Search results
Results from the WOW.Com Content Network
The advantage of merging ordered runs instead of merging fixed size sub-lists (as done by traditional mergesort) is that it decreases the total number of comparisons needed to sort the entire list. Each run has a minimum size, which is based on the size of the input and is defined at the start of the algorithm. If a run is smaller than this ...
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.
The difference between pigeonhole sort and counting sort is that in counting sort, the auxiliary array does not contain lists of input elements, only counts: 3: 1; 4: 0; 5: 2; 6: 0; 7: 0; 8: 1; For arrays where N is much larger than n, bucket sort is a generalization that is more efficient in space and time.
Conceptually, the merge sort algorithm consists of two steps: Recursively divide the list into sublists of (roughly) equal length, until each sublist contains only one element, or in the case of iterative (bottom up) merge sort, consider a list of n elements as n sub-lists of size 1. A list containing a single element is, by definition, sorted.
If the running time (number of comparisons) of merge sort for a list of length n is T(n), then the recurrence relation T(n) = 2T(n/2) + n follows from the definition of the algorithm (apply the algorithm to two lists of half the size of the original list, and add the n steps taken to merge the resulting two lists). [5]
procedure heapsort(a, count) is input: an unordered array a of length count (Build the heap in array a so that largest value is at the root) heapify(a, count) (The following loop maintains the invariants that a[0:end−1] is a heap, and every element a[end:count−1] beyond end is greater than everything before it, i.e. a[end:count−1] is in ...
The simplest form goes through the whole list each time: procedure cocktailShakerSort(A : list of sortable items) is do swapped := false for each i in 0 to length(A) − 1 do: if A[i] > A[i + 1] then // test whether the two elements are in the wrong order swap(A[i], A[i + 1]) // let the two elements change places swapped := true end if end for if not swapped then // we can exit the outer loop ...
Given we sort using bytes or words of length W bits, the best case is O(KN) and the worst case O(2 K N) or at least O(N 2) as for standard quicksort, given for unique keys N<2 K, and K is a hidden constant in all standard comparison sort algorithms including quicksort.