STUDENT KIT MCA – Fifth Semester July-December, 2009 Devi Ahilya Vishwavidyalaya School of Computer Science & IT “We make things happen . . .” Producing world – class IT Professionals Since 1986 www.scs.dauniv.ac.in MISSION OF SCS • To produce world-class professionals who have excellent analytical skills, communication skills, team building spirit and ability to work in cross cultural environment. • To produce international quality IT professionals, who can independently design, develop and implement computer applications. • Professionals who dedicate themselves to mankind. SCHOOL OF COMPUTER SCIENCE & IT DEVI AHILYA VISWAVIDYALAYA Takshashila Campus, Khandwa Road, Indore – 452017 Tel. (0731) – 2470027, 2461548 Fax : (0731) – 2763618 Email: [email protected]
Transcript
STUDENT KIT
MCA – Fifth Semester
July-December, 2009
Devi Ahilya VishwavidyalayaSchool of Computer Science & IT
“We make things happen . . .”
Producing world – class
IT Professionals
Since 1986
www.scs.dauniv.ac.in
MISSION OF SCS
• To produce world-class professionals who have excellent analytical skills, communication skills, team building spirit and ability to work in cross cultural environment.
• To produce international quality IT professionals, who can independently design, develop and implement computer applications.
• Professionals who dedicate themselves to mankind.
SCHOOL OF COMPUTER SCIENCE & ITDEVI AHILYA VISWAVIDYALAYA
College/Department School of Computer Science & Information Technology
Code Subject L T P C Internal Practical/Project
End Sem
Total
CS-5216
Design and Analysis of Algorithms
3 1 2 5 30 20 50 100
CS-6623
Mobile and Wireless Systems
3 1 0 4 40 - 60 100
CS-4409
Enterprise Resource Planning
3 1 0 4 40 - 60 100
CS-5413
Data Mining and Warehousing
3 1 4 6 30 20 50 100
Project 4Comprehensive Viva 4
27
CS-5413 Data Mining & Data Warehousing
1. Course title and code: CS-5413 Data Mining & Data Warehousing
2. Credit hours-63. Program(s) in which the course is offered. MCA-V4. Name of faculty member responsible for the course- Ms. Shraddha Masih
5. Level/year at which this course is offered – Post Graduate6. Pre-requisites for this course – Good familiarity with relational databases and programming. Basic knowledge of Data structures, Internet and web technology & Statistics.
7. Co-requisites for this course The course will be structured around a comprehensive set of computer assignments to enable you to get hands on experience. Our tool of choice will be any data mining freeware. 8. Date of approval of the course specification within the institution
9. Location if not on main campus
B Aim and Objectives
1. Aim The main aim of this course is to clear the concept and applications of data mining and data warehousing. Data warehousing focuses on storage and management of overwhelmingly large amounts of data as well as supporting the analysis of data in a multidimensional way. Data mining focuses on inducing compressed representations of data in the form of descriptive and predictive models.
2. Objective• To give students a good overview of the ideas and the techniques which are behind
recent developments in the data warehousing • To make students understand On Line Analytical Processing (OLAP) • Learn to create data models• Work on data mining query languages, conceptual design methodologies, and storage
techniques.• Identify and develop useful algorithms to discover useful knowledge out of
tremendous data volumes. Also to determine in what application areas can data mining be applied.
• To motivate, define and characterize data mining as a process.• To survey, and present in some detail, a small range of representative data mining
techniques and tools.
Course Description
DATE TOPIC READINGWeek 1 Unit 1:Introduction: Data Warehouse, Evolution, Definition, Very large
database, Application, Multidimensional Data Model, OLTP vs Data Warehouse, Warehouse Schema, Data Warehouse Architecture.
Chap - 1AKP,Chap - 2AKP,Lecture Notes
Week 2 Unit 1:Data Warehouse Server, Data Warehouse Implementation, Metadata, Data Warehouse Backend Process: Data Extraction, Data Cleaning, Data Transformation, Data Reduction, Data loading and refreshing. ETL and Data warehouse, Metadata, Components of metadata.
