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Key Topics
  • College Programming Assignment Help
  • Implementation of Merge Sort Algorithm
  • Benefits of Getting Help with College Programming Assignments from Our Experts
  • Extensive Topics Covered by Our College Programming Assignment Experts
  • Different Payment Alternatives in Our College Programming Assignment Help Service
  • Elite University Students around the World Turn to Our College Programming Assignment Help Service
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Implementation of Merge Sort Algorithm

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 # Example usage array = [12, 11, 13, 5, 6, 7] merge_sort(array) print("Sorted array is:", array)

The Merge Sort Algorithm is a classic divide-and-conquer sorting algorithm that is highly effective for sorting large datasets. It operates by recursively dividing the array into two halves until each sub-array contains a single element. Then, it merges these sub-arrays in a sorted manner to produce a fully sorted array.

Merge sort has a time complexity of O(n logn), which makes it more efficient than simpler sorting algorithms like bubble sort or insertion sort, especially for larger datasets. Learning this helps students appreciate the importance of algorithm efficiency in programming.

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