Logic Visualizer | Python

Merge Sort Algorithm Visualization

Explore the visualization of Merge Sort algorithm through a flowchart and pseudocode, showcasing the recursive divide-and-conquer sorting process.


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Prompt

def merge_sort(arr):
    if len(arr) <= 1:
        return arr
    mid = len(arr) // 2
    left = merge_sort(arr[:mid])
    right = merge_sort(arr[mid:])
    return merge(left, right)

def merge(left, right):
    result = []
    i = j = 0
    while i < len(left) and j < len(right):
        if left[i] < right[j]:
            result.append(left[i])
            i += 1
        else:
            result.append(right[j])
            j += 1
    result.extend(left[i:])
    result.extend(right[j:])
    return result

arr = [38, 27, 43, 3, 9, 82, 10]
sorted_arr = merge_sort(arr)
print(sorted_arr)

Answer

Visual Representation of Merge Sort Algorithm

Flowchart Representation

graph TD
    A(Start) --> B{len(arr) <= 1}
    B -- No --> C[mid = len(arr) // 2]
    C -- Merge Sort(arr[:mid]) --> D
    D -- Merge Sort(arr[mid:]) --> E
    E -- Merge --> F
    F -- Result --> G
    G(End)

    B -- Yes --> G(End)

Pseudocode Representation

Start
if len(arr) <= 1:
    return arr
mid = len(arr) // 2
left = merge_sort(arr[:mid])
right = merge_sort(arr[mid:])
return merge(left, right)

Merge(left, right)
result = []
i = 0
j = 0
while i < len(left) and j < len(right):
    if left[i] < right[j]:
        result.append(left[i])
        i = i + 1
    else:
        result.append(right[j])
        j = j + 1
result.extend(left[i:])
result.extend(right[j:])
return result

arr = [38, 27, 43, 3, 9, 82, 10]
sorted_arr = merge_sort(arr)
print(sorted_arr)

Annotations

  • The algorithm starts with merge_sort function, which recursively divides the array into smaller subarrays until each subarray has only one element. It then merges these subarrays in a sorted manner using the merge function.
  • The merge function compares elements from the left and right subarrays and merges them in sorted order.
  • Key variables like mid, left, right, result, i, and j are used to keep track of indices and subarrays during the sorting and merging process.
  • The algorithm effectively utilizes recursion to divide and conquer the sorting process, ensuring a sorted final array is returned.

By visualizing the merge sort algorithm using the provided flowchart and pseudocode, the logic behind sorting an array using this efficient divide-and-conquer approach becomes clearer and more accessible.

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Description

Explore the visualization of Merge Sort algorithm through a flowchart and pseudocode, showcasing the recursive divide-and-conquer sorting process.

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