Data Structures - I

Features Includes:

  • 75 - 3D/2D Animation
  • 314 Pages of Content
  • 60 Lecture Hours
  • 5 Solved Problems
  • 80 Quiz
  • Suitable for All Technical University Syllabus

Course Description

Data Structure is a way to store and organize data so that it can be used efficiently. Data structure, way in which data are stored for efficient search and retrieval. Different data structures are suited for different problems. A data structure is a data organization, management, and storage format that enables efficient access and modification.

OBJECTIVES:

  • To understand an overview of data structures
  • Understand Linear Data structures. Perform insertion and deletion operation on a singly linked list
  • Define a tree. Explain the linear representation and linked list representation of a Binary tree
  • Define balanced tree and how to determine if a binary tree is height-balanced?
UNIT I - BASICS DATA STRUCTURES

Abstract Data Type(ADT) - Introduction to data structures - Representation - Implementation - Implementation - Application - Balancing symbols - Conversion of infix to postfix expression - Evaluating a postfix expression - Recursive function call - Linked list ADT - Implementation using arrays - Limitations - Linked list using dynamic variables - Linked implementation of stacks - Circular list - Doubly linked lists. Applications of lists - Polynomial Manipulation - All operation (Insertion, Deletion, Merge, Traversal).

UNIT II - LINEAR DATA STRUCTURES

Stack and list : - Representing stack - Queue ADT - circular queue implementation - Double ended Queues - applications of queue. Definition and applications of Stacks, Queues, Linked lists and trees.

UNIT III - TREE STRUCTURES

General trees - Binary tree - Traversal methods - Expression trees - Game trees. - Binary search trees - AVL trees - Red-Black trees - Threaded binary trees, Max Priority Queue ADT

UNIT IV - BALANCED TREES

Splay trees - B Trees - B+ Trees - Tries - Application - Binomial Heaps – Fibonacci Heaps – Disjoint Sets – Amortized Analysis – Accounting method – Potential method – Aggregate analysis.