Volume
LIPIcs, Volume 191
32nd Annual Symposium on Combinatorial Pattern Matching (CPM 2021)
-
Part of:
Series:
Leibniz International Proceedings in Informatics (LIPIcs)
Conference: Annual Symposium on Combinatorial Pattern Matching (CPM)
Event
CPM 2021, July 5-7, 2021, Wrocław, PolandEditors
Publication Details
- published at: 2021-06-30
- Publisher: Schloss Dagstuhl – Leibniz-Zentrum für Informatik
- ISBN: 978-3-95977-186-3
- DBLP: db/conf/cpm/cpm2021
Access Numbers
- Detailed Access Statistics available here
-
Total Document Accesses (updated on a weekly basis):
0PDF Downloads
Documents
No documents found matching your filter selection.
Document
Complete Volume
LIPIcs, Volume 191, CPM 2021, Complete Volume
Abstract
LIPIcs, Volume 191, CPM 2021, Complete Volume
Cite as
32nd Annual Symposium on Combinatorial Pattern Matching (CPM 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 191, pp. 1-404, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)
Copy BibTex To Clipboard
@Proceedings{gawrychowski_et_al:LIPIcs.CPM.2021,
title = {{LIPIcs, Volume 191, CPM 2021, Complete Volume}},
booktitle = {32nd Annual Symposium on Combinatorial Pattern Matching (CPM 2021)},
pages = {1--404},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-186-3},
ISSN = {1868-8969},
year = {2021},
volume = {191},
editor = {Gawrychowski, Pawe{\l} and Starikovskaya, Tatiana},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CPM.2021},
URN = {urn:nbn:de:0030-drops-139509},
doi = {10.4230/LIPIcs.CPM.2021},
annote = {Keywords: LIPIcs, Volume 191, CPM 2021, Complete Volume}
}
Document
Front Matter
Front Matter, Table of Contents, Preface, Conference Organization
Abstract
Front Matter, Table of Contents, Preface, Conference Organization
Cite as
32nd Annual Symposium on Combinatorial Pattern Matching (CPM 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 191, pp. 0:i-0:xiv, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)
Copy BibTex To Clipboard
@InProceedings{gawrychowski_et_al:LIPIcs.CPM.2021.0,
author = {Gawrychowski, Pawe{\l} and Starikovskaya, Tatiana},
title = {{Front Matter, Table of Contents, Preface, Conference Organization}},
booktitle = {32nd Annual Symposium on Combinatorial Pattern Matching (CPM 2021)},
pages = {0:i--0:xiv},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-186-3},
ISSN = {1868-8969},
year = {2021},
volume = {191},
editor = {Gawrychowski, Pawe{\l} and Starikovskaya, Tatiana},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CPM.2021.0},
URN = {urn:nbn:de:0030-drops-139512},
doi = {10.4230/LIPIcs.CPM.2021.0},
annote = {Keywords: Front Matter, Table of Contents, Preface, Conference Organization}
}
Document
Invited Talk
Repetitions in Strings: A "Constant" Problem (Invited Talk)
Abstract
Repeating structures in strings is one of the most fundamental characteristics of strings, and has been an important topic in the field of combinatorics on words and combinatorial pattern matching since their beginnings. In this talk, I will focus on squares and maximal repetitions and review the "runs" theorem [Hideo Bannai et al., 2017] as well as related results (e.g. [Aviezri S. Fraenkel and Jamie Simpson, 1998; Yuta Fujishige et al., 2017; Ryo Sugahara et al., 2019; Philip Bille et al., 2020; Hideo Bannai et al., 2020; Jonas Ellert and Johannes Fischer, 2021]) which address the two main questions: how many of them can be contained in a string of given length, and algorithms for computing them.
Cite as
Hideo Bannai. Repetitions in Strings: A "Constant" Problem (Invited Talk). In 32nd Annual Symposium on Combinatorial Pattern Matching (CPM 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 191, p. 1:1, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)
Copy BibTex To Clipboard
@InProceedings{bannai:LIPIcs.CPM.2021.1,
author = {Bannai, Hideo},
title = {{Repetitions in Strings: A "Constant" Problem}},
booktitle = {32nd Annual Symposium on Combinatorial Pattern Matching (CPM 2021)},
pages = {1:1--1:1},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-186-3},
ISSN = {1868-8969},
year = {2021},
volume = {191},
editor = {Gawrychowski, Pawe{\l} and Starikovskaya, Tatiana},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CPM.2021.1},
URN = {urn:nbn:de:0030-drops-139523},
doi = {10.4230/LIPIcs.CPM.2021.1},
annote = {Keywords: Maximal repetitions, Squares, Lyndon words}
}
Document
Invited Talk
Computing Edit Distance (Invited Talk)
Abstract
The edit distance (or Levenshtein distance) between two strings x, y is the minimum number of character insertions, deletions, and substitutions needed to convert x into y. It has numerous applications in various fields from text processing to bioinformatics so algorithms for edit distance computation attract lot of attention. In this talk I will survey recent progress on computational aspects of edit distance in several contexts: computing edit distance approximately, sketching and computing it in streaming model, exchanging strings in communication complexity model, and building error correcting codes for edit distance. I will point out many problems that are still open in those areas.
Cite as
Michal Koucký. Computing Edit Distance (Invited Talk). In 32nd Annual Symposium on Combinatorial Pattern Matching (CPM 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 191, p. 2:1, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)
Copy BibTex To Clipboard
@InProceedings{koucky:LIPIcs.CPM.2021.2,
author = {Kouck\'{y}, Michal},
title = {{Computing Edit Distance}},
booktitle = {32nd Annual Symposium on Combinatorial Pattern Matching (CPM 2021)},
pages = {2:1--2:1},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-186-3},
ISSN = {1868-8969},
year = {2021},
volume = {191},
editor = {Gawrychowski, Pawe{\l} and Starikovskaya, Tatiana},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CPM.2021.2},
URN = {urn:nbn:de:0030-drops-139534},
doi = {10.4230/LIPIcs.CPM.2021.2},
annote = {Keywords: edit distance, streaming algorithms, approximation algorithms, sketching}
}
Document
Invited Talk
On-Line Pattern Matching on D-Texts (Invited Talk)
Abstract
The Elastic Degenerate String Matching (EDSM) problem is defined as that of finding an occurrence of a pattern P of length m in an ED-text T. A D-text (Degenerate text) is a string that actually represents a set of similar and aligned strings (e.g. a pan-genome [The Computational Pan-Genomics Consortium, 2018]) by collapsing common fragments into a standard string, and representing variants with sets of alternative substrings. When such substrings are not bound to have the same size, then we talk about elastic D-strings (ED-strings). In [R.Grossi et al., 2017] we gave an O(nm²+N) time on-line algorithm for EDSM, where n is the length of T and N is its size, defined as the total number of letters. A fundamental toolkit of our algorithm is the O(m²+N) time solution of the later called Active Prefixes problem (AP). In [K.Aoyama et al., 2018], a O(m^{1.5} √{log m}+N) solution for AP was shown, leading to a O(nm^{1.5} √{log m}+N) time solution for EDSM. The natural open problem was thus whether the 1.5 exponent could furtherly be decreased. In [G.Bernardini et al., 2019], we prove several properties that answer this and other questions: we give a conditional O(nm^{1.5}+N) lower bound for EDSM, proving that a combinatorial algorithm solving EDSM in O(nm^{1.5-ε} +N) time would break the Boolean Matrix Multiplication (BMM) conjecture; we use this result as a hint to devise a non-combinatorial algorithm that solves EDSM in O(nm^{1.381}+N) time; we do so by successfully combining Fast Fourier Transform and properties of string periodicity. In my talk I will overview the results above, as well as some interesting side results: the extension to a dictionary rather than a single pattern [S.P.Pissis and A.Retha, 2018], the introduction of errors [G.Bernardini et al., 2020], and a notion of matching among D-strings with its linear time solution [M.Alzamel et al., 2020].