Chap- 2 AKP,Lecture Notes
Week 3 Unit 2: Structuring/Modelling Issues, Derived Data, Schema Design, Dimension Tables, Fact Table, Star Schema, Snowflake schema, Fact Constellation, De-normalization, Data Partitioning, Data Warehouse and Data Marts.
Chap- 2 AKP,Lecture Notes
Week 4 Unit 2:SQL Extensions, PLSQL. Chap- 2 AKP,Lecture Notes
Week 5 Unit 2:OLAP, Strengths of OLAP, OLTP vs OLAP, Multi-dimensional Data, Slicing and Dicing, Roll-up and Drill Down, OLAP queries, Successful Warehouse, Data Warehouse Pitfalls, DW and OLAP Research Issues, Tools.
Chap- 2 AKP,Lecture Notes
Week 6 Unit 3: Fundamentals of data mining, Data Mining definitions, KDD vs Data Mining, Data Mining Functionalities, From Data Warehousing to Data Mining, DBMS vs DM, Issues and challenges in Data Mining.
Chap- 3 AKP,Lecture Notes
Week 7 Unit 3: Data Mining Primitives, Data Mining Query Languages. Data Mining applications-Case studies.
Chap- 3 AKP,Lecture Notes
Week 8 Unit 4: Association rules: Methods to discover association rules. Various algorithms to discover association rules like A Priori Algorithm. Partition, Pincer search, Dynamic Item set Counting Algorithm etc.
Chap- 4 AKP,Lecture Notes
Week 9 Unit 5: Cluster Analysis Introduction : Types of Data in Cluster Analysis, A Categorization of Major Clustering Methods, Partitioning Algorithms, Hierarchical and Categorical clustering,
Week 11 Unit 6: Web Mining , Web content mining, Web Structure mining, Text mining.
Chap- 8 AKPLecture Notes
Week 12 Unit 6: Temporal Data Mining, Spatial Data Mining. Chap- 9 AKPLecture Notes
Week13 Lab work Presentations comprising of mini projects using freeware data mining tools. Reviewing practical and assignments.Final exam
Subject Learning Outcomes:
Development of Learning Outcomes in Domains of Learning (i) Description of knowledge to be acquired :
A student completing course unit 1 should:
1) Have an understanding of the foundations, the design, the maintenance, the evolution, and the use of data warehouses
2) To understand data warehouse architecture.3) To understand the step by step process of data warehouse development including data extraction,
cleaning, loading and refreshing.4) To understand various issues related to improvement in performance of data warehouse.
A student completing course unit 2 should:
1) Practice SQL & PL/ SQL required in data warehouse environment.2) To master the basic range of techniques for creating, controlling, and navigating dimensional
business databases, by being able to use a powerful tool for dimensional modeling and analysis. 3) Understand multidimensional data model, OLAP, OLAP operations and work on OLAP queries
A student completing course unit 3 should:
1) Understand the fundamentals of data mining Data Mining Functionalities.2) Have an understanding of the data mining process, its motivation, applicability, advantages and
pitfalls. 3) Understand how to move from Data Warehousing to Data Mining, 4) Understand Issues and challenges in Data Mining.5) Understand Data Mining Query Languages and Data Mining applications
A student completing course unit 4 should:
1) Understand different data mining techniques.2) Understand various algorithms to find association rules.3) Have an understanding of the principles, methods, techniques, and tools that underpin successful
data mining applications.
A student completing course unit 5 should:
1) Understand different clustering techniques.2) Understand data mining through Decision Trees, Neural networks and Genetic
Algorithm.
A student completing course unit 6 should:
1) Understand what is Web Mining, Web content mining, Web Structure mining and to know the concept of Text mining.
2) Understand the concept of Temporal Data Mining, Spatial Data Mining.
3) Be able to apply the methods and techniques surveyed in the course using a data mining workbench.
Scheduling of Assessment Tasks for Students
Assessment
Assessment task (eg. essay, test, group project, examination etc.)
