UNIVERSITY DEPARTMENTS
ANNA UNIVERSITY :: CHENNAI 600 025
REGULATIONS – 2008
B.E. COMPUTER SCIENCE AND ENGINEERING
SEMESTER V
CODE NO COURSE TITLE L T P C
THEORY
CS9301 Object Oriented Analysis and Design 3 0 0 3
CS9302 Theory of Computation 3 0 0 3
CS9303 System Software Internals 3 0 0 3
CS9304 Artificial Intelligence 3 0 0 3
CS9305 Data Communication and Computer Networks 3 1 0 4
Elective I 3 0 0 3
PRACTICAL
CS9306 Computer Networks Laboratory 0 0 3 2
CS9307 Case Tools Laboratory 0 0 3 2
GE9371 Communication Skills and Soft Skills lab 0 0 2 1
CS 9301 OBJECT ORIENTED ANALYSIS AND DESIGN L T P C
3 0 0 3
AIM:
To study object oriented analysis and design and the techniques needed to apply them.
OBJECTIVES:
To study the concepts of modelling in object oriented context.
To learn about the Object Constraint Language.
To study and learn how to apply analysis techniques and methodologies including
Use cases, System Sequence Diagrams.
To study and learn how to apply design techniques and methodologies including
Interaction Diagrams, Class Diagrams.
To study implementation related issues.
To study and learn how to apply advanced techniques including Architectural Analysis
and Design Patterns.
UNIT I INTRODUCTION 8
Introduction – Modelling as a design technique – UML diagrams - Class modeling –
Object Constraint Language – State modeling – Interaction Modeling
UNIT II OVERVIEW OF USECASES 9
Inception – Evolutionary Requirements – Use Cases – Other Requirements – Domain
Models – System Sequence Diagrams – Operation Contracts
UNIT III MODELING AS DESIGN TECHNIQUE 10
Requirements to Design – Logical Architecture and UML Package Diagrams – Object
Design – Interaction Diagrams – Class Diagrams – Designing Objects with
Responsibilities – Object Design Examples – Designing for Visibility
UNIT IV MAPPING 8
Mapping designs to code – Test Driven development and refactoring – UML Tools and
UML as blueprint
UNIT V PATTERNS 10
More Patterns – Analysis update – Objects with responsibilities – Applying design
patterns – Architectural Analysis – Logical Architecture Refinement – Package Design –
Persistence framework with patterns
TOTAL: 45 PERIODS
TEXTBOOKS:
1. Michael Blaha and James Rumbaugh, “Object-oriented modeling and design with
UML”, Prentice-Hall of India, 2005. (Unit 1)
2. Craig Larman. “Applying UML and Patterns – An introduction to Object-Oriented
Analysis and Design and Iterative Development”, 3rd ed, Pearson Education, 2005.
REFERENCES:
1. Booch, Grady,”Object Oriented Analysis and Design”, 2
nd
ed. Pearson Education.
2000.
2. Ali Bahrami, “Object Oriented Systems Development”, McGraw-Hill, 1999.
3. Fowler, Martin. UML Distilled. 3
rd
ed. Pearson Education. 2004.
4. Lunn, Ken, “Software development with UML”,Palgrave Macmillan. 2003.
5. O’Docherty, Mike,”Object-Oriented Analysis & Design”,Wiley. 2005.
CS 9302 THEORY OF COMPUTATION L T P C
3 0 0 3
AIM:
To have foundation on automata languages and grammar.
OBJECTIVES:
Develop the concepts and skills necessary to be able to evaluate the compatibility
and undecidability.
UNIT I AUTOMATA 9
Introduction to formal proof – Additional forms of proof – Inductive proofs –Finite
Automata (FA) – Deterministic Finite Automata (DFA) – Non-deterministic Finite
Automata (NFA) – Finite Automata with Epsilon transitions.
UNIT II REGULAR EXPRESSIONS AND LANGUAGES 9
Regular Expression – FA and Regular Expressions – Proving languages not to be
regular – Closure properties of regular languages – Equivalence and minimization of
Automata.
UNIT III CONTEXT-FREE GRAMMARS AND LANGUAGES 9
Context-Free Grammar (CFG) – Parse Trees – Ambiguity in grammars and languages –
Definition of the Pushdown automata – Languages of a Pushdown Automata –
Equivalence of Pushdown automata and CFG– Deterministic Pushdown Automata.
UNIT IV PROPERTIES OF CONTEXT-FREE LANGUAGES 9
Normal forms for CFG – Pumping Lemma for CFL – Closure Properties of CFL – Turing
Machines – Programming Techniques for TM.
UNIT V UNDECIDABILITY 9
A language that is not Recursively Enumerable (RE) – An undecidable problem that is
RE – Undecidable problems about Turing Machine – Post’s Correspondence Problem –
The classes P and NP.
