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Why quick sort better than merge sort?
it has less complexity
What is the memory complexity of quick sort algorithm?
The memory complexity of the quick sort algorithm is O(log n) in the best case and O(n) in the worst case.
What is the space complexity of quick sort algorithm?
The space complexity of the quick sort algorithm is O(log n) in the best and average cases, and O(n) in the worst case.
What is the space complexity of the Quick Sort algorithm?
The space complexity of the Quick Sort algorithm is O(log n) in the best and average cases, and O(n) in the worst case.
What is the time complexity of quick sort algorithm?
The time complexity of the quick sort algorithm is O(n log n) in the average case and O(n2) in the worst case.
What is the worst case time complexity of quick sort algorithm?
The worst case time complexity of the quick sort algorithm is O(n2), where n is the number of elements in the input array.
Why quick sort is called quick?
Although quick sort has a worst case time complexity of O(n^2), but for sorting a large amount of numbers, quick sort is very efficient because of the concept of locality of reference.
What is the time and space complexity of the Quick Sort algorithm?
The time complexity of the Quick Sort algorithm is O(n log n) on average and O(n2) in the worst case scenario. The space complexity is O(log n) on average and O(n) in the worst case scenario.
What is the recurrence relation for the quick sort algorithm and how does it affect the time complexity of the sorting process?
The recurrence relation for the quick sort algorithm is T(n) T(k) T(n-k-1) O(n), where k is the position of the pivot element. This relation affects the time complexity of the sorting process because it represents the number of comparisons and swaps needed to sort the elements. The time complexity of quick sort is O(n log n) on average, but can degrade to O(n2) in the worst case scenario.
How do you select pivot in quick sort?
quick sort has a best case time complexity of O(nlogn) and worst case time complexity of 0(n^2). the best case occurs when the pivot element choosen as the center or close to the center element of the list.the time complexity can be derived for this case as: t(n)=2*t(n/2)+n. whereas the worst case time complexity for quick sort happens when the pivot element is towards the end of the list.the time complexity for this can be derived using the recurrence eqn: t(n)=t(n-1)+n
What are the key differences between quick sort and insertion sort in terms of their efficiency and performance?
Quick sort is generally faster than insertion sort for large datasets because it has an average time complexity of O(n log n) compared to insertion sort's O(n2) worst-case time complexity. Quick sort also uses less memory as it sorts in place, while insertion sort requires additional memory for swapping elements. However, insertion sort can be more efficient for small datasets due to its simplicity and lower overhead.
What are the key differences between insertion sort and quick sort in terms of their efficiency and performance?
Insertion sort is a simple sorting algorithm that works well for small lists, but its efficiency decreases as the list size grows. Quick sort, on the other hand, is a more efficient algorithm that works well for larger lists due to its divide-and-conquer approach. Quick sort has an average time complexity of O(n log n), while insertion sort has an average time complexity of O(n2).
