Randomized QuickSort addresses the worst-case time complexity of standard QuickSort by randomly selecting a pivot, ensuring average efficiency of O(n log n) even in adverse scenarios.
By implementing random pivot selection in QuickSort, we can effectively mitigate instances of poor performance, as seen when handling already sorted or reverse sorted arrays.
The proposed C++ implementation exemplifies the Randomized QuickSort algorithm, showcasing its ability to efficiently handle various array configurations while maintaining an in-place sorting strategy.
Thorough testing across multiple scenarios, including random arrays and duplicates, demonstrates the robust efficiency and resilience of Randomized QuickSort against performance pitfalls.
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