Review of basic data structures and their realization in object oriented environment. The
following topics will be covered with emphasis on formal analysis and design, Dynamic Datastructures; 2‐3 trees, Red‐black trees, binary heaps, binomial and Fibonacci heaps, Skip lists,
universal hashing. Data structures for maintaining ranges, intervals and disjoint sets with
applications. Basic algorithmic techniques like dynamic programming and divide‐ and‐conquer,
Sorting algorithms with analysis, integer sorting algorithms with analysis, integer selection,
Graph algorithms like DFS with applications, MSTs and shortest paths.
Database System Architecture ‐ Data Abstraction, Data Independence, Data Definition and Data
Manipulation Languages. Data Models ‐ Entity‐Relationship, Network, Relational and Object
Oriented Data Models, Integrity Constraints, and Data Manipulation Operations. Relational
Query Languages: Relational Algebra, Tuple and Domain Relational Calculus, SQL and QBE.
Relational Database Design: Domain and Data dependency, Armstrong’s Axioms, Normal
Forms, Dependency Preservation, Lossless design. Query Processing and Optimization:
Evaluation of Relational Algebra Expressions, Query Equivalence, Join strategies, Query
Optimization Algorithms. Storage Strategies: Indices, B‐trees, Hashing; Transaction Processing :
Recovery and Concurrency Control, Locking and Timestamp based Schedulers, Multiversion
and Optimistic Concurrency Control schemes. Advanced Topics; Object‐oriented and Object
Relational Databases, Logical Databases, Web Databases, Distributed Databases, Data
Warehouse and Data Mining.

1. Gregory L. Heileman , Data Structure, Algorithm and OOP, Tata Mc Graw Hill, NewDelhi.

2. Adam Drozdek, Data Structures & Algorithm in C++,Vikas publication House.

3. Silberschatz, H. Korth, Database System Concepts, 5th Edition, McGraw‐Hill.

4. Raghu Ramakrishnan, Database Management Systems, Johannes Gehrke 4th Edition, McGraw‐Hill

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