TOTAL: 45 PERIODS
TEXT BOOK
1. J.E. Hopcroft, R. Motwani and J.D. Ullman, “Introduction to Automata Theory,
Languages and Computations”, second Edition, Pearson Education, 2003.
REFERENCES:
1. H.R. Lewis and C.H. Papadimitriou, “Elements of the theory of Computation”,
Second Edition, Pearson Education, 2003.
2. J. Martin, “Introduction to Languages and the Theory of Computation”, Third Edition,
Tata Mc Graw Hill, 2003.
3. Micheal Sipser, “Introduction of the Theory and Computation”, Thomson Brokecole,
1997.
CS 9303 SYSTEM SOFTWARE INTERNALS LT P C
3 0 0 3
AIM
To study the internal structures and methodologies used in System Software
OBJECTIVES
To study the design and implementation issues in implementing assemblers.
To study the role of linkers and loaders and the interaction with hardware.
To study how macroprocessors work, and a brief introduction to compilers.
To study various issues in the design of Virtual Machines
To study the techniques used in other system software contexts such as emulators,
process virtual machines, profiling, migration and grids.
UNIT I ASSEMBLERS 9
Review of Computer Architecture – Machine Instructions and Programs – Assemblers –
Basic Assembler Functions – Assembler Features – Assembler Design Options
UNIT II LOADERS AND LINKERS 10
Loaders and Linkers – Basic Loader Functions – Machine-Dependent Loader Features –
Machine-Independent Loader Features – Loader Design Options – Architectural Issues
– Object Files – Storage Allocation – Symbol Management – Libraries – Relocation –
Loading and Overlays – Shared Libraries – Dynamic Linking and Loading – Advanced
Techniques 24
UNIT III MACROPROCESSORS AND COMPILERS 8
Macroprocessors – Basic Macro Processor Functions – Machine-Independent Macro
Processor Features – Macro Processor Design Options – Basic Compiler Functions –
Grammars – Lexical Analysis – Syntactic Analysis – Code Generation
UNIT IV VIRTUAL MACHINES 9
Introduction to Virtual Machines (VM) – Pascal P-Code VM – Object-Oriented VMs –
Java VM Architecture – Common Language Infrastructure – Dynamic Class Loading –
Security – Garbage Collection – Optimization
UNIT V PROCESS VIRTUAL MACHINES 9
Emulation – Interpretation and Binary Translation – Instruction Set Issues – Process
Virtual Machines – Profiling – Migration – Grids – Examples of real world
implementations of system software
TOTAL: 45 PERIODS
TEXT BOOKS:
1. Leland L. Beck, “System Software”, 3
rd
ed., Pearson Education, 1997.
2. John R. Levine, “Linkers & Loaders”, Morgan Kauffman, 2003.
3. James E Smith and Ravi Nair, “Virtual Machines”, Elsevier, 2005.
REFERENCES:
1. Alfred V Aho, Ravi Sethi, Jeffrey D Ullman, “Compilers”, Pearson Education, 1986.
2. Robert W. Sebesta, “Concepts of Programming Languages”, 7
th
ed., Pearson
Education, 2006.
3. Terrance W Pratt, Marvin V Zelkowitz, T V Gopal, “Programming Languages”, 4
th
ed., Pearson Education, 2006.
4. Carl Hamacher, Zvonko Vranesic, Safwat Zaky, “Computer Organization”, 5
th
ed.,
McGraw Hill, 2002.
5. Silberschatz, Galvin, Gagne, “Operating System Concepts”, 6
th
ed., Wiley, 2003.
CS 9304 ARTIFICIAL INTELLIGENCE L T P C
3 0 0 3
AIM:
The aim of this course is to provide an introduction to some basic issues and algorithms
in artificial intelligence (AI). The course also provides an overview of Intelligent agent
design, where agents perceive their environment and act rationally to fulfill their goals.
The course approaches AI from an algorithmic, computer science-centric perspective.
OBJECTIVES:
To be familiar with the history of AI, philosophical debates, and be able to discuss
the potential and limitations of the subject in its current form.
To identify the kind of problems that can be solved using AI technique: to know the
relation between AI and other areas of computer science.
To have knowledge of generic problem-solving methods in AI.
To understand the basic techniques of knowledge representation and their use.
To know what the basic components of an intelligent agent are, and how this relates
to other advanced subjects such as information retrieval, database systems,
computer vision, robotics, human-computer interaction, reactive systems etc.
To be able to implement basic decision making algorithms, including search-based
problem solving techniques, and first-order logic. 25
To know the basic issues in machine learning, and be able to apply straightforward
techniques to learn from observed data.
To be able to explain the difficulty of computer perception with examples from
different modalities, and be able to show how perception affects intelligent systems
design.
