Search results
Results from the WOW.Com Content Network
As another example, many sorting algorithms rearrange arrays into sorted order in-place, including: bubble sort, comb sort, selection sort, insertion sort, heapsort, and Shell sort. These algorithms require only a few pointers, so their space complexity is O(log n). [1] Quicksort operates in-place on the data to be sorted.
In computer science, selection sort is an in-place comparison sorting algorithm. It has a O ( n 2 ) time complexity , which makes it inefficient on large lists, and generally performs worse than the similar insertion sort .
For typical serial sorting algorithms, good behavior is O(n log n), with parallel sort in O(log 2 n), and bad behavior is O(n 2). Ideal behavior for a serial sort is O(n), but this is not possible in the average case. Optimal parallel sorting is O(log n). Swaps for "in-place" algorithms. Memory usage (and use of other computer resources).
The other major O(n log n) sorting algorithm is merge sort, but that rarely competes directly with heapsort because it is not in-place. Merge sort's requirement for Ω(n) extra space (roughly half the size of the input) is usually prohibitive except in the situations where merge sort has a clear advantage: When a stable sort is required; When ...
Swapping pairs of items in successive steps of Shellsort with gaps 5, 3, 1. Shellsort, also known as Shell sort or Shell's method, is an in-place comparison sort.It can be understood as either a generalization of sorting by exchange (bubble sort) or sorting by insertion (insertion sort). [3]
Insertion sort is a simple sorting algorithm that builds the final sorted array (or list) one item at a time by comparisons.It is much less efficient on large lists than more advanced algorithms such as quicksort, heapsort, or merge sort.
Cycle sort is an in-place, unstable sorting algorithm, a comparison sort that is theoretically optimal in terms of the total number of writes to the original array, unlike any other in-place sorting algorithm.
A further relaxation requiring only a list of the k smallest elements, but without requiring that these be ordered, makes the problem equivalent to partition-based selection; the original partial sorting problem can be solved by such a selection algorithm to obtain an array where the first k elements are the k smallest, and sorting these, at a total cost of O(n + k log k) operations.