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0.5.1 Core Courses
ITMS2101: Discrete Mathematics
Core/Elective: Core Semester: I Credits: 3
1. Propositional logic, propositional equivalences, predicates and quantifiers, nestedquantifiers, rules of inference and introduction to proofs, Sets, set operations, functions,
sequences and summations.
2. Algorithms, the growth of functions, complexity of algorithms, the integers and division,primes and greatest common divisors, integers and algorithms.
3. Mathematical induction, strong induction and well-ordering, recursive definitions,recursive algorithms.
4. The basics of counting, the pigeonhole principle, permutations and combinations,binomial coefficients, Recurrence relations, solving linear recurrence relations,
inclusion-exclusion principle, applications of inclusion exclusion principle, Relations and
their properties, representing relations, closures of relations, equivalence relations,
partial orderings.
5. Graphs and graph models, graph terminology and special types of graphs, representinggraphs and graph isomorphism, connectivity.
Text Books
1. Kenneth Rosen, Discrete Mathematics and its Applications, 6th edition, Tata McGrawHill, New Delhi, 2007.
2. R. Johnsonbough, Discrete Mathematics, 5th ed., Pearson, New Delhi, 2000.
References
3. C.L. Liu, Elements of Discrete Mathematics, 2nd edition, Tata McGraw Hill, New Delhi,2000.
ITMS2102: Computer Architecture and Organization
Core/Elective: Core Semester: I Credits: 4
1. Basic Structure of Computer Hardware and Software: Basic Computer Structures, BusStructure, Control Unit Von Neumann Architecture. Instruction Sets and Addressing
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Methods: Instruction Sets, Addressing Modes, Data Transfer and Manipulation Program
Control, Assembly Language, Subroutines, RISC and CISC.
2. Programming the Basic Computer: Machine Language, Assembler, I/O Programming.Processing Unit: General Register Organization, Bus Structure, Design of Control Unit, Hardwired Controllers, Micro-programmed Controllers, Control Memory, Address
Sequencing, Micro program Example Arithmetic Unit: Addition and Subtraction, Design
of Fast Adders, Multiplication Algorithms, Division Algorithms, Floating-Point
Arithmetic Operations, Fast Adders.
3. Input-Output Organization: Peripheral Devices, I/O Interface, I/O Hardware, Asynchronous Data Transfer, Modes of Transfer, Interrupts, Direct Memory Access,
Serial Communication Memory Organization: Memory Hierarchy, Main Memory,
Auxiliary Memory, Associative Memory, Cache Memory, Virtual Memory, Memory
management.
4. Pipelining: Instruction Pipeline, RISC Pipeline, Data Dependency5. Advanced Computer Architecture: Parallel Processing, Characteristics of
Multiprocessors, Interconnection Structures, Interprocessor Arbitration, Interprocessor
Communication and Synchronization, Cache Coherence, Vector/Array Processing.
References
1. John L. Hennesy, David A. Patterson Computer Organization and Design: The Hardware/ Software Interface (Third Edition), Morgan Kaufmann, 2004
2. William Stallings, Computer Organization and Architecture: Designing for Performance(Seventh Edition), Prentice-Hall India, 2006
3. Carl Hamacher, Zvonko Vranesic and Safwat Zaky, Computer Organization (FifthEdition), McGraw Hill, 2002
ITMS2103: Principles of Programming
Core/Elective: Core Semester: I Credits: 4
1. Datatypes and Designing Programs: Primitive Data, Expressions, Simple Functions,Designing Programs, Structured Data: Simple examples of structured data types, Tuples
in Scheme using list, Constructors and Destructors, Data type-verifiers (tagging),
Inductive Data: Numbers, Lists, Trees (XML and DOM), Recursively specified data andprograms.
2. Scope, Contracts and Invariants: Local variables, Scoping and Binding of variables,Environments, Composing functions, Function call stacks, Closures, Pre-conditions, Post
conditions, Invariants
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3. Higher Order Functions and Recursion: Map, Reduce, Fold, Iterators, Recursion, Tail Recursion, Converting tail recursion to iteration, Procedures, Statements, A simple
interpreter.
4. Mutation and Sequencing: Variable assignment, Structure mutation, Sequentialexecution, Persistence
5. Objects: Objects in Javascript, Prototyping, Implementing an object system in Schemeusing environments, Exceptions, Event handlers, Observers.
Text Books
1. Harold Abelson and Gerald Jay Sussman, with Julie Sussman, Structure andInterpretation of Computer Programs, MIT Press, 2nd ed., 1996.
2. Felleisen, Findler, Flatt and Krishnamurthi, How to Design Programs, MIT Press, 2003.3. Anders Mller and Michael I. Schwartzbach, An Introduction to XML and Web
Technologies, Addison-Wesley, January 2006.