UNIT I INTRODUCTION 9
Intelligent Agents –Environments – Behavior – Structure – Artificial Intelligence –
Present and Future - Problem Solving –agents – examples– uninformed search
strategies – Avoiding repeated states – searching with partial information.
UNIT II SEARCHING TECHNIQUES 9
Informed search strategies –greedy – best first – A* - local search algorithms and
optimization – local search in continuous spaces – Constraint satisfaction problems
(CSP) – Backtracking search and Local search – Structure – Adversarial Search –
Games – Optimal decisions in games – Alpha – Beta Pruning – imperfect real-time
decision games – elements of chance.
UNIT III KNOWLEDGE REPRESENTATION AND REASONING 9
Logical Agents – Wumpus world - Propositional logic - First order logic - syntax and
semantics – Using first order logic – Inference – forward chaining – backward chaining–
Knowledge representation – Ontological Engineering – Categories and objects –
Actions – Simulation and events – Mental events and mental objects.
Reasoning with Default Information – Truth Maintenance Systems – Reasoning with
Uncertain Information – Axioms of Probability – Independence – Bayes’ Rule and it’s
use.
UNIT IV LEARNING 9
Learning from observations – forms of learning – Inductive learning - Learning decision
trees – Ensemble learning – Knowledge in learning – Logical formulation of learning –
Explanation based learning – Learning using relevant information - Reinforcement
learning – Passive reinforcement learning – Active reinforcement learning –
Generalization in reinforcement learning.
UNIT V APPLICATIONS 9
Communication – Communication as action – Formal grammar for a fragment of English
– Syntactic analysis – Augmented grammars – Semantic interpretation - Perception –
image Formation – Image Processing – Object Recognition – Robotics – Robotic
Perception – Planning –Moving –Robotic Software Architecture.
TOTAL: 45 PERIODS
TEXT BOOK:
1. Stuart Russell, Peter Norvig, “Artificial Intelligence – A Modern Approach”, Second
Edition, Pearson Education, 2004.
REFERENCES:
1. Nils J. Nilsson, “Artificial Intelligence: A new Synthesis”, Harcourt Asia Pvt. Ltd.,
2000.
2. Elaine Rich and Kevin Knight, “Artificial Intelligence”, Second Edition, Tata McGraw
Hill, 2003.
3. George F. Luger, “Artificial Intelligence-Structures And Strategies For Complex
Problem Solving”, Pearson Education, 2002.
CS 9305 DATA COMMUNICATION AND COMPUTER NETWORKS L T P C
3 1 0 4
AIM :
To understand the concepts of data communication and computer networks
OBJECTIVES:
To grasp the principles of data communication.
To understand the layering concepts in computer networks.
To understand the functions of each layer.
To have knowledge in different applications that use computer networks.
UNIT I PHYSICAL LAYER 11 + 3
Data transmission – Transmission media – Signal encoding techniques – Multiplexing –
Spread spectrum
UNIT II DATA LINK LAYER 11 + 3
Network architecture – Layers – Channel access on links – SDMA – TDMA - FDMA –
CDMA – Hybrid multiple access techniques - Issues in the data link layer - Framing –
Error correction and detection – Link-level Flow Control – Medium access – Ethernet –
Token ring – FDDI – Wireless LAN – Bridges and Switches
UNIT III NETWORKING LAYER 9 + 3
Circuit switching – Packet switching – Virtual circuit switching – IP – ARP – RARP –
DHCP – ICMP – Routing algorithms – RIP – OSPF – Subnetting – CIDR – Interdomain
routing – BGP – IPv6 – Multicasting – Congestion avoidance in network layer
UNIT IV TRANSPORT LAYER 7 + 3
UDP – TCP – Flow Control – Congestion control – Queuing discipline – Congestion
avoidance – QoS – RPC
UNIT V APPLICATIONS 7 + 3
Email (SMTP, MIME, POP3, IMAP) – HTTP – DNS- SNMP – Telnet – FTP
L: 45, T: 15, TOTAL = 60 PERIODS
TEXT BOOKS:
1. William Stallings, “Data and Computer Communications”, Eighth Edition, Pearson
Education, 2007.
2. Larry L. Peterson, Bruce S. Davie, “Computer Networks: A Systems Approach”,
Fourth Edition, Morgan Kaufmann Publishers Inc., 2007.
3. James F. Kurose, Keith W. Ross, “Computer Networking, A Top-Down Approach
Featuring the Internet”, Third Edition, Addison Wesley, 2005.
REFERENCES:
1. Nader F. Mir, “Computer and Communication Networks”, Pearson Education, 2007.
2. Douglas E. Comer, “Computer Networks and Internets with Internet Applications”,
Fourth Edition, Pearson Education, 2003.