Week due Proportion of Final Assessment
1
Test I 06 10
2 Case Study (Seminar) 07 10
3 Test II 12 10
4 Project 15 205 Quizzes Continuous
basis05
6 Classroom interaction and attendance Continuous basis
05
7 End semester exam After completion of the course
40
8 Total 100
Learning Resources
Required Text(s)- 1. Data Mining Techniques – ARUN K PUJARI, University Press2. Data Mining – Concepts and Techniques - JIAWEI HAN & MICHELINE KAMBER Harcourt India.3. Building the Data Warehouse- W. H. Inmon, Wiley Dreamtech India Pvt. Ltd.. 4. The Data Warehouse Life cycle Tool kit – RALPH KIMBALL WILEY STUDENT
EDITION
2. Essential References 1. Data Warehousing in the Real World – SAM ANAHORY & DENNIS MURRAY. Pearson Edn Asia.2. Data Warehousing Fundamentals – PAULRAJ PONNAIAH WILEY STUDENT EDITION3. Data Mining Introductory and advanced topics –MARGARET H DUNHAM, PEARSON EDUCATION
3- Recommended Books and Reference Material (Journals, Reports, etc) (Attach List) Research papers related to data mining and warehousing published in international journals.
4-.Electronic Materials, Web Sites etc
Will be uploaded on www.scs.dauniv.ac.in
ASSIGNMENTS: 1. Search a voluminous data file and understand it.(hint: you may get free data from
internet)2. Replace all tabs with commas from file or vice versa.3. Normalize the data: for each value, set the minimum value to 0 and the maximum
to 100.
4. Transform the data file (text, excel etc) into database.5. Analysis of existing data (semantic correctness, completeness) 6. Use of free ETL tool.7. Review of data mining tools, applications, and algorithms.8. Describe a new application area where data mining algorithms can be applied.
Description should contain application scenario, scale of the problem, existingapproach, data mining algorithm that can be used and the benefits of using thealgorithms.
9. Analysis of various data presentation and visualization formats.
Note: Extra assignments may be given in classroom.
CASE STUDY: A case study on existing data warehouse should be done. Based on the case study, create a subject oriented data warehouse model.
PROJECT (Any One for one team):1. Efficient Implementation of any data mining algorithm.2. Design a data warehouse based on the available data. Integrate the data from the
two separate data sources and import into your data warehouse.3. Research Paper in recent developments in data mining and warehousing.4. Data mining application using any freeware data mining tool.
Deliverables:
a. Project proposal: A one-page description of what you plan to do for your project, due Nov. 1st. Please include:
i. Who is in your group? ii. Project title
iii. Brief description of the problem you'll solve or the question you'll investigate
iv. What data you'll use and where you'll get it?v. Which algorithms/techniques you plan to use?
vi. What you expect to submit at the end of the quarter?b. Final project write up This is a comprehensive description of your
project. You should include the following:
1.Project idea 2.Your specific implementation 3.Key results and metrics of your system 4.What worked, what did not work, what surprised you, and why
c. Final presentation: In the last week of class, each team presents their project to the rest of the class. The presentation should be no more than 15 minutes.
CS- 4409Enterprise Resource Planning
1. Course title and code: Enterprise Resource Planning (CS-4409)
2. Credit hours: Four3. Program(s) in which the course is offered. (If general elective available in many programs indicate this rather than list programs) MCA V semester4. Name of faculty member responsible for the course Ms. Archana Chaudhary
5. Level/year at which this course is offered: III year of learning6. Pre-requisites for this course (if any) Basic understanding of information systems
helpful for managers. 7. Co-requisites for this course (if any) - Information systems for managers and E-commerce8. Date of approval of the course specification within the institution9. Location if not on main campus Not applicable
Aim and Objectives
1. Aim of the CourseThe objective of this course is to help students acquire the basic understanding of the major enterprise wide business processes , their integration through IT enabled applications and to develop a managerial perspective to leverage them for competitive advantage.
