtruction of Gomory’s constraints, Fractional Cut Method: All Integer & Mixed Integer, Revised Simplex Method, Bounded Variable, Parametric LPP, Karmakar Algorithm.

MODULE - V Dynamic Programming & Introduction: Characteristic of Dynamic Programming, Dynamic Programming Algorithm, Solution of LPP by Dynamic Programming.

MCA 5005

Optimization Theory

Credits: 3

L-T-P: (3-0-0)


Course Outcomes

1. Prepare the operational models for the real-world Applications.

2. Apply the techniques to solve the linear and non-linear programming models.

3. Analyse the computational feasibility of the solutions using the available optimization algorithms.

4. Compare and evaluate the suitability of the available techniques for the problem at hand.

5. Develop the algorithms for optimization.


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MODULE – VI NLPP: Introduction, Formulality a NLPP, General NLPP, Constrained Optimization with Equality Constraints and Inequality constraints, Saddle Points.

MODULE – VII NLPP Methods: Introduction, Graphical solution, Kuhn – Tucker Conditions with Non Negative Constraints, Quadratic Programming, Wolfe’s Modified Simplex Method, Separable Convex Programming & Algorithm.

Text Books

1. Kanti Swarup, P.K. Gupta, Man Mohan – “Opeations Reaearch, Sultan Chand & Sons, New Delhi, 2001.

Reference Books:

1. Ronald L. Rardin “Optimization in Operations Research”, pearson Education, New Delhi – 2003. 2. S.S. Rao, “Optimization Theory & Application”, Wiley Eastern Ltd, 1979.


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Electives


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Group I

Data Base Technology


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MCA 7101 Distributed Databases [3 (3-0-0)]

Module – I

Introduction to Distributed Data Processing: Advantages of DDB’s, Problem areas.

Module – II

Distribute Database Management System Architecture: DBMS Standardization, Architectural models for

DDBMS Distribute DBMS Architecture.

Module – III

Distributed Database Design: Design Strategies, Distribution design issues, Fragmentation, Allocation.

Module – IV

Semantic Data Control : view management, data security, Integrity control.

Module – V

Query processing and Optimization: Quarry Processing Problem, Characterization of Query Processors,

Layers of query Processing, Query decomposition, Query Optimization, Centralized query optimization,

Join ordering in fragment queries, Distributed Query Optimization Algorithms.

Module – VI

Transaction Management and Concurrency Control: Introduction, Properties, Serializability Theory,

Locking Based Concurrency control Algorithm Time Stamp based concurrency control Algorithms, Dead

Lock management.

Module – VII

Recovery and Reliability: Failures and fault tolerance in distributed system, Distributed & local reliability

protocol, Sits failures, network partitioning.

Text Book:

Course Outcomes

1. Understand the fundamental principles and architecture of distributed database systems.

2. Familiar with the different methods and techniques distributed query processing.

3. Develop the understanding of choosing the optimized query execution plan for distributed queries.

4. Have a broad picture of distributed transaction management and concurrency Control and distributed DBMS reliability and replication techniques.


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M. Tamer Ozsee, Patric Valduriez - Principle of Distributed Database Systems 2nd Edn., Pearson Education

Asia, 2001.


[Type here] 60 2011

MCA 7103 Decision Support System [3 (3-0-0)]

Module – I

Decision Making Process: An Over view, Introduction, Managerial decision making and Information

System, Need for computerized decision support and the supporting technologies, Framework of DSS,

Group Support System, Executive information system, Knowledge management Systems.

Module – II

Decision Making, System, Models : Decision Making – Introduction and Definition, System, Models,

previews of modeling process, Decision making – The intelligence phase, the design phase and the choice

phase.

Evaluation – Multiple Goals, sensitivity analysis, What – if and goal seeking.

Decision Making - The implementation phase, Alternative decision making models.

Module – III

DSS – Configurations, Definitions, Characteristics & Capabilities, Components, The Data management

Subsystem, Model Management Subsystem, Knowledge – based management, Subsystem, User interface

Subsystem, DSS Classification, DSS H/W, Difference between Management Science and MIS.

Module – IV

Modeling & Analysis - Modeling for MSS, Static & Dynamic Models, Treating Certainty, Uncertainty and

Risk, Interface diags, MSS modeling in spreadsheets, Decision analysis (Decision tables and Decision trees),

Optimization via mathematied programming, Meusistic Programming, Multidimensional Modeling –

OLAP.

Module – V

DSS Development – Introduction, The Traditional System Development life cycle, Alternate Development

Methodologies, Prototyping, DSS Technology Levels and Tools, DSS Development Platforms, DSS

Development Tool Selection, Team Developed DSS, End – User Developed DSS, DSS System Integration.

Course Outcomes

1. understand the usefulness of decision support systems arising in the practice of industrial and systems engineering

2. become expert users of spreadsheets and to learn how to take advantage of a large array of tools available in spreadsheet programs

3. learn how to accomplish tasks programmatically in a spreadsheet and how to design user friendly graphical user interfaces

4. understand the issues that arise in the conceptual development and implementation of effective and user-friendly decision support systems

5. design, develop, and implement integrated decision support systems for industrial and

systems engineering applications.


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Module – VI

Collaboration Communication, Enterprise DSS Group Decision Making – Communication & Collaboration,

Communication Support, Collaboration Support – Computer Supported Co-operative work, Group

Support System, GSS Technologies.

Module – VII

Enterprise DSS – Information need concepts & definitions, Evaluation of EIS, Comparing and Integrating

EIS and DSS, Data Access, Data Collection, Problem & Quality, DBMS in DSS, Data Warehousing, Data

Query, OLAP Multidimensional Analysis and Presentation, Data Visualization and Multidimensionality,

Organizational DSS.

Text Book:

1. E. Turloan & E. Aronson- Decision Support System & Intelligent System, 6th Edn., Pearson Education.

Reference Book:

1. G.M. Marakas- Decision Support Systems, 2nd Edn., Pearson /Prentice Hall of India.


[Type here] 62 2011

MCA 7105 Enterprise Resource Planning [3 (3-0-0)]

Module-I

Introduction to ERP : Evolution of ERP, What is ERP, Reasons for the growth of the ERP market,

Advantages of ERP, Reasons of Failure.

Module-II&III

Enterprise- An Oberview : Integrated Management information, Business Modeling, Integrated Data

Model. ERP and Related Technologies : BRP (Business Process Reengineering), MIS (Management

Information System), DSS (Decision Support System), EIS (Executive Information system), OLAP, Supply

Chain Management.

Module-IV

A Manufacturing Perspective : ERP, CAD/CAM, MRP (Material Requirement Planning), Bill of Material,

Closed loop MRP, MRP-II, DRP (Distributed Requirement Planning), Product Data Management, Data

Management,

Module-V

Benefits of PDM : ERP Modules, Finance, Plant Maintenance, Quality Management, Material

Management. Benefits of ERP :

Module-VI

ERP Market : SAP, BAAN, Oracle Corporation, People Soft. ERP Implementation Life Cycle .

Course Outcomes

1. Demonstrate a good understanding of basic issues in Enterprise Systems, 2. Explain the scope of common Enterprise Systems (e.g., MM, SCM, CRM, HRM,

procurement), 3. Explain the challenges associated with implementing enterprise systems and their impacts

on organisations. 4. Describe the selection, acquisition and implementation of enterprise systems. 5. Assess an organisation's readiness for enterprise system implementation.

1.


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Module-VII

Vendors, Consultants & Users’s : In – house Implementation – pros & cons, Vendors, Consultants, End-

users. Future Directions in ERP. ERP Case Studies.

Text Book :

1. Enterprise Resource Planning by Alexis Leon TMH Fourth Reprint 2001.


[Type here] 64 2011

MCA 7107 Data Mining and Warehousing [3 (3-0-0)]

Module – I

Introduction: Introduction, Data Mining as subject, What motivated Data mining, Why is its importance?

Data warehousing: Introduction, What is a Data Warehousing Definition, Multidimensional Data Model,

OLAP Operation, warehouse Scheme, Data Warehousing, Architecture, Metadata, OLAP ENGINE, Data

warehouse Backend Process.

Module – II

Data Mining: Introduction, What is Data Mining, Data Mining Definition, KDD Vs, Data Mining, DBMS Vs.

DM, Other related area, DM Technique, Other Mining Problem, Issue and challenge is in DM, DM

Application area, DM Application, Case Sturdy.

