Slowsort
Slowsort is a sorting algorithm. It is of humorous nature and not useful. It's based on the principle of multiply and surrender, a tongue-in-cheek joke of divide and conquer. It was published in 1986 by Andrei Broder and Jorge Stolfi in their paper Pessimal Algorithms and Simplexity Analysis[1] (a parody of optimal algorithms and complexity analysis).
Algorithm
Slowsort is a recursive algorithm.
An in-place implementation in pseudo code:
procedure slowsort(A, i, j) // sorts Array A[i],...,A[j]
if i ≥ j then
return
m := ⌊(i+j) / 2⌋
slowsort(A, i, m) // (1.1)
slowsort(A, m+1, j) // (1.2)
if A[j] < A[m] then
swap A[j] and A[m] // (1.3)
slowsort(A, i, j-1) // (2)
- Sort the first half recursively (1.1)
- Sort the second half recursively (1.2)
- Find the maximum of the whole array by comparing the results of 1.1 and 1.2 and place it at the end of the list (1.3)
- Recursively sort the entire list without the maximum in 1.3 (2).
An implementation in Haskell (purely functional) may look as follows.
slowsort :: (Ord a) => [a] -> [a]
slowsort xs
| length xs <= 1 = xs
| otherwise = slowsort xs' ++ [max llast rlast] -- (2)
where m = length xs `div` 2
l = slowsort $ take m xs -- (1.1)
r = slowsort $ drop m xs -- (1.2)
llast = last l
rlast = last r
xs' = init l ++ min llast rlast : init r
Complexity
The runtime for Slowsort is . A lower asymptotic bound for in Landau notation is for any . Slowsort is therefore not in polynomial time. Even the best case is worse than Bubble sort.
References
- "CiteSeerX — Pessimal Algorithms and Simplexity Analysis". CiteSeerX 10.1.1.116.9158. Cite journal requires
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