The number of probes in interpolation search (see ,  or ) in the best case is also just 1, in the average case it is in O(loglogn) and in the worst case it is in O(n). For example, if we are looking for 91 in the original array above, then on our first pass we compute middle as: 91 - 1 middle â (43-1) * ----- + 1 99 - 1 = (42 * 0.918) + 1 = 39.571 = 39 ... (In the worst case, interpolation search performs worse than straight binary search!) Interpolation search Performance. Remark: The complexity in the worst case could be improved by running interpolation search In such cases interpolation search will be O(n). The space complexity of the Interpolation search is O(1) as Single auxiliary space is required to hold a position variable. Consider the following array of elements: 9, 21, 32, 38, 51, 59, 68, 80, 91, 97, 113, 119, 131, 142, 149; How many steps would binary search require in order to find 68? Therefore, the time complexities in the best case will be: T BSeqSearch (n)=4=Î(1) - The Worst case time complexities: when k â¦ The interpolation search is very beneficial when the elements are arranged in more sequencial way (for example, if we have a sorted array of elements whose elements have a common difference of 2 then in such case we can find the position of â¦ Example. In worst case time complexity can be O(n). The average time complexity of Interpolation search is O(log(log(n))) if all elements are uniformly distributed. This makes the best case time complexity is O(1). So if the values are: 1,2,3,4,5,6,7,8,9,10000000 And we search for number 9, searching using linear interpolation will go through all (excluding the first and last) the indices before finding the correct one. The successful Searches: - The Best case time complexities: When k number found in the position a(n). That's all for this topic Interpolation Search Program in Java. In either situation, we have, C (n) = n. Now, C (n) = n is the worst-case complexity of linear or sequential search algorithm. How many steps would interpolation search require in order to find 68? See What is the time complexity of interpolation search and why? Solution: In this example, the search process begins from the end of a. Worst case time complexity: O(N) Average case time complexity: O(log log N) Best case time complexity: O(1) Space complexity: O(1) On assuming a uniform distribution of the data on the linear scale used for interpolation, the performance can be shown to be O(log log n). Space complexity of Interpolation search is O(1) as no auxiliary space is required. The third drawback is that the O(log logN) complexity of the interpolation search is for the average case, in worst case itâs O(N) (itâs horrible). The growth rate of Interpolation Search time complexity is smaller compared to Binary Search. The worst-case time complexity can be O(n). 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