SOFTWARE TESTING & QUALITY ASSURANCE

Mumbai University-Fourth / Final Year -Semester VII Information Technology Syllabus (Revised) SOFTWARE TESTING & QUALITY ASSURANCE

SOFTWARE TESTING &QUALITY ASSURANCE
CLASS B.E. ( INFORMATION TECHNOLOGY) SEMESTER VII
HOURS PER WEEK	LECTURES	:	04
TUTORIALS	:	--
PRACTICALS	:	02
	HOURS	MARKS
EVALUATION SYSTEM:	THEORY		3	100
PRACTICAL		--
ORAL		--	25
TERM WORK		--	25
Prerequisite: Software Engineering
Objective: This course equips the students with a solid understanding of: • Practices that support the production of quality software • Software testing techniques • Life-cycle models for requirements, defects, test cases, and test results • Process models for units, integration, system, and acceptance testing • Quality Models

1. Introduction: Software Quality, Role of testing, verification and validation, objectives and issues of testing, Testing activities and levels, Sources of Information for Test Case Selection, White-Box and Black-Box Testing , Test Planning and Design, Monitoring and Measuring Test Execution, Test Tools and Automation, Test Team Organization and Management .

2. Unit Testing: Concept of Unit Testing , Static Unit Testing , Defect Prevention , 3.4 Dynamic Unit Testing , Mutation Testing , Debugging , Unit Testing in eXtreme Programming

3. Control Flow Testing: Outline of Control Flow Testing, Control Flow Graph, Paths in a Control Flow Graph, Path Selection Criteria, All-Path Coverage Criterion , Statement Coverage Criterion, Branch Coverage Criterion, Predicate Coverage Criterion, Generating Test Input, Examples of Test Data Selection.

4. Data Flow Testing: Data Flow Anomaly,. Overview of Dynamic Data Flow Testing, Data Flow Graph, Data Flow Terms, Data Flow Testing Criteria, Comparison of Data Flow Test Selection Criteria, Feasible Paths and Test Selection Criteria, Comparison of Testing Techniques.

5. System Integration Testing: Concept of Integration Testing, Different Types of Interfaces and Interface Errors, Granularity of System Integration Testing, System Integration Techniques, Software and Hardware Integration, Test Plan for System Integration, Off-the-Shelf Component Integration, Off-the-Shelf Component Testing, Built-in Testing

6. System Test Categories: Basic Tests, Functionality Tests, Robustness Tests, Interoperability Tests, Performance Tests, Scalability Tests, Stress Tests, Load and Stability Tests, Reliability Tests, Regression Tests, Documentation Tests.

7. Functional Testing: Equivalence Class Partitioning, Boundary Value Analysis, Decision Tables, Random Testing, Error Guessing, Category Partition.

8. System Test Design: Test Design Factors, Requirement Identification, Characteristics of Testable Requirements, Test Design Preparedness Metrics, Test Case Design Effectiveness

9. System Test Planning And Automation: Structure of a System Test Plan, Introduction and Feature Description, Assumptions, Test Approach, Test Suite Structure, Test Environment, Test Execution Strategy, Test Effort Estimation, Scheduling and Test Milestones, System Test Automation, Evaluation and Selection of Test Automation Tools, Test Selection Guidelines for Automation, Characteristics of Automated Test Cases, Structure of an Automated Test Case, Test Automation Infrastructure

10. System Test Execution: Preparedness to Start System Testing, Metrics for Tracking System Test, Metrics for Monitoring Test Execution, Beta Testing, First Customer Shipment, System Test Report, Product Sustaining, Measuring Test Effectiveness.

11. Acceptance Testing: Types of Acceptance Testing, Acceptance Criteria, Selection of Acceptance Criteria, Acceptance Test Plan, Acceptance Test Execution, Acceptance Test Report, Acceptance Testing in eXtreme Programming.

