Why is merge sort not in place?

Merge sort is not in place because it requires additional memory space to store the auxiliary arrays. The quick sort is in place as it doesn’t require any additional storage. Efficiency : Merge sort is more efficient and works faster than quick sort in case of larger array size or datasets.

What is the advantage of dividing the array into two equal halves in binary search algorithm?

This is the case for other search algorithms based on comparisons, as while they may work faster on some target values, the average performance over all elements is worse than binary search. By dividing the array in half, binary search ensures that the size of both subarrays are as similar as possible.

Why do we need auxiliary array in merge sort?

There is another method to use an auxiliary array (a copy of the original array) to help with sorting in-place, which would give a solution with the same time complexity and O(n) auxiliary space. Generally speaking, Merge Sort has a Time Complexity of O(nlog(n)) and a space complexity of O(n).

Is merge sort divide and conquer?

Merge sort is a divide-and-conquer algorithm based on the idea of breaking down a list into several sub-lists until each sublist consists of a single element and merging those sublists in a manner that results into a sorted list.

How does merge sort merge the lists?

A merge sort is a sorting algorithm that starts by splitting an unordered list of items into two halves called sublists. Then the algorithm repeatedly splits the sublists into smaller sublists until it reaches sublists of single elements.

Why is it necessary to have the auxiliary array in merge ()?

Need: if we want to compare standard sorting algorithms on the basis of space, then Auxiliary Space would be a better criteria than Space Complexity. Merge Sort uses O(n) auxiliary…

How mergemerge sort works?

Merge sort works on divide and conquer approach. Now the idea is to keep on dividing the array till the point we cannot divide it further. This means that we keep on dividing the array in such a way that we are left with many arrays which has only 1 element left. Any array with only one element is already sorted.

Can We do merge sort with a three-way split?

Suppose we do merge sort with a three-way split: divide the array into 3 equal parts, sort each part and do a 3 way merge. What would the worst-case complexity of this version be?

When do we stop dividing array further in mergesort?

Generally in standard mergesort , when we have single element we stop dividing array further , when you want to split in to more than 2parts ,what is your condition for stopping the while in divide method ( its complex).

What is the complexity of the merge sort algorithm?

The complexity of merge sort is O(nlogn) and NOT O(logn). Merge sort is a divide and conquer algorithm. The divide step computes the midpoint of each of the sub-arrays. Each of this step just takes O(1) time. The conquer step recursively sorts two subarrays of n/2 (for even n) elements each.