2. Briefly describe any course development objectives that are being implemented. (eg increased use of IT or web based reference material, changes in content as a result of new research in the field)Along with the textbook, recent changes will also be incorporated in the course using web-based material. Students will also be given case studies as cases form the crux for this subject.
Course DescriptionWEEK TOPIC UNIT
Week 1 Process view of organization: Introduction to business process, problems of functional division, ERP-introduction.Assignment 1: Discuss manufacturing business process as regards to an enterprise.
Chapter 1 Page no.1-37TB
Week 2 Evolution of Enterprise applications, Technology as process enabler, Mapping an existing process, Process redesign, new process validation.Assignment 2: Discuss accounting process as regards to an enterprise.
Chapter 1 Page no.1-37TB
Week 3 Approaches to process improvement: Salient features of Re-engineering, Re-engineering initiatives, Managerial implications of process Re-engineering efforts, Kaizen.Assignment 3: Discuss sales and distribution business process as regards to an enterprise.
Chapter 1 Page no.38-90TB
Week 4 Total quality management, implementing new process.Assignment 4 : Discuss purchasing business process as regards to an enterprise.
Chapter 3 Page no. 204-211TB
Week5 Critical success factors of re-engineering project , comparison of different approaches.Assignment 5: Fed-Ex e-Procurement journey.
Chapter 1 Page no. 44-61TB
Week6 Introduction to Enterprise Resource Planning: Reasons for the growth of the ERP market, ERP packages role.Assignment 6 :Business case: ERP implementation at BPCL
Chapter 2 Page no. 97-129TB
Week7 Enterprise application implementation projects: Rationale for ERP, Enterprise architecture planning, Selection of an ERP vendor, Contracts with vendors, consultants and employees, ERP project management and monitoring, Pitfalls of ERP packages, ERP implementation lifecycle, Implementation methodology, organizing the implementation.Assignment 7 : Business case: ERP implementation at BPCL
Chapter 2 Page no. 130-157TB
Week8 Overview of ERP modules, ERP market place - SAP AG, PeopleSoft, Baan company, JD Edwards’s world solutions company, Oracle Corporation, ERP and related technologies.Assignment 8 : Supply Chain Applications– SCM Practices (A), Wal-Mart SCM Practices(B)
Chapter 3 Page no.163-214TB
Week9 Supply chain and CRM applications: Overview of supply and demand chain, Supply chain framework, advanced planning systems.Assignment 8 : Supply Chain Applications– SCM Practices (A), Wal-Mart SCM Practices(B)
Chapter 1 Page no.88-90TB
Week10 Introduction to CRM applications, Growth of CRM applications.Assignment 9 : CRM Applications – CRM initiatives at 3M , Mobile CRM , Dow Chemical e-CRM Strategy.
Chapter 5 Page no.277-299TB
Week11 ERP package application: Detailed study of any one ERP package with emphasis On: - Application basics , cross-sectional analysis of the other ERP systems with the application.Assignment 9: CRM Applications – CRM initiatives at 3M , Mobile CRM , Dow Chemical e-CRM Strategy.
Chapter 4 Page no.229-272TB
Week12 Package architecture, understanding of the application with the Business process reference model.Assignment 10: Sears Logistics Management Practices.
Chapter 4 Page no.229-272TB
Week13 Business process integration part IAssignment 10: Sears Logistics Management Practices.
Lecture notes
Week14 Business process integration part I Lecture notes
Subject Learning Outcomes:
Development of Learning Outcomes in Domains of Learning
i An overview of the subject, future scope of the subject, evaluation criteria.ii Students will be acquainted with the concept of business processes, problems of
functional division and a brief ERP introduction.iii Students will have an understanding of the concept of business process reengineering.iv Students will be acquainted with the scope and evolution of ERP systems.v Students will have an understanding of the different approaches of Business Process
Improvement.vi Students will understand Kaizen and Total quality management and how the
philosophies are useful in improving quality.vii Students will have an understanding of supply networks and also how they are helpful
for organizations.viiiStudents will have an understanding of CRM applications and also how they are
helpful for organizations.ix Students will have an understanding of different ERP package applications.