Module – III

Mining Association Rule in Large Database: Introduction, what is an Association Rule, Method to

discover association Rule, A Priori Algorithm, Partition Algorithm, Pincer- Search algorithm, Dynamic

item set Counting Algorithm, FP – Tree Growth Algorithm, Discussion and Different Algorithm,

Generalized, Association Rule, Association Rules with Item Constraints.

Module – IV

Clustering Techniques: Introduction, Clustering Paradigm, Partition Algorithm, K- Medoid Algorithm,

CLARA, CLARANS, Hierarchical Clustering, DBSCAN, BIRCH, CURE, Categorical Clustering Algorithms, STIRR,

ROCK, CACTUS.

Course Outcomes

1. Summarize and understand basic principle, concepts and applications of data mining and data ware housing.

2. Assess the problem and justify what data mining activities are required to obtain the desired objectives.

3. Compare and contrast between the specific operations, data structures and schema that are used in data warehouses vis a vis databases.

4. Infer, analyse and evaluate algorithms for performing common data mining activities like Association rule mining, Classification, Clustering etc.

5. Demonstrate the data mining techniques in various field of real life problems like medical science, weather analysis, soil type prediction, financial analysis etc.


[Type here] 65 2011

Module – V

Data Mining Primitives, Language and System Architecture: Data Mining Primitives, what defines a Data Mining task, Task relevant Data, The Kind of Knowledge to Mined, Concept Hierarches, Interestingness Measures, presentation and visualization of Discovered Patterns, Data Mining Query Language.

Module – VI

Decision Trees: Introductions, What is decision Tree, Tree Construction Principle, Best split splitting

Indices, Splitting criteria, Decision Tree Construction with Presenting, Pruning Technique, Integration of

Pruning Technique and Construction.

Module – VII

Temporal and Spatial Data Mining: Introduction, What is Temporal Data Mining temporal Association

Rules, Sequence Mining, The GSP Algorithm, SPIRIT, Spatial Mining, Spatial Clustering, Spatial Trends.

Text Book:

1. A.K. Pujari, “A Data Mining Technique”, University press (India) Limited, 2001

Reference Books:

1. A Han and M. Kamber, “Data Mining Concept and Technique”, Morgan. Kauffmann Publishers, Else river India, New Delhi, 2003.

2. Recherd J, Roiger and Michance W. Creatz, Data Mining: a tutorial Based Primer, Addision Wesley, 2003. 3. M.H. Dunham, Data Mining : Introductory and Advanced Topics, Printice Hall 2003.


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MCA 7109 Multimedia Databases [3 (3-0-0)]

Module I

Introduction ,Multimedia Information Applications , Issues and Challenges .

Module II

Semantic Models for Multimedia Information Systems, Multimedia Semantic Models.

Module III & IV

Multimedia database Searching, Image Segmentation ,Video Parsing and Segmentation Approaches

,Iconic-Based Grouping and Browsing Approaches , Knowledge-Based Event Modeling Approaches ,

Characteristics of Video Data Modeling , Motion Detection and Tracking Approaches ,Object Recognition

Approaches ,Content-Based Retrieval

Module V

Multimedia Browsing, Video Browsing, Key Frame Selections.

Module VI

Augmented Transition Network Model (ATN), Spatial and Temporal Relations of Semantic Objects,

Multimedia Presentations, Multimedia Database Searching, Multimedia Browsing, User Interactions and

Loops.

Module VII

Object Composition Petri Net Model, Interval Based Conceptual Models

Text Book:

1. Chen S C, Kashyap R L, Ghafoor A; Semantic Models for Multimedia Database Searching and

Browsing, Kluwer Academic Publishers,

Course Objectives

1. understand the place of the multimedia database systems among database systems 2. understand what the central issues in multimedia data and multimedia database management

3. understand the central architectural concepts related with multimedia database management systems

4. model multimedia data and create multimedia database schemas - can store and retrieve data from

multimedia databases

5. develop simple multimedia applications that offer multimedia data (video clips, images, voice) to

web browsers from a multimedia database management system


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Reference Book:

1. Muneesawang P ,Guan L-Multimedia Database Retrieval A Human-Centered Approach, Springer

Publication, 2006


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Group II Software Technology


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MCA 7201 Advance Java Programming [3 (3-0-0)]

Module-I &II

Components and Facilities or Rich Graphical User Interfaces: Programming with the JFC, Swing API

Components, J component Class, Windows, Dialog Boxes, and Panels, Labels, Buttons, and Check Boxes,

Menus, Toolbars, and Actions, Sliders, Spinners, Progress Bars, and Scrollbars, Lists and Combo Boxes,

Text-Entry Components, Color and File Choosers, Tables and Trees, Printing with the 2D API, Java Print

Service API.

Module-III

Using Relational Database: Introduction, Best Practices for Programming for Databases, JDBC Drivers for

RDBM Systems, SQL to Java Type Mappings, Understanding the Database used in this chapter, Using the

java.sql API, Coding Transactions, Using the javax.sql API, Connection Pooling.

Module-IV

XML: Introduction, XML Structure, XML Example Document with SAX, Parsing an XML Document with

DOM, Generating an XML Document with DOM, Validating XML Documents using DTD and XML Schema,

Transforming XML using XSLT.

Module-V

Network Programming: Introduction, Working with URLs, Working with Sockets, Remote Method

Invocation.

Module-VI

Building Web Applications: Introduction, The Technology of the Web, J2EE Web Application Packaging,

Servlets, The Servlet API, The User Experience, Building a Web App with Continuity, Java Server Pages, JSP

Tags and API, How the Server Processes JSPs, Java Coding in JSPs, Frameworks for Building Web

Applications, Building Robust Web Apps.

Module-VII

Course Outcomes

1. Learn the architecture of advanced swing components and design GUIs using them.

2. Learn to interface with external data sources with Java.

3. Leverage Java to create and deploy network programs.

4. Use Java to design enterprise level Web sites.

5. Understand Java’s component based programming model.


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Enterprise JavaBeans: Introduction, Enterprise Programming, What are EJBs? Session EJBs, EJB Clients,

Entity EJBs, Message-Driven Beans, EJB Transactional Characteristics, EJB Security, Best Practices for

Designing EJB-Based Applications.

Text Book:

1. Wigglesworth & McMillan – JavaTM Programming Advanced Topics, 3rd Edn., India Edition, Thomson Education, New Delhi, 2007


[Type here] 71 2011

MCA 7203 Systems Programming [3 (3-0-0)]

Module – I

Introduction: System Soft wares & its Components, Evolution of System Soft wares- Operating System,

Loaders, Interpreters, Compilers, Linkers, Assemblers.

Module-II

Assemblers: Elements of Assembly Language Programming, Assembly Process, Single Pass Assembler,

Design of a 2-Pass assembler for In 8088.

Module –III

Macros & Macro processors: Macros, Different forms of Macros, Macros using AIF, AGO, REPT. etc, Design

of a Macro Processor, Macro Assembler.

Module-IV

Loaders: Basic Loader Functions, Absolute Loader, Compile & go Loader, Relocating Loader, Direct Linking

Loader.

Module – V

Linkage Editors: Linking and Relocation, Program Relocability, Linkage Editor and its Application in IBP-PC,

Linking for Program Overlays.

Module-VI & VII

Software Tools: Spectrum of Software Tools, Text Editors, Interpreter and Program Generators, Debug

Monitors, Programming Environments.

Text Book:

1. D.M. Dhamdhere-System Programming and Operating Systems, 2en Edn., TMH, New Delhi.

Reference Book:

1. J.J. Donovon- System Programming, TMH, New Delhi.

Course Outcomes

1. Support, dependency and limitations of system software on available system architecture. 2. Understand O/s support for system software and system calls. 3. Clarity about the concrete view on the theoretical and practical aspects of designing system

software. 4. Understand the working of various system software such as assemblers, linkers, loaders and

macro-processors. 5. Ability to design and develop system software (complete life cycle).


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MCA 7205 Programming Language Design and Concepts [3 (3-0-0)]

Module - I

Introduction: The Role of Programming Languages: Toward Higher-Level Languages, Programming

Paradigms, Languages Implementation: Bridging the Gap.Language Description: Syntactic Structure:

Expression Notations, Abstract Syntax Trees, Lexical Syntax, Context- Free Grammars, Grammars for

Expressions.

Module - II & III

Imperative Programming: Statements: Structured Programming: The Need for Structured Programming, Syntax-Directed Control Flow, Design Considerations: Syntax, Handling Special Cases in Loops, Programming with Invariants, Proof Rules for Partial Correctness, Control Flow in C.Types: Data Representation: The Role of Types, Basic Types, Arrays: Sequences of Elements, Records: Named Fields, Unions and Variant Records, Sets, Pointers: Efficiency and Dynamic Allocation, Two String Tables, Types and Error Checking. Procedure Activations: Introduction to Procedures, Parameter- Passing Methods, Scope Rules for Names, Nested Scopes in the Source Text, Activation Records, Lexical Scope: Procedures as in C.

