What Is Binary Search Tree in Data Structure?


Heather Bennett

A binary search tree (BST) is a fundamental data structure in computer science that allows for efficient searching, insertion, and deletion of elements. It is a type of binary tree where each node has at most two children – a left child and a right child.

Structure of a Binary Search Tree

In a BST, the elements are organized in a hierarchical manner. The root node is at the top, followed by its two children nodes (left and right). Each subsequent level down the tree follows the same pattern.

A BST has the following properties:

  • Ordering: The elements in the left subtree of any node are always smaller than the node’s value, while the elements in the right subtree are always greater.
  • Uniqueness: Each element in the tree must be unique. There cannot be duplicate values.

Searching in a Binary Search Tree

The main advantage of using a BST is its efficient search operation. To search for an element in a BST, we compare it with the value at the current node.

If it matches, we have found our element. If it is smaller, we move to the left subtree; if it is larger, we move to the right subtree.

This process continues until we find our desired element or reach a leaf node (a node with no children). If we reach a leaf node without finding our element, it means that the element does not exist in the BST.

Insertion into a Binary Search Tree

To insert an element into a BST, we traverse down from the root following similar comparisons as during searching. Once we reach an empty spot (a null child), we insert our new element there as a leaf node.

When inserting elements, we must make sure to maintain the ordering property of the BST. If the element to be inserted is smaller than the current node, we move to its left child; if it is larger, we move to the right child.

Deletion from a Binary Search Tree

The deletion operation in a BST can be slightly more complex than searching and insertion. When deleting a node, we need to consider three cases:

  1. Deleting a Leaf Node: In this case, we simply remove the node from the tree.
  2. Deleting a Node with One Child: We replace the node with its child and adjust the tree accordingly.
  3. Deleting a Node with Two Children: We replace the node with its inorder predecessor or inorder successor (a node with either the largest value in its left subtree or the smallest value in its right subtree) and delete that predecessor/successor recursively.

Advantages of Binary Search Trees

  • Efficient Searching: BSTs provide fast search operations with an average time complexity of O(log n) for balanced trees and O(n) for skewed trees.
  • Simplicity: The structure and operations of BSTs are relatively easy to understand and implement compared to other complex data structures like AVL trees or red-black trees.


A binary search tree is an essential data structure that allows for efficient searching, insertion, and deletion operations. It maintains an ordered hierarchy that enables quick access to elements. By understanding how BSTs work and utilizing their advantages, you can optimize your algorithms and solve various problems efficiently.

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