eng
Schloss Dagstuhl – Leibniz-Zentrum für Informatik
Leibniz International Proceedings in Informatics
1868-8969
2019-09-06
49:1
49:14
10.4230/LIPIcs.ESA.2019.49
article
Optimal Sorting with Persistent Comparison Errors
Geissmann, Barbara
1
https://orcid.org/0000-0002-9236-8798
Leucci, Stefano
2
https://orcid.org/0000-0002-8848-7006
Liu, Chih-Hung
1
https://orcid.org/0000-0001-9683-5982
Penna, Paolo
1
https://orcid.org/0000-0002-5959-2421
Department of Computer Science, ETH Zürich, Switzerland
Department of Algorithms and Complexity, Max Planck Institute for Informatics, Germany
We consider the problem of sorting n elements in the case of persistent comparison errors. In this problem, each comparison between two elements can be wrong with some fixed (small) probability p, and comparisons cannot be repeated (Braverman and Mossel, SODA'08). Sorting perfectly in this model is impossible, and the objective is to minimize the dislocation of each element in the output sequence, that is, the difference between its true rank and its position. Existing lower bounds for this problem show that no algorithm can guarantee, with high probability, maximum dislocation and total dislocation better than Omega(log n) and Omega(n), respectively, regardless of its running time.
In this paper, we present the first O(n log n)-time sorting algorithm that guarantees both O(log n) maximum dislocation and O(n) total dislocation with high probability. This settles the time complexity of this problem and shows that comparison errors do not increase its computational difficulty: a sequence with the best possible dislocation can be obtained in O(n log n) time and, even without comparison errors, Omega(n log n) time is necessary to guarantee such dislocation bounds.
In order to achieve this optimality result, we solve two sub-problems in the persistent error comparisons model, and the respective methods have their own merits for further application. One is how to locate a position in which to insert an element in an almost-sorted sequence having O(log n) maximum dislocation in such a way that the dislocation of the resulting sequence will still be O(log n). The other is how to simultaneously insert m elements into an almost sorted sequence of m different elements, such that the resulting sequence of 2m elements remains almost sorted.
https://drops.dagstuhl.de/storage/00lipics/lipics-vol144-esa2019/LIPIcs.ESA.2019.49/LIPIcs.ESA.2019.49.pdf
approximate sorting
comparison errors
persistent errors