Module – IV & V

Object-Oriented Programming: Grouping of Data and Operations: Constructs for Program Structuring,

Information Hiding, Program Design with Modules, Modules and Defined Types, Class Declarations in C++,

Dynamic Allocation in C++, Templates: Parameterized Types, Implementation of Objects in C++.

Object-Oriented Programming: What is an Object?, Object-Oriented Thinking, Inheritance, Object-

Oriented Programming in C++, Derived Classes and Information Hiding, Objects in Smalltalk, Smalltalk

Objects have a Self.

Module-VI & VII

Functional Programming: Elements of Functional Programming: A Little Language of Expressions, Types:

Values and Operations, Approaches to Expression Evaluation, Lexical Scope, Type Checking.

Course Outcomes

1. Students will get familiar with various programming paradigms.

2. They will know the fundamental features of each of the programming paradigms- (Imperative, Object Oriented and Functional).

3. They will understand the differences in the approaches in the different programming paradigms.

4. They will be able to analyze the suitability of a particular programming paradigm for a given problem.

5. The programming skills of students will improve.


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Functional Programming in a Typed Language: Exploring a List, Function Declaration by Cases, Functions

as First-Class Values, ML: Implicit Types, Data Types, Exception handling in ML.

Functional Programming with Lists: Scheme, Dialect of Lisp, The Structure of Lists, List Manipulation, A

Motivating Example: Differentiation, Simplification of Expressions.

Text Book:

1. R.Sethi & K.V. Viswanathan- Programming Languages Concepts & Constructs, 2nd Edn., Pearson

Education, 2007.


[Type here] 74 2011

MCA 7207 Assembly Language Programming [3 (3-0-0)]

Module – I

Introduction to PC H/W and S/W: The Processor, Internal Memory, Segments & Addressing, Registers,

Operating System Characteristics, The Boot Process, DOS-BIOS Interface, System Programming Loader,

The Stack, Program Addressing, Memory of Register References.

Module – II

Execution of Instructions: The Debug Program, Viewing Memory Locations, Entering a symbolic Assembly

Program, Using the INT instruction, Saving a Program from within DEBUG, The PTR Operator.

Module – III

Fundamentals of Assembly Language: (a) Requirements: Assembler & Compilers, Assembly language,

Comments, Reserved words, Identifiers, Statements, Direction, Initializing a Program for Execution,

Initializing for Protecting Mode, Simplified Segment Directives, Data Definition, Directive for Defining

Data, The EQU Directive. Assembling, Linking, and Executing a Program, Processor Instruction &

Addressing, Writing Com Programs, Program Logic & Control.

Module – IV

Screen & Keyboard Operation : Selecting the Cursor, Clearing the screen, DOS Function 02H, 09H, 0AH,

Use of Control Characters for Displaying, File Handling, File Handles for keyboard Input, Advance Setting

video Mode, Text Mode, Screen Pages, BIOS Interrupt 10H for Text Mode, Blinking, Reverse video &

Scrolling, BIOS Interrupt 10H for Graphics, Setting & Displaying Graphics Mode.

Advance Keyboard Processing: DOS Interrupt 21H, 16H, 09H, Keyboard Buffer, Extended Function Keys &

Scan codes, Selecting from Menu.

Module – V

Data Manipulation: Repeat String Prefix, Move String, Load String, Store String, Transferring Data,

Compare String, Scan String, Scan & Replace, Duplicating a pattern, Right Adjusting on the screen.

Processing Binary Data: Addition & Subtraction, Multiword Arithmetic, Unsigned & Signal Data,

Multiplication with Stiffing, Division & Division with Stipling, Reversing the Sign, Numeric Data Processing.

Course Outcomes 1. Edit, compile, execute, and debug an assembler program. 2. Use a subroutine library within an assembler program. 3. Manipulate standard data types and other forms of data within an assembler

program. 4. Implement conditional and looping structures within an assembler program. 5. Create and use assembly subroutines and macros.


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Module – VI

Input / Output: Disk Storage Organization, Disk Processing (Writing & Reading files), DOS operations for Supporting Disk & files, BIOS Disk operations, Printing.

Module – VII

Advance Programming: Writing Macros, Linking to Subprograms, DOS Memory Management.

Text Book:

1. Pelter Abel, “IBM PC Assembly Language & Programming”, 4th Edn, PHI.

Reference Book :

1. Brey & Borry, Intel Microprocessor 8080,86,186,286, 386,486, Pentium,5th Edn., PHI.


[Type here] 76 2011

MCA 7209 Web Programming [3 (3-0-0)]

Module - I

XML: Part I: Creating Basic XML Document, Parsing an XML Document, Writing Well -Formed Documents,

Working with Special characters.

XML: Part II : Organizing Elements with Namespaces, Defining elements with DTDs, Validating XML

Documents Against DTDs, Declaring Elements in a DTD, Declaring Attributes in a DTD.

Module - II

Visual Basic .NET: Part I: Understanding the Basic of Visual Studio .NET, Using the Visual Studio .NET

Integrated Developer Interface (IDE), Creating the User Interface for a Solution, Using VB .NET Controls,

Examining the Structure of a VB .NET Module, Understanding VB .NET Data Types and Variables,

Introduction to Event Handlers, Writing Decision-Making Statements, Using Repetition Statements.

Module-III

Visual Basic .NET: Part II: Getting Started, An Overview of ADO .NET, Creating the Data Adapter, Storing

Data in Data Set and Data Table Objects, Binding Controls to a Data Set, Navigating Through the Records

in a Database Table, Modifying a Database Record.

Module - IV

ASP .NET: Part I: Building Web Forms Using ASP .NET, Exploring ASP .NET Server Controls, Using ASP .NET

Server Controls to Create Web Forms, Understanding the Code Behind the Page.

ASP .Net Part II: Working With User Controls, Exposing User Control Properties and Methods, Using ASP

.NET Server Controls in User Controls, Using Validation Controls to Improve Web Forms, Uploading Files

to a Web Server.

Course Outcomes

1. . To identify the basic architectures found in web sites with brief introduction to n-tier architectures.

2. To categorize the available programming language choices from the established stables like .NET, PHP, Java etc .and their relative strengths and weaknesses. Students are also introduced to data access techniques and optimizations.

3. To use web programming skills like handling of cookies, sessions, state management, style sheets, themes etc.

4. To develop user friendly, highly accessible, easy to navigate web sites .

5. Analysing and criticizing the web server architectures and features available to configure web servers for optimal performance under high load.


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Module - V

CGI/Perl: Part I: Writing Your First CGI Script in Perl, Testing a Perl CGI Script, Debugging a Perl CGI Script,

Creating a Link to a CGI Script, Using a Link to Send One Item of Data to a CGI Script, Parsing the Data Sent

to a Perl CGI Script, Using a Link to Send Multiple Items of Data to a CGI Script.

Module - VI

CGI/Perl: Part II: Using a CGI Script to Process From Data, Planning a CGI Script, Declaring Scalar Variables

in Perl, Using Assignment Statements to Assign Values to Variables, Using Arithmetic Operators in Perl,

Accessing the Values Received from an Online Form, Including a Dollar sign in a Number, Using the printf

function.

Module - VII

PHP: Part I: Preparing the Use PHP, Exploring PHP for the First Time, Understanding PHP Basics, Displaying

PHP Output, Managing PHP Program Flow.

PHP: Part II: Examining the Relationship Between PHP and MySQL, Planning a PHP Web Application,

Creating and Using a Logon Window, Managing System Data, Updating a PHP Web Application.

Text Book:

1. Xue Bai, Michael Ekedahl, Joyce Farrell, DonGosselin, Diane Zak, Shashi Kaparthi, Peter Maclntyre, Bill Morrissey - The Web Warrior Guide to Web Programming, India Edition,Thomson Education


[Type here] 78 2011

MCA 7211 Software Project Management [3 (3-0-0)]

Module – I

Managing Software Project: Process & Project Management, Project Management and the CMM, Project

Management at Infosys, Introduction to CMMI, PCMM.

The Project Planning Infrastructure: The process data base, The process capability Baseline, Process

Assets and the Body of Knowledge System.

Module – II

Process Planning: The Infosys Development Process, Requirement Change Management

Effort Estimation & Scheduling: Estimation and Scheduling Concepts, Effort – Estimation, Scheduling.

