What is the time complexity of binary search trees?

What is the time complexity of binary search trees?

The average time complexity for search, insert, and delete operations in a binary search tree is O(log n). However, in the worst case, it can degrade to O(n) if the tree becomes unbalanced.

How can we ensure that a binary search tree remains balanced?

To keep a binary search tree balanced, you can use self-balancing trees like AVL trees or Red-Black trees, which automatically adjust their structure during insertions and deletions.

What are the advantages of using a balanced binary search tree?

Balanced binary search trees provide faster search, insert, and delete operations, maintaining O(log n) time complexity, which is crucial for performance in large datasets.

Can you explain the difference between AVL trees and Red-Black trees?

Sure! AVL trees maintain a stricter balance than Red-Black trees, which can lead to faster lookups. However, Red-Black trees allow for faster insertions and deletions due to less frequent rotations.