12. Software Quality: Five Views of Software Quality, McCall’s Quality Factors and Criteria, Quality Factors Quality Criteria, Relationship between Quality Factors and Criteria, Quality Metrics, ISO 9126 Quality Characteristics, ISO 9000:2000 Software Quality Standard ISO 9000:2000 Fundamentals, ISO 9001:2000 Requirements

Text Book

1. “Software Testing and Quality Assurance: Theory and Practice”, Sagar Naik, University of Waterloo, Piyu Tripathy, Wiley , 2008

References:

1. “Effective methods for Software Testing “William Perry, Wiley.

2. “Software Testing - A Craftsman’s Approach”, Paul C. Jorgensen, CRC Press, 1995.

3. “The Art of Creative Destruction”, Rajnikant Puranik, SPD.

4. “Software Testing”, Srinivasan Desikan and Gopalaswamy Ramesh - Pearson Education 2006.

5. “Introducing to Software Testing”, Louis Tamres, Addison Wesley Publications, First Edition.

6. “Software Testing”, Ron Patton, SAMS Techmedia Indian Edition, Pearson Education 2001.

7. “The Art of Software Testing”, Glenford J. Myers, John Wiley & Sons, 1979.

8. “Testing Object-Oriented Systems: Models Patterns and Tools”, Robert V. Binder, Addison Wesley, 2000.

9. “Software Testing Techniques”, Boris Beizer, 2nd Edition, Van Nostrand Reinhold, 1990.

10. “Software Quality Assurance”, Daniel Galin, Pearson Education.

Term Work: Term work shall consist of at least 10 experiments covering all topics and one written test.

Distribution of marks for term work shall be as follows: Attendance (Theory and Practical) 05 Marks Laboratory work (Experiments and Journal) 10 Marks Test (at least one) 10 Marks The final certification and acceptance of TW ensures the satisfactory Performance of laboratory Work and Minimum Passing in the term work.

SIMULATION AND MODELING Sem 7 IT

Mumbai University-Fourth / Final Year -Semester VII Information Technology Syllabus (Revised) SIMULATION AND MODELING

SIMULATION AND MODELING
CLASS B.E. ( INFORMATION TECHNOLOGY) SEMESTER VII
HOURS PER WEEK	LECTURES	:	04
TUTORIALS	:	--
PRACTICALS	:	02
	HOURS	MARKS
EVALUATION SYSTEM:	THEORY		3	100
PRACTICAL		--	25
ORAL		--	--
TERM WORK		--	25
Prerequisite: Probability and Statistics
Objective: The objective of this course is to teach students methods for modeling of systems using discrete event simulation. Emphasis of the course will be on modeling and on the use of simulation software. The students are expected to understand the importance of simulation in IT sector, manufacturing, telecommunication, and service industries etc. By the end of the course students will be able to formulate simulation model for a given problem, implement the model in software and perform simulation analysis of the system.

1. Introduction to Simulation and Modeling: Simulation – introduction, appropriate and not appropriate, advantages and disadvantage, application areas, history of simulation software, an evaluation and selection technique for simulation software, general – purpose simulation packages. System and system environment, components of system, type of systems, model of a system, types of models and steps in simulation study.

2. Manual Simulation of Systems: Simulation of Queuing Systems such as single channel and multi channel queue, lead time demand, inventory system, reliability problem, time-shared computer model, job-shop model.

3. Discrete Event Formalisms: Concepts of discrete event simulation, model components, a discrete event system simulation, simulation world views or formalisms, simulation of single channel queue, multi channel queue, inventory system and dump truck problem using event scheduling approach.

4. Statistical Models in Simulation: Overview of probability and statistics, useful statistical model, discrete distribution, continuous distribution, empirical distribution and Poisson process.

5. Queueing Models: Characteristics of queueing systems, queueing notations, long run measures of performance of queueing systems, Steady state behavior of Markovian models (M/G/1, M/M/1, M/M/c) overview of finite capacity and finite calling population models, Network of Queues.

