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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 kind of opposite of a sorting algorithm is a shuffling algorithm. These are fundamentally different because they require a source of random numbers. Shuffling can also be implemented by a sorting algorithm, namely by a random sort: assigning a random number to each element of the list and then sorting based on the random numbers.
More efficient algorithms such as quicksort, timsort, or merge sort are used by the sorting libraries built into popular programming languages such as Python and Java. [ 2 ] [ 3 ] However, if parallel processing is allowed, bubble sort sorts in O(n) time, making it considerably faster than parallel implementations of insertion sort or selection ...
In computer science, heapsort is a comparison-based sorting algorithm which can be thought of as "an implementation of selection sort using the right data structure." [3] Like selection sort, heapsort divides its input into a sorted and an unsorted region, and it iteratively shrinks the unsorted region by extracting the largest element from it and inserting it into the sorted region.
The worstsort algorithm is based on a bad sorting algorithm, badsort. The badsort algorithm accepts two parameters: L , which is the list to be sorted, and k , which is a recursion depth. At recursion level k = 0 , badsort merely uses a common sorting algorithm, such as bubblesort , to sort its inputs and return the sorted list.
Quicksort is an efficient, general-purpose sorting algorithm. Quicksort was developed by British computer scientist Tony Hoare in 1959 [1] and published in 1961. [2] It is still a commonly used algorithm for sorting. Overall, it is slightly faster than merge sort and heapsort for randomized data, particularly on larger distributions. [3]
In computer science, radix sort is a non-comparative sorting algorithm.It avoids comparison by creating and distributing elements into buckets according to their radix.For elements with more than one significant digit, this bucketing process is repeated for each digit, while preserving the ordering of the prior step, until all digits have been considered.
In computer programming, the Schwartzian transform is a technique used to improve the efficiency of sorting a list of items. This idiom [1] is appropriate for comparison-based sorting when the ordering is actually based on the ordering of a certain property (the key) of the elements, where computing that property is an intensive operation that should be performed a minimal number of times.