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Topics Covered | Turnaround Time | Price (USD) |
---|---|---|
Basic Programming Help | 2-3 Days | $50 |
Intermediate Coding Assignments | 3-4 Days | $80 |
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- College Programming Assignment Help
- Implementation of Merge Sort Algorithm
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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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🇬🇧 United Kingdom
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Master’s in Computer Science
🇳🇿 New Zealand
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PhD in Programming
🇺🇸 United States
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PhD in Programming
🇺🇸 United States
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PhD in Programming
🇺🇸 United States
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PhD in Programming
🇺🇸 United States
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Ph.D. in Programming
🇺🇸 United States
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Ph.D. in Computer Science
🇬🇧 United Kingdom
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Ph.D. in Computer Science
🇨🇦 Canada
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Ph.D. in Computer Science
🇺🇸 United States
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🇨🇦 Canada
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Master's in Computer Science
🇳🇿 New Zealand
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Master's in Computer Science
🇦🇺 Australia
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Master's in Computer Science
🇬🇧 United Kingdom
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Ph.D. in Computer Science
🇬🇧 United Kingdom
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Ph.D. in Computer Science
🇨🇦 Canada
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