Divide and Conquer is a paradigm for solving problems that involves breaking a problem into smaller sub-problems, solving the sub-problems recursively, and then combining their solutions to solve the original problem.

Merge Sort is a popular sorting algorithm that follows the divide and conquer strategy. It divides the input array into two halves, recursively sorts the halves, and then merges them.

**Algorithm Overview:**

- **Divide:** Divide the unsorted list into two sublists of about half the size.

- **Conquer:** Recursively sort each sublist.

- **Combine:** Merge the sorted sublists back into one sorted list.

def merge_sort(arr):

if len(arr) > 1:

mid = len(arr) // 2

left_half = arr[:mid]

right_half = arr[mid:]

merge_sort(left_half)

merge_sort(right_half)

i = j = k = 0

while i < len(left_half) and j < len(right_half):

if left_half[i] < right_half[j]:

arr[k] = left_half[i]

i += 1

else:

arr[k] = right_half[j]

j += 1

k += 1

while i < len(left_half):

arr[k] = left_half[i]

i += 1

k += 1

while j < len(right_half):

arr[k] = right_half[j]

j += 1

k += 1

arr = [12, 11, 13, 5, 6, 7]

merge_sort(arr)

print("Sorted array:", arr)

- **Time Complexity:** O(n log n) in all cases

- **Space Complexity:** O(n) additional space for the merge operation