B.E/B.Tech DEGREE EXAMINATION Apr/May 2008
Fifth semester
Computer Science and Engineering
(Regulation 2004)
Time: 3 hours Maximum marks: 100
Answer ALL questions
PART A (10 x 2 =20 marks)
1. Define Data independence.
2. Distinguish between primary key and candidate key
3. With an example explain a weak entity in an ER diagram.
4. With an example explain referential integrity.
5. What is domain integrity? Give example.
6. Distinguish between dense and sparse indices.
7. List the properties that must be satisfied by a transaction,
8. Define deadlock.
9. State the advantages of distributed systems.
10. What is data warehousing?
PART B (5 x 16 = 80)
11. (a) (i) Construct an ER diagram for a car insurance company that has a set of customers, each of whom owns one/more cars. Each car has associated with it zero to any number of recorded accidents. (Cool
(ii) Construct appropriate tables for the above ER diagram. (Cool
(or)
(b) (i) Define data model. Explain the different types of data models with relevant examples. (10)
(ii) Explain the role and functions of the database administrator. (6)
12 (a) (i) with relevant examples discuss the following in SQL.
(i) Data Definition Language. (4)
(ii) Data Manipulation Language (4)
(iii) Data Control Language (4)
(iv) Views (4)
(or)
(b) What is normalization? Explain normalization techniques using functional dependencies with relevant examples. (16)
13 (a) Explain following with relevant examples:
(i) B tree (5)
(ii) B+ tree (5)
(iii) Static and dynamic hashing (6)
(or)
(b) With a relevant example discuss the steps involved in processing a query. (16)
14 (a) Explain testing for serializability with respect to concurrency control schemes. How will you determine, whether a schedule is serializable or not. (16)
(or)
(b) Explain the following concurrency control:
(i) Lock based protocol (Cool
(ii) Time stamp based protocol (Cool
15 (a) State and explain the object oriented data model. Use banking application as an example. (16)
(or)
(b) Write detail notes on following:
(i) Distributed Databases (Cool
(ii) Data Mining (Cool
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