Which search algorithm efficiently finds a match through recursive search?

Binary search is an efficient algorithm that finds a match through a recursive search process. It operates on a sorted array or list of elements. The key principle behind binary search is to repeatedly divide the search interval in half, allowing it to significantly reduce the number of elements to be checked with each step.

Starting with the middle element of the array, the algorithm compares this value to the target value. If the middle element matches the target, the search is successful. If the target is less than the middle element, the search continues in the left half of the array. Conversely, if the target is greater than the middle element, the search focuses on the right half. This process continues recursively until the target is found or the subarray size is reduced to zero, indicating that the target is not present.

This efficiency arises because the algorithm discards half of the elements in the array during each iteration. As a result, the time complexity of binary search is O(log n), making it much faster than linear search, particularly for large datasets.

In contrast, linear search checks each element one by one, resulting in a time complexity of O(n). Hash search relies on hash tables for constant time complexity but does not involve a recursive search. Jump search improves upon linear