BSc CSIT (TU) Science Advanced Database (BSc CSIT, CSC461) Question Paper 2075
This is the official BSc CSIT (TU) (Science stream) Advanced Database (BSc CSIT, CSC461) question paper for 2075, as set in the regular annual examination. It carries 60 full marks and a time allowance of 180 minutes, across 12 questions. On Kekkei you can attempt this Advanced Database (BSc CSIT, CSC461) past paper online with a timer, get instant AI feedback and step-by-step solutions, and track the topics where you lose marks — completely free. Whether you are revising for your BSc CSIT (TU) Advanced Database (BSc CSIT, CSC461) exam or solving previous years' question papers, this 2075 paper is a great way to practise under real exam conditions.
Section A: Long Answer Questions
Attempt any TWO questions.
What is concurrency control? Explain the two-phase locking protocol and timestamp-based ordering protocol for concurrency control with suitable examples.
What is a NoSQL database? Explain the characteristics of NoSQL systems and discuss the CAP theorem. Compare document-based, key-value, column-based and graph-based NoSQL data stores.
Explain the Enhanced Entity-Relationship (EER) model. Discuss specialization, generalization, categorization and aggregation with suitable diagrams and examples.
Section B: Short Answer Questions
Attempt any EIGHT questions.
What is a deductive database? Explain the use of Datalog with an example.
Explain the two-phase locking (2PL) protocol for concurrency control.
Explain the two-phase commit (2PC) protocol used in distributed transactions.
What is indexing? Differentiate between primary, secondary and clustering indexes.
Explain the architecture of parallel databases. What is inter-query and intra-query parallelism?
What is an object-relational database? How does it differ from a purely relational database?
What is XML data model? Explain how XML is used to represent and query data in databases.
Explain log-based recovery techniques in a database system.
Write short notes on the MapReduce programming model for big data processing.