Please help me with this assignment. For this assignment you will implement divide and conquer algorithms: merge sort . For merge sort, you will just implement the algorithm on an array of ints. I have provided the pseudo code for algorithms. You will need to handle cases of all sizes, not just powers of 2. Implement Merge Sort Create a class called MergeSorter in the divideandconquer package. This class will implement merge sort on an array of ints. Implement the following method with the exact signature below. You will need to create private helper methods that do most of the work. public static void mergeSort(int[] arr) This method sorts the int[] arr using the merge sort algorithm described in the pseudocode above.
Please help me with this assignment.
For this assignment you will implement divide and conquer algorithms: merge sort . For merge sort, you will just implement the
Implement Merge Sort
Create a class called MergeSorter in the divideandconquer package. This class will
implement merge sort on an array of ints. Implement the following method with the exact
signature below. You will need to create private helper methods that do most of the work. public static void mergeSort(int[] arr)
This method sorts the int[] arr using the merge sort algorithm described in the pseudocode
above.
![Merge Sort
merge Sort (arr, start, end)
if start>=end
return
mid
midpoint of arr
merge Sort (arr, start, mid)
merge Sort (arr, mid+1, end)
//merge the two parts.
merge (arr, start, mid, end)
merge (arr, start,mid, end)
leftSize =
mid
rightSize = end
left [0..leftSize]
right [0..rightSize]
start + 1;
mid;
for leftIndex-0 to leftSize
left [left Index]
for rightIndex=0 to rightSize
right [right Index] arr [mid+right Index-1]
leftIndex=0
right Index = 0
= arr [start+leftIndex]
left [leftSize] = MAX
right [rightSize] = MAX
for mergeIndex-start to end
else
if left [leftIndex] ≤right [rightIndex]
arr [merge Index] = left [left Index]
leftIndex = leftIndex+1
arr [merge Index] = right [rightIndex]
right Index = rightIndex+1](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F165f5551-99fc-4800-9810-1597ce53807c%2F269348b0-3cbc-4124-af33-04cc48f1b60a%2Fixh56c6_processed.png&w=3840&q=75)
Introduction
Sorting:
The act of sorting involves placing items in a predetermined order. Numerous approaches, such as alphabetical, numerical, or historical ordering, are possible. Programming techniques like sorting algorithms can start sorting an array of elements. These algorithms operate by comparing items and inserting them in the proper order into a new array. One common sorting algorithm is selection sort, which finds the smallest element and moves it to the start of the array. Another well-liked method is bubble sort, which compares two nearby elements and swaps their locations if they aren't in the correct order. In computer science and programming, sorting algorithms are frequently employed for effective data organizing and manipulation.
Merge Sort:
A divide-and-conquer algorithm called merge sort is used to order a list of objects. It functions by splitting the input group into two parts, using merge sort to recursively sort each half, and then combining the two sorted lists.
This is how the algorithm operates:
Make n sublists out of the unsorted list, each with one item (a list of one element is considered sorted).
When there is just one sublist left, continuously merge sublists to create new sorted sublists. This list will be sorted.
The algorithm's performance depends on the merge process. In order to add a new element to the sorted list, it compares the first item of each sublist, chooses the shorter one, and does so. Repeating this cycle until all elements have been merged.
Merge sort has a time complexity of O(n log n), which is much more efficient than most other sorting algorithms, especially for large lists. However, it does require additional memory for the temporary sublists created during the sorting process.
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