References
4. Glynn Winskel, The Formal Semantics of Programming Languages, MIT Press, 1993.5. John C. Reynolds, Theories of programming languages, Cambridge University Press,
1998.
ITMS2104: Technical Communication
Core/Elective: Core Semester: I Credits: 3
1. Introduction to technical communication, understanding the ethical and legalconsiderations, understanding the writing process and writing collaboratively, planning
the document: Understanding the audience and purpose, communicating persuasively,
researching the subject and organizing the information.
2. Developing the textual elements: Drafting and revising definitions and descriptions,drafting and revising coherent documents, drafting and revising elective sentences,
drafting and revising front and back matter, Developing the visual elements: Designing
the document and creating graphics
3. Applications: Writing letters, memos and e-mails, writing job application materials,writing proposals, Technology in communication: use of SVN, Wiki, LaTeX, etc.
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4. Giving technical talks: introduction, the preparation process, organization of the talk, thepresentation process, handling questions and useful tips for effective talks.
5. Effective participation in group discussions, debates, job-interviewsText Books
1. Mike Markel, Technical Communication, Bedford books, 20042. Anderson, Technical Communication, 6th Edition, Thomson Learning, 2002.
References
3. Meenakshi Raman and Sangeeta Sharma, Technical Communication: Theory andPractice, Oxford University Press, 2008.
ITMS2105: Object Oriented Programming in JAVA
Core/Elective: Core Semester: I Credits: 4
1. Object Oriented Paradigm and JAVA overview: Object oriented Concepts: Introductionto OOPS, Abstraction, Encapsulation, Objects and Classes, Constructors Inheritance,
Polymorphism, Abstract Classes, Interfaces, Introduction to Java, JVM, Primitive data
types, Control Statements, Methods, Classes Introduction to Java Compilers and Lab
2. JAVA statements: Java's selection statements, iteration statements, jump statements, Introduction to classes: Class fundamentals, declaring object reference variable,
Introducing methods, constructors, the key word, garbage collection, the finalize (),
method. Methods and Classes Overloading methods, using objects as parameters
3. Java Arrays, Utilities and Packages: Java Arrays, Wrapper Classes, Java IO, Inheritance, Super class, Polymorphism, java Packages, class libraries, Interfaces,
Exception Handling, JAVA Strings
4. Multithreading and JAVA Networking: The Java thread model, the main thread, creatingthread, creating multiple thread, using is alive () and join (). Thread priorities,
synchronization, Inter thread communications, suspending resuming and stopping thread
using multithreading Networking: Networking basics, Java and the Internet Address,
TCP/IP client Sockets, URL, URL connection, TCP/IP server Sockets The Applet Class
5. Applet and Swing: its architecture displays methods. The HTML AP PLET. Passingparameters to Applet, Java GUI, AWT, Text Box, Menu, Event Handling, Frames, Java
Swing.
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Text Books
1. Patrick Naughton, Helbert Schildt, "The Complete Reference JAVA 2", Tata McGraw-Hill, 1999
2. C. Thomas Wu, "Introduction to Java programming", Second Edition, John Wiley andSons 2000
References
3. Bruce Eckel, Chuck Allison, "Thinking in Java", Edition 2, Prentice Hall, 20004. Cay Horstmann, Computing Concepts With JAVA 2 Essentials, 2ND ED, Published by
Wiley-India, 2006
ITMS2201: Data Structures and Algorithms
Core/Elective: Core Semester: II Credits: 4
1. Introduction to ADT and Algorithms: Principles of DSA, ADT, computational problem,algorithm notion, time complexity, space complexity, asymptotic analysis, analysis of
algorithms, design of algorithms, data, abstract data type, procedural abstraction, worst
case complexity, Big-Oh notation, incremental design.
2. Stack and Queues: Introduction to stack, basic operations, implementation using arrayand linked list, computational problems relating to stack, parenthesis matching,
expression representation using Polish and reverse Polish notations, evaluation of
expression using stack, introduction to queues, basic operations, implementation
3. Lists and Linked List: Lists in ADT, List implementation in Stack and Queue, Linked list, Insert, delete operations, doubly linked list, implementation, ADT and applications,
INFIX and POSTFIX evaluations.
4. Recursion and Heap: Closed form, recursive form, problem solving, Fibonacci series,Towers of Hanoi, celebrity problem (with and without recursion, Efficiency of Recursion
Algorithm, eight Queens, Heap: Introduction, max heap, min heap, representation,
complexity.
5. Trees, Graphs and Hashing: Binary tree, traversal in a tree, level order traversal, ADTdictionary, dictionary implementation, balanced binary search tree, binary search tree,
extended binary tree, insertion, deletion, AVL trees, Fibonacci tree, B-tree, red black
tree.