6. Random Number Generation: Properties of random numbers, generation of true and pseudo random numbers, techniques for generating random numbers, hypothesis testing, various tests for uniformity (Kolmogorov-Smirnov and chi-Square) and independence (runs, autocorrelation, gap, poker).

7. Random Variate Generation: Introduction, different techniques to generate random variate:- inverse transform technique, direct transformation technique, convolution method and acceptance rejection techniques.

8. Input Modeling: Introduction, steps to build a useful model of input data, data collection, identifying the distribution with data, parameter estimation, suggested estimators, goodness of fit tests, selection input model without data, covariance and correlation, multivariate and time series input models.

9. Verification and Validation of Simulation Model: Introduction, model building, verification of simulation models, calibration and validation of models:- validation process, face validity, validation of model, validating input-output transformation, t-test, power of test, input output validation using historical data and Turing test.

10. Output Analysis: Types of simulations with respect to output analysis, stochastic nature of output data, measure of performance and their estimation, output analysis of terminating simulators, output analysis for steady state simulation.

11. Case Studies: Simulation of manufacturing systems, Simulation of Material Handling system, Simulation of computer systems, Simulation of super market, Cobweb model, and any service sectors.

Text Book: Banks J., Carson J. S., Nelson B. L., and Nicol D. M., “Discrete Event System Simulation”, 3rd edition, Pearson Education, 2001. Reference Books:

1. Gordon Geoffrey, “System Simulation”, 2nd edition, PHI, 1978.

2. Law A. M., and Kelton, W. D., “Simulation Modeling and Analysis”, 3rd edition, McGraw-Hill, 2000.

3. Narsing Deo, “System Simulation with Digital Computer”, PHI.

4. Frank L. Severance, “System Modeling and Simulation”

5. Trivedi K. S., “Probability and Statistics with Reliability, Queueing, and Computer Science Applications”, PHI, 1982.

6. Wadsworth G. P., and Bryan, J. G., “Introduction to Probability and Random Variables”, McGraw-Hill, 1960.

7. Donald W. Body, “System Analysis and Modeling”, Academic Press Harcourt India.

8. Bernard, “Theory Of Modeling and Simulation”

9. Levin & Ruben, “Statistics for Management”.

10. Aczel & Sounderpandian, “Business Statistics”.

Term Work: Term work shall consist of at least 10 experiments covering all topics and one written test. Distribution of marks for term work shall be as follows: Attendance (Theory and Practical) 05 Marks Laboratory work (Experiments and Journal) 10 Marks Test (at least one) 10 Marks

The final certification and acceptance of TW ensures the satisfactory Performance of laboratory Work and Minimum Passing in the term work. Suggested Experiment list The experiments should be implemented using Excel, simulation language like GPSS and/or any simulation packages. Case studies from the reference book can be used for experiment.

1. Single Server System

2. Multi serve system like Able – Baker

3. (M, N) - Inventory System

4. Dump Truck Problem

5. Job-Shop Model

6. Manufacturing System

7. Cafeteria

8. Telecommunication System

9. Uniformity Testing

10. Independence Testing

DATA WAREHOUSING AND MINING & BUSINESS INTELLIGENCE

Mumbai University-Fourth / Final Year -Semester VII Information Technology Syllabus (Revised) DATA WAREHOUSING AND MINING & BUSINESS INTELLIGENCE

DATA WAREHOUSING AND MINING & BUSINESS INTELLIGENCE
CLASS B.E. ( INFORMATION TECHNOLOGY) SEMESTER VII
HOURS PER WEEK	LECTURES	:	04
TUTORIALS	:	--
PRACTICALS	:	02
	HOURS	MARKS
EVALUATION SYSTEM:	THEORY		3	100
PRACTICAL		--	--
ORAL		--	25
TERM WORK		--	25
Prerequisite: Data Base Management System
Objective: Today is the era characterized by Information Overload – Minimum knowledge. Every business must rely extensively on data analysis to increase productivity and survive competition. This course provides a comprehensive introduction to data mining problems concepts with particular emphasis on business intelligence applications. The three main goals of the course are to enable students to: 1. Approach business problems data-analytically by identifying opportunities to derive business value from data. 2. know the basics of data mining techniques and how they can be applied to extract relevant business intelligence.

