k-Approximate Quasiperiodicity under Hamming and Edit Distance

Quasiperiodicity in strings was introduced almost 30 years ago as an extension of string periodicity. The basic notions of quasiperiodicity are cover and seed. A cover of a text T is a string whose occurrences in T cover all positions of T. A seed of text T is a cover of a superstring of T. In various applications exact quasiperiodicity is still not sufficient due to the presence of errors. We consider approximate notions of quasiperiodicity, for which we allow approximate occurrences in T with a small Hamming, Levenshtein or weighted edit distance. In previous work Sip et al. (2002) and Christodoulakis et al. (2005) showed that computing approximate covers and seeds, respectively, under weighted edit distance is NP-hard. They, therefore, considered restricted approximate covers and seeds which need to be factors of the original string T and presented polynomial-time algorithms for computing them. Further algorithms, considering approximate occurrences with Hamming distance bounded by k, were given in several contributions by Guth et al. They also studied relaxed approximate quasiperiods that do not need to cover all positions of T. In case of large data the exponents in polynomial time complexity play a crucial role. We present more efficient algorithms for computing restricted approximate covers and seeds. In particular, we improve upon the complexities of many of the aforementioned algorithms, also for relaxed quasiperiods. Our solutions are especially efficient if the number (or total cost) of allowed errors is bounded. We also show NP-hardness of computing non-restricted approximate covers and seeds under Hamming distance. Approximate covers were studied in three recent contributions at CPM over the last three years. However, these works consider a different definition of an approximate cover of T, that is, the shortest exact cover of a string T\u27 with the smallest Hamming distance from T

Approximate Covers of Strings

Tato práce staví na publikaci Kędzierského and Radoszewského, kteří představili vylepšené polynomiální algoritmy řešící problém k-přibližných pokrytí řetězců nad Hammingovou, Levenshteinovou a váženou editační vzdáleností. Práce tyto algoritmy důkladně popisuje, vysvětluje a poskytuje jiný úhel pohledu. Algoritmy jsou implementovány a problémy, které řesí jsou zasazeny do kontextu dalších pravidelností v řetězcích. Implementce je experimentálně otestována a jsou popsány hlavní implementační kroky.This thesis builds upon recent findings of Kędzierski and Radoszewski who presented improved polynomial time algorithms for computing k-approximate covers of strings under Hamming, Levenshtein and weighted edit distance. These algorithms are thoroughly described providing explanations from different point of view. The algorithms are implemented and the problems they solve are inset into the context of other string regularities. The implementation is experimentally evaluated alongside with the description of the main implementation decisions

String Covering: A Survey

The study of strings is an important combinatorial field that precedes the digital computer. Strings can be very long, trillions of letters, so it is important to find compact representations. Here we first survey various forms of one potential compaction methodology, the cover of a given string x, initially proposed in a simple form in 1990, but increasingly of interest as more sophisticated variants have been discovered. We then consider covering by a seed; that is, a cover of a superstring of x. We conclude with many proposals for research directions that could make significant contributions to string processing in future

Can We Recover the Cover?

Data analysis typically involves error recovery and detection of regularities as two different key tasks. In this paper we show that there are data types for which these two tasks can be powerfully combined. A common notion of regularity in strings is that of a cover. Data describing measures of a natural coverable phenomenon may be corrupted by errors caused by the measurement process, or by the inexact features of the phenomenon itself. Due to this reason, different variants of approximate covers have been introduced, some of which are NP-hard to compute. In this paper we assume that the Hamming distance metric measures the amount of corruption experienced, and study the problem of recovering the correct cover from data corrupted by mismatch errors, formally defined as the cover recovery problem (CRP). We show that for the Hamming distance metric, coverability is a powerful property allowing detecting the original cover and correcting the data, under suitable conditions. We also study a relaxation of another problem, which is called the approximate cover problem (ACP). Since the ACP is proved to be NP-hard [Amir,Levy,Lubin,Porat, CPM 2017], we study a relaxation, which we call the candidate-relaxation of the ACP, and show it has a polynomial time complexity. As a result, we get that the ACP also has a polynomial time complexity in many practical situations. An important application of our ACP relaxation study is also a polynomial time algorithm for the cover recovery problem (CRP)

28th Annual Symposium on Combinatorial Pattern Matching : CPM 2017, July 4-6, 2017, Warsaw, Poland

Peer reviewe

LIPIcs, Volume 274, ESA 2023, Complete Volume

LIPIcs, Volume 274, ESA 2023, Complete Volum