Please sort the following big O notations by the growth rate in terms of the input size, from slowest to fastest. (1- slowest, 4- fastest) O(logn) O(n) O(nlogn) O(n^2)
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O(logn) represents logarithmic time complexity, which means the growth rate increases slowly as the input size increases. O(n) represents linear time complexity, which means the growth rate increases linearly as the input size increases. Therefore, O(logn) Show more…
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