1. Introduction to Data Mining: Motivation for Data Mining, Data Mining-Definition & Functionalities, Classification of DM systems, DM task primitives, Integration of a Data Mining system with a Database or a Data Warehouse, Major issues in Data Mining.

2. Data Warehousing – (Overview Only): Overview of concepts like star schema, fact and dimension tables, OLAP operations, From OLAP to Data Mining.

3. Data Preprocessing: Why? Descriptive Data Summarization, Data Cleaning: Missing Values, Noisy Data, Data Integration and Transformation. Data Reduction:-Data Cube Aggregation, Dimensionality reduction, Data Compression, Numerosity Reduction, Data Discretization and Concept hierarchy generation for numerical and categorical data.

4. Mining Frequent Patterns, Associations, and Correlations: Market Basket Analysis, Frequent Itemsets, Closed Itemsets, and Association Rules, Frequent Pattern Mining, Efficient and Scalable Frequent Itemset Mining Methods, The Apriori Algorithm for finding Frequent Itemsets Using Candidate Generation, Generating Association Rules from Frequent Itemsets, Improving the Efficiency of Apriori, Frequent Itemsets without Candidate Generation using FP Tree, Mining Multilevel Association Rules, Mining Multidimensional Association Rules, From Association Mining to Correlation Analysis, Constraint-Based Association Mining.

5. Classification & Prediction: What is it? Issues regarding Classification and prediction:

• Classification methods: Decision tree, Bayesian Classification, Rule based

• Prediction: Linear and non linear regression

Accuracy and Error measures, Evaluating the accuracy of a Classifier or Predictor.

6. Cluster Analysis: What is it? Types of Data in cluster analysis, Categories of clustering methods, Partitioning methods – K-Means, K-Mediods. Hierarchical Clustering- Agglomerative and Divisive Clustering, BIRCH and ROCK methods, DBSCAN, Outlier Analysis

7. Mining Stream and Sequence Data: What is stream data? Classification, Clustering Association Mining in stream data. Mining Sequence Patterns in Transactional Databases.

8. Spatial Data and Text Mining: Spatial Data Cube Construction and Spatial OLAP, Mining Spatial Association and Co-location Patterns, Spatial Clustering Methods, Spatial Classification and Spatial Trend Analysis. Text Mining Text Data Analysis and Information Retrieval, Dimensionality Reduction for Text, Text Mining Approaches.

9. Web Mining: Web mining introduction, Web Content Mining, Web Structure Mining, Web Usage mining, Automatic Classification of web Documents.

10. Data Mining for Business Intelligence Applications: Data mining for business Applications like Balanced Scorecard, Fraud Detection, Clickstream Mining, Market Segmentation, retail industry, telecommunications industry, banking & finance and CRM etc.

Text Books:

1. Han, Kamber, "Data Mining Concepts and Techniques", Morgan Kaufmann 2nd Edition

2. P. N. Tan, M. Steinbach, Vipin Kumar, “Introduction to Data Mining”, Pearson Education

Reference Books:

1. MacLennan Jamie, Tang ZhaoHui and Crivat Bogdan, “Data Mining with Microsoft SQL Server 2008”, Wiley India Edition.

2. G. Shmueli, N.R. Patel, P.C. Bruce, “Data Mining for Business Intelligence: Concepts, Techniques, and Applications in Microsoft Office Excel with XLMiner”, Wiley India.

