The definition of antipower introduced by Fici et al. (ICALP 2016) captures the notion of being the opposite of a power: a sequence of k pairwise distinct blocks of the same length. Recently, Alamro et al. (CPM 2019) defined a string to have an antiperiod if it is a prefix of an antipower, and gave complexity bounds for the offline computation of the minimum antiperiod and all the antiperiods of a word. In this paper, we address the same problems in the online setting. Our solutions rely on new arrays that compactly and incrementally store antiperiods and antipowers as the word grows, obtaining in the process this information for all the word’s prefixes. We show how to compute those arrays online in O(n log n) space, O(n log n) time, and o(n^epsilon) delay per character, for any constant epsilon > 0. Running times are worst-case and hold with high probability. We also discuss more space-efficient solutions returning the correct result with high probability, and small data structures to support random access to those arrays.

Online Algorithms on Antipowers and Antiperiods

A. Conte;GUERRINI, VERONICA;N. Pisanti;PUNZI, GIULIA;G. Rosone
2019-01-01

Abstract

The definition of antipower introduced by Fici et al. (ICALP 2016) captures the notion of being the opposite of a power: a sequence of k pairwise distinct blocks of the same length. Recently, Alamro et al. (CPM 2019) defined a string to have an antiperiod if it is a prefix of an antipower, and gave complexity bounds for the offline computation of the minimum antiperiod and all the antiperiods of a word. In this paper, we address the same problems in the online setting. Our solutions rely on new arrays that compactly and incrementally store antiperiods and antipowers as the word grows, obtaining in the process this information for all the word’s prefixes. We show how to compute those arrays online in O(n log n) space, O(n log n) time, and o(n^epsilon) delay per character, for any constant epsilon > 0. Running times are worst-case and hold with high probability. We also discuss more space-efficient solutions returning the correct result with high probability, and small data structures to support random access to those arrays.
2019
978-3-030-32685-2
978-3-030-32686-9
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/1002118
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