The given code implements the QuickSort algorithm to sort an array.
In terms of efficiency, the code has a time complexity of O(n log n) in the average and best case, and O(n^2) in the worst case (when the array is already sorted or in reverse order). This is because in the partition function, it divides the array into two parts and calls itself recursively on the two smaller subarrays.
In terms of correctness, the algorithm is correct as it sorts the array in ascending order. It correctly partitions the array by choosing a pivot element and placing it at its correct position. The recursive calls to quickSort on the smaller subarrays ensure that the entire array is sorted.
In terms of clarity, the code is relatively clear and concise. The use of meaningful variable names helps in understanding its purpose. The logic of the QuickSort algorithm is implemented correctly, with the partition function handling the partitioning part and the recursive calls to quickSort handling the sorting of subarrays. However, the lack of comments or explanations makes it slightly less clear, especially for someone unfamiliar with QuickSort. Adding comments to explain the steps and purpose of each function would improve clarity.
Evaluate the following algorithms in terms of its efficiency, correctness, and clarity. Explain your answer in 3-5 sentences. def partition(arr, low, high): i = (low - 1) pivot = arr[high] for j in range(low, high): if arr[j] <= pivot: i = i + 1 arr[i], arr[j] = arr[j], arr[i] arr[i + 1], arr[high] = arr[high], arr[i + 1] return (i + 1) def quickSort(arr, low, high): if len(arr) == 1: return arr if low < high: pi = partition(arr, low, high) quickSort(arr, low, pi - 1) quickSort(arr, pi + 1, high) (4 points)
1 answer