Consider merging two sorted subarrays of array A = (8 10 12 23 5 17 30) by calling merge(A 1 4 7). How many key comparisons will be made? Consider merging the two sorted subarrays of array A = ( 8, 10, 12, 23, 5, 17, 30 ) bycalling Merge(A, 1, 4, 7). How many key comparisons will be made?

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orted subarrays of array A = (8 10 12 23 5 17 30) by calling merge(A 1 4 7). How many key comparisons will be made?

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

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Concept explainers

Counting sort

The counting sort algorithm sorts an array’s contents by counting the repetition of each element that occurs in the array. A counting sort algorithm is a stable algorithm that works the best when the range of elements in the array is small, say for example from 0 to 9. The count which is the number of repetitions of an element in the array is mapped to an index of an auxiliary array, which is then saved in an auxiliary array. The counting sort algorithm has a stable time complexity of the order of O(size of array + size of auxiliary array). Let’s discuss the algorithm in detail as follows.

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Consider merging two sorted subarrays of array A = (8 10 12 23 5 17 30) by calling merge(A 1 4 7). How many key comparisons will be made?

Consider merging the two sorted subarrays of array A = ( 8, 10, 12, 23, 5, 17, 30 ) by
calling Merge(A, 1, 4, 7). How many key comparisons will be made?

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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 a variant of merge() that merges back to a[ after copying the second half of a[] to aux[] in decreasing order. With this modification, the code that checks if each of the halves has been used up in the inner loop may be removed. The resultant sort is unstable, please note.
Dr. Sponge thinks it's too hard to implement Merge. So, he wants to replace Merge with Insertion Sort (yes, the insertion sort you learned in class). The following is the pseudo-code of the new Merge-Sort, Merge-Sort(p, r) 1. if p == r return 2. q = floor of (p+ r) / 2 3. Merge-Sort(p, q) 4. Merge-Sort(q+1, r) 5. Insertion-Sort(p, r) Give the recurrence for the running time of this new Merge-Sort and solve it. We let T(n) denote the running time when input array has n elements. By solving the recurrence (no need to show how you solved it), we obtain T(n) =
Please give me correct solution.
What's the worst-case runtime of merge sort on an array of size 2n?
e. Implement a version of merge() that copies the second half ofa[] to aux[] in decreasing order and then does the merge back to a[]. This change allows you to remove the code to test that each of the halves has been exhausted from theinner loop. Note: The resulting sort is not stable
Why you guy's are copaying and pasting the asnswer do your known.
Implement a merge() variant that replicates the second half of a[] to aux[] in decreasing order before merging back to a[]. This update allows you to delete the code from the inner loop that tests that each of the halves has been exhausted. Please keep in mind that the resulting sort is not stable.
PLEASE DRAW IT. IT IS NOT CODING
Follow these steps every time it has to identify two arrays to merge in order to develop a bottom-up mergesort that takes use of the order of the arrays: To make a sorted subarray, locate the first item of an array that is smaller than its predecessor, then the second, and so on. Consider the array size and the number of maximal ascending sequences in the array when calculating the execution time of this method.
Write a program to compute the exact value of the number of array accesses usedby top-down mergesort and by bottom-up mergesort. Use your program to plot the values for N from 1 to 512, and to compare the exact values with the upper bound 6N lg N.
For a sequence of {5, 2, 6, 3, 8}, use the first element as pivot, which of the following is the result after performing one time partition in quick sort? (A) 2, 3, 5, 8, 6 (B) 3, 2, 5, 8, 6 (C) 3, 2, 5, 6, 8 (D) 2, 3, 6 5, 8