AVL Tree Rotations Tutorial: Fixing Imbalance After Adding a Node
Posted inAVL Trees Binary Search Trees Computer Science

AVL Tree Rotations Tutorial: Fixing Imbalance After Adding a Node

Learn how to maintain balance in AVL trees through rotations. This tutorial shows inserting a new node into an AVL tree, recalculating balance factors up the path to the root, identifying the first imbalanced node, selecting X Y Z nodes based on subtree heights, and executing a double right rotation to restore the AVL property while preserving binary search tree ordering.
AVL Tree Rotation Types Explained for Self-Balancing Binary Search Trees
Posted inAVL Trees Binary Search Trees Computer Science

AVL Tree Rotation Types Explained for Self-Balancing Binary Search Trees

In AVL trees, when we find a node with a balance factor of 2 or worse, we perform rotations on the trinode subtree. There are four input patterns that all resolve to the same balanced output pattern through single or double rotations. Single rotations handle straight line imbalances while double rotations address the zigzag cases. Each rotation rearranges parent-child pointers to reduce the height from 3 to 2, helping keep the overall tree balanced for log time operations.
AVL Tree Tutorial: Balance Factors and Why They Fix Slow BSTs
Posted inAVL Trees Binary Search Trees Computer Science

AVL Tree Tutorial: Balance Factors and Why They Fix Slow BSTs

AVL trees are self-balancing binary search trees that prevent the tree from becoming unbalanced. We compute balance factors as the absolute value of left subtree height minus right subtree height. If any node has a balance factor of 2 or worse, we rebalance using rotations on trinode subtrees. This keeps search, insert, and other operations efficient at logarithmic time.
How to Search in a Binary Search Tree (BST) – Step by Step Explanation with Examples
Posted inBinary Search Trees Computer Science Data Structures

How to Search in a Binary Search Tree (BST) – Step by Step Explanation with Examples

Learn how to search in a Binary Search Tree. We demonstrate searching for existing and non-existing values, explain why BST search is O(log n) on average, and show how poor data ordering can turn your tree into a slow linear structure similar to a linked list. Includes discussion of tree height and balanced vs unbalanced BSTs.
Binary Search Tree Insertion Tutorial: Building a BST from Scratch Step by Step
Posted inBinary Search Trees Computer Science Data Structures

Binary Search Tree Insertion Tutorial: Building a BST from Scratch Step by Step

Learn how to build a binary search tree (BST) by inserting numbers one by one. Follow the insertion process for the sequence 88, 21, 3, 6, 72, 34, 11, 1, 90, 65, 55, 17, 23, 9. See left/right decisions, pointer updates, inorder verification for sorted order, tree height calculation (6), and discussion of O(h) time complexity versus log n for balanced trees. Clear explanations without skipping steps.
Building a Binary Search Tree – Insertion Tutorial
Posted inBinary Search Trees Computer Science Data Structures

Building a Binary Search Tree – Insertion Tutorial

In this tutorial we build a binary search tree together by inserting the numbers 73, 98, 12, 45, 67, 10, 43, 11, 99, and 32 one by one. Starting from an empty tree, each number is placed according to binary search tree rules: smaller values go left, larger values go right. We let the nodes fall where they belong without any rearranging, resulting in a realistic (and slightly lopsided) BST. The video explains tree depth, height, and confirms the final structure maintains all BST properties with a properly sorted in-order traversal.