![]() ![]() ![]() Then the base case time complexity would be O(n) because we only run i =0, j = 0~n, and break. But if we set a flag to stop the function when the inner for loop didn’t do any swap (It means the array is sorted). Note however, that even though they have the same worst-case complexity, bubble sort performs many more swaps than selection sort does. ![]() O(n²) is the worst case of a Bubble sort algorithm. ![]() Time Complexity: O(n²) Auxiliary Space: O(1) def bubble_sort(arr): n = len(arr) for i in range(n): # O(n) # each i time will put the maximum element in place # so no need to compare again for j in range(0, n-i-1): # O(n) # swap if the element is greater than the next element if arr > arr : arr, arr = arr, arr return arr arr = sorted_arr = bubble_sort(arr) print(sorted_arr) > The algorithm maintains two subarrays in a given array. Since it continuously moves the larger one to the next position and then compares it with the next element, for each loop, it puts the maximum value at the end of the array, and so on. The selection sort algorithm sorts an array by repeatedly finding the minimum element (considering ascending order) from the unsorted part and putting it at the beginning. Starting from the first element, the two groups check whether they need to be exchanged until all the elements are moved to the correct positions, no more exchanges are needed. ![]()
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