6. Graph: Weighted graph, spanning tree, greedy method, Krushkals algorithm,implementation, equivalence relation, parent chasing, traversal, DFS and BFS, Hashing:
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open address hashing, double hashing, chaining, Different search and sort algorithms:
Bubble, quick sort, merge sort-divide and conquer method, Heap sort.
Text Books
1. A.D Aho, J. E. Hopcroft and J. D. Ullman, Data Structures and Algorithms, Pearsoneducation Asia, 1983.
2. Y. Langsam, M. J. Augenstein and A. M. Tenenbaum, Data Structures using C, PearsonEducation Asia, 2004
References
3. T.H. Cormen, C.E.Leiserson, R.L.Riverst and C. Stien, Introductin to algorithms, SecondEdition. MIT Press and McGraw-Hill, 2001.
4. Adam Drozdek, Data Structures and Algorithms in Java, Published by Brooks/Cole, 2000
ITMS2202: Operating Systems
Core/Elective: Core Semester: II Credits: 4
1. Basic Concepts: Historical Perspective and Evolution - Computer System Operation -Operating System Components - Operating System Services - Operating System Structure
- Operating System Functions - System Calls - System Programs - Interrupts - Operating
Systems view of Computer. Process Management: Process Scheduling - Operations on
Processes - Cooperating Processes - Basic Concepts of CPU Scheduling - Scheduling
Criteria - Scheduling Algorithms - Multiple-Processor Scheduling - Real-Time
Scheduling - Inter-Process Communication - Communication in Client Server Systems.
Thread: Benefits of Threads - User and Kernel Threads - Multithreading Modules - Linux
Threads
2. Process Synchronization: Race Conditions - The Critical-Section Problem - MutualExclusion - Semaphores - Monitors. Deadlock: Deadlock Characterization - Methods for
Handling Deadlocks - Deadlock Prevention - Deadlock Avoidance - Deadlock Detection
- Recovery from Deadlock - Two Phase Locking
3. Memory Management: Memory Management Functions - Memory Architecture Evolution- Swapping - Multiprogramming with Partitions - Contiguous Memory Allocation -
Paging - Design issues for paging systems - Segmentation. Virtual Memory: Demand
Paging - Page Replacement - Allocation of Frames - Thrashing - Memory Management
with bit maps, linked lists - Buddy Systems
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4. File System: File Concepts - Access Methods - Directory Structure - Security andProtection - File-System Structure - Allocation Methods - Free-Space Management -
Directory Implementation - Efficiency and Performance - Disk Scheduling - Log-
Structured File System. I/O System: Principles of I/O hardware - Principles of I/Osoftware - I/O Requests Handling - Transforming I/O to Hardware Operations - Kernel
I/O Subsystem Performance
5. Distributed Systems: Design Issues - Sockets - Remote Procedure Calls - Remote MethodInvocation - Object Registration - Event Ordering - Synchronization - Mutual Exclusion -
Deadlock Handling Election Algorithms. Protection: Domain of Protection - Access
Matrix - Revocation of Access Rights - Language-Based Protection. Security:
Authentication - Program Threats - System Threats - Threat Monitoring - Encryption -
Computer-Security Classifications
Text Books
1. Avi Silberschatz and Peter Galvin, and Greg Gagne, Applied Operating SystemConcepts, WSE WILEY, 7th Edition 2007
2. Gary Nutt, Operating Systems: A Modern Perspective, Pearson Education Asia 2ndEdition 2000
References
3. Andrew S. Tanenbaum Albert S.Woodhull, Operating Systems Design andImplementation, Second Edition, 2006
ITMS2203: Computer Networks
Core/Elective: Core Semester: II Credits: 4
1. Introduction: Layering concept - OSI reference model - Components of a LAN - Physicallayer. Data Link Layer: Services providedError Control - Medium Access Control Sub
layer - Flow control protocols - LAN Protocols - IEEE 802 LANs
2. Network Layer: Services provided - Routing Algorithms Congestion control algorithms- Internetworking issues
3. Transport Layer: Design Issues - Connection management - TCP/IP protocol suite. OtherLayers: Session layer - Presentation and Application layers - Higher level protocols
Programming
4. Asynchronous Transfer Mode: Introduction, ATM Concepts, Emerging High speednetworks - Gigabit networks
5. Distributed Computing: Distributed Processing, Models for distributed computing, Localbalancing, Remote Procedure Call, Process migration, Concurrency issues in databases
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6. Case Study: IIITMK Firewall IIITMK DNS IIITMK Virtual Server IIITMK ProjectServices
Text Books
1. Doublas E. Comer, Internetworking with TCP/IP Vol.1: Principles, Protocols, andArchitecture (4th Edition) Prentice Hall, 4th Edition.
