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**Published in:** LIPIcs, Volume 296, 35th Annual Symposium on Combinatorial Pattern Matching (CPM 2024)

We study the problem of making a de Bruijn graph (dBG), constructed from a collection of strings, weakly connected while minimizing the total cost of edge additions. The input graph is a dBG that can be made weakly connected by adding edges (along with extra nodes if needed) from the underlying complete dBG. The problem arises from genome reconstruction, where the dBG is constructed from a set of sequences generated from a genome sample by a sequencing experiment. Due to sequencing errors, the dBG is never Eulerian in practice and is often not even weakly connected. We show the following results for a dBG G(V,E) of order k consisting of d weakly connected components:
1) Making G weakly connected by adding a set of edges of minimal total cost is NP-hard.
2) No PTAS exists for making G weakly connected by adding a set of edges of minimal total cost (unless the unique games conjecture fails). We complement this result by showing that there does exist a polynomial-time (2-2/d)-approximation algorithm for the problem.
3) We consider a restricted version of the above problem, where we are asked to make G weakly connected by only adding directed paths between pairs of components. We show that making G weakly connected by adding d-1 such paths of minimal total cost can be done in 𝒪(k|V|α(|V|)+|E|) time, where α(⋅) is the inverse Ackermann function. This improves on the 𝒪(k|V|log(|V|)+|E|)-time algorithm proposed by Bernardini et al. [CPM 2022] for the same restricted problem.
4) An ILP formulation of polynomial size for making G Eulerian with minimal total cost.

Giulia Bernardini, Huiping Chen, Inge Li Gørtz, Christoffer Krogh, Grigorios Loukides, Solon P. Pissis, Leen Stougie, and Michelle Sweering. Connecting de Bruijn Graphs. In 35th Annual Symposium on Combinatorial Pattern Matching (CPM 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 296, pp. 6:1-6:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{bernardini_et_al:LIPIcs.CPM.2024.6, author = {Bernardini, Giulia and Chen, Huiping and G{\o}rtz, Inge Li and Krogh, Christoffer and Loukides, Grigorios and Pissis, Solon P. and Stougie, Leen and Sweering, Michelle}, title = {{Connecting de Bruijn Graphs}}, booktitle = {35th Annual Symposium on Combinatorial Pattern Matching (CPM 2024)}, pages = {6:1--6:16}, series = {Leibniz International Proceedings in Informatics (LIPIcs)}, ISBN = {978-3-95977-326-3}, ISSN = {1868-8969}, year = {2024}, volume = {296}, editor = {Inenaga, Shunsuke and Puglisi, Simon J.}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CPM.2024.6}, URN = {urn:nbn:de:0030-drops-201168}, doi = {10.4230/LIPIcs.CPM.2024.6}, annote = {Keywords: string algorithm, graph algorithm, de Bruijn graph, Eulerian graph} }

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Track A: Algorithms, Complexity and Games

**Published in:** LIPIcs, Volume 261, 50th International Colloquium on Automata, Languages, and Programming (ICALP 2023)

Consider words of length n. The set of all periods of a word of length n is a subset of {0,1,2,…,n-1}. However, any subset of {0,1,2,…,n-1} is not necessarily a valid set of periods. In a seminal paper in 1981, Guibas and Odlyzko proposed to encode the set of periods of a word into an n long binary string, called an autocorrelation, where a one at position i denotes the period i. They considered the question of recognizing a valid period set, and also studied the number of valid period sets for strings of length n, denoted κ_n. They conjectured that ln(κ_n) asymptotically converges to a constant times ln²(n). Although improved lower bounds for ln(κ_n)/ln²(n) were proposed in 2001, the question of a tight upper bound has remained open since Guibas and Odlyzko’s paper. Here, we exhibit an upper bound for this fraction, which implies its convergence and closes this longstanding conjecture. Moreover, we extend our result to find similar bounds for the number of correlations: a generalization of autocorrelations which encodes the overlaps between two strings.

Eric Rivals, Michelle Sweering, and Pengfei Wang. Convergence of the Number of Period Sets in Strings. In 50th International Colloquium on Automata, Languages, and Programming (ICALP 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 261, pp. 100:1-100:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{rivals_et_al:LIPIcs.ICALP.2023.100, author = {Rivals, Eric and Sweering, Michelle and Wang, Pengfei}, title = {{Convergence of the Number of Period Sets in Strings}}, booktitle = {50th International Colloquium on Automata, Languages, and Programming (ICALP 2023)}, pages = {100:1--100:14}, series = {Leibniz International Proceedings in Informatics (LIPIcs)}, ISBN = {978-3-95977-278-5}, ISSN = {1868-8969}, year = {2023}, volume = {261}, editor = {Etessami, Kousha and Feige, Uriel and Puppis, Gabriele}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICALP.2023.100}, URN = {urn:nbn:de:0030-drops-181527}, doi = {10.4230/LIPIcs.ICALP.2023.100}, annote = {Keywords: Autocorrelation, period, border, combinatorics, correlation, periodicity, upper bound, asymptotic convergence} }