Cite as
Nadia Pisanti. On-Line Pattern Matching on D-Texts (Invited Talk). In 32nd Annual Symposium on Combinatorial Pattern Matching (CPM 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 191, pp. 3:1-3:2, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)
Copy BibTex To Clipboard
@InProceedings{pisanti:LIPIcs.CPM.2021.3,
author = {Pisanti, Nadia},
title = {{On-Line Pattern Matching on D-Texts}},
booktitle = {32nd Annual Symposium on Combinatorial Pattern Matching (CPM 2021)},
pages = {3:1--3:2},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-186-3},
ISSN = {1868-8969},
year = {2021},
volume = {191},
editor = {Gawrychowski, Pawe{\l} and Starikovskaya, Tatiana},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CPM.2021.3},
URN = {urn:nbn:de:0030-drops-139548},
doi = {10.4230/LIPIcs.CPM.2021.3},
annote = {Keywords: pattern matching, elastic-degenerate string, matrix multiplication}
}
Document
Ranking Bracelets in Polynomial Time
Abstract
The main result of the paper is the first polynomial-time algorithm for ranking bracelets. The time-complexity of the algorithm is O(k²⋅ n⁴), where k is the size of the alphabet and n is the length of the considered bracelets. The key part of the algorithm is to compute the rank of any word with respect to the set of bracelets by finding three other ranks: the rank over all necklaces, the rank over palindromic necklaces, and the rank over enclosing apalindromic necklaces. The last two concepts are introduced in this paper. These ranks are key components to our algorithm in order to decompose the problem into parts. Additionally, this ranking procedure is used to build a polynomial-time unranking algorithm.
Cite as
Duncan Adamson, Vladimir V. Gusev, Igor Potapov, and Argyrios Deligkas. Ranking Bracelets in Polynomial Time. In 32nd Annual Symposium on Combinatorial Pattern Matching (CPM 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 191, pp. 4:1-4:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)
Copy BibTex To Clipboard
@InProceedings{adamson_et_al:LIPIcs.CPM.2021.4,
author = {Adamson, Duncan and Gusev, Vladimir V. and Potapov, Igor and Deligkas, Argyrios},
title = {{Ranking Bracelets in Polynomial Time}},
booktitle = {32nd Annual Symposium on Combinatorial Pattern Matching (CPM 2021)},
pages = {4:1--4:17},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-186-3},
ISSN = {1868-8969},
year = {2021},
volume = {191},
editor = {Gawrychowski, Pawe{\l} and Starikovskaya, Tatiana},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CPM.2021.4},
URN = {urn:nbn:de:0030-drops-139554},
doi = {10.4230/LIPIcs.CPM.2021.4},
annote = {Keywords: Bracelets, Ranking, Necklaces}
}
Document
The k-Mappability Problem Revisited
Abstract
The k-mappability problem has two integers parameters m and k. For every subword of size m in a text S, we wish to report the number of indices in S in which the word occurs with at most k mismatches.
The problem was lately tackled by Alzamel et al. [Mai Alzamel et al., 2018]. For a text with constant alphabet Σ and k ∈ O(1), they present an algorithm with linear space and O(nlog^{k+1}n) time. For the case in which k = 1 and a constant size alphabet, a faster algorithm with linear space and O(nlog(n)log log(n)) time was presented in [Mai Alzamel et al., 2020].
In this work, we enhance the techniques of [Mai Alzamel et al., 2020] to obtain an algorithm with linear space and O(n log(n)) time for k = 1. Our algorithm removes the constraint of the alphabet being of constant size. We also present linear algorithms for the case of k = 1, |Σ| ∈ O(1) and m = Ω(√n).
Cite as
Amihood Amir, Itai Boneh, and Eitan Kondratovsky. The k-Mappability Problem Revisited. In 32nd Annual Symposium on Combinatorial Pattern Matching (CPM 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 191, pp. 5:1-5:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)
Copy BibTex To Clipboard
@InProceedings{amir_et_al:LIPIcs.CPM.2021.5,
author = {Amir, Amihood and Boneh, Itai and Kondratovsky, Eitan},
title = {{The k-Mappability Problem Revisited}},
booktitle = {32nd Annual Symposium on Combinatorial Pattern Matching (CPM 2021)},
pages = {5:1--5:20},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-186-3},
ISSN = {1868-8969},
year = {2021},
volume = {191},
editor = {Gawrychowski, Pawe{\l} and Starikovskaya, Tatiana},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CPM.2021.5},
URN = {urn:nbn:de:0030-drops-139566},
doi = {10.4230/LIPIcs.CPM.2021.5},
annote = {Keywords: Pattern Matching, Hamming Distance, Suffix Tree, Suffix Array}
}
Document
Internal Shortest Absent Word Queries
Abstract
Given a string T of length n over an alphabet Σ ⊂ {1,2,…,n^{𝒪(1)}} of size σ, we are to preprocess T so that given a range [i,j], we can return a representation of a shortest string over Σ that is absent in the fragment T[i]⋯ T[j] of T. For any positive integer k ∈ [1,log log_σ n], we present an 𝒪((n/k)⋅ log log_σ n)-size data structure, which can be constructed in 𝒪(nlog_σ n) time, and answers queries in time 𝒪(log log_σ k).
Cite as
Golnaz Badkobeh, Panagiotis Charalampopoulos, and Solon P. Pissis. Internal Shortest Absent Word Queries. In 32nd Annual Symposium on Combinatorial Pattern Matching (CPM 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 191, pp. 6:1-6:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)
Copy BibTex To Clipboard
@InProceedings{badkobeh_et_al:LIPIcs.CPM.2021.6,
author = {Badkobeh, Golnaz and Charalampopoulos, Panagiotis and Pissis, Solon P.},
title = {{Internal Shortest Absent Word Queries}},
booktitle = {32nd Annual Symposium on Combinatorial Pattern Matching (CPM 2021)},
pages = {6:1--6:18},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-186-3},
ISSN = {1868-8969},
year = {2021},
volume = {191},
editor = {Gawrychowski, Pawe{\l} and Starikovskaya, Tatiana},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CPM.2021.6},
URN = {urn:nbn:de:0030-drops-139570},
doi = {10.4230/LIPIcs.CPM.2021.6},
annote = {Keywords: string algorithms, internal queries, shortest absent word, bit parallelism}
}
Document
Constructing the Bijective and the Extended Burrows-Wheeler Transform in Linear Time
Abstract
The Burrows-Wheeler transform (BWT) is a permutation whose applications are prevalent in data compression and text indexing. The bijective BWT (BBWT) is a bijective variant of it. Although it is known that the BWT can be constructed in linear time for integer alphabets by using a linear time suffix array construction algorithm, it was up to now only conjectured that the BBWT can also be constructed in linear time. We confirm this conjecture in the word RAM model by proposing a construction algorithm that is based on SAIS, improving the best known result of O(n lg n / lg lg n) time to linear. Since we can reduce the problem of constructing the extended BWT to constructing the BBWT in linear time, we obtain a linear-time algorithm computing the extended BWT at the same time.