2. Andrew Tanenbaum, Computer Networks, Prentice Hall 3rd and 4 th EditionReferences
3. Alberto Leon-Garcia and Indra Widjaja, Communication Networks: FundamentalConcepts and Key Architectures, McGraw-Hill
ITMS2204: Database Management System
Core/Elective: Core Semester: II Credits: 4
1. Introduction to Database Management Systems: Data, Information, Database,Transaction and its desired properties, File Server Model, Client Server Model,
Advantages of using DBMS over conventional methods, DBMS Features, Components of
DBMS, Data Abstraction, Data Independence.
2. Data Modeling: Logical and Physical Data Models, E-R Modeling A detailed study,Record Based Models, Relational Model An overview, Relational Concepts, Tables, Keys,
Constraints, Data Integrity and Constraints, Integrity Rules, Database Objects Schema
and Non-schema, Normalisation, Codds Rules.
3. Introduction to SQL: Introduction to SQL, SQL Features, SQL Operators, SQLDatatypes, SQL Parsing, Types of SQL Commands, Advanced Study of Structured Query
Language, Querying Data from the database, Correlated Sub-queries, Joins,
Hierarchical Queries, PL/SQL A detailed study, Introduction, PL/SQL Architecture,
Types of PL/SQL programs, Operators in PL/SQL, Datatypes in PL/SQL, Bind Variables,
Cursors A detailed study, Functions, Stored Procedures, Triggers A detailed study
4. Distributed Databases: Structure and design, Distributed query processing, Recovery,Commit protocols, Concurrency controls, Deadlock handling, Shadow paging
5. Emerging trends Object Oriented databases, Object oriented queries Active databases Deductive databases concepts of next generation databases, XML, Data Warehouses
Data Mining
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Text Books
1. Abraham Silberschatz; Henry F Korth, Database System Concepts, McGraw HillPublication, 2002
2. Won Kim, Introduction to Object-Oriented Databases, MIT Press, 19903. Elmasri,Ramez; Navathe, Shamkant B, Fundamentals of Database Systems, Pearson,
2000
References
4. Stefano Ceri; Giuseppe Pelagatti, Distributed Databases: Principles and Systems,Universities Press, 2000
5. Jan L Harrington, Object Oriented Database Design Clearly Explained, Harcourt, 2000ITMS2EX1: Principles of Management
Core/Elective: Core Semester: II Credits: 3
1. Principles and practices of Management: Organizations and the need for Management, Role of Management theory and Management techniques, Systems approach to
Management and the Management functions, Challenges of Management.
2. Organizational Behavior: Values, attitudes and the foundations of individual behavior,Motivation: From concepts to applications, Group Behavior and working in teams, Basic
approaches to Leadership, Foundations of organization structure, Organizational culture
3. Business Environment: Theoretical framework of Business Environment, Significanceand the elements of economic, political and socio-cultural environment, Relevance of
international and technological environment
4. Human Resource Management: Human resources planning, Group dynamics andbehavior, Job satisfaction and change management, Recruitment, Selection, Training and
Development, Job design, Job Appraisal, Job rotation and promotion policies, Marketing
Management, Nature and functions of marketing, Services Marketing, Customer
Relationship Management, Financial Management: Nature and scope of Financial
Management, Overview of Financial Statements: Balance sheets, Income Statements and
Statements of cash flows.
5. Strategic Management: Overview of Strategic Management, Strategic ManagementProcess, Formulating the strategy: Company Mission, Internal and the External analysis
of the environment, Strategic Analysis and choice: Criteria for evaluating strategic
alternatives, Strategic analysis at corporate level-BCG Matrix, SWOT Analysis, Porters
Model, Project Management: Concepts of Project Management: Categories, Project Life
Cycle Phases, Tools and techniques, Establishing and organizing systems and procedures
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for project implementation, Project direction, co-ordination and control, Project
Management Performance
6. Information Systems Management: Mangers view of Information Systems, Strategic usesof Information Technology, Types and levels of Information Systems, Information SystemsPlanning, System analysis and design, Business Process Re-engineering and Information
Technology, Overview of SCM, KM, ERP, E-Governance models
Text Books
1. Harold Koontz, Heinz Weihrich, Essentials of Management, 6/e: An InternationalPerspective, Tata McGraw-Hill, 2004
2. Philip Kotler and K.L. Kotler, Marketing Management, 12th edition, Prentice Hall, 2006.3. James. A.OBrien, Management Information Systems (5th edition), McGraw Hill, 2006
References
4. John.M.Nicholas, Project Management for Business and Technology (2nd edition)Butterworth-Heinemann; 2 editions, 2004
5. Stephen P Robbins, Organizational Behavior (13th Edition), Prentice Hall, 2008
ITMS2301: Object Oriented Analysis and Design
Core Semester: III Credits: 4
1. Best Practices of Software Engineering and Introduction to OMT: Develop iteratively,models and visualizations, UML, best practices in software engineering. Object modeling
Technology, basic principles of object orientation, UML modeling mechanisms,
Relationships, Class diagrams, Instances, Object diagrams, Packages, Interfaces.
