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
- Tree traversal (DFS vs BFS)
- Finding height/depth
- Checking if balanced
- Finding LCA (Lowest Common Ancestor)
- 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