Scheduling of Assessment Tasks for Students
Assessment
Assessment task (eg. essay, test, group project, examination etc.)
Week due Proportion of Final Assessment
1 Test 1 August 2nd
week15%
2. Test 2 September 2nd
week15%
2. Assignments Twice a month 5%
4 Quizzes and Questionnaires October 4th
week5%
5 Final Examination I week of December (Tentative)
60%
Learning Resources
1. Required Text(s) Enterprise Resource Planning –Alexis Leon -Tata McGraw Hill publication.2. References Books :
a)Concepts in Enterprise Resource Planning - Brady , Monk and Wagner – Thomson Learning.b)CRM at the speed of Light .- Greenberg , Paul – TMHc) The E-Marketplace: Strategies for success in B2B commerce – Raisch ,Warren D – McGraw Hill inc.2000.d)ERP strategy – Vinod Kumar Garg , Bharat Vakharia , Jaico
3- Recommended Books and Reference Material (Journals, Reports, etc)
4-.Electronic Materials, Web Sites etc
www.ibm.com/solutions/businesssolutions/erp/
www.sap.com/solutions/business-suite/erp/
www.sap.com/usa/solutions/index.epx5- Other learning material such as computer-based programs/CD, professional standards/regulations
Business Process Integration Part-I and Business Process Integration Part-II
1. Course title and code: Mobile and Wireless Systems (CS-6623).
2. Credit hours: 04.
3. Program(s) in which the course is offered: MCA–V Semester.
4. Name of faculty member responsible for the course: Mr. Anand More.
5. Level/year at which this course is offered: Post Graduate (MCA –V) /III year.
6. Pre-requisites for this course (if any): Computer Networks, Digital Communications.
7. Co-requisites for this course (if any) : Mobile Application Languages, MOS.
8. Date of approval of the course specification within the institution -
9. Location if not on main campus – Main Campus
Aim and Objectives
1. Aim of the Course: Future wireless networks will allow people on the move to communicate with anyone, anywhere, at any time, using a range of multimedia services. Wireless communications will also enable a new class of intelligent home electronics that can interact with each other and with the Internet. The course explains working of wireless systems, mobility supported, and infrastructure for mobile systems.Briefly describe any course development objectives that are being implemented. (eg increased use of IT or web based reference material, changes in content as a result of new research in the field)
Objectives: - To familiarise students with recent wireless technology used. The course will be taught through LCD projector & laboratory experiments on communication for the, therefore the objective is to develop journals for laboratory work.
Course Description
Week TOPIC READING
Week 1 Overview of the emerging field of mobile computing; Historical perspectives (mainly from the perspective of radio), Land mobile vs. Satellite vs. In-building communications systems, RF vs. IR. Assignment -1
B -Ch 1A-Ch 1
Week 2 Characteristic of Cellular Systems, Mobility support in cellular telephone networks, Personal Communications Systems/Personal Communications Networks, Mobile applications, Limitations, Health Concerns, Cordless phone.Assignment -2
B-Ch 5C-Ch 1
Week3 Wireless Personal Area Network, Wireless Local Area Network and Internet Access. Mobility management, Security. Cellular telephony as a case study in network support: hand-off, mobility, roaming, billing/authorization/authentication.Assignment -3
C-Ch 2, 9
Week 4 Mobile communication: Fiber or wire based transmission, Wireless Transmission: Frequencies, Antennas and Signal Propagation, Modulation Techniques, Multiplexing techniques, Coding techniques.Assignment -4
A- Ch 2
Week 5 Cellular structure, Voice Oriented Data Communication: GSM, CDMA.GSM Architecture, Authentication & security, frequency hopping.Assignment -5
A- Ch 4
Week 6 Speech coding, Data communication with PCs, Wireless web browsing, Testing cellular Systems.Case Study on GSM.Assignment -6
B- Ch 10
Week 7 Satellite Systems: History, Application, and Basics of Satellite Systems: LEO, MEO, GEO, Routing, Handover, VSAT, installation & Configuration.