Cite as
Hideo Bannai, Juha Kärkkäinen, Dominik Köppl, and Marcin Piątkowski. Constructing the Bijective and the Extended Burrows-Wheeler Transform in Linear Time. In 32nd Annual Symposium on Combinatorial Pattern Matching (CPM 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 191, pp. 7:1-7:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)
Copy BibTex To Clipboard
@InProceedings{bannai_et_al:LIPIcs.CPM.2021.7,
author = {Bannai, Hideo and K\"{a}rkk\"{a}inen, Juha and K\"{o}ppl, Dominik and Pi\k{a}tkowski, Marcin},
title = {{Constructing the Bijective and the Extended Burrows-Wheeler Transform in Linear Time}},
booktitle = {32nd Annual Symposium on Combinatorial Pattern Matching (CPM 2021)},
pages = {7:1--7:16},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-186-3},
ISSN = {1868-8969},
year = {2021},
volume = {191},
editor = {Gawrychowski, Pawe{\l} and Starikovskaya, Tatiana},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CPM.2021.7},
URN = {urn:nbn:de:0030-drops-139588},
doi = {10.4230/LIPIcs.CPM.2021.7},
annote = {Keywords: Burrows-Wheeler Transform, Lyndon words, Circular Suffix Array, Suffix Array Construction Algorithm}
}
Document
Weighted Ancestors in Suffix Trees Revisited
Abstract
The weighted ancestor problem is a well-known generalization of the predecessor problem to trees. It is known to require Ω(log log n) time for queries provided 𝒪(n polylog n) space is available and weights are from [0..n], where n is the number of tree nodes. However, when applied to suffix trees, the problem, surprisingly, admits an 𝒪(n)-space solution with constant query time, as was shown by Gawrychowski, Lewenstein, and Nicholson (Proc. ESA 2014). This variant of the problem can be reformulated as follows: given the suffix tree of a string s, we need a data structure that can locate in the tree any substring s[p..q] of s in 𝒪(1) time (as if one descended from the root reading s[p..q] along the way). Unfortunately, the data structure of Gawrychowski et al. has no efficient construction algorithm, limiting its wider usage as an algorithmic tool. In this paper we resolve this issue, describing a data structure for weighted ancestors in suffix trees with constant query time and a linear construction algorithm. Our solution is based on a novel approach using so-called irreducible LCP values.
Cite as
Djamal Belazzougui, Dmitry Kosolobov, Simon J. Puglisi, and Rajeev Raman. Weighted Ancestors in Suffix Trees Revisited. In 32nd Annual Symposium on Combinatorial Pattern Matching (CPM 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 191, pp. 8:1-8:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)
Copy BibTex To Clipboard
@InProceedings{belazzougui_et_al:LIPIcs.CPM.2021.8,
author = {Belazzougui, Djamal and Kosolobov, Dmitry and Puglisi, Simon J. and Raman, Rajeev},
title = {{Weighted Ancestors in Suffix Trees Revisited}},
booktitle = {32nd Annual Symposium on Combinatorial Pattern Matching (CPM 2021)},
pages = {8:1--8:15},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-186-3},
ISSN = {1868-8969},
year = {2021},
volume = {191},
editor = {Gawrychowski, Pawe{\l} and Starikovskaya, Tatiana},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CPM.2021.8},
URN = {urn:nbn:de:0030-drops-139594},
doi = {10.4230/LIPIcs.CPM.2021.8},
annote = {Keywords: suffix tree, weighted ancestors, irreducible LCP, deterministic substring hashing}
}
Document
Constructing Strings Avoiding Forbidden Substrings
Abstract
We consider the problem of constructing strings over an alphabet Σ that start with a given prefix u, end with a given suffix v, and avoid occurrences of a given set of forbidden substrings. In the decision version of the problem, given a set S_k of forbidden substrings, each of length k, over Σ, we are asked to decide whether there exists a string x over Σ such that u is a prefix of x, v is a suffix of x, and no s ∈ S_k occurs in x. Our first result is an 𝒪(|u|+|v|+k|S_k|)-time algorithm to decide this problem. In the more general optimization version of the problem, given a set S of forbidden arbitrary-length substrings over Σ, we are asked to construct a shortest string x over Σ such that u is a prefix of x, v is a suffix of x, and no s ∈ S occurs in x. Our second result is an 𝒪(|u|+|v|+||S||⋅|Σ|)-time algorithm to solve this problem, where ||S|| denotes the total length of the elements of S.
Interestingly, our results can be directly applied to solve the reachability and shortest path problems in complete de Bruijn graphs in the presence of forbidden edges or of forbidden paths.
Our algorithms are motivated by data privacy, and in particular, by the data sanitization process. In the context of strings, sanitization consists in hiding forbidden substrings from a given string by introducing the least amount of spurious information. We consider the following problem. Given a string w of length n over Σ, an integer k, and a set S_k of forbidden substrings, each of length k, over Σ, construct a shortest string y over Σ such that no s ∈ S_k occurs in y and the sequence of all other length-k fragments occurring in w is a subsequence of the sequence of the length-k fragments occurring in y. Our third result is an 𝒪(nk|S_k|⋅|Σ|)-time algorithm to solve this problem.
Cite as
Giulia Bernardini, Alberto Marchetti-Spaccamela, Solon P. Pissis, Leen Stougie, and Michelle Sweering. Constructing Strings Avoiding Forbidden Substrings. In 32nd Annual Symposium on Combinatorial Pattern Matching (CPM 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 191, pp. 9:1-9:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)
Copy BibTex To Clipboard
@InProceedings{bernardini_et_al:LIPIcs.CPM.2021.9,
author = {Bernardini, Giulia and Marchetti-Spaccamela, Alberto and Pissis, Solon P. and Stougie, Leen and Sweering, Michelle},
title = {{Constructing Strings Avoiding Forbidden Substrings}},
booktitle = {32nd Annual Symposium on Combinatorial Pattern Matching (CPM 2021)},
pages = {9:1--9:18},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-186-3},
ISSN = {1868-8969},
year = {2021},
volume = {191},
editor = {Gawrychowski, Pawe{\l} and Starikovskaya, Tatiana},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CPM.2021.9},
URN = {urn:nbn:de:0030-drops-139604},
doi = {10.4230/LIPIcs.CPM.2021.9},
annote = {Keywords: string algorithms, forbidden strings, de Bruijn graphs, data sanitization}
}
Document
Gapped Indexing for Consecutive Occurrences
Abstract
The classic string indexing problem is to preprocess a string S into a compact data structure that supports efficient pattern matching queries. Typical queries include existential queries (decide if the pattern occurs in S), reporting queries (return all positions where the pattern occurs), and counting queries (return the number of occurrences of the pattern). In this paper we consider a variant of string indexing, where the goal is to compactly represent the string such that given two patterns P₁ and P₂ and a gap range [α, β] we can quickly find the consecutive occurrences of P₁ and P₂ with distance in [α, β], i.e., pairs of subsequent occurrences with distance within the range. We present data structures that use Õ(n) space and query time Õ(|P₁|+|P₂|+n^{2/3}) for existence and counting and Õ(|P₁|+|P₂|+n^{2/3}occ^{1/3}) for reporting. We complement this with a conditional lower bound based on the set intersection problem showing that any solution using Õ(n) space must use Ω̃(|P₁| + |P₂| + √n) query time. To obtain our results we develop new techniques and ideas of independent interest including a new suffix tree decomposition and hardness of a variant of the set intersection problem.