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**Published in:** LIPIcs, Volume 259, 34th Annual Symposium on Combinatorial Pattern Matching (CPM 2023)

An elastic-degenerate (ED) string T is a sequence of n sets T[1],…,T[n] containing m strings in total whose cumulative length is N. We call n, m, and N the length, the cardinality and the size of T, respectively. The language of T is defined as ℒ(T) = {S_1 ⋯ S_n : S_i ∈ T[i] for all i ∈ [1,n]}. ED strings have been introduced to represent a set of closely-related DNA sequences, also known as a pangenome. The basic question we investigate here is: Given two ED strings, how fast can we check whether the two languages they represent have a nonempty intersection? We call the underlying problem the ED String Intersection (EDSI) problem. For two ED strings T₁ and T₂ of lengths n₁ and n₂, cardinalities m₁ and m₂, and sizes N₁ and N₂, respectively, we show the following:
- There is no 𝒪((N₁N₂)^{1-ε})-time algorithm, thus no 𝒪((N₁m₂+N₂m₁)^{1-ε})-time algorithm and no 𝒪((N₁n₂+N₂n₁)^{1-ε})-time algorithm, for any constant ε > 0, for EDSI even when T₁ and T₂ are over a binary alphabet, unless the Strong Exponential-Time Hypothesis is false.
- There is no combinatorial 𝒪((N₁+N₂)^{1.2-ε}f(n₁,n₂))-time algorithm, for any constant ε > 0 and any function f, for EDSI even when T₁ and T₂ are over a binary alphabet, unless the Boolean Matrix Multiplication conjecture is false.
- An 𝒪(N₁log N₁log n₁+N₂log N₂log n₂)-time algorithm for outputting a compact (RLE) representation of the intersection language of two unary ED strings. In the case when T₁ and T₂ are given in a compact representation, we show that the problem is NP-complete.
- An 𝒪(N₁m₂+N₂m₁)-time algorithm for EDSI.
- An Õ(N₁^{ω-1}n₂+N₂^{ω-1}n₁)-time algorithm for EDSI, where ω is the exponent of matrix multiplication; the Õ notation suppresses factors that are polylogarithmic in the input size.
We also show that the techniques we develop have applications outside of ED string comparison.

Esteban Gabory, Moses Njagi Mwaniki, Nadia Pisanti, Solon P. Pissis, Jakub Radoszewski, Michelle Sweering, and Wiktor Zuba. Comparing Elastic-Degenerate Strings: Algorithms, Lower Bounds, and Applications. In 34th Annual Symposium on Combinatorial Pattern Matching (CPM 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 259, pp. 11:1-11:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{gabory_et_al:LIPIcs.CPM.2023.11, author = {Gabory, Esteban and Mwaniki, Moses Njagi and Pisanti, Nadia and Pissis, Solon P. and Radoszewski, Jakub and Sweering, Michelle and Zuba, Wiktor}, title = {{Comparing Elastic-Degenerate Strings: Algorithms, Lower Bounds, and Applications}}, booktitle = {34th Annual Symposium on Combinatorial Pattern Matching (CPM 2023)}, pages = {11:1--11:20}, series = {Leibniz International Proceedings in Informatics (LIPIcs)}, ISBN = {978-3-95977-276-1}, ISSN = {1868-8969}, year = {2023}, volume = {259}, editor = {Bulteau, Laurent and Lipt\'{a}k, Zsuzsanna}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CPM.2023.11}, URN = {urn:nbn:de:0030-drops-179650}, doi = {10.4230/LIPIcs.CPM.2023.11}, annote = {Keywords: elastic-degenerate string, sequence comparison, languages intersection, pangenome, acronym identification} }

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**Published in:** LIPIcs, Volume 223, 33rd Annual Symposium on Combinatorial Pattern Matching (CPM 2022)