Module – III

Quality Planning: Quality Concepts, Quantitative quality Management Planning, Defect Prevention

Planning.

Risk Management: Concepts of Risks and Risk Management, Risk Assessment, Risk Control, Examples.

Module – IV

Measurement and Tracking Planning: Concepts in measurement, Measurements, Project tracking.

Project Management Plan: Team Management, Customer Communication and Issue Resolution,

Structure of the Project Management Plan.

Module – V

Configuration Plan: Concepts in Configuration Management, Configuration Management Process.

Reviews: The Reviews, Review process Data Collection, Monitoring & Control, Introduction of Reviews &

the NAH Syndrome.

Module – VI

Project Monitoring & Control: Project tracing, Milestone Analysis, Activity Level Analysis using SPC, Defect

Analysis & Prevention Process Monitoring & audit.

Course Outcomes

1. student will have good knowledge of the issues and challenges faced while doing the Software Project Management

2. student will also be able to understand why majority of the software projects fails and how that failure probability can be reduced effectively.

3. Student will be able to do Project Scheduling and tracking 4. Students will understand Risk analysis models 5. Know about Quality management and Project Cost estimation using different techniques


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Module – VII

Project Closure: Project closure Analysis.

Text Book:

1. Pankaj Jalote – Software Project Management in Practice, Pearson Education, New Delhi, 2002.

Reference Books:

1. B.Huges and M.Cotterell – Software Project Management, 3/e, Tata Mcgraw Hill, New Delhi, 2004. 2. Pankaj Jalote – CMM in Practice, Pearson Education, New Delhi, 2002 3. W. Humph Grey – Managing the Software Process, Addition – Wesley, 1989.


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Group III

Cognitive Sciences

and

Intelligent Systems


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MCA 7301 Natural Language Processing [3 (3-0-0)]

Module-I & II

Introduction to NLP : Definition, issues and strategies, application domain, tools for NLP, Linguistic

organization of NLP, NLP vs PLP. Word Classes Review of Regular Expressions, CFG and different parsing

techniques. Morphology: Inflectional, derivational, parsing and parsing with FST, Combinational Rules.

Phonology: Speech sounds, phonetic transcription, phoneme and phonological rules, optimality theory,

machine learning of phonological rules, phonological aspects of prosody and speech synthesis.

Module-III & IV

Pronunciation, Spelling and N-grams: Spelling errors, detection and elimination using probabilistic

models, pronunciation variation (lexical, allophonic, dialect), decision tree model, counting words in

Corpora, simple N-grams, smoothing (Add One, Written-Bell, Good-Turing), N-grams for spelling and

pronunciation.

Syntax : POS Tagging: Tagsets, concept of HMM tagger, rule based and stochastic POST, algorithm for

HMM tagging, transformation based tagging

Module-V

Sentence level construction & unification: Noun phrase, co-ordination, sub-categorization, concept of

feature structure and unification. Semantics: Representing Meaning: Unambiguous representation,

canonical form, expressiveness, meaning structure of language, basics of FOPC. Semantic Analysis: Syntax

driven, attachment & integration, robustness.

Module-VI

Lexical Semantics: Lexemes (homonymy, polysemy, synonymy, hyponymy), WordNet, internal structure

of words, metaphor and metonymy and their computational approaches. Word Sense Disambiguation:

Selectional restriction based, machine learning based and dictionary based approaches.

Course Outcomes

1. Define various levels of processing of natural language text and identify the tasks required to perform on a given a NLP problem.

2. Illustrate the methodology for various character and word level NLP tasks.

3. Explain the techniques applied to develop various sentence level and semantic NLP tasks.

4. Analyze the accuracy of a NLP system or technique.

5. Develop a system to solve a given NLP problem.


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Module-VII

Pragmatics: Discourse: Reference resolution and phenomena, syntactic and semantic constraints on Co-

reference, pronoun resolution algorithm, text coherence, discourse structure. Dialogues: Turns and

utterances, grounding, dialogue acts and structures. Natural Language Generation: Introduction to

language generation, architecture, discourse planning (text schemata, rhetorical relations).

Text Book:

1. D. Jurafsky & J. H. Martin – “Speech and Language Processing – An introduction to Language processing, Computational Linguistics, and Speech Recognition”, Pearson Education

Reference Books:

1. Allen, James – “Natural Language Understanding”. Benjamin/Cummings, 2nd Edn.,1995

2. Bharathi, A., Vineet Chaitanya and Rajeev Sangal., Natural Language Processing- “A

Pananian Perspective”, Eastern Economy Edition,PHI, 1995

3. Eugene Cherniak: “Statistical Language Learning”, MIT Press, 1993.

4. Manning, Christopher and Heinrich Schutze, “Foundations of Statistical Natural Language

Processing”. MIT Press, 1995


[Type here] 83 2011

MCA 7303 Genetic Algorithm and Swarm Intelligence [3 (3-0-0)]

Module – I

Introduction: Biological Background, Conventional Genetic Algorithms, Theory and Hypothesis,

Modifications to Genetic Algorithms, Chromosome representation, Objective and Fitness Function,

Selection method, Genetic Operators, Replacement Schemes, A Game of Genetic creative (Example).

Module – II

Intrinsic Characteristics : Parallel Genetic Algorithm, Multiple Objective, Robustness, Multimodel,

Constraints Hierarchical Genetic Algorithm, Biological Inspiration, Hierarchical Chromosome Formulation,

Genetic operations, Multiple Objective Approach.

Module – III

Application of Genetic Algorithms: Genetic Algorithm in speech Recognition Systems, Genetic Algorithm

in Communication Systems.

SWARM INTELIGENCE

Module – IV

Introduction: social insets, modeling collective behavior in social inset – modeling and designing, self-

organization in social insets, stinger, Modeling as an interface from Algorithms to Robotics.

Module – V

Ant Foraging Behavior Combinational Optimization and Routing in Communication Networks:

Overview, Foraging Strategies in ANTS, Natural Optimization, Rapid patterns of Array Ants, Ant colony

optimization, The traveling salesman problem, Ant system, Ant colony system, The Quadratic assignment

problem.

Module – VI

Division of Labor and Task Allocation: Overview, Division of Labor in social insects, Response threshold,

introduction, model with one task, Formal analysis of the model, Deterministic equations, Model with

several tasks adoption task allocation.

Course Outcomes

1. Understand the types of problems to which heuristic algorithms are most suitable for. 2. Understand the basic operators used in GA, their relevance and their variants. 3. Design fitness functions and chromosome structures for solving real life problems using

GA. 4. Know about the various swarm prototypes used for solving practical problems. 5. Understand how to handle constraints in heuristic programming.


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Module – VII

Self Organization and Templates: Overview, the interplay of self organization and templates, A Reaction

Diffusion model of the construction of the Royal Chamber, Wall building in Laptotheras albepennis,

Applications, Data Analysis, Graph Partitioning, Nest Building in social insects, Strigmerry and Self

organization, Discrete stignersy.

Text Books:

1. Eric Bonabeau, Marco Dorigo, Guy Theraulaz – “Swarm Intelligence From Natural to Artificial Systems”, Oxford University Press, 1999.

2. K.F. Man, K.S. Tang, S. Kwong – “Genetic Algorithms : Concepts and Designs, Spinger – verlag, 1999.

Reference Book:

1. David E. Goldberg – “Genetic Algorithms in Search, Optimization and Machine Designing,PearsonEducation,1989.


[Type here] 85 2011

MCA 7305 Artificial Intelligence [3 (3-0-0)]

Module-I & II

Introduction: Overview Of Artificial Intelligence- Problems Of AI, AI Technique, Tic - Tac - Toe Problem.

Intelligent Agents: Agents & Environment, Nature Of Environment, Structure Of Agents, Goal Based

Agents, Utility Based Agents, Learning Agents.

Problem Solving : Problems, Problem Space & Search: Defining The Problem As State Space Search,

Production System, Problem Characteristics, Issues In The Design Of Search Programs.

Module-III

Search Techniques: Solving Problems By Searching, Problem Solving Agents, Searching For Solutions;

Uniform Search Strategies: Breadth First Search, Depth First Search, Depth Limited Search, Bi-directional

Search, Comparing Uniform Search Strategies.

Search Techniques : Solving Problems By Searching :Problem Solving Agents, Searching For Solutions;

Uniform Search Strategies: Breadth First Search, Depth First Search, Depth Limited Search, Bi-directional

Search, Comparing Uniform Search Strategies.

