Find an exact formula for the worst-case number of comparisons between array elements made by selection_sort on arrays of n elements. Do the same for the number of swaps. // selection sort array 1[0..n-1] void selection_sort(int A], int n) if (n == 1) roturn; // swap largast U rightmost, than racurse swap(A[pmax(A, n)], A[n-1]); selection_sort (A, n-1);

Find an exact formula for the worst-case number of comparisons between array elements made by selection_sort on arrays of n elements. Do the same for the number of swaps. // selection sort array 1[0..n-1] void selection_sort(int A], int n) if (n == 1) roturn; // swap largast U rightmost, than racurse swap(A[pmax(A, n)], A[n-1]); selection_sort (A, n-1);

Database System Concepts

7th Edition

ISBN:9780078022159

Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Chapter1: Introduction

Section: Chapter Questions

Problem 1PE

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Java! please explain clearly with the answer by hand-writing or typing Using merge sort to sort an array of size n, then use binary search to find (1/2)n elements. Using merge sort to sort an array of size n, then run sequential search on it.
Instead of using exch(), provide a version of insertion sort that shifts heavier elements one place to the right with a single array access per entry. To determine whether doing so is successful, use SortCompare.
Write an algorithmic faster version of this code. So the version that copies values from the first sorted half to a temp array then merges the values from the temp arr and the second sorted half into the original arr. public static <T extends Comparable<T>> void MergeSorting(T[] arr) {T[] tep = (T[]) new Comparable[arr.length];MergeSorting(arr, tep, 0, arr.length - 1);}//Recursive helper method for the merge sort algorithm.//arr The array to sort//tep Temporary array for merge operation//start Index of the left end of the region to sort //end Index of the right end of the region to sort. private static <T extends Comparable<T>> void mergeSort(T[] arr, T[] tep, int start,int end) {if (start >= end) {return;}int middle = (left + right) / 2;MergeSorting(arr, tep, start, middle); // first halfMergeSorting(arr, tep, middle + 1, end); //second halfMerge(arr, tep, start, middle, end);}private static <T extends Comparable<T>> void Merge(T[] arr, T[] tep,…
implement merge-sort multithreadA is an array and p and q indexes of the array such as you gonna sort the sub-array A[p..r]. B is a sub-array which willbe populated by the sort.A call to p-merge-sort(A,p,r,B,s) sorts elements from A[p..r] and put them in B[s..s+r-p]
What is time complexity for this Bubble Sort algorithm in seconds/minutes? def bubbleSort(array): length = len(array) for i in range(length-1): for j in range(0, length-i-1): if array[j] > array[j+1] : array[j], array[j+1] = array[j+1], array[j] arr = [56,7,1,9,0,4,34,100,67] print ("Elements of array before sorting:") for i in range(len(arr)): print ("%d" %arr[i]), bubbleSort(arr) print ("Elements of array after sorting:") for i in range(len(arr)): print ("%d" %arr[i])
Let A be an array, where each of the n elements is a randomly chosen integer between 1 and n. For example, if n = 12, this array could be A = [3,5,1,10,5,7,9,12,2,8,8,6]. Determine whether Bubble Sort or Bucket Sort sorts this array faster.
Let M(n) be the minimum number of comparisons needed to sort an array A with exactly n ele- ments. For example, M(1) = 0, M(2) = 1, and M(4) = 4. If n is an even number, clearly explain why M(n) = 2M(n/2) + n/2.
Trace each pass of selection, insertion, and quick sort for the list of values below. For quick sort, assumethat the pivot is the middle value in the portion of the array to be sorted. If there are an even number ofitems in the unsorted part of the list, so that two values “tie” for the middle value, pick the one on theleft as the pivot.The numbers are: 6, 3, 11, 4, 9, 8, 17 ,7
Code only_Given an unsorted array A of size N that contains only positive integers, find a continuous sub-array that adds to a given number S and return the left and right index(1-based indexing) of that subarray. In case of multiple subarrays, return the subarray indexes which come first on moving from left to right. Note:- You have to return an ArrayList consisting of two elements left and right. In case no such subarray exists return an array consisting of element -1..
how do i calculate the time taken to execute this algorithm? import randomdef insertionSort(arr): for i in range(1, len(arr)): key = arr[i] j = i-1 while j >=0 and key < arr[j] : arr[j+1] = arr[j] j -= 1 arr[j+1] = key rand_list = []for k in range (0,100):num= random.randint(0,100)rand_list.append(num)insertionSort(rand_list) print ("Sorted array is:") for i in range(len(rand_list)): print ("%d" %rand_list[i])
A variation of the bubble sort algorithm known as a gap sort examines elements that are some number I positions apart, where I is an integer less than n, rather than neighbouring elements each time through the list. The first element, for instance, would be compared to the element I + 1), the second element, to the element I + 2), the nth element, to the element (n - I and so on. Once all the components that can be compared have been done so, the iteration is finished. I am decreased by a factor greater than 1 on the following iteration, and the procedure continues until I is less than 1. Apply the gap filter.
n a sorted array, from lowest to highest, of all prime numbers less than 100 - searching for which prime numbers using linear search will be better than or equal to binary search? NOTE - in this question marking wrong answers will result in negative scoring, so be extremely careful when answering. Group of answer choices 11 41 5 23 43 29 7 17 37 13 31 2 19 3 47