3. Michael Berry and Gordon Linoff “Data Mining Techniques”, 2nd Edition Wiley Publications.

4. Alex Berson and Smith, “Data Mining and Data Warehousing and OLAP”, McGraw Hill Publication.

5. E. G. Mallach, “Decision Support and Data Warehouse Systems", Tata McGraw Hill.

6. Michael Berry and Gordon Linoff “Mastering Data Mining- Art & science of CRM”, Wiley Student Edition

7. Arijay Chaudhry & P. S. Deshpande, “Multidimensional Data Analysis and Data Mining Dreamtech Press

8. Vikram Pudi & Radha Krishna, “Data Mining”, Oxford Higher Education.

9. Chakrabarti, S., “Mining the Web: Discovering knowledge from hypertext data”,

10. M. Jarke, M. Lenzerini, Y. Vassiliou, P. Vassiliadis (ed.), “Fundamentals of Data Warehouses”, Springer-Verlag, 1999.

Term Work: Term work shall consist of at least 10 experiments covering all topics Term work should consist of at least 6 programming assignments and one mini project in Business Intelligence and two assignments covering the topics of the syllabus. One written test is also to be conducted. Distribution of marks for term work shall be as follows: Attendance (Theory and Practical) 05 Marks Laboratory work (Experiments and Journal) 10 Marks

Test (at least one) 10 Marks The final certification and acceptance of TW ensures the satisfactory Performance of laboratory Work and Minimum Passing in the term work. Suggested Experiment List

1. Students can learn to use WEKA open source data mining tool and run data mining algorithms on datasets.

2. Program for Classification – Decision tree, Naïve Bayes using languages like JAVA

3. Program for Clustering – K-means, Agglomerative, Divisive using languages like JAVA

4. Program for Association Mining using languages like JAVA

5. Web mining

6. BI projects: any one of Balanced Scorecard, Fraud detection, Market Segmentation etc.

7. Using any commercial BI tool like SQLServer 2008, Oracle BI, SPSS, Clementine, and XLMiner etc.

ORAL EXAMINATION An oral examination is to be conducted based on the above syllabus.

The Know The Signs “Breathalyzer” iPhone Application

This is a Sponsored Post written by me on behalf of Heineken. All opinions are 100% mine.

Recently I had a situation when going to a party. A friend of mine had drunk a bit more than he could handle. Well, it’s kind of an awkward situation when you have to tell your friend that he has drunk too much. Not that you can’t tell him normally but he’s drunk! Another friend of mine had a cool app for the exact situation. He told this person to blow in his iphone. The iphone acted like an actual breath analyzer. And we were shell shocked!

It was actually an iphone application from Heineken. What has to be done is you feed in the level you want to show, tell your friend to blow in, and it will display the same level. So it’s not an actual breath analyzer, but a moral stimulator kind of thing where a person can be told that he has drunk too much. To check it out Download the Heineken Breathalyzer iPhone app.

What’s cool in this app is that you can do a lot more things like tag your friend as one of the characters defined by Heineken which normally people turn into after drinking more. You can share it at places and tell your friends more clearly about their facts.

They have also got a nice website where you can try and identify the different characters your friends might turn into after one too many to drink. Visit The Heineken Know The Signs website.

The important fact here to understand is the effort Heineken is taking to spread the message. They tried the same before in a similar campaign “Know The Signs - Enjoy Heineken Responsibly” before and achieved a great success. This time they have come only to take the message even further. Based on their research and opinion from the people they have made the campaign even better than before. They have added some new characters to their old ones.

It is a positive move by them which we should definitely support. Knowing the facts that the number of deaths due to alcoholism has raised twofold in the last 15years. Over 17,000 people in the U.S. die in alcohol-related motor vehicle crashes each year, representing 41% of all traffic-related deaths (NHTSA). Approximately 1.5 million drivers are arrested every year for driving under the influence of alcohol or narcotics.

The KnowTheSigns campaign videos have reached over 750,000 views within one week. Hopefully these large numbers will contribute to an interactive responsible drinking message. With these videos and tools, the users can explore the impact ‘one too many to drink’ can have on people around them. It also enables Heineken to develop a conversation between friends with the iPhone “Breathalyzer” and the social network application ‘Tag of Shame’.