Cite as
Philip Bille, Inge Li Gørtz, Max Rishøj Pedersen, and Teresa Anna Steiner. Gapped Indexing for Consecutive Occurrences. In 32nd Annual Symposium on Combinatorial Pattern Matching (CPM 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 191, pp. 10:1-10:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)
Copy BibTex To Clipboard
@InProceedings{bille_et_al:LIPIcs.CPM.2021.10,
author = {Bille, Philip and G{\o}rtz, Inge Li and Pedersen, Max Rish{\o}j and Steiner, Teresa Anna},
title = {{Gapped Indexing for Consecutive Occurrences}},
booktitle = {32nd Annual Symposium on Combinatorial Pattern Matching (CPM 2021)},
pages = {10:1--10:19},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-186-3},
ISSN = {1868-8969},
year = {2021},
volume = {191},
editor = {Gawrychowski, Pawe{\l} and Starikovskaya, Tatiana},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CPM.2021.10},
URN = {urn:nbn:de:0030-drops-139615},
doi = {10.4230/LIPIcs.CPM.2021.10},
annote = {Keywords: String indexing, two patterns, consecutive occurrences, conditional lower bound}
}
Document
Disorders and Permutations
Abstract
The additive x-disorder of a permutation is the sum of the absolute differences of all pairs of consecutive elements. We show that the additive x-disorder of a permutation of S(n), n ≥ 2, ranges from n-1 to ⌊n²/2⌋ - 1, and we give a complete characterization of permutations having extreme such values. Moreover, for any positive integers n and d such that n ≥ 2 and n-1 ≤ d ≤ ⌊n²/2⌋ - 1, we propose a linear-time algorithm to compute a permutation π ∈ S(n) with additive x-disorder d.
Cite as
Laurent Bulteau, Samuele Giraudo, and Stéphane Vialette. Disorders and Permutations. In 32nd Annual Symposium on Combinatorial Pattern Matching (CPM 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 191, pp. 11:1-11:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)
Copy BibTex To Clipboard
@InProceedings{bulteau_et_al:LIPIcs.CPM.2021.11,
author = {Bulteau, Laurent and Giraudo, Samuele and Vialette, St\'{e}phane},
title = {{Disorders and Permutations}},
booktitle = {32nd Annual Symposium on Combinatorial Pattern Matching (CPM 2021)},
pages = {11:1--11:15},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-186-3},
ISSN = {1868-8969},
year = {2021},
volume = {191},
editor = {Gawrychowski, Pawe{\l} and Starikovskaya, Tatiana},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CPM.2021.11},
URN = {urn:nbn:de:0030-drops-139628},
doi = {10.4230/LIPIcs.CPM.2021.11},
annote = {Keywords: Permutation, Algorithm}
}
Document
Computing Covers of 2D-Strings
Abstract
We consider two notions of covers of a two-dimensional string T. A (rectangular) subarray P of T is a 2D-cover of T if each position of T is in an occurrence of P in T. A one-dimensional string S is a 1D-cover of T if its vertical and horizontal occurrences in T cover all positions of T. We show how to compute the smallest-area 2D-cover of an m × n array T in the optimal 𝒪(N) time, where N = mn, all aperiodic 2D-covers of T in 𝒪(N log N) time, and all 2D-covers of T in N^{4/3}⋅ log^{𝒪(1)}N time. Further, we show how to compute all 1D-covers in the optimal 𝒪(N) time. Along the way, we show that the Klee’s measure of a set of rectangles, each of width and height at least √n, on an n × n grid can be maintained in √n⋅ log^{𝒪(1)}n time per insertion or deletion of a rectangle, a result which could be of independent interest.
Cite as
Panagiotis Charalampopoulos, Jakub Radoszewski, Wojciech Rytter, Tomasz Waleń, and Wiktor Zuba. Computing Covers of 2D-Strings. In 32nd Annual Symposium on Combinatorial Pattern Matching (CPM 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 191, pp. 12:1-12:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)
Copy BibTex To Clipboard
@InProceedings{charalampopoulos_et_al:LIPIcs.CPM.2021.12,
author = {Charalampopoulos, Panagiotis and Radoszewski, Jakub and Rytter, Wojciech and Wale\'{n}, Tomasz and Zuba, Wiktor},
title = {{Computing Covers of 2D-Strings}},
booktitle = {32nd Annual Symposium on Combinatorial Pattern Matching (CPM 2021)},
pages = {12:1--12:20},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-186-3},
ISSN = {1868-8969},
year = {2021},
volume = {191},
editor = {Gawrychowski, Pawe{\l} and Starikovskaya, Tatiana},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CPM.2021.12},
URN = {urn:nbn:de:0030-drops-139635},
doi = {10.4230/LIPIcs.CPM.2021.12},
annote = {Keywords: 2D-string, cover, dynamic Klee’s measure problem}
}
Document
A Fast and Small Subsampled R-Index
Abstract
The r-index (Gagie et al., JACM 2020) represented a breakthrough in compressed indexing of repetitive text collections, outperforming its alternatives by orders of magnitude. Its space usage, 𝒪(r) where r is the number of runs in the Burrows-Wheeler Transform of the text, is however larger than Lempel-Ziv and grammar-based indexes, and makes it uninteresting in various real-life scenarios of milder repetitiveness. In this paper we introduce the sr-index, a variant that limits a large fraction of the space to 𝒪(min(r,n/s)) for a text of length n and a given parameter s, at the expense of multiplying by s the time per occurrence reported. The sr-index is obtained by carefully subsampling the text positions indexed by the r-index, in a way that we prove is still able to support pattern matching with guaranteed performance. Our experiments demonstrate that the sr-index sharply outperforms virtually every other compressed index on repetitive texts, both in time and space, even matching the performance of the r-index while using 1.5-3.0 times less space. Only some Lempel-Ziv-based indexes achieve better compression than the sr-index, using about half the space, but they are an order of magnitude slower.