3. Andrew S. Tanenbaum, “Computer Networks”, Fourth Edition, Pearson Education,
2003.
4. Wayne Tomasi, “Introduction to Data Communications and Networking”, Pearson
Education, First Edition, 2002.
CS 9306 COMPUTER NETWORKS LABORATORY L T P C
0 0 3 2
AIM:
To have hands-on experience in network programming and to use simulation tools to
analyse network protocols.
OBJECTIVES:
To learn socket programming.
To use simulation tools.
To analyse the performance of protocols in different layers in computer networks
using simulation tools.
EXPERIMENTS IN THE FOLLOWING
1. Applications using TCP Sockets like
a. Echo client and echo server.
b. File transfer.
c. Remote command execution.
d. Chat.
e. Concurrent server.
2. Applications using UDP Sockets like
a. DNS.
b. SNMP.
3. Applications using Raw Sockets like
a. Ping.
b. Traceroute.
4. RPC
5. Experiments using simulators like OPNET:
a. Performance comparison of MAC protocols.
b. Performance comparison of Routing protocols.
Study of TCP/UDP performance.
TOTAL: 45 PERIODS
CS 9307 CASE TOOLS LABORATORY L T P C
0 0 3 2
AIM:
Scope of this lab is to understand the application of case tools, which focuses on the
software engineering activities.
OBJECTIVES:
• Software requirements analysis and specification
• Software design
• Software implementation
• Software testing and maintenance
• Communication skills and teamwork
• Modeling techniques and CASE tools
• Software project planning and management 28
EXPERIMENTS IN THE FOLLOWING TOPICS
1. Study of case tools such as rational rose or equivalent tools.
2. Requirements
Implementation of requirements engineering activities such as elicitation,
validation, management using case tools
4. Analysis and design
Implementation of analysis and design using case tools.
5. Study and usage of software project management tools for cost estimation and
scheduling
6. Documentation generators - Study and practice of Documentation generators.
7. Data modeling using automated tools.
8. Practice reverse engineering and re engineering using tools.
9. Exposure towards test plan generators, test case generators, test coverage and
software metrics.
10. Meta modeling and software life cycle management.
TOTAL: 45 PERIODS
GE 9371 COMMUNICATION SKILLS AND SOFT SKILLS L T P C
LABORATORY FIFTH / SIXTH SEMESTER 0 0 2 1
AIM
To enhance the overall capability of students and to equip them with the necessary
Communication Skills and Soft Skills that would help them excel in their profession.
OBJECTIVES
To equip students of engineering and technology with effective speaking and listening
skills in English.
To help them develop their soft skills and interpersonal skills, which will make the
transition from college to workplace smoother and help them excel in their jobs.
To enhance the performance of students at Placement Interviews, Group Discussions
and other recruitment exercises.
A. Viewing and discussing audio-visual materials (6 periods)
1. Resume / Report Preparation / Letter Writing 2
Letter writing – Job application with Resume - Project report - Email etiquette.
2. Presentation skills 1
Elements of effective presentation – Structure of presentation - Presentation tools
– Body language.
3. Soft Skills
Time management – Stress management – Assertiveness – Negotiation strategies. 29
4. Group Discussion 1
Group discussion as part of selection process, Structure of group discussion –
Strategies in group discussion – Mock group discussions.
5. Interview Skills 1
Kinds of interviews – Interview techniques – Corporate culture – Mock interviews.
(Career Lab Software may be used for this section).
Note: Career Lab software may be used to learn the skills, to be applied in the
practice session.
B. PRACTICE SESSION (24 periods)
1. Resume / Report Preparation / Letter writing: Students prepare their (4)
own resume and report.
2. Presentation Skills: Students make presentations on given topics. (8)
3. Group Discussion: Students participate in group discussions. (6)
4. Interview Skills: Students participate in Mock Interviews (6)
TOTAL : 30 PERIODS
REFERENCES
1. Anderson, P.V, “Technical Communication”, Thomson Wadsworth, Sixth Edition,
New Delhi, 2007.
2. Prakash P, “Verbal and Non-Verbal Reasoning”, Macmillan India Ltd., Second
Edition, New Delhi, 2004.
3. John Seely, “The Oxford Guide to Writing and Speaking”, Oxford University Press,
New Delhi 2004.
4. David Evans, “Decisionmaker”, Cambridge University Press, 1997.
5. Thorpe, E and Thorpe, “S Objective English”, Pearson Education,
Second Edition, New Delhi 2007.
6. Turton, N.D and Heaton, J.B, “Dictionary of Common Errors”, Addision Wesley
Longman Ltd., Indian reprint 1998.
For more information contact us via Studentstrainer@gmail.com. Caring is sharing, show your caring to us by sharing our post in social sites and keep like us,,,
{ 0 comments... read them below or add one }
Post a Comment
Enter your comments here