Binary Tree Implementation Guide

AI Generated
Key PointsHigh Priority
Subject: Computer Science
Created: 2024-12-15
Reviews: 3

Content

Binary Tree Implementation Essentials

Node Structure

class TreeNode {
    int data;
    TreeNode left;
    TreeNode right;
}

Key Operations to Remember

  • Insert: Always maintain BST property (left < parent < right)
  • Delete: Three cases - leaf, one child, two children
  • Search: Recursive or iterative, O(log n) for balanced trees

Common Interview Patterns

  1. Tree traversal (DFS vs BFS)
  2. Finding height/depth
  3. Checking if balanced
  4. Finding LCA (Lowest Common Ancestor)
  5. Serialization/Deserialization

Remember: Most tree problems can be solved recursively!

Key Takeaways

  • Binary trees have at most two children per node
  • BST property enables O(log n) search
  • Recursion is key for tree algorithms
  • Balance factor determines tree efficiency
  • In-order traversal of BST gives sorted sequence

Study Questions

  • 1.What is the difference between a binary tree and a BST?
  • 2.How do you determine if a binary tree is balanced?
  • 3.What are the time complexities of tree operations?
  • 4.When would you use BFS vs DFS for tree traversal?

Tags

data-structuresbinary-treesalgorithmsinterview-prep

Last reviewed: 2024-12-19