## How do you calculate Big O of merge sort?

So we can say that the big o of merge sort is the total cost of splitting plus the total cost of merging or log n + n log n.

## What is merge sorting?

Merge sort is a sorting technique based on divide and conquer technique. With worst-case time complexity being Ο(n log n), it is one of the most respected algorithms. Merge sort first divides the array into equal halves and then combines them in a sorted manner.

**How do you merge in merge sort?**

Step 1: Find the middle index of the array. Step 2: Divide the array from the middle. Step 4: Call merge sort for the second half of the array. Step 5: Merge the two sorted halves into a single sorted array.

**What is merge sort with example?**

Merge sort. An example of merge sort. First divide the list into the smallest unit (1 element), then compare each element with the adjacent list to sort and merge the two adjacent lists. Finally all the elements are sorted and merged.

### Why merge sort complexity is nLogn?

This is because whether it be worst case or average case the merge sort just divide the array in two halves at each stage which gives it lg(n) component and the other N component comes from its comparisons that are made at each stage. So combining it becomes nearly O(nlg n).

### Is MergeSort stable?

YesMerge sort / Stable

**Is merge sort recursive?**

Merge sort is a recursive algorithm that continually splits a list in half. If the list is empty or has one item, it is sorted by definition (the base case). If the list has more than one item, we split the list and recursively invoke a merge sort on both halves.

**Does merge sort requires extra space?**

Space. Merge sort takes up O ( n ) O(n) O(n) extra space, including O ( l g ( n ) ) O(lg(n)) O(lg(n)) space for the recursive call stack.

## Which is better O N or O Nlogn?

Usually the base is less than 4. So for higher values n, n*log(n) becomes greater than n. And that is why O(nlogn) > O(n).