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Heap Sort Time Complexity

Heap Sort is an efficient sorting algorithm that operates using a data structure known as a heap. The time complexity of Heap Sort can be analyzed in two main phases: building the heap and performing the sorting.

  1. Building the Heap: This phase takes O(n)O(n)O(n) time, where nnn is the number of elements in the array. The reason for this efficiency is that the heap construction process involves adjusting elements from the bottom of the heap up to the top, which requires less work than repeatedly inserting elements into the heap.

  2. Sorting Phase: This involves repeatedly extracting the maximum element from the heap and placing it in the sorted array. Each extraction operation takes O(log⁡n)O(\log n)O(logn) time since it requires adjusting the heap structure. Since we perform this extraction nnn times, the total time for this phase is O(nlog⁡n)O(n \log n)O(nlogn).

Combining both phases, the overall time complexity of Heap Sort is:

O(n+nlog⁡n)=O(nlog⁡n)O(n + n \log n) = O(n \log n)O(n+nlogn)=O(nlogn)

Thus, Heap Sort has a time complexity of O(nlog⁡n)O(n \log n)O(nlogn) in the average and worst cases, making it a highly efficient algorithm for large datasets.

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