AVL TREE Practice Questions

Duration: 2 min

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Inside: a video lesson and guided study material.

Module outline

  1. C: C Programming by Yash Sir
  2. C++: Programming in C++
  3. Java: Java
  4. Python: Python for Placements by Yash Sir
  5. OOPs Concept: Object Oriented Programming (OOPS)
  6. Pseudo Code: Pseudo Codes
  7. Data Structure: Introduction to DS, Array, Stack, Queue, Linked List, Tree, Graphs, Hashing
  8. Algorithm: Algorithm Analysis, Sorting Algorithms, Greedy Algorithms, Dynamic Programming, Minimum Spanning Trees, Shortest Path Algos, Time Complexity Analysis, Advanced Algorithms
  9. DSA Implementation: DSA using Python
  10. Competitive Coding: Coding Questions by Yash Sir, Coding Questions Bank
  11. Mega Test:
  12. Grand Test:
  13. Live Class Notes: Placement Live Classes
AI summary & chapters

AI Summary

An AI-generated summary of this video lecture.

This educational video segment focuses on solving a specific practice problem involving AVL tree construction. The instructor demonstrates how to build an AVL tree from the sequence 70, 60, 80, 50, 65, and 68 while maintaining the balance factor property. The core objective is to determine the number of leaf nodes in the final balanced tree structure.

Chapters

  1. 0:00 – 1:50 00:00-01:50

    The instructor addresses the question 'Create an AVL tree with 70, 60, 80, 50, 65 and 68 how many leaves are there in the resultant tree?' displayed on screen. The process involves inserting nodes sequentially, crossing out numbers as they are added to the structure. Key visible events include drawing a partial tree with 70 as root, 60 and 80 as children, and further insertion of 50 under 60. The instructor performs necessary rotations (indicated by 'L' and 'R') to maintain AVL balance. Three hand-drawn tree diagrams illustrate the construction stages, culminating in a final structure where the instructor counts and marks option (b) 3 as the correct answer for the number of leaf nodes.

The video provides a focused walkthrough of AVL tree balancing mechanics using a concrete numerical example. The teaching flow moves from problem identification to step-by-step insertion, highlighting the necessity of rotations when balance factors are violated. The final conclusion relies on correctly identifying leaf nodes in the resulting balanced binary search tree, reinforcing that insertion order and balancing operations directly impact the final topology.

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