AVL TREE Practice Questions

Duration: 2 min

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  1. Communication Round: Vocabulary, Subject Verb Agreement (Verb Noun Agreement), Tenses, Comprehension / Reading Comprehension / Unseen Passages (Critical Reasoning) (Paragraph Questions), Cloze Test (Cloze Passage), Sentence Correction (Error Correction), Sentence Completion (Fill in the blanks), Sentence Re-arrangements (Para Jumbles) (Narrative Sequencing), Direct and Indirect Speech, Active Passive Voice (Voice), Verbal Analogy (Word Based Analogy), Articles, Preposition, Conjunction, Sentence Construction, English Writing Ability, Communication Assessment
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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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