2. UML Behavioural Modeling: Use cases, Use case diagrams, Activity diagrams, Analysis-Use case behavior, finding classes and relationships Identify Design Elements, Design
Mechanism
3. Interaction Diagrams: Sequence diagram, Collaboration Diagram, activity diagram,activity states, transitions, state chart diagram, Events Signals State machines Processes
Threads State chart diagrams
4. Architectural Analysis and Component Diagram: 4+1 view architecture, analysismechanism, use case realization, Components Collaborations Patterns Frameworks,
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Process and Threads, Concurrency, Synchronization, Collaborations, Component
diagrams
5. Deployment Diagram: Distribution diagrams, runtime architecture, concurrency,configurations, process, nodes, networks, Deployment diagramsText Books
1. Grady Booch, James Rambaugh, Ivar Jacobson, The United Modeling Language UserGuide- Published by Addison-Wesley, 2005
2. James Rambaugh et. al., Object Modeling and Design Prentice Hall,1991References
3. Meilier Page Jones, Fundamentals of Object Oriented Design in UML, PearsonEducation, Asia, 2002
ITMS2302: Web Technology
Core Semester: III Credits: 4
1. HTTP and CGI, Web Server: Introduction to the web model of computing: distribution,protocols, user interface ad HTML, HTTP Protocol, Implementation of a simple HTTP
Server (Hello server), CGI in Python, GET and POST methods, Apache Web Server (case
study), Web.py (case study), PLT Web server
2. Web Programming in Python, Scheme and Java: Templating, URL mapping, CGIprogramming in Scheme, Introduction to Continuations, Continuation-based stateful web
programming in Scheme, Web applications in Java (servlets), Web applications in JSP,
Using Java Beans with JSP's
3. Database connectivity and Data Abstractions Database connectivity: Python, Java,Scheme, SQL Alchemy in Python, Hibernate in Java, Database abstraction layer in
Scheme
4. Communicating Web applications and RIA Screen Scraping, API for communication:REST, web services, SOAP, DOM and XML parsing: Tidy, Xquery, RIA: CSS, Javascript,AJAX, Mashups
5. Performance, Scalability and Security Load testing: Profiling, Tools: siege web stresstesting tool, httperf, Performance tuning and Scalability, Content Caching, Client page-
load performance tuning, Replication, Load balancing, Protocols: Password Hashing,
Symmetric and asymmetric keys (PKI), Security threats: (SQL injection, Invalid inputs,
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buffer overflows, cross-site scripting, thread safety, hidden fields), How to build secure
applications
Text Books
1. Anders Miller and Michael I. Schwartzbach, An Introduction to XML and WebTechnologies, Addison-Wesley, January 2006.
2. Mark Lutz, Programming Python, O'Reilly, 2006.3. Stephanie Bodo_, Dale Green, Kim Haase, Eric Jendrock, Monica Pawlan, Beth Stearns,
The J2EE tutorial, Addison-Wesley, 2002.
References
4. Christian Bauer and Gavin King, Hibernate in Action, Manning Publications, 2004.5. Ramesh Nagappan, Robert Skoczylas, Rima Patel Sriganesh, Developing Java Web
services: architecting and developing secure Web services using Java, John Wiley and
Sons, 2003.
0.5.2 ELECTIVES
ITMS23EX2: Soft Computing
Elective Course: Elective Semester: III Credits: 3
1. Introduction: Introduction to soft computing, introduction to biological and artificialneural networks, introduction to fuzzy sets and fuzzy logic systems
2. Artificial Neural Networks and Applications: Different artificial neural network models,learning in artificial neural networks, neural network applications in control systems
3. Fuzzy Systems and Applications: Fuzzy sets, fuzzy reasoning, fuzzy inference systems,fuzzy control, fuzzy clustering, applications of fuzzy systems
4. Neuro-fuzzy systems: Neuro-fuzzy modeling, neuro-fuzzy control, Genetic algorithms:Simple GA, crossover and mutation, genetic algorithms in search and optimization,
Introduction to Ant Colony Optimization method and Swam Intelligence
5. Applications of soft computing: Pattern recognitions, image processing, biologicalsequence alignment and drug design, robotics and sensors, information retrieval systems,
share market analysis, natural language processing
Text Books
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1. M. Friedman and A. Kandal, Introduction to Pattern Recognition Statistical, Structural,Neural and Fuzzy Logic Approaches, World Scientific, 2005.
2. Timothy J. Ross, Fuzzy Logic with Engineering Applications, McGraw Hill, 1997.3. J.S.R. Jang, C.T. Sun, E. Mizutani, Neuro-Fuzzy and Soft Computing: A Computational
Approach to Learning and Machine Intelligence, Prentice Hall, 1996.