The Central Board of Secondary Education (CBSE) has announced the dates for the next Standard X and XII examinations beginning from March 3, 2010. The time-table for both exams will be released by December-end. This will be the last Class X board exam to be conducted by CBSE before a total ban on exams comes into effect and a grading system takes its place.

CBSE Class 12 DateSheet 2010

Central Board of Secondary Education Date Sheet

DATE-SHEET SENIOR SCHOOL EXAMINATION, 2010

DAY,DATE AND TIME SUBJECT NAME AND SUB-C

Wednesday, 03rd March, 2010 - 10:30 AM
PHYSICS 042
RADIO ENG.&AUD.SYS 635
M PROD TPT &M COOP 640
POST HARV TECH&PRD 644
OPTICS 658
CLINICAL BIO-CHEM. 661
COMM. HEALTH NURII 664
RADIOGRAPHY-I GENL 667
DESG & PAT MAKING 685
DYEING & PRINTING 688
ACCOMODAT. SERVICE 691
TRAVEL TRADE MGMT 694
CONFECTIONERY 698
CLSFN.& CATLOGUING 703
POULTRY PDTS& TECH 717
H EDN.& PUB HELATH 728

Thursday, 04th March, 2010 - 10:30 AM
BUSINESS STUDIES 054

Friday, 05th March, 2010 - 10:30 AM
FASHION STUDIES 053

Saturday, 06th March, 2010 - 10:30 AM
POLITICAL SCIENCE 028

Monday, 08th March, 2010 - 10:30 AM
CHEMISTRY 043
CONS BEHV & PROTCN 615
MGMT OF BANK OFFCE 621
APPLIED PHYSICS 625
MECH. ENGINEERING 626
FABRICATN.TECH-III 631
TV & VIDEO SYSTEMS 636
ELECTRICAL ENGG. 637
MILK & MILK PRODS. 639
B THERAPY &H DR-II 654
BIOLOGY-OPTHALMIC 657
LAB. MEDICINE 660
FUND OF NURSING II 663
RADIATION PHYSICS 666
ADVANCE FOOD PREP 675
CLOTHING CONST 686
BASIC DESIGN 687
FOOD PREPARATION 690
INDIA-TOURIST DEST 693
FOOD SCI.& HYGIENE 696
I T SYSTEMS 699
LIB. ADMN & MGMT. 702
PRIN &PRA-LIFE INS 705
POULTRY NUTR & PHY 716
INT TO FINANCL MKT 723
B CONCEPT-H &MED T 729

Wednesday, 10th March, 2010 - 10:30 AM
ENGLISH ELECTIVE 001
FUNCTIONAL ENGLISH 101
ENGLISH CORE 301

Friday, 12th March, 2010 - 10:30 AM
HISTORY 027
BIOTECHNOLOGY 045
SECT PRAC & ACCNTG 605
STORE KEEPING 617
CASH MGMT & H-KEEP 619
ELECT APPLIANCES 624
AUTOSHOP REP& PRAC 628
CIVIL ENGINEERING 629
FABRICATN.TECH-II 630
AC & REFRGTN-III 632
ELN.DEV.& CIRCUITS 634
D E MICROPROCESSOR 638
OPHTHALMIC TECH. 659
MICROBIOLOGY 662
MAT.&CHILD H.NURII 665
RADIOGRAPHY-II SPL 668
BAKERY SCIENCE 697
TPT. SYSTEMS &MGMT 712
POULTRY DISE & CNT 718
ACTG FOR BUSINESS 722
FIRST AID &MEDCL C 730

Saturday, 13th March, 2010 - 10:30 AM
DANCE-KATHAK 056
DANCE-BHARATNATYAM 057
DANCE-KUCHIPUDI 058
DANCE-ODISSI 059
DANCE-MANIPURI 060
DANCE-KATHAKALI 061
DANCE-MOHINIYATTAM 062
MULTIMEDIA & WEB T 067