Heuristic Search Strategies: Greedy Best-First Search, A* Search, Memory Bounded Heuristic Search:

Local Search Algorithms & Optimization Problems: Hill Climbing Search, Simulated Annealing Search, Local

Beam Search, Genetic Algorithms; Constraint Satisfaction Problems, Local Search For Constraint

Satisfaction Problems.

Module-IV

Adversarial Search : Games, Optimal Decisions & Strategies In Games, The Minimax Search Procedure,

Alpha-Beta Pruning, Additional Refinements, Iterative Deepening.

Course Outcomes

1. Recall the principles and approaches of artificial intelligence.

2. Understand different aspects of Intelligent agent.

3. Apply different search techniques for solving real world problems and select the most appropriate

solution by comparative evaluation.

4. Understanding the various concepts of knowledge representations and demonstrate working

knowledge of reasoning in the presence of incomplete and/or uncertain information.

5. To develop a basic understanding of some of the more advanced topics of AI such as learning,

natural language processing, expert systems, and planning.


[Type here] 86 2011

Knowledge & Reasoning : Knowledge Representation Issues, Representation & Mapping, Approaches To

Knowledge Representation, Issues In Knowledge Representation.

Module-V

Using Predicate Logic : Representing Simple Fact In Logic, Representing Instant & ISA Relationship,

Computable Functions & Predicates, Resolution, Natural Deduction.

Representing Knowledge Using Rules : Procedural Verses Declarative Knowledge, Logic Programming,

Forward Verses Backward Reasoning, Matching, Control Knowledge.

Module-VI

Probabilistic Reasoning: Representing Knowledge In An Uncertain Domain, The Semantics Of Bayesian

Networks, Dempster-Shafer Theory, Fuzzy Sets & Fuzzy Logics.

Planning : Overview, Components Of A Planning System, Goal Stack Planning, Hierarchical Planning, Other

Planning Techniques.

Natural Language Processing : Introduction, Syntactic Processing, Semantic Analysis, Discourse &

Pragmatic Processing.

Module-VII

Learning : Forms Of Learning, Inductive Learning, Learning Decision Trees, Explanation Based Learning,

Learning Using Relevance Information, Neural Net Learning & Genetic Learning.

Expert Systems : Representing And Using Domain Knowledge, Expert System Shells, Knowledge

Acquisition.

Text Book:

1. Ritch & Knight -Artificial Intelligence, TMH

Reference Books:

1. S. Russel and P. Norvig- Artificial Intelligence A Modern Approach, Pearson Education.

2. Patterson -Introduction to Artificial Intelligence & Expert Systems, PHI


[Type here] 87 2011

MCA 7307 Image Processing [3 (3-0-0)]

Module – I

What Is Digital Image Processing , Fundamental Steps in Digital Image Processing ,Components of an

Image Processing System , Elements of Visual Perception , Light and the Electromagnetic Spectrum ,

Image Sensing and Acquisition , Image Sampling and Quantization , Some Basic Relationships Between

Pixels, Linear and Nonlinear Operations.

Module – II

Enhancements in Spatial Domain: Some Basic Gray Level Transformations , Histogram Processing ,

Enhancement Using Arithmetic/Logic Operations , Basics of Spatial Filtering , Smoothing Spatial Filters ,

Sharpening Spatial Filters , Combining Spatial Enhancement Methods

Module – III

Enhancements in Frequency Domain: Introduction to the Fourier Transform and the Frequency Domain ,

Smoothing Frequency-Domain Filters , Sharpening Frequency Domain Filters , Homomorphic Filtering

Module – IV

Image Restoration: A Model of the Image Degradation/Restoration Process , Noise Models. Restoration

in the Presence of Noise Only-Spatial Filtering , Periodic Noise Reduction by Frequency Domain Filtering.

Linear, Position-Invariant Degradations , Estimating the Degradation Function. Inverse Filtering , Minimum

Course Outcomes

1. Understand the concept of image formation, digitization and the role human visual

system plays in perception of image data.

2. Acquire an appreciation for spatial and frequency based techniques for enhancing the appearance of an image duly applying them in different applications.

3. Discern the difference between noise models, gain an insight into assessing the degradation function and realize different spatial and frequency based filtering techniques for reduction and removal of noise.

4. Synthesize a solution to image compression using the concept of information theory and lossless and lossy compression techniques.

5. Design and create practical solutions using morphological operators for common image processing problems and assess the results.


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Mean Square Error (Wiener) Filtering , Constrained Least Squares Filtering. Geometric Mean Filter ,

Geometric Transformations.

Module – V

Image Compression: Fundamentals , Image Compression Models , Elements of Information Theory , Error-

Free Compression , Lossy Compression

Module – VI & VII

Morphological Image Processing and Segmentation: Preliminaries , Dilation and Erosion , Opening and

Closing , The Hit-or-Miss Transformation. Some Basic Morphological Algorithms , Detection of

Discontinuities , Edge Linking and Boundary Detection , Thresholding , Region-Based Segmentation.

Text Book:

1. Gonzalez R., Woods R.; Digital Image Processing, 2nd Edition, Prentice Hall of India, New Delhi

Reference Book:

1. Jain, A. K. ; Fundamentals of Digital Image Processing, Prentice Hall of India, New Delhi


[Type here] 89 2011

MCA 7309 Soft Computing [3 (3-0-0)]

Module – I

Introduction To Artificial Intelligence System, Neural Network, Fuzzy Logic & Genetic Algorithm. Fuzzy Set

Theory : Fuzzy Versus Crisp, Crisp Set, Fuzzy Set, Crip Relation, Fuzzy Relations.

Module – II

Fuzzy System: Crisp Logic, Predicate Logic, Fuzzy Logic, Fuzzy Rule Based System, Defuzzification Methods,

Applications.

Module – III

Genetic Algorithms, Basic Concepts, Creation Of Offspring, Working Principle, Encoding, Fittness Function,

Reproduction.

Module – IV

Genetic Modelling, Inheritance Operations, Cross Over, Inversion And Deletion, Mutation Operator, Bit

Wise Operators, Generation Cycle, Convergence Of Genetic Algorithm, Application, Multi Level

Optimization, Real Life Problems, Difference And Similarities Between GA And Other Traditional Methods,

Advanced In GA.

Module – V

Fundamentals Of Neural Networks, Basic Concepts Of Neural Network, Human Brain, Model Of An

Artificial Neuron, Neural Network Architectures, Characteristic Of Neural Networks, Learning Method,

Taxomany Of Neural Network Architectures, History Of Neural Network Research, Early Neural Network

Architectures, Some Application Domains.

Module – VI

Back Propagation Network Architecture Of Back Propagation Network, Back Propagation Learning,

Illustration, Applications, Effect Of Tuning Parameters Of The Back Propagation Neural Network, Selection

Of Various Parameters In BPN, Variations Of Standard Back Propagation Algorithm.

Course Outcomes

1. Understand the kind of problems for which soft computing approaches are relevant. 2. Develop an intuition for the basic mathematics involved in designing soft computing

models. 3. Understand the concepts of fuzzy and approximate reasoning. 4. Be able to hybridize fuzzy solution models with learning models and measure the

improvement in results. 5. Have a fundamental idea of heuristic search techniques.


[Type here] 90 2011

Module – VII

Associative Memory And Adaptive Resonance Theory, Autocorrelators, Hetrocorrelators, Multiple

Training Encoding Strategy, Exponential BAM, Associative Memory For Real Coded Pattern Pairs,

Applications, Introduction To Adaptive Resonance Theory, ARTI, Character Recognition Using ARI1

Text Book:

1. S. Rajasekharan & G. A. Vijayalakshmi – “ Neural Network, Fuzzy Logic And Gentic Algorithm Synthesis And Applications”, Prentice Hall Of India PLT, Pai – 2004

Reference Book:

1. Jyh – Shing R Jang, C. T. Sun, E Mizutani – Neuro Fuzzy And Soft Computing – A Computational Approach To Learning And Machine Intelligence”, Prentice Hall Of India – 1997.


[Type here] 91 2011

Group IV

Networking

and

Distributed System


[Type here] 92 2011

MCA 7401 Network Security and Cryptography [3 (3-0-0)]

Module-I & II

Attacks on Computers and Computer Security: Introduction, The Need for Security, Security Approaches,

Principles of Security, Types of Attacks.

Cryptography: Concepts and Techniques: Introduction, Plain Text and Cipher Text, Substitution

Techniques, Transposition Techniques, Encryption and Decryption, Symmetric and Asymmetric Key

Cryptography, Steganography, Key range and Key Size, Possible Types of Attacks.

