Merge Sort Time Complexity Explained: Best, Worst & Average Cases with Examples

Merge Sort Time Complexity Explained: Best, Worst & Average Cases with Examples

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Merge Sort is one of the most efficient and reliable sorting algorithms used in computer science. It follows the Divide and Conquer strategy, breaking down large problems into smaller chunks.

Its time complexity is what makes it stand out:

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  Best Case: O(n log n)

  
  


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  Average Case: O(n log n)

  
  


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  Worst Case: O(n log n)

  
  

Unlike Bubble Sort or Insertion Sort, Merge Sort maintains its performance across all cases — even on already sorted data. It’s especially useful for sorting linked lists and large datasets.

However, its space complexity is O(n), since it requires extra memory for merging.

In summary, Merge Sort is a powerful, predictable, and stable sorting technique — ideal for performance-critical applications. Understand more here-

 

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