Cite as
Dustin Cobas, Travis Gagie, and Gonzalo Navarro. A Fast and Small Subsampled R-Index. In 32nd Annual Symposium on Combinatorial Pattern Matching (CPM 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 191, pp. 13:1-13:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)
Copy BibTex To Clipboard
@InProceedings{cobas_et_al:LIPIcs.CPM.2021.13,
author = {Cobas, Dustin and Gagie, Travis and Navarro, Gonzalo},
title = {{A Fast and Small Subsampled R-Index}},
booktitle = {32nd Annual Symposium on Combinatorial Pattern Matching (CPM 2021)},
pages = {13:1--13:16},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-186-3},
ISSN = {1868-8969},
year = {2021},
volume = {191},
editor = {Gawrychowski, Pawe{\l} and Starikovskaya, Tatiana},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CPM.2021.13},
URN = {urn:nbn:de:0030-drops-139647},
doi = {10.4230/LIPIcs.CPM.2021.13},
annote = {Keywords: Pattern matching, r-index, compressed text indexing, repetitive text collections}
}
Document
The Longest Run Subsequence Problem: Further Complexity Results
Abstract
Longest Run Subsequence is a problem introduced recently in the context of the scaffolding phase of genome assembly (Schrinner et al., WABI 2020). The problem asks for a maximum length subsequence of a given string that contains at most one run for each symbol (a run is a maximum substring of consecutive identical symbols). The problem has been shown to be NP-hard and to be fixed-parameter tractable when the parameter is the size of the alphabet on which the input string is defined. In this paper we further investigate the complexity of the problem and we show that it is fixed-parameter tractable when it is parameterized by the number of runs in a solution, a smaller parameter. Moreover, we investigate the kernelization complexity of Longest Run Subsequence and we prove that it does not admit a polynomial kernel when parameterized by the size of the alphabet or by the number of runs. Finally, we consider the restriction of Longest Run Subsequence when each symbol has at most two occurrences in the input string and we show that it is APX-hard.
Cite as
Riccardo Dondi and Florian Sikora. The Longest Run Subsequence Problem: Further Complexity Results. In 32nd Annual Symposium on Combinatorial Pattern Matching (CPM 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 191, pp. 14:1-14:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)
Copy BibTex To Clipboard
@InProceedings{dondi_et_al:LIPIcs.CPM.2021.14,
author = {Dondi, Riccardo and Sikora, Florian},
title = {{The Longest Run Subsequence Problem: Further Complexity Results}},
booktitle = {32nd Annual Symposium on Combinatorial Pattern Matching (CPM 2021)},
pages = {14:1--14:15},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-186-3},
ISSN = {1868-8969},
year = {2021},
volume = {191},
editor = {Gawrychowski, Pawe{\l} and Starikovskaya, Tatiana},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CPM.2021.14},
URN = {urn:nbn:de:0030-drops-139652},
doi = {10.4230/LIPIcs.CPM.2021.14},
annote = {Keywords: Parameterized complexity, Kernelization, Approximation Hardness, Longest Subsequence}
}
Document
Data Structures for Categorical Path Counting Queries
Abstract
Consider an ordinal tree T on n nodes, each of which is assigned a category from an alphabet [σ] = {1,2,…,σ}. We preprocess the tree T in order to support {categorical path counting queries}, which ask for the number of distinct categories occurring on the path in T between two query nodes x and y. For this problem, we propose a linear-space data structure with query time O(√n lg((lg σ)/(lg w))), where w = Ω(lg n) is the word size in the word-RAM. As shown in our proof, from the assumption that matrix multiplication cannot be solved in time faster than cubic (with only combinatorial methods), our result is optimal, save for polylogarithmic speed-ups. For a trade-off parameter 1 ≤ t ≤ n, we propose an O(n+ n²/t²)-word, O(t lg ((lg σ)/(lg w))) query time data structure. We also consider c-approximate categorical path counting queries, which must return an approximation to the number of distinct categories occurring on the query path, by counting each such category at least once and at most c times. We describe a linear-space data structure that supports 2-approximate categorical path counting queries in O((lg n)/(lg lg n)) time.
Next, we generalize the categorical path counting queries to weighted trees. Here, a query specifies two nodes x,y and an orthogonal range Q. The answer to thus formed categorical path range counting query is the number of distinct categories occurring on the path from x to y, if only the nodes with weights falling inside Q are considered. We propose an O(n lg lg n +(n/t)⁴)-word data structure with O(t lg lg n) query time, or an O(n+(n/t)⁴)-word} data structure with O(t lg^ε n) query time. For an appropriate choice of the trade-off parameter t, this implies a linear-space data structure with O(n^{3/4} lg^ε n) query time. We then extend the approach to the trees weighted with vectors from [n]^{d}, where d is a constant integer greater than or equal to 2. We present a data structure with O(n lg^{d-1+ε} n + (n/t)^{2d+2}) words of space and O(t (lg^{d-1} n)/((lg lg n)^{d-2})) query time. For an O(n⋅polylog n)-space solution, one thus has O(n^{{2d+1}/{2d+2}}⋅polylog n) query time.
The inherent difficulty revealed by the lower bound we proved motivated us to consider data structures based on {sketching}. In unweighted trees, we propose a sketching data structure to solve the approximate categorical path counting problem which asks for a (1±ε)-approximation (i.e. within 1±ε of the true answer) of the number of distinct categories on the given path, with probability 1-δ, where 0 < ε,δ < 1 are constants. The data structure occupies O(n+n/t lg n) words of space, for the query time of O(t lg n). For trees weighted with d-dimensional weight vectors (d ≥ 1), we propose a data structure with O((n + n/t lg n) lg^d n) words of space and O(t lg^{d+1} n) query time.
All these problems generalize the corresponding categorical range counting problems in Euclidean space ℝ^{d+1}, for respective d, by replacing one of the dimensions with a tree topology.
Cite as
Meng He and Serikzhan Kazi. Data Structures for Categorical Path Counting Queries. In 32nd Annual Symposium on Combinatorial Pattern Matching (CPM 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 191, pp. 15:1-15:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)
Copy BibTex To Clipboard
@InProceedings{he_et_al:LIPIcs.CPM.2021.15,
author = {He, Meng and Kazi, Serikzhan},
title = {{Data Structures for Categorical Path Counting Queries}},
booktitle = {32nd Annual Symposium on Combinatorial Pattern Matching (CPM 2021)},
pages = {15:1--15:17},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-186-3},
ISSN = {1868-8969},
year = {2021},
volume = {191},
editor = {Gawrychowski, Pawe{\l} and Starikovskaya, Tatiana},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CPM.2021.15},
URN = {urn:nbn:de:0030-drops-139662},
doi = {10.4230/LIPIcs.CPM.2021.15},
annote = {Keywords: data structures, weighted trees, path queries, categorical queries, coloured queries, categorical path counting, categorical path range counting}
}
Document
Compressed Weighted de Bruijn Graphs
Abstract
We propose a new compressed representation for weighted de Bruijn graphs, which is based on the idea of delta-encoding the variations of k-mer abundances on a spanning branching of the graph. Our new data structure is likely to be of practical value: to give an idea, when combined with the compressed BOSS de Bruijn graph representation, it encodes the weighted de Bruijn graph of a 16x-covered DNA read-set (60M distinct k-mers, k = 28) within 4.15 bits per distinct k-mer and can answer abundance queries in about 60 microseconds on a standard machine. In contrast, state of the art tools declare a space usage of at least 30 bits per distinct k-mer for the same task, which is confirmed by our experiments. As a by-product of our new data structure, we exhibit efficient compressed data structures for answering partial sums on edge-weighted trees, which might be of independent interest.
