6 Search Results for "Stordalen, Tord"

Document
DOI: 10.4230/LIPIcs.CPM.2026.14
Hardness Results on Characteristics for Elastic-Degenerate Strings

Authors: Dominik Köppl and Jannik Olbrich

Published in: LIPIcs, Volume 369, 37th Annual Symposium on Combinatorial Pattern Matching (CPM 2026)

Abstract
Generalizations of plain strings have been proposed as a compact way to represent a collection of nearly identical sequences or to express uncertainty at specific text positions by enumerating all possibilities. While a plain string stores a character at each of its positions, generalizations consider a set of characters (indeterminate strings), a set of strings of equal length (generalized degenerate strings, or shortly GD strings), or a set of strings of arbitrary lengths (elastic-degenerate strings, or shortly ED strings). These generalizations are of importance to compactly represent such type of data, and find applications in bioinformatics for representing and maintaining a set of genetic sequences of the same taxonomy or a multiple sequence alignment. To be of use, attention has been drawn to answering various query types such as pattern matching or measuring similarity of ED strings by generalizing techniques known to plain strings. However, for some types of queries, it has been shown that a generalization of a polynomial-time solvable query on classic strings becomes NP-hard on ED strings, e.g. [Russo et al., 2022]. In that light, we wonder about other types of queries that are of particular interest to bioinformatics: unique substrings, absent words, anti-powers, longest previous factors, and Lempel-Ziv-like compression schemes. While we obtain a polynomial time algorithm for a variation of longest previous factors, we show that all other problems are NP-hard to compute, some of them even under the restriction that the input can be modeled as an indeterminate or GD string.
Cite as

Dominik Köppl and Jannik Olbrich. Hardness Results on Characteristics for Elastic-Degenerate Strings. In 37th Annual Symposium on Combinatorial Pattern Matching (CPM 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 369, pp. 14:1-14:25, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@InProceedings{koppl_et_al:LIPIcs.CPM.2026.14,
  author =	{K\"{o}ppl, Dominik and Olbrich, Jannik},
  title =	{{Hardness Results on Characteristics for Elastic-Degenerate Strings}},
  booktitle =	{37th Annual Symposium on Combinatorial Pattern Matching (CPM 2026)},
  pages =	{14:1--14:25},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-420-8},
  ISSN =	{1868-8969},
  year =	{2026},
  volume =	{369},
  editor =	{Bille, Philip and Prezza, Nicola},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CPM.2026.14},
  URN =		{urn:nbn:de:0030-drops-259409},
  doi =		{10.4230/LIPIcs.CPM.2026.14},
  annote =	{Keywords: Elastic-degenerate strings, NP-hardness, longest common factor, minimal unique substring, minimal absent word, anti-power, longest previous factor}
}
Artifact
Software
DOI: 10.4230/artifacts.24667
A Dynamic Piecewise-Linear Geometric Index with Worst-Case Guarantees

Authors: Emil Toftegaard Gæde, Ivor van der Hoog, Eva Rotenberg, and Tord Stordalen

Abstract
Cite as

Emil Toftegaard Gæde, Ivor van der Hoog, Eva Rotenberg, Tord Stordalen. A Dynamic Piecewise-Linear Geometric Index with Worst-Case Guarantees (Software, Source Code). Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@misc{impl_index,
   title = {{A Dynamic Piecewise-Linear Geometric Index with Worst-Case Guarantees}}, 
   author = {G{\ae}de, Emil Toftegaard and van der Hoog, Ivor and Rotenberg, Eva and Stordalen, Tord},
   note = {Software, Carlsberg Fonden CF21-0302, Villum Fonden VIL37507, Marie Skłodowska-Curie 899987, swhId: \href{https://archive.softwareheritage.org/swh:1:dir:b8763eb0504d33beb81ee89d230a30dca8ab0b66;origin=https://github.com/Sgelet/DynamicLearnedIndex;visit=swh:1:snp:4cb5f98448fd35e1092239476b3dd4b7fa157fa9;anchor=swh:1:rev:e668899dab95046384f68723e53e0aacbad32feb}{\texttt{swh:1:dir:b8763eb0504d33beb81ee89d230a30dca8ab0b66}} (visited on 2025-10-01)},
   url = {https://github.com/Sgelet/DynamicLearnedIndex},
   doi = {10.4230/artifacts.24667},
}
Artifact
Software
DOI: 10.4230/artifacts.24668
Testbed for our learned index repository

