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Bubble sort has a worst-case and average complexity of (), where is the number of items being sorted. Most practical sorting algorithms have substantially better worst-case or average complexity, often O ( n log n ) {\displaystyle O(n\log n)} .
But given a worst-case input, its performance degrades to O(n 2). Also, when implemented with the "shortest first" policy, the worst-case space complexity is instead bounded by O(log(n)). Heapsort has O(n) time when all elements are the same. Heapify takes O(n) time and then removing elements from the heap is O(1) time for each of the n elements.
This algorithm's average time and worst-case performance is O(n 2), so it is rarely used to sort large, unordered data sets. Bubble sort can be used to sort a small number of items (where its asymptotic inefficiency is not a high penalty).
In the worst case, the number of comparisons and swaps are both unbounded, for the same reason that a tossed coin might turn up heads any number of times in a row. The best case occurs if the list as given is already sorted; in this case the expected number of comparisons is n − 1, and no swaps at all are carried out. [1]
Performing a Fast Fourier transform; heapsort, quicksort (best and average case), or merge sort quadratic: Multiplying two n-digit numbers by a simple algorithm; bubble sort (worst case or naive implementation), Shell sort, quicksort , selection sort or insertion sort (), >
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Cocktail shaker sort, [1] also known as bidirectional bubble sort, [2] cocktail sort, shaker sort (which can also refer to a variant of selection sort), ripple sort, shuffle sort, [3] or shuttle sort, is an extension of bubble sort. The algorithm extends bubble sort by operating in two directions. While it improves on bubble sort by more ...