What is the primary advantage of using an AVL tree over a regular binary search

What is the primary advantage of using an AVL tree over a regular binary search tree?

AVL trees are easier to implement.
AVL trees maintain a balanced height, ensuring O(log n) time complexity for search operations.
AVL trees allow duplicate values.
AVL trees require less memory.

What is the primary advantage of using an AVL tree over a regular binary search tree?

Step 1: Understand what a binary search tree (BST) is. A BST is a data structure that stores data in a way that for any given node, all values in the left subtree are smaller and all values in the right subtree are larger.
Step 2: Know that in a regular BST, if you keep adding values in a sorted order (like 1, 2, 3, 4), it can become unbalanced and look like a straight line.
Step 3: Realize that when a BST is unbalanced, searching for a value can take a long time, up to O(n) time, where n is the number of nodes.
Step 4: Learn about AVL trees, which are a type of self-balancing binary search tree. They automatically keep themselves balanced after every insertion or deletion.
Step 5: Understand that because AVL trees are balanced, the height of the tree remains logarithmic in relation to the number of nodes, allowing search operations to be performed in O(log n) time.
Step 6: Conclude that the primary advantage of using an AVL tree over a regular BST is that AVL trees ensure faster search times by maintaining a balanced height.

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