Searching Algorithms Questions Medium
The time complexity of searching in a binary search tree (BST) is O(log n), where n is the number of nodes in the tree.
In a binary search tree, each node has a key value, and the left child of a node contains a smaller key value, while the right child contains a larger key value. This property allows for efficient searching.
When searching for a specific key in a BST, the search starts at the root node and compares the key with the current node's key. If the key is smaller, the search continues in the left subtree; if the key is larger, the search continues in the right subtree. This process is repeated until the key is found or until a leaf node is reached, indicating that the key is not present in the tree.
Since at each step the search is effectively halving the remaining search space by traversing either the left or right subtree, the time complexity of searching in a BST is logarithmic. In the worst case scenario, where the tree is completely unbalanced and resembles a linked list, the time complexity can be O(n). However, in a balanced BST, the average time complexity for searching is O(log n), making it an efficient searching algorithm.