A- Ch 5
Week 8 Cyclic repetition of data, Digital Audio Video Broadcasting, Multi media object transfer Protocol, Wireless LAN topologies, requirements.Assignment -7
A- Ch 6
Week 9 Physical layer, MAC layer, IEEE802.11.HIPERLAN: Protocol architecture, layers, Information bases and networking, Bluetooth.Case Study on Wireless LAN infrastructure.
A- Ch 7
Week 10 Basics of Discrete Event Simulation, Application and Experimentation, Simulation models.Case Study on Performance Evolution of IEEE 802.11 WLAN configuration Using Simulation.Assignment -8
C-Ch 13
Week 11 Economics Benefits of Wireless Networks, Wireless Data Forecast, Charging issues, role of Government, Infrastructure manufacturer, Enabling Applications.Assignment -9
C-Ch 14
Week 12 Mobile IP, goals, assumptions requirements, entities & terminology, IP packet delivery, tunnelling and encapsulation, Feature & formate IPv6, DHCP, TCP over Wireless.
B-Ch12
Week 13 Characteristic of Ad Hoc networks, Applications, need for routing, routing classification, Wireless sensor networks, classification & Fundamental of MAC protocol for wireless sensor networks.Assignment -10
B-Ch 13
Week 14 Mobile operating System, file system, Process, Task, Thread, ISR and IST, CODA, HTTP versus HTML.WML, XML application for wireless handheld devices.
A-Ch11B-Ch 15
Week 15 UWB systems Characteristics, Signal propagations, technology, Mobility management for integrated systems, Current approaches for security.Assignment -11
B-Ch 15
Week 16 Revision, Discussions & End Semester Examinations.
Subject Learning Outcomes:
Development of Learning Outcomes in Domains of Learning: Applications of Wireless systems. Wireless technology has enormous potential to change the way people and things communicate. A wireless communications infrastructure is needed for automated highways and for sensor networks and wireless video will support applications such as distance learning and remote medicine. The course explains working of wireless systems, mobility supported, and infrastructure for mobile systems. The major learning out comes are:1 Introduction to communication systems & their applications.2. Understanding of Wireless transmission techniques, infrastructure and devices.3 Understanding of GSM Architecture and its functions. Uses of cellular systems.4. Concepts of video broadcasting, Wireless LAN topologies.5. Application and uses of protocol and developing wireless LAN infrastructure.6. Understanding of Feature & formate of advance IP schemes, economic benefits of technology, Wireless Data Forecast.7. Developing concepts on Characteristics, classification of routing algorithms, Mobile operating System and applications. 8. Administration & management of mobile systems, security issues.
Scheduling of Assessment Tasks for Students
Assessment
Assessment task (eg. essay, test, group project, examination etc.)
Week due Proportion of Final Assessment
1 Lab assignment I /Presentation 05 022 Test I 08 103 Lab assignment II/Presentation 12 034 Test II 15 105 Mini project /Presentation 16 056 Performance in tutorials /Presentation Continuous
basis05
7 Classroom interaction and attendance Continuous basis
05
8 End semester exam After completion of the course
60
Learning Resources
1-Required Text(s) A: Mobile Communications author Jochen Schiller, publication John Willy & Sons, Ltd. B: Wireless And Mobile Systems author D P Agrawal & Qing-An zeng, publication Thomson. C: Wireless Networks author P Nicopotidis, publication Addision –Wesley.
2-Essential References(s)1. Mobile Wireless Communications author Mischa Schwartz, publication Cambridge University Press.2. Mobile Computing Principles author Reza B’Far, publication Cambridge University Press. 3-Recommended Books and Reference Material (Journals, Reports, etc) (Attach List) 1. Mobile computing author Prof Rajkaml publications Oxford U. press.4-Electronic Materials, Web Sites etcwww.stanford.edu/class , www.iitk.ac.in 5- Other learning material such as computer-based programs/CD, professional standards/regulations : http://scsintanet/
Assignments:Name of Subject : Wireless & Mobile Systems
Objective : The assignment focuses on wireless and mobile Systems. The topics include digital communication with applications to next generation wireless systems. Students can have, understanding of the concepts.
