Quicksort uses Hoare partitioning. Assume an array contains ten keys: 6 3 1 7 9 5 8 2 4 0. After a first round of simple Hoare partitioning (not median-of-three), the array looks like so: Group of answer choices 5 3 1 0 4 2 6 8 9 7 2 3 1 0 4 5 6 8 9 7 3 1 5 2 4 0 6 7 9 8 2 3 0 1 5 4 6 7 8 9 5 3 1 4 0 2 6 7 9 8
Question
Quicksort uses Hoare partitioning. Assume an array contains ten keys: 6 3 1 7 9 5 8 2 4 0. After a first round of simple Hoare partitioning (not median-of-three), the array looks like so: Group of answer choices
5 3 1 0 4 2 6 8 9 7
2 3 1 0 4 5 6 8 9 7
3 1 5 2 4 0 6 7 9 8
2 3 0 1 5 4 6 7 8 9
5 3 1 4 0 2 6 7 9 8
Solution
The correct answer is: 5 3 1 0 4 2 6 8 9 7.
Here's why:
Quicksort uses Hoare partitioning, which involves selecting a pivot and then partitioning the array into two halves - one with elements less than the pivot and one with elements greater than the pivot.
In this case, the pivot is the first element of the array, which is 6.
After the first round of partitioning, all elements less than 6 are on the left and all elements greater than 6 are on the right.
So, the array becomes: 5 3 1 0 4 2 6 8 9 7.
Similar Questions
Consider a modification to QuickSort where each time the partition function is called, the median of the partition array is always found (in constant time) and used as the pivot. The worst-case running time for the algorithm is: Group of answer choices Θ(nlogn) Θ(n^2) Θ(n) Θ(logn)
The O(n log n) average-case running time analysis of quicksort relies on several assumptions. Which of the following does not need to be assumed:Group of answer choicesThat each function call can be carried out in O(1) timeThat each comparison of two elements can be carried out in O(1) timeThat the result of each partitioning step is an arrangement in which the pivot value is equally likely to end up in each position of the partitioned arrayThat the result of each partitioning step is an arrangement in which the pivot value ends up close to the middle of the partitioned arrayThat each swap of two elements can be carried out in O(1) time
def partition(array, low, high): pivot = array[high] i = low - 1 for j in range(low, high): if array[j] <= pivot: i += 1 array[i], array[j] = array[j], array[i] array[i+1], array[high] = array[high], array[i+1] return i+1def quicksort(array, low=0, high=None): if high is None: high = len(array) - 1 if low < high: pivot_index = partition(array, low, high) quicksort(array, low, pivot_index-1) quicksort(array, pivot_index+1, high)my_array = [64, 34, 25, 12, 22, 11, 90, 5]quicksort(my_array)print("Sorted array:", my_array)
When sorting the following array in ascending order with quick sort:16 6 14 12 8 18 4 20 10if choosing the 4th element (i.e. 8) as the pivot, which of the following choices represents the array at one of the middle steps when partitioning the array?
The running time of quick sort depends heavily on the selection of Select one:Pivot elementNo of inputs Arrangement of elements in array Size of elements
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