Module-III

Symmetric Key Algorithms and AES: Introduction, Algorithm Types and Modes, An Overview of

Symmetric Key Cryptography, Data Encryption Standard (DES), International Data Encryption Algorithm

(IDEA), RC4, RC5, Blowfish, Advanced Encryption Standard (AES).

Module-IV

Asymmetric Key Algorithms, Digital Signatures and RSA: Introduction, Brief History of Asymmetric Key

Cryptography, An Overview of Asymmetric Key Cryptography, The RSA Algorithm, Symmetric and

Asymmetric Key Cryptography Together, Digital Signatures, Knapsack Algorithm, Some Other Algorithms.

Module-V

Digital Certificates and Public Key Infrastructure(PKI): Introduction, Digital Certificates, Private Key

Management, The PKIX Model, Public Key Cryptography Standards (PKCS), XML, PKI and Security, Creating

Digital Certificates Using Java.

Course Outcomes

1. Understand theory of fundamental cryptography, encryption and decryption algorithms, identify the appropriate cryptography scheme & security mechanism for different computing environment and information systems.

2. Explain the basic concepts of symmetric & asymmetric cryptography, Demonstrate a systematic and critical understanding of the theories, principles and practices.

3. Understand the different internet security protocols. Apply the security techniques in solving security problems in practical systems.

4. Understand the fundamental concepts of different authentication and digital signature, schemes, Build secure authentication systems by use of message authentication techniques.

5. Apply the cryptographic algorithms learnt so far to build a secure information and network security mechanisms.


[Type here] 93 2011

Module-VI

Internet Security Protocols: Introduction, Basic Concepts, Secure Socket Layer (SSL), Transport Layer

Security (TLS), Secure Hyper Text Transfer Protocol (SHTTP) , Time Stamping Protocol (TSP) , Secure

Electronic Transaction (SET), SSL versus SET, 3-D Secure Protocol, Electronic Money, Email Security,

Wireless Application Protocol (WAP) Security, Security in GSM, Security in 3G.

Module-VII

User Authentication and Kerberos: Introduction, Authentication Basics, Passwords, Authentication

Tokens, Certificate-based Authentication, Kerberos, Key Distribution Center (KDC), Security Handshake

Pitfalls, Single Sign on (SSO) Approaches.

Network Security, Firewalls and Virtual Private Networks (VPN): Introduction, Brief Introduction to

TCP/IP, Firewalls, IP Security, Virtual Private Networks (VPN), Intrusion.

Text Book:

1. A.Kahate- Cryptography and Network Security , 2nd Edn., Tata McGraw Hill Publication, New Delhi,

2007

Reference Books:

1. B.A. Foronzan – Cryptography & Network Security, TMH, New Delhi, 2007 2. S. Stalling – Cryptography and Network Security, Pearson Edn., New Delhi, 2006


[Type here] 94 2011

MCA 7403 Grid Computing [3 (3-0-0)]

Module-I

Introduction: Motivation; Definitions of Grid Computing; Evolution of the Grid; Differences with similar

efforts (Meta, cluster, heterogeneous, Internet); Examples of usage; Research possibilities / scope in Grid

Computing; Thrust areas.

Module-II

High Performance computing : PACX-MPI, MPI-Connect, P-MPI; I-WAY experiment.

Module-III

Earliest Grid Tools / Projects : Condor Part 1, Part 2; Globus Part 1, Part 2; Nimrod.

Module-IV

Grid Basics - Technologies / Challenges: Security - Different models: SSL, Kerberos, SASL, GSI, Others;

Information Services: NWS.

Module-V & VI

HPC and Grids : Scheduling HPC applications in Grids: AppLeS, Scheduling Parameter sweep applications,

Metascheduling Part1, Part2; Grid RPC mechanisms - Part1, Part2; Rescheduling; Computational Steering,

Scientific visualization of Grid applications; Grid Applications - Everywhere and Cactus experiments; Data

management: Data distribution, Redistribution, Data cache maintenance.

Module-VII

Recent Efforts / Challenges : Grid economy; Grid simulation - SimGrid, GridSim, MicroGrid; Grid standards

and forums - OGSA, GGF and Other topics.

Course Outcomes

1. evaluate enabling technologies such as high-speed links and storage area networks for building computer grids

2. utilise grid computing and clustering middleware, such as Parallel Virtual Machine (PVM), Message Passing Interface (MPI), HPC Portals

3. understand Peer-to-Peer networks for implementing virtual super computing resources; 4. design a grid computing application in one of the key application areas e.g. Computer

Animation, E-Research 5. can install a grid computing environment


[Type here] 95 2011

Text Books:

1. [Module: 1] Ian Foster, Carl Kesselman; The Grid: Blueprint for a New Computing Infrastructure (2nd edition); Morgan Kaufmann Publishers; 2nd edition, 2003.

2. [Module: 2, 3, and 4] Francine Berman, Geoffrey Fox, Tony Hey; Grid Computing: Making the Global Infrastructure a Reality; John Wiley & Sons, 2003.

3. [Modules: 5, 6, and 7] Jarek Nabrzyski, Jennifer M. Schopf, Jon Weglarz; Grid Resource Management: State of the Art and Future Trends; Kluwer Academic Publishers, 2003.


[Type here] 96 2011

MCA 7405 Wireless Technology [3 (3-0-0)]

Module-I

Introduction to Networking : Technology and Change, The Internet, Reference Models, Layering, and

Protocols, OSI and Other Models, Network Types, Network Media, Network Topologies, Connectivity

Devices, Evolution of Networking.

Introduction to Wireless Communications: Why Wireless?, Types and Range of Wireless

Communications, Growth of Wireless Communications, Wireless Technologies, Wireless LANs, Satellite

Communications, Wireless Application Protocol, Other Wireless Systems.

Module-II

Technical Foundation of Wireless Technologies: What is Wireless? Antennas, Narrowband and Spread

Spectrum Technology, Accessing Channels: Spread Spectrum and Cellular Telephony, Propagation,

Frequencies and Spectrum, Signals, Personal Communications System, How an Organization Gets a Piece

of Spectrum.

Module-III & IV

Wireless Application Protocol: Background, History, Design and Principles of Operation, WAP

Architecture Requirements, WAP Architecture Overview, The WAP Model, WAP Architecture

Components, Compliance and Interoperability, WAE Overview, The WWW Model, The WAE Model, WAE

Services and Formats, Internationalization, Security and Access Control, WTA Architecture Overview, WTA

Framework Components, Telephony-Specific Exchanges, Wireless Telephony Application Interface

Specification, Supported Content Formats, Wireless Session Protocol Specification, Wireless Transaction

Protocol Specification, Wireless Transport Layer Security Specification, Handshake Protocol Overview,

Wireless Data gram Protocol Specification, Wireless Control Message Protocol Specification, The Future.

Module-V & VI

Bluetooth : Purpose and Beginnings, Design and Principles of Operation, Transmitter Characteristics,

Spurious Emissions, Baseband Characteristics, Physical Channel, Physical Links, General Format,

Transmit/Receive Timing, Channel Control, Bluetooth Security, Link Manager Protocol, Logical Link Control

and Adaptation Layer Protocol, General Operation, Data Packet Format, Service Discovery Protocol,

Course Outcomes

1. Evaluate the feasibility of various applications with wireless technology 2. Select development tools for mobile and wireless application development 3. Design and develop simple applications with mobile devices, wireless Internet and

networks.


[Type here] 97 2011

Rfcomm, Telephony Control Protocol Specification, Interoperability Requirements for Bluetooth as a WAP

Bearer, Alternatives to Bluetooth, The Outlook, Recent Events in the Bluetooth World.

Cellular Telephony: History of Cellular Telephony, Design and Principles of Cellular Operation, Cellular

Telephony Operations, Analog Cellular Telephones, Digital Cellular Telephones, The Digital Network,

Personal Communications System, Third Generation, Recent Events in the Cellular World.

Module-VII

Public Services: Interoperability in Communications, Aspects for the Law Enforcement Community,

Incident Response Plans, Design and Principles of Operation, Specialized Mobile Radio.

Wireless LANs: Introduction, Benefits of WLANs, Design and Principles of Operation, WLAN

Configurations, Microcells and Roaming, Types of WLANs, WLAN Customer Considerations, Wireless LAN

Standard IEEE 802.11, 802.11b, and 802.11a, Planning for a New Network, Selecting a WLAN, Microwave

LANs, Recent Events.

