The time complexity of running merge sort on an array of size n which is already sorted is O(n log n).

Here's why:

1. Merge sort is a divide and conquer algorithm. It works by dividing the array into two halves, sorting them separately, and then merging them.

2. Even if the array is already sorted, merge sort doesn't know this and will still perform the same steps.

3. The division step is O(log n) because each division splits the array in half. This will be done log n times until each array is of size 1.

4. The merge step is O(n) because in the worst case, we have to look at every element in both halves of the array to merge them back together.

5. Since these steps are done together for each division and merge, we multiply their time complexities together, giving us a total time complexity of O(n log n).

So, even if the array is already sorted, merge sort will still take O(n log n) time.

Question

The time complexity of running merge sort on an array of size n which is already sorted is O(n log n).

Here's why:

1. Merge sort is a divide and conquer algorithm. It works by dividing the array into two halves, sorting them separately, and then merging them.

2. Even if the array is already sorted, merge sort doesn't know this and will still perform the same steps.

3. The division step is O(log n) because each division splits the array in half. This will be done log n times until each array is of size 1.

4. The merge step is O(n) because in the worst case, we have to look at every element in both halves of the array to merge them back together.

5. Since these steps are done together for each division and merge, we multiply their time complexities together, giving us a total time complexity of O(n log n).

So, even if the array is already sorted, merge sort will still take O(n log n) time.

Knowee AI · Accepted Answer

The time complexity of running merge sort on an array of size n which is already sorted is O(n log n).

Here's why:

1. Merge sort is a divide and conquer algorithm. It works by dividing the array into two halves, sorting them separately, and then merging them.

2. Even if the array is already sorted, merge sort doesn't know this and will still perform the same steps.

3. The division step is O(log n) because each division splits the array in half. This will be done log n times until each array is of size 1.

4. The merge step is O(n) because in the worst case, we have to look at every element in both halves of the array to merge them back together.

5. Since these steps are done together for each division and merge, we multiply their time complexities together, giving us a total time complexity of O(n log n).

So, even if the array is already sorted, merge sort will still take O(n log n) time.

Running merge sort on an array of size n which is already sorted isO(n)O(nlogn)O(n2) None

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Running merge sort on an array of size n which is already sorted is

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