References
4. Melanie Mitchell, An Introduction to Genetic Algorithms, Prentice Hall of India, 2004.5. David E. Goldberg, Genetic Algorithms in Search, Optimization and Machine Learning,
Addison-Wesley Professional, 1989.
ITMS2301: Software Engineering
Core Semester: III Credits: 3
1. Introduction to Software Engineering and Models: History of the development ofSoftware Engineering and its importance, Software Life cycle Models, Water fall,
Incremental, Prototype, Spiral, Iterative models
2. Requirements Management: Requirement Analysis, SRS preparation, RequirementReview
3. Software Measurements, Configuration and Risk Management: Software Metrics,Software costing, Function Point analysis, COCOMO model, SCM Processes, version
control, change management, Risk Management
4. Software Testing and Quality: Various testing Methodologies like unit testing, functional,integrated, stress testing, Performance evaluation, Defect density, Test case
preparations, Quality Assurance, Quality control, Statistical Quality control, Software
Defects, reviews, SQA plan, Review/inspection procedure document, checklists,
Recording Defects and Actions.
5. Software Project Management and Process Frameworks Project Management Processes,Project Estimations, Project Planning and Tracking, scheduling, Scope Management,
Communications Management, Cost Management, Integrated Change Management, Fivelevels of CMM, Introduction to CMM, Introduction to six sigma, DMAIC model
Text Books
1. Pressman R.S, Software Engineering: A Practitioner's Approach (6th Edition), McGrawHill, 2005
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2. Ian Sommerville, Software Engineering (7th Edition), Pearson Education Asia, 2004References
3. Steve Schach, Classical and Object Oriented Software Engineering (6th Edition),McGraw-Hill International, 2005
ITMS2312: Geographical Information Systems
Core/Elective: Elective Semester: III Credits: 3
1. Introduction and Overview of Geographical Information Systems: Fundamental Conceptsof GIS, functional components of GIS, applications of GIS, contributing and allied
disciplines, maps, map projections and coordinate systems, Important GIS software tools.
2. Data Models and Data Sources of GIS: Automated cartography versus GIS, concept ofspatial data models (vector, raster, grid, TIN), attribute data model, major data feeds to
GIS and their characteristics, maps, GPS, images, databases, commercial data, locating
and evaluating data, data formats, data quality, metadata, database concepts and
components, databases and GIS
3. GIS Data Management: Managing Vector and Rater data, Creating and editing vectordata, managing attribute data
4. Spatial Modeling and Analysis: GIS analytical functions, database query, overlay, proximity analysis, network analysis, digital terrain model, statistical and tabular
analysis
5. Modern Trends in GIS: Open Geo-spatial Consortium (OGC), Open sources GIS tools,Interoperability, map servers and spatial databases, Internet map servers, configuration,
authoring and publishing the maps, designing interfaces.
Text Books
1. P.A. Burrough and R.A. McDonnell, Principles of Geographical Information Systems,2nd edition, Oxford University Press, 1998.
2. Kang-Tsung Chang, Introduction to Geographic Information Systems, 3rd edition,McGraw Hill, 2006.
3. Nicholas Chrisman, Exploring Geographic Information Systems, 2ndedition, Wiley, 2001.References
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4. Elliott D. Kaplan and Christopher Hegarty, Understanding GPS: Principles andApplications, 2nd edition, Artech House Publishers, 2005.
5. Anji M. Reddy, Textbook of Remote Sensing and Geographical Information Systems, B.S.Publications, Hyderabad, 2000.
ITMS2313: Computational Biology
Core/Elective: Elective Semester: III Credits: 3
1. Basic probability and statistics, Markov processe, Dynamic programming2. Genetic algorithms, Exact and approximation algorithm, Data structures (strings and
trees)
3. Regression analysis, Programming4. Basic biochemistry: structure of amino acids, proteins and gene, Evolution, mutation,
Comparative genomics, Gene expression and regulation
5. ProteomicS, Neuro-informaticsText Books
1. R. Durbin, S. Eddy et al., Biological Sequence Analysis: Probabilistic models of proteinsand nucleo-acids, Cambridge, 1998.
2. T.M. Cover and J.A. Thomas, Elements of Information theory, Wiley, 2006.3. Dan Gusfield, Algorithms on Strings, Trees and Sequences Computer Sciences and
Computational Biology, Cambridge University Press, 1997.