Cite as
Giuseppe F. Italiano, Nicola Prezza, Blerina Sinaimeri, and Rossano Venturini. Compressed Weighted de Bruijn Graphs. In 32nd Annual Symposium on Combinatorial Pattern Matching (CPM 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 191, pp. 16:1-16:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)
Copy BibTex To Clipboard
@InProceedings{italiano_et_al:LIPIcs.CPM.2021.16,
author = {Italiano, Giuseppe F. and Prezza, Nicola and Sinaimeri, Blerina and Venturini, Rossano},
title = {{Compressed Weighted de Bruijn Graphs}},
booktitle = {32nd Annual Symposium on Combinatorial Pattern Matching (CPM 2021)},
pages = {16:1--16:16},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-186-3},
ISSN = {1868-8969},
year = {2021},
volume = {191},
editor = {Gawrychowski, Pawe{\l} and Starikovskaya, Tatiana},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CPM.2021.16},
URN = {urn:nbn:de:0030-drops-139675},
doi = {10.4230/LIPIcs.CPM.2021.16},
annote = {Keywords: weighted de Bruijn graphs, k-mer annotation, compressed data structures, partial sums}
}
Document
Optimal Construction of Hierarchical Overlap Graphs
Abstract
Genome assembly is a fundamental problem in Bioinformatics, where for a given set of overlapping substrings of a genome, the aim is to reconstruct the source genome. The classical approaches to solving this problem use assembly graphs, such as de Bruijn graphs or overlap graphs, which maintain partial information about such overlaps. For genome assembly algorithms, these graphs present a trade-off between overlap information stored and scalability. Thus, Hierarchical Overlap Graph (HOG) was proposed to overcome the limitations of both these approaches.
For a given set P of n strings, the first algorithm to compute HOG was given by Cazaux and Rivals [IPL20] requiring O(||P||+n²) time using superlinear space, where ||P|| is the cumulative sum of the lengths of strings in P. This was improved by Park et al. [SPIRE20] to O(||P||log n) time and O(||P||) space using segment trees, and further to O(||P||(log n)/(log log n)) for the word RAM model. Both these results described an open problem to compute HOG in optimal O(||P||) time and space. In this paper, we achieve the desired optimal bounds by presenting a simple algorithm that does not use any complex data structures. At its core, our solution improves the classical result [IPL92] for a special case of the All Pairs Suffix Prefix (APSP) problem from O(||P||+n²) time to optimal O(||P||) time, which may be of independent interest.
Cite as
Shahbaz Khan. Optimal Construction of Hierarchical Overlap Graphs. In 32nd Annual Symposium on Combinatorial Pattern Matching (CPM 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 191, pp. 17:1-17:11, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)
Copy BibTex To Clipboard
@InProceedings{khan:LIPIcs.CPM.2021.17,
author = {Khan, Shahbaz},
title = {{Optimal Construction of Hierarchical Overlap Graphs}},
booktitle = {32nd Annual Symposium on Combinatorial Pattern Matching (CPM 2021)},
pages = {17:1--17:11},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-186-3},
ISSN = {1868-8969},
year = {2021},
volume = {191},
editor = {Gawrychowski, Pawe{\l} and Starikovskaya, Tatiana},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CPM.2021.17},
URN = {urn:nbn:de:0030-drops-139683},
doi = {10.4230/LIPIcs.CPM.2021.17},
annote = {Keywords: Hierarchical Overlap Graphs, String algorithms, Genome assembly}
}
Document
A Compact Index for Cartesian Tree Matching
Abstract
Cartesian tree matching is a recently introduced string matching problem in which two strings match if their corresponding Cartesian trees are the same. It is considered appropriate to find patterns regarding their shapes especially in numerical time series data. While many related problems have been addressed, developing a compact index has received relatively less attention. In this paper, we present a 3n+o(n)-bit index that can count the number of occurrences of a Cartesian tree pattern in 𝒪(m) time where n and m are the text and pattern length. To the best of our knowledge, this work is the first 𝒪(n)-bit compact data structure for indexing for this problem.
Cite as
Sung-Hwan Kim and Hwan-Gue Cho. A Compact Index for Cartesian Tree Matching. In 32nd Annual Symposium on Combinatorial Pattern Matching (CPM 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 191, pp. 18:1-18:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)
Copy BibTex To Clipboard
@InProceedings{kim_et_al:LIPIcs.CPM.2021.18,
author = {Kim, Sung-Hwan and Cho, Hwan-Gue},
title = {{A Compact Index for Cartesian Tree Matching}},
booktitle = {32nd Annual Symposium on Combinatorial Pattern Matching (CPM 2021)},
pages = {18:1--18:19},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-186-3},
ISSN = {1868-8969},
year = {2021},
volume = {191},
editor = {Gawrychowski, Pawe{\l} and Starikovskaya, Tatiana},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CPM.2021.18},
URN = {urn:nbn:de:0030-drops-139699},
doi = {10.4230/LIPIcs.CPM.2021.18},
annote = {Keywords: String Matching, Suffix Array, FM-index, Compact Index, Cartesian Tree Matching}
}
Document
String Sanitization Under Edit Distance: Improved and Generalized
Abstract
Let W be a string of length n over an alphabet Σ, k be a positive integer, and 𝒮 be a set of length-k substrings of W. The ETFS problem (Edit distance, Total order, Frequency, Sanitization) asks us to construct a string X_ED such that: (i) no string of 𝒮 occurs in X_ED; (ii) the order of all other length-k substrings over Σ (and thus the frequency) is the same in W and in X_ED; and (iii) X_ED has minimal edit distance to W. When W represents an individual’s data and 𝒮 represents a set of confidential patterns, the ETFS problem asks for transforming W to preserve its privacy and its utility [Bernardini et al., ECML PKDD 2019].
ETFS can be solved in 𝒪(n²k) time [Bernardini et al., CPM 2020]. The same paper shows that ETFS cannot be solved in 𝒪(n^{2-δ}) time, for any δ > 0, unless the Strong Exponential Time Hypothesis (SETH) is false. Our main results can be summarized as follows:
- An 𝒪(n²log²k)-time algorithm to solve ETFS.
- An 𝒪(n²log²n)-time algorithm to solve AETFS (Arbitrary lengths, Edit distance, Total order, Frequency, Sanitization), a generalization of ETFS in which the elements of 𝒮 can have arbitrary lengths. Our algorithms are thus optimal up to subpolynomial factors, unless SETH fails.
In order to arrive at these results, we develop new techniques for computing a variant of the standard dynamic programming (DP) table for edit distance. In particular, we simulate the DP table computation using a directed acyclic graph in which every node is assigned to a smaller DP table. We then focus on redundancy in these DP tables and exploit a tabulation technique according to dyadic intervals to obtain an optimal alignment in 𝒪̃(n²) total time. Beyond string sanitization, our techniques may inspire solutions to other problems related to regular expressions or context-free grammars.