Format of Assignment • For each assignment , it is expected each student writes a report to :-o Explain her/his observations from the experiment/libray
o Each student is expected to analyze the issues and understand for her/his benefit.
o Report submitted will consists of proper diagram with good presentation in folder.
Sr No. Title of Assignments1 Explain Amplitude Modulation with advantages &
disadvantages.2 Explain Pulse Width Modulation3 Explain Amplitude Shift Keying4 Explain Frequency Shift Keying5 Explain Time Division Multiplexing6 Explain Frequency Modulation (VCO-PLL Type)7 Explain Study of Frequency Reuse (Simulation)8 Explain Design of Cellular Structure (Simulation)9 Explain Installation of V-SAT (Simulation)10 Explain Web browsing in mobile systems 11 Explain VPN Configuration for mobile systems
CS 5216 Design and Analysis of algorithms
1. Course title and code: Design and Analysis of algorithms CS 5216
2. Credit hours 05
3. Program(s) in which the course is offered (If general elective available in many programs indicate this rather than list programs): M.C.A.
4. Name of faculty member responsible for the course : Mr. Deepak Abhyankar
5. Level/year at which this course is offered: M.C.A. (V)
6. Pre-requisites for this course (if any) Data Structures, C language
7. Co-requisites for this course (if any): None
8. Date of approval of the course specification within the institution: Since beginning of the courses
9. Location if not on main campus: Main Campus
Aim and Objectives
1. Aim of the Course:
The course aims to introduce students to the algorithmic solution and analysis of problems that are of fundamental importance in computer science and engineering. These problems will be drawn from areas such as sorting, searching, string matching, data compression, graph theory, algebra and number theory. Moreover, students will also be introduced to computational complexity; the theory of the inherent limitations of feasible computation.
Upon completion of this course the student should be able to:
• learn good principles of algorithm design; • learn how to analyse algorithms and estimate their worst-case and average-case
behaviour (in easy cases); • become familiar with fundamental data structures and with the manner in which
these data structures can best be implemented; become accustomed to the description of algorithms in both functional and procedural styles;
• learn how to apply their theoretical knowledge in practice (via the practical component of the course).
• Apply the algorithm analysis and algorithm design techniques to solve problems;
• Have a sense of the complexities of various problems in different domains.
2. Objectives:
The course objectives are to ensure that students understand: how the worst-case time complexity of an algorithm is defined; how asymptotic notation is used to provide a rough classification of algorithms, and the drawbacks of this notation; how a number of algorithms for fundamental problems in computer science and engineering work and compare with one another; and how there are still some problems for which it is unknown whether there exist efficient algorithms.
Course Description
CLR: Cormen, Leiserson, and Rivest. Algorithms, MIT Press 2001ES: Fundamentals of Computer Algorithms by Ellis Horowitz and Sartaj Sahni (Galgotia Publication 1998SA: Computer Algorithms Introduction to Design & Analysis by Sara Baase and Allen Van Gelder(Pearson Education 1999)
Week
TOPIC READING
1Order Analysis: Objectives of time analysis of algorithms; Big-oh and Theta notations.
Assignments: all exercises of CLR ch1, CLR ch2, CLR ch3
CLR ch1, ch2, ch3
2Master Theorem and its proof, solution of divide and conquer recurrence relations
Assignments: all exercises of CLR ch4
CLR ch4
3Searching, Sorting and Divide and Conquer Strategy:Linear Search, Binary Search
Assignments: all exercises of CLR ch6, ch7
CLR ch6, ch7
4Searching, Sorting and Divide and Conquer Strategy:Merge-sort; Quick-sort with average case analysis. Heapsand heap-sort. Lower bound on comparison-basedsorting and Counting sort.