Text Book:

1. Gary S. Rogers, John Edwards, “An Introduction to Wireless Technology”, 1st Edn., Pearson Education, New Delhi – 2007


[Type here] 98 2011

MCA 7407 Parallel and Distributed Computing [3 (3-0-0)]

Sec A: Parallel Computing

Module-I

Introduction: Computational Demand of Modern Science, Advent of Practical Processing, Parallel

Processing Terminology- Contrasting Pipelining and Data Parallelism, Control Parallelism, Scalability,

Control-Parallel Approach, Data-Parallel Approach with I/O.

Module-II

PRAM Algorithm: A Model of Serial Computation, The PARAM Model of Parallel Computation, PARAM

Algorithm- Parallel Reduction, Prefix Sums, List Ranking, Preorder Tree Traversal, Merging Two Sorted

Lists, Graph Colouring, Problem defining Fast Solutions on PRAMS.

Module-III

Elementary Parallel Algorithm: Classifying MIMD Algorithm, Reduction.

Matrix Multiplication: Sequential Matrix Multiplication, Algorithms for Processor Array, Algorithms

for Multiprocessors.

Module-IV

Solving Linear Systems: Terminology, Back Substitution, ODD-EVEN Reduction, Gaussian Elimination,

The JACOBI Algorithm, The Gauss-Seidel Algorithm, Jacobi Overrelaxation and Successive

Overrelaxation, Mulyigrid Methods, Conjugate Gradient.

Sec B: Distributed Computing

Module-V

Basic Algorithms in Message-Passing Systems: Formal Models for Message Passing Systems,

Broadcast and Convergecast on a Spanning Tree, Flooding and Building a Spanning Tree, Constructing

a Depth-First Search Spanning Tree for a Specified Root, Constructing a Depth-First Search Spanning

Tree without a Specified Root.

Course Outcomes

1. Explain the range of requirements that modern parallel/distributed systems have to address.

2. Define the functionality that parallel/distributed systems must deliver to meet some need. 3. Articulate design tradeoffs inherent in large-scale parallel and distributed system design. 4. Describe how the resources in a parallel and distributed system are managed by software. 5. Justify the presence of concurrency within the framework of a parallel and distributed

system.


[Type here] 99 2011

Leader Election in Rings: The Leader Election Problem, Anonymous Rings, Asynchronous Rings,

Synchronous Rings.

Module-VI & VIIMutual Exclusion in Shared Memory: Formal Model for Shared Memory Systems,

The Mutual Exclusion Problem, Mutual Exclusion using Powerful Primitives, Mutual Exclusion using

Read/Write Registers.

A formal Model for Simulations: Problem Specifications, Communication Systems, Processes,

Admissibility, Simulations, Pseudocode Conventions.

Broadcast and Multicast: Specification of Broadcast Services, Implementing a Broadcast Service,

Multicast in Groups, An Application: Replication

Distributed Shared Memory: Linearizability Shared Memory, Sequentially Consistent Shared

Memory, Algorithms, Lower Bounds.

Text Books:

1. H. Attiya & J. Welch- Distributed Computing- Fundamentals, Simulations and Advanced Topics,2nd Edn., Wiley India Publication, New Delhi, 2006. 2. M.J. Quinn-Parallel Computing-Theory and Practice, 2nd Edn., McGraw Hill Inc., New York.


[Type here] 100 2011

MCA 7409 Mobile Computing [3 (3-0-0)]

Module-I

Mobile Computing Architecture: Internet – The ubiquous network; Schematic representation of mobile

computing environment; The Three-Tier mobile computing architecture; Design considerations for

mobile computing; Mobile computing through Internet; Making existing applications mobile-enabled.

Module-II

Mobile Communications: Introduction; The GSM architecture; Call routing in GSM; Network aspects in

GSM; GSM frequency allocation; Authentication and security; GPRS system architecture and routing.

Module-III

Mobility Management: Mobility management; Location Management Principles and Techniques;

Location Management Case studies: PCS, Mobile IP.

Module-IV

Data Dissemination and Management: Challenges; Data Dissemination; Mobile Data Caching; Mobile

Cache Maintenance Schemes; Mobile Web Caching; Case studies.

Module-V

Mobile Middleware: Introduction; Adaption: The spectrum of adaption, Resource monitoring,

Characterizing adaption strategies, Odyssey-An application aware adaption architecture, Sample Odyssey

application; Mobile Agents: Agent architectures, Migration strategies, Communication strategies.

Module-VI

Service Discovery Middleware: Middleware services: Universally unique identifiers, Standardization,

Textual Descriptions, Interfaces for standardization; Discovery and Advertisement Protocols: Unicast

discovery, Multicast discovery and advertisement, Service catalogs; Garbage collection: Leasing,

Advertised expirations; Eventing; Security: Jini, Service location protocol, Ninja; Interoperability.

Course Outcomes

1. Describe the basic concepts and principles in mobile computing 2. Understand the concept of Wireless LANs, PAN, Mobile Networks, and Sensor

Networks 3. Explain the structure and components for Mobile IP and Mobility Management 4. Understand positioning techniques and location-based services and applications 5. Describe the important issues and concerns on security and privacy



Module-VII

Device Operating System: Introduction to Symbian Operating System; Symbian OS architecture;

Applications for Symbian; Special feature:- Event Driven Multitasking using Active objects; Client-Server

framework model on Symbian OS.

Text Books:

1. [Modules: 1, 2, and 7] Asoke K Talukder and Roopa R. Yavagal; Mobile Computing – Technology, Applications and Service Creation; TMH Publication, New Delhi, 2006

2. [Modules: 3, 4, 5, and 6] Frank Adelstein et.al.; Fundamentals of Mobile and Pervasive Computing; TMH Publication, New Delhi, 2005



Group V Applications of Information

Technology



MCA 7501 Bioinformatics [3 (3-0-0)]

Module – I

Bioinformatics: An Introduction, Bio informatics Application, Major Database in Bio informatics,

Molecular Biology and Bio informatics. Control Dogma of Molecular Biology.

Genome Analysis and Gene Mapping: Introduction, Genome Analysis, Genome Mapping, Genetic

Mapping and Linkage Analysis, Cloning the Entire Genome, Genome Sequencing.

Module – II

Alignment of Pairs of Sequence: Introduction, Biological Motivation and alignment Problems, Methods

of Sequence Alignment, Using Scoring Matrix, Measuring Sequence Detection Efficiency.

Module – III

Alignment of Multiple Sequence and Phylogenetic Analysis: Introduction, Methods of Multifile sequence

alignment, Evaluating of Multiple Alignment, Application of Multiple Alignment, Phylogentic Analysis,

Method of Phylogentic analysis, Problem of Phylogenetic Analysis.

Module – IV

Tools for similarity search and Sequence Alignment: Introduction, Working with FASTA, Working with

BIASTA, Filtering and Gapped BLAST, FASTA and BLAST Algorithm comparison

.Profile and Hidden Markov Models: Introduction, Using Profile, Hidden Marker Models (HMMs)

Module – V

Gene Identification, Predication and Gene Expression: Introduction, Basis of Gene Prediction, Pattern

Recognition, Gene Prediction Methods, Gene Prediction Tools, Clustering Gene Expression Profile.

Course Outcomes

1. Students will get familiar with how information is represented and transmitted in biological system.

2. They will know various computational problems in biology.

3. They will learn how to map these problems to computer algorithms.

4. They will learn how to utilize different biological databases to solve realistic problems.

5. This will help in designing efficient solutions to various compute-intensive biological problems which involves processing of huge data.



Module – VI

Protein Classification and Structure Visualization: Introduction, Overview of protein structure, Protein

Structure Visualization, Structure based Protein classification, Protein Structure database, Protein

Structure alignment, Tools for Plotting Protein – Ligand Interaction.

Module – VII

Protein Structure Prediction: Introduction, Protein Identification and Characterization, Primary Structure

analysis and Prediction, Secondary Structure analysis and Prediction, Modify, Profile, Pattern and

Fingerprint Search, Methods of Sequence based protein Prediction, Methods of 2D Structure Prediction,

Protein Function Prediction.