A directed multigraph is called Eulerian if it has a circuit which uses each edge exactly once. Euler’s theorem tells us that a weakly connected directed multigraph is Eulerian if and only if every node is balanced. Given a collection S of strings over an alphabet Σ, the de Bruijn graph (dBG) of order k of S is a directed multigraph G_{S,k}(V,E), where V is the set of length-(k-1) substrings of the strings in S, and G_{S,k} contains an edge (u,v) with multiplicity m_{u,v}, if and only if the string u[0]⋅ v is equal to the string u⋅ v[k-2] and this string occurs exactly m_{u,v} times in total in strings in S. Let G_{Σ,k}(V_{Σ,k},E_{Σ,k}) be the complete dBG of Σ^k. The Eulerian Extension (EE) problem on G_{S,k} asks to extend G_{S,k} with a set ℬ of nodes from V_{Σ,k} and a smallest multiset 𝒜 of edges from E_{Σ,k} to make it Eulerian. Note that extending dBGs is algorithmically much more challenging than extending general directed multigraphs because some edges in dBGs are by definition forbidden. Extending dBGs lies at the heart of sequence assembly [Medvedev et al., WABI 2007], one of the most important tasks in bioinformatics. The novelty of our work with respect to existing works is that we allow not only to duplicate existing edges of G_{S,k} but to also add novel edges and nodes, in an effort to (i) connect multiple components and (ii) reduce the total EE cost. It is easy to show that EE on G_{S,k} is NP-hard via a reduction from shortest common superstring. We further show that EE remains NP-hard, even when we are not allowed to add new nodes, via a highly non-trivial reduction from 3-SAT. We thus investigate the following two problems underlying EE in dBGs:
1) When G_{S,k} is not weakly connected, we are asked to connect its d > 1 components using a minimum-weight spanning tree, whose edges are paths on the underlying G_{Σ,k} and weights are the corresponding path lengths. This way of connecting guarantees that no new unbalanced node is added. We show that this problem can be solved in 𝒪(|V|klog d+|E|) time, which is nearly optimal, since the size of G_{S,k} is Θ(|V|k+|E|).
2) When G_{S,k} is not balanced, we are asked to extend G_{S,k} to H_{S,k}(V∪ℬ,E∪𝒜) such that every node of H_{S,k} is balanced and the total number |𝒜| of added edges is minimized. We show that this problem can be solved in the optimal 𝒪(k|V| + |E|+ |𝒜|) time. Let us stress that, although our main contributions are theoretical, the algorithms we design for the above two problems are practical. We combine the two algorithms in one method that makes any dBG Eulerian; and show experimentally that the cost of the obtained feasible solutions on real-world dBGs is substantially smaller than the corresponding cost obtained by existing greedy approaches.

Giulia Bernardini, Huiping Chen, Grigorios Loukides, Solon P. Pissis, Leen Stougie, and Michelle Sweering. Making de Bruijn Graphs Eulerian. In 33rd Annual Symposium on Combinatorial Pattern Matching (CPM 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 223, pp. 12:1-12:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

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@InProceedings{bernardini_et_al:LIPIcs.CPM.2022.12, author = {Bernardini, Giulia and Chen, Huiping and Loukides, Grigorios and Pissis, Solon P. and Stougie, Leen and Sweering, Michelle}, title = {{Making de Bruijn Graphs Eulerian}}, booktitle = {33rd Annual Symposium on Combinatorial Pattern Matching (CPM 2022)}, pages = {12:1--12:18}, series = {Leibniz International Proceedings in Informatics (LIPIcs)}, ISBN = {978-3-95977-234-1}, ISSN = {1868-8969}, year = {2022}, volume = {223}, editor = {Bannai, Hideo and Holub, Jan}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CPM.2022.12}, URN = {urn:nbn:de:0030-drops-161391}, doi = {10.4230/LIPIcs.CPM.2022.12}, annote = {Keywords: string algorithms, graph algorithms, Eulerian graph, de Bruijn graph} }

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**Published in:** LIPIcs, Volume 223, 33rd Annual Symposium on Combinatorial Pattern Matching (CPM 2022)

Let Substr_k(X) denote the set of length-k substrings of a given string X for a given integer k > 0. We study the following basic string problem, called z-Shortest 𝒮_k-Equivalent Strings: Given a set 𝒮_k of n length-k strings and an integer z > 0, list z shortest distinct strings T₁,…,T_z such that Substr_k(T_i) = 𝒮_k, for all i ∈ [1,z]. The z-Shortest 𝒮_k-Equivalent Strings problem arises naturally as an encoding problem in many real-world applications; e.g., in data privacy, in data compression, and in bioinformatics. The 1-Shortest 𝒮_k-Equivalent Strings, referred to as Shortest 𝒮_k-Equivalent String, asks for a shortest string X such that Substr_k(X) = 𝒮_k.
Our main contributions are summarized below:
- Given a directed graph G(V,E), the Directed Chinese Postman (DCP) problem asks for a shortest closed walk that visits every edge of G at least once. DCP can be solved in 𝒪̃(|E||V|) time using an algorithm for min-cost flow. We show, via a non-trivial reduction, that if Shortest 𝒮_k-Equivalent String over a binary alphabet has a near-linear-time solution then so does DCP.
- We show that the length of a shortest string output by Shortest 𝒮_k-Equivalent String is in 𝒪(k+n²). We generalize this bound by showing that the total length of z shortest strings is in 𝒪(zk+zn²+z²n). We derive these upper bounds by showing (asymptotically tight) bounds on the total length of z shortest Eulerian walks in general directed graphs.
- We present an algorithm for solving z-Shortest 𝒮_k-Equivalent Strings in 𝒪(nk+n²log²n+zn²log n+|output|) time. If z = 1, the time becomes 𝒪(nk+n²log²n) by the fact that the size of the input is Θ(nk) and the size of the output is 𝒪(k+n²).