Cite as
Takuya Mieno, Solon P. Pissis, Leen Stougie, and Michelle Sweering. String Sanitization Under Edit Distance: Improved and Generalized. In 32nd Annual Symposium on Combinatorial Pattern Matching (CPM 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 191, pp. 19:1-19:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)
Copy BibTex To Clipboard
@InProceedings{mieno_et_al:LIPIcs.CPM.2021.19,
author = {Mieno, Takuya and Pissis, Solon P. and Stougie, Leen and Sweering, Michelle},
title = {{String Sanitization Under Edit Distance: Improved and Generalized}},
booktitle = {32nd Annual Symposium on Combinatorial Pattern Matching (CPM 2021)},
pages = {19:1--19:18},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-186-3},
ISSN = {1868-8969},
year = {2021},
volume = {191},
editor = {Gawrychowski, Pawe{\l} and Starikovskaya, Tatiana},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CPM.2021.19},
URN = {urn:nbn:de:0030-drops-139709},
doi = {10.4230/LIPIcs.CPM.2021.19},
annote = {Keywords: string algorithms, data sanitization, edit distance, dynamic programming}
}
Document
An Invertible Transform for Efficient String Matching in Labeled Digraphs
Abstract
Let G = (V, E) be a digraph where each vertex is unlabeled, each edge is labeled by a character in some alphabet Ω, and any two edges with both the same head and the same tail have different labels. The powerset construction gives a transform of G into a weakly connected digraph G' = (V', E') that enables solving the decision problem of whether there is a walk in G matching an arbitrarily long query string q in time linear in |q| and independent of |E| and |V|. We show G is uniquely determined by G' when for every v_𝓁 ∈ V, there is some distinct string s_𝓁 on Ω such that v_𝓁 is the origin of a closed walk in G matching s_𝓁, and no other walk in G matches s_𝓁 unless it starts and ends at v_𝓁. We then exploit this invertibility condition to strategically alter any G so its transform G' enables retrieval of all t terminal vertices of walks in the unaltered G matching q in O(|q| + t log |V|) time. We conclude by proposing two defining properties of a class of transforms that includes the Burrows-Wheeler transform and the transform presented here.
Cite as
Abhinav Nellore, Austin Nguyen, and Reid F. Thompson. An Invertible Transform for Efficient String Matching in Labeled Digraphs. In 32nd Annual Symposium on Combinatorial Pattern Matching (CPM 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 191, pp. 20:1-20:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)
Copy BibTex To Clipboard
@InProceedings{nellore_et_al:LIPIcs.CPM.2021.20,
author = {Nellore, Abhinav and Nguyen, Austin and Thompson, Reid F.},
title = {{An Invertible Transform for Efficient String Matching in Labeled Digraphs}},
booktitle = {32nd Annual Symposium on Combinatorial Pattern Matching (CPM 2021)},
pages = {20:1--20:14},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-186-3},
ISSN = {1868-8969},
year = {2021},
volume = {191},
editor = {Gawrychowski, Pawe{\l} and Starikovskaya, Tatiana},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CPM.2021.20},
URN = {urn:nbn:de:0030-drops-139717},
doi = {10.4230/LIPIcs.CPM.2021.20},
annote = {Keywords: pattern matching, string matching, Burrows-Wheeler transform, labeled graphs}
}
Document
R-enum: Enumeration of Characteristic Substrings in BWT-runs Bounded Space
Abstract
Enumerating characteristic substrings (e.g., maximal repeats, minimal unique substrings, and minimal absent words) in a given string has been an important research topic because there are a wide variety of applications in various areas such as string processing and computational biology. Although several enumeration algorithms for characteristic substrings have been proposed, they are not space-efficient in that their space-usage is proportional to the length of an input string. Recently, the run-length encoded Burrows-Wheeler transform (RLBWT) has attracted increased attention in string processing, and various algorithms for the RLBWT have been developed. Developing enumeration algorithms for characteristic substrings with the RLBWT, however, remains a challenge. In this paper, we present r-enum (RLBWT-based enumeration), the first enumeration algorithm for characteristic substrings based on RLBWT. R-enum runs in O(n log log (n/r)) time and with O(r log n) bits of working space for string length n and number r of runs in RLBWT. Here, r is expected to be significantly smaller than n for highly repetitive strings (i.e., strings with many repetitions). Experiments using a benchmark dataset of highly repetitive strings show that the results of r-enum are more space-efficient than the previous results. In addition, we demonstrate the applicability of r-enum to a huge string by performing experiments on a 300-gigabyte string of 100 human genomes.
Cite as
Takaaki Nishimoto and Yasuo Tabei. R-enum: Enumeration of Characteristic Substrings in BWT-runs Bounded Space. In 32nd Annual Symposium on Combinatorial Pattern Matching (CPM 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 191, pp. 21:1-21:21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)
Copy BibTex To Clipboard
@InProceedings{nishimoto_et_al:LIPIcs.CPM.2021.21,
author = {Nishimoto, Takaaki and Tabei, Yasuo},
title = {{R-enum: Enumeration of Characteristic Substrings in BWT-runs Bounded Space}},
booktitle = {32nd Annual Symposium on Combinatorial Pattern Matching (CPM 2021)},
pages = {21:1--21:21},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-186-3},
ISSN = {1868-8969},
year = {2021},
volume = {191},
editor = {Gawrychowski, Pawe{\l} and Starikovskaya, Tatiana},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CPM.2021.21},
URN = {urn:nbn:de:0030-drops-139723},
doi = {10.4230/LIPIcs.CPM.2021.21},
annote = {Keywords: Enumeration algorithm, Burrows-Wheeler transform, Maximal repeats, Minimal unique substrings, Minimal absent words}
}
Document
A Linear Time Algorithm for Constructing Hierarchical Overlap Graphs
Abstract
The hierarchical overlap graph (HOG) is a graph that encodes overlaps from a given set P of n strings, as the overlap graph does. A best known algorithm constructs HOG in O(||P|| log n) time and O(||P||) space, where ||P|| is the sum of lengths of the strings in P. In this paper we present a new algorithm to construct HOG in O(||P||) time and space. Hence, the construction time and space of HOG are better than those of the overlap graph, which are O(||P|| + n²).