Text Book:

1. S. C. Ratogi, N. Mendiratha, P Rastogi, “Bioinformatics Methods and Applications”, PHI, New Delhi, 2005.

Reference Books:

1. D. E. Krane & M. L. Ragmer - Fundamental of Concept of Bioinformatics, Pearson Education, New Delhi – 2003.

2. V. R. Srinivas – Bioinformatics : A Modern Approach, PHI, New Delhi – 2005 3. A. M. Lesk – Introduction to Bioinformatics, Oxford ( Indian Edn ) New Delhi – 2004



MCA 7505 Multimedia and Animation [3 (3-0-0)]

Module I

Introduction: Multimedia Elements and Applications, Multimedia Systems Architecture, Defining Objects

for Multimedia Systems, Multimedia Data Interface Standards, Multimedia databases

Module II

Compression and Decompression: Types of Compression, Binary Image Compression Schemes, CCITT

Group 3 1-D, 2-D, 3-D, JPEG, Video Image Compression, MPEG, Motion Compensation, Vector

Quantization, Audio Compression, Adaptive DPCM

Module III

Data and File formats: Rich Text formats, TIFF, Resource Interchange File Format (RIFF), MIDI File format,

RDIB file format, TWAIN

Module IV

Multimedia Input Output Technology: Electronic Pen, Video and Image Display Systems, Print Output

Technology, Image Scanners, Video Images and Animation, Full motion video

Module V

Multimedia Application Design: Multimedia Application Classes, Types of Multimedia Systems, Virtual

Reality, Application Workflow Design Issues

Module VI

Multimedia Authoring: Multimedia Authoring Systems, Hypermedia Application Design Considerations,

Linking and Embedding, CORBA

Module VII

Multimedia Content Development Tools: HTML, XML, Macromedia Flash, Shockwave, Modelling and

Animation concepts

Course Outcomes

1. Evaluate the uses of multimedia and different standards in graphics, video, audio, animation, CDROM and other hardware

2. Apply the principles of multimedia development, including story-board techniques and develop a suitable story-board for a small multimedia project

3. Implement the multimedia project using appropriate technology 4. Describe and evaluate a variety of 3D principles and techniques 5. Design and create concept artwork for a short animated project, including storyboards,

turnaround artwork and technical drawings.



Text Books:

1. Andleig P. K.& Thakrar K.- Multimedia Systems Design, Prentice Hall of India, New Delhi , India

2004

2. Parekh R.-Principles of Multimedia, Tata McGraw Hill, New Delhi, India, 2004



MCA 7507 Supply Chain Management [3 (3-0-0)]

Module-I

Supply Chain Management: An Overview

Introduction to Supply Chain Management: Introduction, What is Supply Chain Management?, Why is

Supply Chain Management Important?, The Origins of Supply Chain Management, Important Elements of

Supply Chain Management, , Future Trends in Supply Chain Management.

Module-II

Purchasing Issues in Supply Chain Management

Purchasing Management: Introduction, The Role of Purchasing in an Organization,

The Purchasing process, Sourcing Decisions: The Make-or-Buy Decision, Roles of Supply Base, Supplier

Selection, How many Suppliers to Use, Purchasing Organization: Centralized versus Decentralized

Purchasing, International Purchasing/Global Sourcing.

Creating and Managing Supplier Relationships: Introduction, Developing Successful Partnerships,

Supplier Evaluation and Certification, Supplier Development, Supplier Awards, Supplier Relationship

Management Software.

Module-III

Strategic Sourcing for Successful Supply Chain Management:-Introduction, Developing Successful

Sourcing Strategies, Supply Base Reduction Programs, Evaluating and Selecting Key Suppliers, Strategic

Alliance and Supplier Certification Programs, Outsourcing Programs, Early Supplier Involvement, Supplier

Management and Alliance Development, Managing and Developing Second-Tier Supplier Relationships,

Use of e-procurement Systems, Rewarding Supplier Performance, Benchmarking Successful Sourcing

Practices, Using Third-Party Supply Chain Management Services, Assessing and Improving the Firm’s

Purchasing Function.

Course Outcomes

1. Students will be able to apply metrics in supply chains. 2. Students will be able to define the principles of scheduling and planning in supply chain

management. 3. Students will be able to apply the principles of Strategic/Master planning of resource in

supply chains. 4. Students will be able to identify the principles of customer and supplier relationship

management in supply chains 5. Students will be able to define the principles of quality and lean manufacturing



Module-IV

Operations Issues in Supply Chain Management

Demand Forecasting and Collaborative Planning, forecasting, and Replenishment: Introduction,

Matching Supply and Demand, Forecasting Techniques, Qualitative Methods, Quantitative Methods,

Forecast Accuracy, Collaborative Planning, Forecasting, and Replenishment, Software Solutions.

Module-V

Enterprise Resource Planning Systems:- Introduction, The Development of Legacy Materials Requirement

Planning Systems, The Development of Enterprise Resource Planning Systems, The Rapid Growth of

Enterprise Resource Planning Systems, Implementing Enterprise Resource Planning Systems, Advantages

and Disadvantages of Enterprise Resource Planning Systems, Enterprise Resource Planning Software

Applications, Enterprise Resource Planning Software Providers.

Module-VI

Process Management: Just-in-Time and Total Quality Management issues in Supply Chain Management:

Introduction, Just-in-Time and Supply Chain management , the Elements of Just-in-Time, total Quality

Management and Supply Chain Management, Total Quality Management and Supply Chain Management.

Distribution Issues in Supply Chain Management

Domestic and International Transportation: Introduction, The Impact of Transportation on Supply Chain

Management, The Fundamentals of Transportation, Warehousing, International Transportation Issues,

Transportation Management, e-Commerce and Transportation.

Module-VII

Customer Relationship Management :- Introduction, Defining Customer Relationship Management,

Customer Relationship Management’s Role in Supply Chain Management, Key Tools and Components of

Customer Relationship Management, Designing and Implementing a Successful Customer, Relationship

Management Program, Some Customer Relationship Management Application Providers, Future Trends

in Customer Relationship Management.

Facility Location Decision:- Introduction, Location Strategies, Critical Location Factors, Facility Location

Models, Helpful On-Line Information for Location Analysis, Business Clusters.

Service Response Logistics :- Introduction, An Overview of Service Operations, Supply Chain Management

is Services, The Primary Concerns of Service Response Logistics.

Text Book:

1. J. D. Wisner, G. Keong Leong & K. Tan- Principles of Supply Chain Management, 1st Edn.,Thomson Education, New Delhi, 2007



MCA7411 Cloud Computing [3(3-0-0)]

Module-I

Introduction: Essentials, Benefits and need for Cloud Computing - Business and IT Perspective - Cloud and Virtualization - Cloud Services Requirements - Cloud and Dynamic Infrastructure - Cloud Computing Characteristics Cloud Adoption.

Module-II

Cloud Models: Cloud Characteristics - Measured Service - Cloud Models - Security in a Public Cloud

Public versus Private Clouds - Cloud Infrastructure Self Service. Cloud as a Service: Gamut of Cloud

Solutions - Principal Technologies - Cloud Strategy Cloud Design and Implementation using SOA -

Conceptual Cloud Model - Cloud Service Defined

Module-III & IV

Cloud Solutions: Cloud Ecosystem - Cloud Business Process Management - Cloud Service

Management - Cloud Stack - Computing on Demand (CoD) – Cloud sourcing. Cloud Offerings:

Information Storage, Retrieval, Archive and Protection - Cloud Analytics Testing under Cloud -

Information Security - Virtual Desktop Infrastructure - Storage Cloud. Cloud Management:

Resiliency – Provisioning - Asset Management - Cloud Governance - High Availability and Disaster

Recovery - Charging Models, Usage Reporting, Billing and Metering.

Module-V

Cloud Virtualization Technology: Virtualization Defined - Virtualization Benefits - Server

Virtualization - Virtualization for x86 Architecture - Hypervisor Management Software - Logical

Partitioning (LPAR) - VIO Server - Virtual Infrastructure Requirements. Cloud Virtualization: Storage

virtualization - Storage Area Networks - Network-Attached storage - Cloud Server Virtualization -

Virtualized Data Center.

Module-VI

Cloud and SOA: SOA Journey to Infrastructure - SOA and Cloud - SOA Defined - SOA and IaaS - SOA-based Cloud Infrastructure Steps - SOA Business and IT Services.

Course Outcomes



Module-VII

Cloud Infrastructure Benchmarking: OLTP Benchmark - Business Intelligence Benchmark - e-Business Benchmark - ISV Benchmarks - Cloud Performance Data Collection and Performance Monitoring Commands - Benchmark Tools.

Text Book:

1. K. Saurabh– Cloud Computing, 2nd Edn, Wiley India, 2014.

Reference Book:

1. T. Velte, A. Velte and R. Elsenpeter-Cloud Computing: A Practical Approach, McGraw Hill, India. 2. R. Buyya, J. Broberg-Cloud Computing: Principles and Paradigms, Wiley. 3. K. Hwang, G. Fox and J. Dongarra-Distributed and Cloud Computing, From Parallel Processing to the Internet of Things, Morgan Kaufmann, 2012.