Journal of the ACM (JACM)
A data structure for manipulating priority queues
Communications of the ACM
Deterministic sorting in O(nlog log n) time and linear space
STOC '02 Proceedings of the thiry-fourth annual ACM symposium on Theory of computing
Information Sciences—Applications: An International Journal
Integer Sorting in 0(n sqrt (log log n)) Expected Time and Linear Space
FOCS '02 Proceedings of the 43rd Symposium on Foundations of Computer Science
Intersection reporting on two collections of disjoint sets
Information Sciences: an International Journal
On embedding subclasses of height-balanced trees in hypercubes
Information Sciences: an International Journal
On the complexity of min-max sorting networks
Information Sciences: an International Journal
Increasing the efficiency of quicksort using a neural network based algorithm selection model
Information Sciences: an International Journal
| Hi-index | 0.07 |
Sorting algorithms based on successive merging of ordered subsequences are widely used, due to their efficiency and to their intrinsically parallelizable structure. Among them, the merge-sort algorithm emerges indisputably as the most prominent method. In this paper we present a variant of merge-sort that proceeds through arbitrary merges between pairs of quasi-ordered subsequences, no matter which their size may be. We provide a detailed analysis, showing that a set of n elements can be sorted by performing at most n@?logn@? key comparisons. Our method has the same optimal asymptotic time and space complexity as compared to previous known unbalanced merge-sort algorithms, but experimental results show that it behaves significantly better in practice.