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Practical InPlace Mergesort
, 1996
"... Two inplace variants of the classical mergesort algorithm are analysed in detail. The first, straightforward variant performs at most N log 2 N + O(N ) comparisons and 3N log 2 N + O(N ) moves to sort N elements. The second, more advanced variant requires at most N log 2 N + O(N ) comparisons and & ..."
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Cited by 12 (3 self)
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Two inplace variants of the classical mergesort algorithm are analysed in detail. The first, straightforward variant performs at most N log 2 N + O(N ) comparisons and 3N log 2 N + O(N ) moves to sort N elements. The second, more advanced variant requires at most N log 2 N + O(N ) comparisons and "N log 2 N moves, for any fixed " ? 0 and any N ? N ("). In theory, the second one is superior to advanced versions of heapsort. In practice, due to the overhead in the index manipulation, our fastest inplace mergesort behaves still about 50 per cent slower than the bottomup heapsort. However, our implementations are practical compared to mergesort algorithms based on inplace merging. Key words: sorting, mergesort, inplace algorithms CR Classification: F.2.2 1.
An InPlace Sorting with O(n log n) Comparisons and O(n) Moves
 In Proc. 44th Annual IEEE Symposium on Foundations of Computer Science
, 2003
"... Abstract. We present the first inplace algorithm for sorting an array of size n that performs, in the worst case, at most O(n log n) element comparisons and O(n) element transports. This solves a longstanding open problem, stated explicitly, e.g., in [J.I. Munro and V. Raman, Sorting with minimum ..."
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Cited by 9 (0 self)
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Abstract. We present the first inplace algorithm for sorting an array of size n that performs, in the worst case, at most O(n log n) element comparisons and O(n) element transports. This solves a longstanding open problem, stated explicitly, e.g., in [J.I. Munro and V. Raman, Sorting with minimum data movement, J. Algorithms, 13, 374–93, 1992], of whether there exists a sorting algorithm that matches the asymptotic lower bounds on all computational resources simultaneously.
On the Performance of WEAKHEAPSORT
, 2000
"... . Dutton #1993# presents a further HEAPSORT variant called WEAKHEAPSORT, which also contains a new data structure for priority queues. The sorting algorithm and the underlying data structure are analyzed showing that WEAKHEAPSORT is the best HEAPSORT variant and that it has a lot of nice propert ..."
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Cited by 8 (4 self)
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. Dutton #1993# presents a further HEAPSORT variant called WEAKHEAPSORT, which also contains a new data structure for priority queues. The sorting algorithm and the underlying data structure are analyzed showing that WEAKHEAPSORT is the best HEAPSORT variant and that it has a lot of nice properties. It is shown that the worst case number of comparisons is ndlog ne# 2 dlog ne + n #dlog ne#nlog n +0:1nand weak heaps can be generated with n # 1 comparisons. A doubleended priority queue based on weakheaps can be generated in n + dn=2e#2 comparisons. Moreover, examples for the worst and the best case of WEAKHEAPSORT are presented, the number of WeakHeaps on f1;:::;ng is determined, and experiments on the average case are reported. 1
Implementing HEAPSORT with n log n  0.9n and QUICKSORT with n log n + 0.2n Comparisons
 ACM Journal of Experimental Algorithms
, 2002
"... With refinements to the WEAKHEAPSORT... ..."
Pushing the Limits in Sequential Sorting
 Proceedings of the 4 th International Workshop on Algorithm Engineering (WAE 2000
, 2000
"... With refinements to the WEAKHEAPSORT algorithm we establish the general and practical relevant sequential sorting algorithm RELAXEDWEAKHEAPSORT executing exactly ndlog ne#2 dlog ne + 1 # n log n # 0:9n comparisons on any given input. The number of transpositions is bounded by n plus the number of ..."
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Cited by 2 (0 self)
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With refinements to the WEAKHEAPSORT algorithm we establish the general and practical relevant sequential sorting algorithm RELAXEDWEAKHEAPSORT executing exactly ndlog ne#2 dlog ne + 1 # n log n # 0:9n comparisons on any given input. The number of transpositions is bounded by n plus the number of comparisons. Experiments show that RELAXEDWEAKHEAPSORT only requires O(n) extra bits. Even if this space is not available, with QUICKWEAKHEAPSORT we propose an efficient QUICKSORT variant with n log n+0:2n+ o(n) comparisons on the average. Furthermore, we present data showing that WEAKHEAPSORT, RELAXEDWEAKHEAPSORT and QUICKWEAKHEAPSORT beat other performant QUICKSORT and HEAPSORT variants even for moderate values of n.
Quickheapsort: Modifications and improved analysis
 of Lecture Notes in Computer Science
, 2013
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Additional Key Words and Phrases: Sorting inplace
"... Abstract. We present the first inplace algorithm for sorting an array of size n that performs, in the worst case, at most O(n log n) element comparisons and O(n) element transports. This solves a longstanding open problem, stated explicitly, for example, in Munro and Raman [1992], of whether there ..."
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Abstract. We present the first inplace algorithm for sorting an array of size n that performs, in the worst case, at most O(n log n) element comparisons and O(n) element transports. This solves a longstanding open problem, stated explicitly, for example, in Munro and Raman [1992], of whether there exists a sorting algorithm that matches the asymptotic lower bounds on all computational resources simultaneously.
InPlace Sorting With Fewer Moves
 Information Processing Letters
, 1999
"... It is shown that an array of n elements can be sorted using O(1) extra space, O(n log n= log log n) element moves, and n log 2 n+O(n log log n) comparisons. This is the first inplace sorting algorithm requiring o(n log n) moves in the worst case while guaranteeing O(n log n) comparisons but, due to ..."
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It is shown that an array of n elements can be sorted using O(1) extra space, O(n log n= log log n) element moves, and n log 2 n+O(n log log n) comparisons. This is the first inplace sorting algorithm requiring o(n log n) moves in the worst case while guaranteeing O(n log n) comparisons but, due to the constant factors involved, the algorithm is predominantly of theoretical interest. Key words: Inplace algorithms, sorting, merging, mergesort, multiway merge 1
QuickXsort: Efficient Sorting with n log n − 1.399n + o(n) Comparisons on Average
"... In this paper we generalize the idea of QuickHeapsort leading to the notion of QuickXsort. Given some external sorting algorithm X, QuickXsort yields an internal sorting algorithm if X satisfies certain natural conditions. With QuickWeakHeapsort and QuickMergesort we present two examples for the Qui ..."
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In this paper we generalize the idea of QuickHeapsort leading to the notion of QuickXsort. Given some external sorting algorithm X, QuickXsort yields an internal sorting algorithm if X satisfies certain natural conditions. With QuickWeakHeapsort and QuickMergesort we present two examples for the QuickXsortconstruction. Both are efficient algorithms that incur approximately n log n − 1.26n+ o(n) comparisons on the average. A worst case of n log n+O(n) comparisons can be achieved without significantly affecting the average case. Furthermore, we describe an implementation of MergeInsertion for small n. Taking MergeInsertion as a base case for QuickMergesort, we establish a worstcase efficient sorting algorithm calling for n log n−1.3999n+o(n) comparisons on average. QuickMergesort with constant size base cases shows the best performance on practical inputs: when sorting integers it is slower by only 15 % to STLIntrosort. ar X iv