References
4. Pavel A. Pevzner, Computational Molecular Biology: An Algorithmic Approach, MITPress, 2000.
5. Malcolm Campbell and Laurie J. Heyer, Genomics, Proteomics and Bioinformatics,Pearson, 2007.
ITMS2314: Embedded Systems
Core/Elective: Elective Semester: III Credits: 3
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1. Introduction to Embedded Systems: Introduction, overview, characteristics of embeddedcomputing applications, concept of real time systems, challenges in embedded systems
2. Embedded System Architecture: Instruction set architecture, CISC and RISC instructionset architecture, basic embedded processor, microcontroller architecture, CISCexamples, 8051, RISC example, ARM, DSP processors, Harvard architecture, PIC,
memory system architecture, caches
3. Memory Management: virtual memory, memory management, unit and addresstranslation, I/O sub-system, busy-wait I/O, DMA, interrupt driven I/O, co-processors and
hardware accelerators, processor performance enhancement, pipelining, super-scalar
execution
4. Designing Embedded Computing Platform: Using CPU bus, bus organization, memorydevices and their characteristics, RAM, ROM, UVROM, EEPROM, ash memory, DRAM,
I/O devices, timers and counters, watchdog timers, interrupt controllers, A/D and D/Aconverters, displays, keyboards, component interfacing, memory interfacing, I/O device
interfacing, designing with processors, system architecture, hardware design, FPGA
based design
5. ARM Architecture: Registers, modes, exception handling, instruction sets, coprocessors,thumb, jazelle, ARM processor core, ARM7TDMI and ARM9TDMI pipelines, datapaths
and instruction decoding, overview of ARM9E-S, ARM10, StrongARM and Xscale, ARM
developer suite (ADS) overview, ARM and Thumb instruction sets
Text Books
1. Jonathan W. Volvano, Embedded Microcomputer Systems: Real-Time Interfacing, 2ndedition, CENGAGE-Engineering, 2006.
2. Muhammed Ali Mazidi, Janice Mazidi and Rolin McKinlay, 8051 Microcontroller andEmbedded Systems, 2nd edition, Prentice Hall, 2005.
References
3. Kenneth J. Ayala, 8051 Microcontroller, 3rd edition, Thomson, 2005.4. Andrew Sloss, Dominic Symes and Chris Wright, ARM System Developers Guide:
Designing and Optimizing System Software (The Morgan Kaufmann Series in Computer
Architecture and Design), 2004.
ITMS2315: Artificial Intelligence and Software Agents
Core/Elective: Elective Semester: III Credits: 3
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1. Introduction: The concept of AI, approaches to AI, brief history of AI an overview of AI,introduction to artificial neural networks, ES reactive machines: perception and action,
representing and implementing action functions, ANN models, gradient descent methods,
the Widrow Hoff procedure, generalized delta rule, back propagation, Hopfield andKohenens net
2. Search Algorithms: Search in State Spaces: State space approach, state space graph,depth first, breadth first search, iterative deepening, backtracking, heuristic search, A*
algorithm, heuristic functions and search efficiency, approximate searches, learning
heuristic functions
3. Knowledge Representations: Knowledge Representation and Reasoning: Thepropositional calculus, rules of inferences, predicate logic, predicate calculus, semantics,
quantifications, Learning and Acting Bayes Nets: Learning Bayes Nets, probabilistic
inference and actions
4. Fuzzy Sets and Logics: Fuzzy sets, fuzzy operations, membership functions, fuzzification, fuzzy decision making, pattern and fuzzy classification, clustering, c-means algorithm,
genetic algorithm
5. Software Agents: E-mail filter agents, mobile agents, agents programming, cooperatingagents, semantic web, recent trends in AI and applications
Text Books
1. N.J. Nilson, Artificial Intelligence: A New Synthesis, Morgan Kauffmann Publishers,1998.
2. Timothy J. Ross, Fuzzy Logic with Engineering Applications, McGraw Hill, 1995.3. D.W. Patterson, Introduction to AI and Expert Systems, Prentice Hall of India, 1992.
References
4. George J. Klir and Bo Yuan, Fuzzy Sets and Fuzzy Logic Theory and Applications,Prentice Hall of India, 1995.
5. B. Yegnanarayana, Artificial Neural Networks, Prentice Hall of India, 1999.
ITMS2316: Digital Signal Processing
Core/Elective: Elective Semester: III Credits: 3
1. Classification of Signals and Systems:
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Introduction, classification of signals, singularity functions, amplitude and phase spectra,
classification of systems, simple manipulations of discrete-time signals, analog-to-digital
conversion of signals. Fourier Analysis of Periodic and Aperiodic Continuous-Time
Signals and Systems: trigonometric Fourier series, complex form of Fourier seriesParsevals identity for Fourier series, power spectrum of a periodic function, Fourier
transform, Fourier transform of some important signals, power and energy signals
2. Applications of Laplace Transform to System Analysis: Introduction, definition of Laplace transform, region of convergence (ROC), initial and final value theorems,
convolution integral, table of Laplace transforms, partial fraction expansions, network
transfer function, s-plane poles and zeros, Laplace transform of periodic functions, and
application of Laplace transformation in analyzing networks.
