Interpolation Search
Interpolation search is an algorithm for searching for a specific key in a sorted array by estimating its position based on the distribution of values. It improves upon binary search by using linear interpolation to guess the key's location, making it more efficient for uniformly distributed data. This algorithm has an average time complexity of O(log log n) for uniformly distributed arrays, but degrades to O(n) in worst-case scenarios.
Developers should learn interpolation search when working with large, sorted datasets that are uniformly distributed, such as numerical data in databases or arrays, as it can significantly reduce search time compared to binary search. It is particularly useful in applications like searching through sorted lists of timestamps, IDs, or other evenly spaced values, but should be avoided for non-uniform or unknown distributions where binary search is more reliable.