Скачать или смотреть 🥥 Quicksort | Data Structures & Algorithms

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This video introduces Quicksort, another highly efficient, O(n log n) sorting algorithm that is widely used for large datasets. Presented by Hayden Smith, this lecture covers the "divide and conquer" strategy behind Quicksort and common improvements to optimize its performance.

➗ The "Divide and Conquer" Strategy
Quicksort is a recursive algorithm that works by following these steps:
Choose a Pivot: First, an element is chosen from the array to act as the "pivot".
Partition: The array is then rearranged so that all elements smaller than the pivot are moved to its left, and all elements larger than the pivot are moved to its right. After this step, the pivot is in its final, sorted position.
Recurse: The quicksort algorithm is then called recursively on the two sub-arrays on either side of the pivot.

⏱️ Performance and The Pivot
The efficiency of Quicksort is highly dependent on the choice of the pivot element.
Best Case: O(n log n): This occurs when the pivot always splits the array into two roughly equal-sized partitions.
Worst Case: O(n²): This can happen if the chosen pivot is always one of the smallest or largest elements, leading to very unbalanced partitions and degrading the performance to that of a basic sort.

✨ Improvements to Quicksort
To avoid the worst-case scenario and improve performance, several optimizations are commonly used:

Median-of-Three Pivot Selection: Instead of just picking the first element, a more reliable pivot can be chosen by taking the median of the first, middle, and last elements of the array.
Hybrid Approach: Quicksort's recursion has overhead. For very small partitions, it's often faster to switch to a simple algorithm like Insertion Sort, which performs better on small lists.

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