Monday, 15th March, 2010 - 10:30 AM
URDU ELECTIVE 003
AGRICULTURE 068
CR WRTNG TR STUDY 069
GRAPHIC DESIGN 071
PUNJABI 104
BENGALI 105
TAMIL 106
TELUGU 107
SINDHI 108
MARATHI 109
GUJARATI 110
MANIPURI 111
MALAYALAM 112
ORIYA 113
ASSAMESE 114
KANNADA 115
PORTUGUESE 119
GERMAN 120
RUSSIAN 121
NEPALI 124
LIMBOO 125
LEPCHA 126
BHUTIA 195
SPANISH 196
KASHMIRI 197
MIZO 198
URDU CORE 303
MARKETING 613
LENDING OPERATIONS 620
COMPUTER& LIFE I A 706

Wednesday, 17th March, 2010 - 10:30 AM
BIOLOGY 044
OFFCE PRAC & SECT 604
ESTB & MGMT OF FSU 677
DTP CAD & MULTIMED 701

Thursday, 18th March, 2010 - 10:30 AM
ECONOMICS 030

Saturday, 20th March, 2010 - 10:30 AM
PHYSICAL EDUCATION 048

Monday, 22nd March, 2010 - 10:30 AM
MATHEMATICS 041
FLORICULTURE 643
COSMETIC CHEMISTRY 655
TEXTILE SCIENCE 684
(C) SuccessCDs.net

Tuesday, 23rd March, 2010 - 10:30 AM
PSYCHOLOGY 037
STENOGRAPHY-ENG 608
STENOGRAPHY-HINDI 610
Thursday, 25th March, 2010 - 10:30 AM
INFORMATICS PRAC. 065
COMPUTER SCIENCE 083
OFF. COMMUNICATION 606
ELE.COST A/C & AUD 612
SALESMANSHIP 614
ELECTRIC MACHINES 623
AUTO ENGINEERING 627
AC & REFRGTN-IV 633
DAIRY PLANT INSTRU 641
VEGETABLE CULTURE 642
YOGA ANATOMY &PHYS 656
MEAL PLNG & SERVIC 676
TOUR MGMT & MP PLN 695
REFERENCE SERVICE 704
B P O SKILLS 724
Saturday, 27th March, 2010 - 10:30 AM
HINDI ELECTIVE 002
TIBETAN 117
FRENCH 118
PERSIAN 123
HINDI CORE 302
Monday, 29th March, 2010 - 10:30 AM
ACCOUNTANCY 055
STORE ACCOUNTING 618
ENGINEERING SCI. 622
FOOD & BEV SERVICE 692
Tuesday, 30th March, 2010 - 10:30 AM
SANSKRIT ELECTIVE 022
SANSKRIT CORE 322
Wednesday, 31th March, 2010 - 10:30 AM
ENTREPRENEURSHIP 066
Thursday, 01st April, 2010 - 10:30 AM
GEOGRAPHY 029
Monday, 05th April, 2010 - 10:30 AM
HOME SCIENCE 064
ARABIC 116
FINANCIAL ACCNTG 611
BUSINESS DATA PRO. 700
Tuesday, 06th April, 2010 - 10:30 AM
MUSIC CAR.VOCAL 031
MUSIC CAR.INS.MEL. 032
MUSIC CAR.INS.PER. 033
MUSIC HIND.VOCAL 034
MUSIC HIND.INS.MEL 035
MUSIC HIND.INS.PER 036
PHILOSOPHY 040
TYPEWRITING-ENG 607
TYPEWRITING-HINDI 609

Wednesday, 07th April, 2010 - 10:30 AM
SOCIOLOGY 039
ENGG. DRAWING 046
Thursday, 08th April, 2010 - 10:30 AM
PAINTING 049
GRAPHICS 050
SCULPTURE 051
COMMERCIAL ART 052