Assignments: all exercises of CLR ch8, ch9
CLR ch 8, ch 9
5Dynamic Programming: methodology and examples (Fibonaci numbers, Knapsack problem and some other simple examples )
7 Greedy Method: Methodology, examples (lecture Scheduling, process scheduling) and comparison with DP (more examples to come later in graph algorithms)
Assignments: all exercises of CLR ch 16
CLR ch 16
8Greedy Method: Knapsack problem and some othersimple examples
Assignments: Presentation on CLR ch 16
CLR ch 16
9Graph Algorithms: Basics of graphs and their representations. BFS. DFS. Topological sorting.
Assignments: all exercises of CLR ch 22, ch 23
CLR ch 22, ch 23
10 Minimum spanning trees (Kruskal and Prim'salgorithms and brief discussions of disjoint set andFibonacci heap data structures). Shortest Paths (Dijkstra, Bellman-Ford, Floyd-Warshall).
Assignments: all exercises of CLR ch 24, ch 25
CLR ch 24, ch 25
11Hard problems and approximation algorithms. Problemclasses P, NP, NP-hard and NP-complete, deterministic and nondeterministic polynomial-time algorithms.
Assignments: all exercises of CLR ch 34
CLR ch 34
12Approximation algorithms for some NP-complete problems.
Assignments: all exercises of CLR ch 35CLR ch 34
13 Backtracking, Branch and Bound technique ES Ch 7, ch8
14 String Matching, Knave algorithm, KMP algorithm SA Ch 11
15 Parallel Algorithms SA Ch14
Subject Learning Outcomes:
Development of Learning Outcomes in Domains of Learning: Algorithm design and analysisThe course objectives are to:
• Present the concept of algorithm analysis• Study of Notations for Example O notation• Solution of Recurrence Relations• Comprehensive survey of sorting and Searching• Illustrate the idea of Design methods, Divide and conquer, Dynamic programming,
Greedy method• Treatment of graph algorithms• Understanding of NP complete problems and approximation algorithms
Based upon above objectives the course goals / learning outcomes are defined below:
• Define key concepts and key notations: Concept of algorithm analysis, O notation, Ө notation, Solution of divide and conquer recurrence relation using Master theorem, Solution of recurrence relation using generating function technique
• Decent coverage of Searching : Sequential search, QuickSequential search, Binary Search, Interpolation Search, Worst case and average case analysis of above mentioned algorithms
• Comprehensive Coverage of Sorting: Divide and conquer strategy, Merge Sort, Quick Sort
• Fundamental ideas of Greedy method: Greedy method, Comparison with dynamic programming, Knapsack problem, Coin Problem, (more examples to come later in graph algorithms)
• Basics of Graph Algorithms: Breadth first search, Depth first search, Topological sorting, Minimum weight spanning trees, Prim algorithm, Kruskal algorithm, Dijkstra algorithm, Bellman Ford algorithm
• Idea of different problem classes: Class P, Class NP, NP hard problems, NP complete problems, Deterministic and non deterministic polynomial time algorithms, Approximation algorithms for some NP-complete problems for example approximation algorithms for vertex cover problem and Set cover problem
• Important Concepts: Backtracking, Branch and bound technique, solution of n queen problem and night tour problem using above mentioned concepts, String Matching
• Advanced Ideas: Parallel Algorithms
Scheduling of Assessment Tasks for Students
Assessment
Assessment task (eg. essay, test, group project, examination etc.)
Week due Proportion of Final Assessment
1 Test1 8 15
2 Test2 12 15
3 Lab Viva 14 20
4 Final Exam 16 50
Learning Resources
1. Required Text(s). Cormen, Leiserson, and Rivest. Algorithms, MIT Press 2001
Saturday Mar 6 PP Presentations 3rd and 4th week of Mar 2006. 107 Class participation and attendance: Zero marks for below 50% attendance,
100% marks for above 80%. (Daily basis)20
Total Internal assessment: 1. It will be declared in the 2nd week of Apr 2007 or 15 days before the final examination.2. Day to day internal assessment will be shown to the whole class. 3. The day of test, if happens to be a holiday, then next working day. 4. For PPP, a group can be by two to four students, in a group one boy & girl is must. 5. All assignments -manuscript, except for the PPP (that can be in a CD or in an e-mail form).
