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Finally, the sorting method has a simple parallel implementation, unlike the Fisher–Yates shuffle, which is sequential. A variant of the above method that has seen some use in languages that support sorting with user-specified comparison functions is to shuffle a list by sorting it with a comparison function that returns random values.
A sorting algorithm that only works if the list is already in order, otherwise, the conditions of miracle sort are applied. Divine sort A sorting algorithm that takes a list and decides that because there is such a low probability that the list randomly occurred in its current permutation (a probability of 1/n!, where n is the number of ...
A simple algorithm to generate a permutation of n items uniformly at random without retries, known as the Fisher–Yates shuffle, is to start with any permutation (for example, the identity permutation), and then go through the positions 0 through n − 2 (we use a convention where the first element has index 0, and the last element has index n − 1), and for each position i swap the element ...
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. This is generally not done in practice, however, and there is a well-known simple and efficient algorithm for shuffling: the Fisher–Yates shuffle .
Cocktail shaker sort or bidirectional bubble sort, a bubble sort traversing the list alternately from front to back and back to front; Comb sort; Gnome sort; Odd–even sort; Quicksort: divide list into two, with all items on the first list coming before all items on the second list.; then sort the two lists. Often the method of choice
When the array contains only duplicates of a relatively small number of items, a constant-time perfect hash function can greatly speed up finding where to put an item 1, turning the sort from Θ(n 2) time to Θ(n + k) time, where k is the total number of hashes. The array ends up sorted in the order of the hashes, so choosing a hash function ...
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.
We select a random element q of a random permutation and ask about the expected size of the cycle that contains q. Here the function b ( k ) {\displaystyle b(k)} is equal to k 2 {\displaystyle k^{2}} , because a cycle of length k contributes k elements that are on cycles of length k .
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