Cite as
Sangsoo Park, Sung Gwan Park, Bastien Cazaux, Kunsoo Park, and Eric Rivals. A Linear Time Algorithm for Constructing Hierarchical Overlap Graphs. In 32nd Annual Symposium on Combinatorial Pattern Matching (CPM 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 191, pp. 22:1-22:9, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)
Copy BibTex To Clipboard
@InProceedings{park_et_al:LIPIcs.CPM.2021.22,
author = {Park, Sangsoo and Park, Sung Gwan and Cazaux, Bastien and Park, Kunsoo and Rivals, Eric},
title = {{A Linear Time Algorithm for Constructing Hierarchical Overlap Graphs}},
booktitle = {32nd Annual Symposium on Combinatorial Pattern Matching (CPM 2021)},
pages = {22:1--22:9},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-186-3},
ISSN = {1868-8969},
year = {2021},
volume = {191},
editor = {Gawrychowski, Pawe{\l} and Starikovskaya, Tatiana},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CPM.2021.22},
URN = {urn:nbn:de:0030-drops-139736},
doi = {10.4230/LIPIcs.CPM.2021.22},
annote = {Keywords: overlap graph, hierarchical overlap graph, shortest superstring problem, border array}
}
Document
Efficient Algorithms for Counting Gapped Palindromes
Abstract
A gapped palindrome is a string uvu^{R}, where u^{R} represents the reverse of string u. In this paper we show three efficient algorithms for counting the occurrences of gapped palindromes in a given string S of length N. First, we present a solution in O(N) time for counting all gapped palindromes without additional constraints. Then, in the case where the length of v is constrained to be in an interval [g, G], we show an algorithm with running time O(N log N). Finally, we show an algorithm in O(N log² N) time for a more general case where we count gapped palindromes uvu^{R}, where u^{R} starts at position i with g(i) ≤ v ≤ G(i), for all positions i.
Cite as
Andrei Popa and Alexandru Popa. Efficient Algorithms for Counting Gapped Palindromes. In 32nd Annual Symposium on Combinatorial Pattern Matching (CPM 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 191, pp. 23:1-23:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)
Copy BibTex To Clipboard
@InProceedings{popa_et_al:LIPIcs.CPM.2021.23,
author = {Popa, Andrei and Popa, Alexandru},
title = {{Efficient Algorithms for Counting Gapped Palindromes}},
booktitle = {32nd Annual Symposium on Combinatorial Pattern Matching (CPM 2021)},
pages = {23:1--23:13},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-186-3},
ISSN = {1868-8969},
year = {2021},
volume = {191},
editor = {Gawrychowski, Pawe{\l} and Starikovskaya, Tatiana},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CPM.2021.23},
URN = {urn:nbn:de:0030-drops-139746},
doi = {10.4230/LIPIcs.CPM.2021.23},
annote = {Keywords: pattern matching, gapped palindromes, suffix tree}
}
Document
AWLCO: All-Window Length Co-Occurrence
Abstract
Analyzing patterns in a sequence of events has applications in text analysis, computer programming, and genomics research. In this paper, we consider the all-window-length analysis model which analyzes a sequence of events with respect to windows of all lengths. We study the exact co-occurrence counting problem for the all-window-length analysis model. Our first algorithm is an offline algorithm that counts all-window-length co-occurrences by performing multiple passes over a sequence and computing single-window-length co-occurrences. This algorithm has the time complexity O(n) for each window length and thus a total complexity of O(n²) and the space complexity O(|I|) for a sequence of size n and an itemset of size |I|. We propose AWLCO, an online algorithm that computes all-window-length co-occurrences in a single pass with the time complexity of O(n) and space complexity of O(√{n|I|}), assuming perfect hashing. Following this, we generalize our use case to patterns in which we propose an algorithm that computes all-window-length co-occurrence with time complexity O(n|I|), assuming perfect hashing, with an additional pre-processing step and space complexity O(√{n|I|}+|I|), plus the overhead of the Aho-Corasick algorithm [Aho and Corasick, 1975].
Cite as
Joshua Sobel, Noah Bertram, Chen Ding, Fatemeh Nargesian, and Daniel Gildea. AWLCO: All-Window Length Co-Occurrence. In 32nd Annual Symposium on Combinatorial Pattern Matching (CPM 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 191, pp. 24:1-24:21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)
Copy BibTex To Clipboard
@InProceedings{sobel_et_al:LIPIcs.CPM.2021.24,
author = {Sobel, Joshua and Bertram, Noah and Ding, Chen and Nargesian, Fatemeh and Gildea, Daniel},
title = {{AWLCO: All-Window Length Co-Occurrence}},
booktitle = {32nd Annual Symposium on Combinatorial Pattern Matching (CPM 2021)},
pages = {24:1--24:21},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-186-3},
ISSN = {1868-8969},
year = {2021},
volume = {191},
editor = {Gawrychowski, Pawe{\l} and Starikovskaya, Tatiana},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CPM.2021.24},
URN = {urn:nbn:de:0030-drops-139759},
doi = {10.4230/LIPIcs.CPM.2021.24},
annote = {Keywords: Itemsets, Data Sequences, Co-occurrence}
}
Document
Optimal Completion and Comparison of Incomplete Phylogenetic Trees Under Robinson-Foulds Distance
Abstract
The comparison of phylogenetic trees is a fundamental task in phylogenetics and evolutionary biology. In many cases, these comparisons involve trees inferred on the same set of leaves, and many distance measures exist to facilitate such comparisons. However, several applications in phylogenetics require the comparison of trees that have non-identical leaf sets. The traditional approach for handling such comparisons is to first restrict the two trees being compared to just their common leaf set. An alternative, conceptually superior approach that has shown promise is to first complete the trees by adding missing leaves so that the completed trees have identical leaf sets. This alternative approach requires the computation of optimal completions of the two trees that minimize the distance between them. However, no polynomial-time algorithms currently exist for this optimal completion problem under any standard phylogenetic distance measure.
In this work, we provide the first polynomial-time algorithms for the above problem under the widely used Robinson-Foulds (RF) distance measure. This hitherto unsolved problem is referred to as the RF(+) problem. We (i) show that a recently proposed linear-time algorithm for a restricted version of the RF(+) problem is a 2-approximation for the RF(+) problem, and (ii) provide an exact O(nk²)-time algorithm for the RF(+) problem, where n is the total number of distinct leaf labels in the two trees being compared and k, bounded above by n, depends on the topologies and leaf set overlap of the two trees. Our results hold for both rooted and unrooted binary trees.
We implemented our exact algorithm and applied it to several biological datasets. Our results show that completion-based RF distance can lead to very different inferences regarding phylogenetic similarity compared to traditional RF distance. An open-source implementation of our algorithms is freely available from https://compbio.engr.uconn.edu/software/RF_plus.
Cite as
Keegan Yao and Mukul S. Bansal. Optimal Completion and Comparison of Incomplete Phylogenetic Trees Under Robinson-Foulds Distance. In 32nd Annual Symposium on Combinatorial Pattern Matching (CPM 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 191, pp. 25:1-25:23, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)
Copy BibTex To Clipboard
@InProceedings{yao_et_al:LIPIcs.CPM.2021.25,
author = {Yao, Keegan and Bansal, Mukul S.},
title = {{Optimal Completion and Comparison of Incomplete Phylogenetic Trees Under Robinson-Foulds Distance}},
booktitle = {32nd Annual Symposium on Combinatorial Pattern Matching (CPM 2021)},
pages = {25:1--25:23},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-186-3},
ISSN = {1868-8969},
year = {2021},
volume = {191},
editor = {Gawrychowski, Pawe{\l} and Starikovskaya, Tatiana},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CPM.2021.25},
URN = {urn:nbn:de:0030-drops-139769},
doi = {10.4230/LIPIcs.CPM.2021.25},
annote = {Keywords: Phylogenetic tree comparison, Robinson-Foulds Distance, Optimal tree completion, Algorithms, Dynamic programming}
}