What is the time and space complexity of binary trees in C++?

What is the time and space complexity of binary trees in C++?

The time complexity for basic operations like insertion, deletion, and search in a binary tree is O(h), where h is the height of the tree. In a balanced binary tree, this is O(log n), but in the worst case (unbalanced), it can be O(n). The space complexity is O(n) for storing the nodes.

Can you explain how the height of a binary tree affects its complexity?

Certainly! The height of a binary tree directly impacts its time complexity. A taller tree means more levels to traverse, leading to longer search times. In a balanced tree, the height is minimized, ensuring efficient operations.

What are some common types of binary trees?

Common types include binary search trees (BST), AVL trees, red-black trees, and complete binary trees. Each has unique properties and use cases.

How can I implement a binary tree in C++?

You can implement a binary tree in C++ using a struct or class to define the nodes, with pointers to the left and right children. Would you like a code example?