Title
Sublinear Merging and Natural Mergesort
Abstract
The complexity of merging two sorted sequences into one is linear in the worst case as well as in the average case. There are, however, instances for which a sublinear number of comparisons is sufficient. We consider the problem of measuring and exploiting such instance easiness. The merging algorithm presented, Adaptmerge, is shown to adapt optimally to different kinds of measures of instance easiness. In the sorting problem the concept of instance easiness has received a lot of attention, and it is interpreted by a measure of presortedness. We apply Adaptmerge in the already adaptive sorting algorithm Natural Mergesort. The resulting algorithm, Adaptive Mergesort, optimally adapts to several, known and new, measures of presortedness. We also prove some interesting results concerning the relation between measures of presortedness proposed in the literature.
Year
DOI
Venue
1993
10.1007/BF01190160
Algorithmica
Keywords
Field
DocType
Merging,Sorting,Instance easiness,Measures
Sublinear function,Merge sort,Theoretical computer science,Merge (version control),Mathematics
Journal
Volume
Issue
ISSN
9
6
0178-4617
Citations 
PageRank 
References 
16
2.75
6
Authors
3
Name
Order
Citations
PageRank
Svante Carlsson176490.17
Christos Levcopoulos275984.69
Ola Petersson323931.95