How does a self-balancing BST compare to a regular BST?

How does a self-balancing BST compare to a regular BST?

A self-balancing BST automatically maintains its height, ensuring O(log n) time complexity for operations, while a regular BST can degrade to O(n) in the worst case.

What are some examples of self-balancing BSTs?

Common examples include AVL trees and Red-Black trees, both of which ensure balanced height after insertions and deletions.

Why is balancing important in BSTs?

Balancing is crucial because it keeps the tree's height minimal, which optimizes search, insert, and delete operations.

Can you explain how AVL trees maintain balance?

AVL trees maintain balance by performing rotations during insertions and deletions to ensure that the heights of the two child subtrees of any node differ by at most one.

What are the trade-offs of using a self-balancing BST?

The trade-offs include slightly more complex implementation and overhead for maintaining balance, but they provide better performance for dynamic datasets.