Giulia Bernardini, Alessio Conte, Esteban Gabory, Roberto Grossi, Grigorios Loukides, Solon P. Pissis, Giulia Punzi, and Michelle Sweering. On Strings Having the Same Length- k Substrings. In 33rd Annual Symposium on Combinatorial Pattern Matching (CPM 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 223, pp. 16:1-16:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

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@InProceedings{bernardini_et_al:LIPIcs.CPM.2022.16, author = {Bernardini, Giulia and Conte, Alessio and Gabory, Esteban and Grossi, Roberto and Loukides, Grigorios and Pissis, Solon P. and Punzi, Giulia and Sweering, Michelle}, title = {{On Strings Having the Same Length- k Substrings}}, booktitle = {33rd Annual Symposium on Combinatorial Pattern Matching (CPM 2022)}, pages = {16:1--16:17}, series = {Leibniz International Proceedings in Informatics (LIPIcs)}, ISBN = {978-3-95977-234-1}, ISSN = {1868-8969}, year = {2022}, volume = {223}, editor = {Bannai, Hideo and Holub, Jan}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CPM.2022.16}, URN = {urn:nbn:de:0030-drops-161439}, doi = {10.4230/LIPIcs.CPM.2022.16}, annote = {Keywords: string algorithms, combinatorics on words, de Bruijn graph, Chinese Postman} }

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**Published in:** LIPIcs, Volume 191, 32nd Annual Symposium on Combinatorial Pattern Matching (CPM 2021)

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.

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)

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@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} }

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**Published in:** LIPIcs, Volume 191, 32nd Annual Symposium on Combinatorial Pattern Matching (CPM 2021)

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.

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)

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@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} }

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**Published in:** LIPIcs, Volume 161, 31st Annual Symposium on Combinatorial Pattern Matching (CPM 2020)

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 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 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 substrings, algorithms solving ETFS can be applied for utility-preserving string sanitization [Bernardini et al., ECML PKDD 2019]. Our first result here is an algorithm to solve ETFS in 𝒪(kn²) time, which improves on the state of the art [Bernardini et al., arXiv 2019] by a factor of |Σ|. Our algorithm is based on a non-trivial modification of the classic dynamic programming algorithm for computing the edit distance between two strings. Notably, we also show that ETFS cannot be solved in 𝒪(n^{2-δ}) time, for any δ>0, unless the strong exponential time hypothesis is false. To achieve this, we reduce the edit distance problem, which is known to admit the same conditional lower bound [Bringmann and Künnemann, FOCS 2015], to ETFS.

Giulia Bernardini, Huiping Chen, Grigorios Loukides, Nadia Pisanti, Solon P. Pissis, Leen Stougie, and Michelle Sweering. String Sanitization Under Edit Distance. In 31st Annual Symposium on Combinatorial Pattern Matching (CPM 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 161, pp. 7:1-7:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)

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@InProceedings{bernardini_et_al:LIPIcs.CPM.2020.7, author = {Bernardini, Giulia and Chen, Huiping and Loukides, Grigorios and Pisanti, Nadia and Pissis, Solon P. and Stougie, Leen and Sweering, Michelle}, title = {{String Sanitization Under Edit Distance}}, booktitle = {31st Annual Symposium on Combinatorial Pattern Matching (CPM 2020)}, pages = {7:1--7:14}, series = {Leibniz International Proceedings in Informatics (LIPIcs)}, ISBN = {978-3-95977-149-8}, ISSN = {1868-8969}, year = {2020}, volume = {161}, editor = {G{\o}rtz, Inge Li and Weimann, Oren}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CPM.2020.7}, URN = {urn:nbn:de:0030-drops-121324}, doi = {10.4230/LIPIcs.CPM.2020.7}, annote = {Keywords: String algorithms, data sanitization, edit distance, dynamic programming, conditional lower bound} }

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