3. z-transforms and Linear Time Invariant Systems: Introduction, definition of the z-transform, properties of the z-transform, evaluation of the inverse z-transform, properties
of a DSP system, difference equation and its relationship with system function, impulseresponse and frequency response Discrete and Fast Fourier Transforms: Discrete
convolution, discrete time Fourier transform (DTFT), fast Fourier transform (FFT),
computing an inverse DFT by doing a direct DFT, composite-radix FFT, fast convolution
and correlation
4. Finite Impulse Response (FIR) Filters: Introduction, magnitude response and phaseresponse of digital filters, frequency response of linear phase FIR filters, design
techniques for FIR filters and design of optimal linear phase FIR filters
5. Infinite Impulse Response (IIR) Filters: Introduction, IIR filter design by approximationof derivatives, IIR filter design by impulse invariant method, IIR filter design by bilinear
transformation, butterworth filters, Chebyshev filters, inverse Chebyshev filters, ellipticfilters, frequency transformation
Realization of Digital Linear Systems:
Introduction, basic realization block diagram and the signal-flow graph, basic structures
for IIR systems, basic structures for FIR systems
References
1. S. Salivahanan, A. Vallvaraj and C. Gnanapriya, Digital Signal Processing, TataMcGraw-Hill, New Delhi, 2000
2. Sanjit K. Mitra, Digital Signal Processing, 3/e, Tata McGraw-Hill, New Delhi, 20063. A.V. Oppenheim and R.W. Schaffer, Digital Signal Processing, Prentice hall, NJ, 1975
ITMS2317: Scientific Computing
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Core/Elective: Elective Semester: III Credits: 3
1. Introduction to scientific Computing, Approximations in Scientific Computing, Computer Arithmetic, Linear Systems, Solving Linear systems, Special types of linear systems, Linear Least Squares, Problem transformations, Orthogonalization methods, Singular
Value Decomposition, Comparison of methods
2. Eiegen Value Problems, Computing Eiegen Values and Eiegen Vectors, GeneralizedEigen Value Problem
3. Non-linear Equations, Non-linear Equations in one dimension, Systems of Non-linearequations, Optimization problems, Unconstrained Optimizations, Non-linear least
squares, Interpolation, Polynomial interpolation
4. Numerical Integration and differentiation, Numerical quadrature, Ordinary differentialequations, Numerical Solutions to Ordinary Differential Equations, Boundary problemfor ODEs, Partial differential equations
5. Fast Fourier Transform, Trigonometric Interpolation, FFT Algorithm, Applications ofDFT, Wavelets, Random numbers and simulation, stochastic simulation, randomness and
random numbers, random number generators
References
1. M. T. Heath, Scientific Computing, , The McGraw-Hill Companies, Inc.; 2nd edition,2002
2. R. Hamming, Numerical Methods for Scientists and Engineers, Dover Publications; 2edition, 1987
3. Gregoire Allaire and Alan Craig, Numerical Analysis and Optimization: An Introductionto Mathematical Modeling and Numerical Simulation (Numerical Mathematics and
Scientific Computation) , Oxford University Press, USA, 2007
ITMS23E8: Software Project Management
Core/Elective: Elective Semester: III Credits: 3
1. Introduction to Software Project Management: Project Definition Scope of ProjectManagement-Contract Management Activities Covered By Software
Project Management Overview Of Project Planning Stepwise Project Planning.
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2. Project Evaluation: Strategic Assessment Technical Assessment Cost Benefit AnalysisCash, Flow Forecasting Cost Benefit Evaluation Techniques Risk Evaluation.
3. Activity Planning: Objectives Project Schedule Sequencing and Scheduling Activities Network, Planning Models Forward Pass Backward Pass Activity Float Shortening,
Project Duration Activity on Arrow Networks Risk Management Nature Of Risk Types Of
Risk Managing Risk Hazard Identification Hazard Analysis, Risk Planning And Control.
4. Monitoring and Control: Creating Framework Collecting The Data Visualizing ProgressCost, Monitoring Earned Value Prioritizing Monitoring Getting Project Back To Target
Change Control Managing Contracts Introduction Types Of Contract Stages In Contract
Placement Typical Terms Of A Contract Contract Management Acceptance.
5. Managing People and Organizing Teams: Introduction Understanding BehaviorOrganizational Behavior: A Background Selecting The Right Person For The JobInstruction In The Best, Methods Motivation The Oldman Hackman Job Characteristics
Model Working In Groups Becoming A Team Decision Making Leadership
Organizational Structures Stress Health And Safety Case Studies.
Text Books
1. Bob Hughes, Mikecotterell, Software Project Management, Third Edition, Tata McGrawHill, 2004
.
2. Ramesh, Gopalaswamy, Managing Global Projects, Tata McGraw Hill, 2001.References
3. Royce, Software Project Management, Pearson Education, 1999.4. Jalote, Software Project Management in Practice, Pearson Education, 2002.