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In computer science, smoothsort is a comparison-based sorting algorithm.A variant of heapsort, it was invented and published by Edsger Dijkstra in 1981. [1] Like heapsort, smoothsort is an in-place algorithm with an upper bound of O(n log n) operations (see big O notation), [2] but it is not a stable sort.
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.
Tournament sort is a sorting algorithm.It improves upon the naive selection sort by using a priority queue to find the next element in the sort. In the naive selection sort, it takes O(n) operations to select the next element of n elements; in a tournament sort, it takes O(log n) operations (after building the initial tournament in O(n)).
In computing, an odd–even sort or odd–even transposition sort (also known as brick sort [1] [self-published source] or parity sort) is a relatively simple sorting algorithm, developed originally for use on parallel processors with local interconnections. It is a comparison sort related to bubble sort, with which it shares many ...
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The algorithm is defined as follows: If the value at the start is larger than the value at the end, swap them. If there are three or more elements in the list, then: Stooge sort the initial 2/3 of the list; Stooge sort the final 2/3 of the list; Stooge sort the initial 2/3 of the list again
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, 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 .