Authors: Emil Toftegaard Gæde, Ivor van der Hoog, Eva Rotenberg, and Tord Stordalen

Abstract
Cite as

Emil Toftegaard Gæde, Ivor van der Hoog, Eva Rotenberg, Tord Stordalen. Testbed for our learned index repository (Software, Test Bed). Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@misc{impl_bench,
   title = {{Testbed for our learned index repository}}, 
   author = {G{\ae}de, Emil Toftegaard and van der Hoog, Ivor and Rotenberg, Eva and Stordalen, Tord},
   note = {Software, Carlsberg Fonden CF21-0302, Villum Fonden VIL37507, Marie Skłodowska-Curie 899987, swhId: \href{https://archive.softwareheritage.org/swh:1:dir:07ea25cfc176438933c1a5507bfdad3ba9461ab6;origin=https://github.com/Sgelet/LearnedIndexBench;visit=swh:1:snp:b64d98b5a181116695f4f7960511292c6601df13;anchor=swh:1:rev:c3ad0ca2e0149fd2be070b37ba57b12a447bbf71}{\texttt{swh:1:dir:07ea25cfc176438933c1a5507bfdad3ba9461ab6}} (visited on 2025-10-01)},
   url = {https://github.com/Sgelet/LearnedIndexBench},
   doi = {10.4230/artifacts.24668},
}
Document
DOI: 10.4230/LIPIcs.ESA.2025.64
A Dynamic Piecewise-Linear Geometric Index with Worst-Case Guarantees

Authors: Emil Toftegaard Gæde, Ivor van der Hoog, Eva Rotenberg, and Tord Stordalen

Published in: LIPIcs, Volume 351, 33rd Annual European Symposium on Algorithms (ESA 2025)

Abstract
Indexing data is a fundamental problem in computer science. The input is a set S of n distinct integers from a universe 𝒰. Indexing queries take a value q ∈ 𝒰 and return the membership, predecessor or rank of q in S. A range query takes two values q, r ∈ 𝒰 and returns the set S ∩ [q,r]. Recently, various papers study a special case where the the input data behaves in an approximately piece-wise linear way. Given the sorted (rank,value) pairs, and given some constant ε, one wants to maintain a small number of axis-disjoint line-segments such that, for each rank, the value is within ± ε of the corresponding line-segment. Ferragina and Vinciguerra (VLDB 2020) observe that this geometric problem is useful for solving indexing problems, particularly when the number of line-segments is small compared to the size of the dataset. We study the dynamic version of this geometric problem. In the dynamic setting, inserting or deleting just one data point may cause up to three line-segments to be merged, or one line-segment to be split at most three-way. To determine and compute this, we use techniques from dynamic maintenance of convex hulls, and provide new algorithms with worst-case guarantees, including an O(log n) algorithm to compute a separating line between two non-intersecting convex hulls - an operation previously missing from the literature. We then use our fully-dynamic geometry-based subroutine in an indexing data structure, combining it with a natural hashing technique. The resulting indexing data structure has theoretically efficient worst-case guarantees in expectation. We compare its practical performance to the solution of Ferragina and Vinciguerra, which was shown to perform better in certain structured settings [Sun, Zhou, Li VLDB 2023]. Our empirical analysis shows that our solution supports more efficient range queries in the special case where the update sequence contains many deletions.
Cite as

Emil Toftegaard Gæde, Ivor van der Hoog, Eva Rotenberg, and Tord Stordalen. A Dynamic Piecewise-Linear Geometric Index with Worst-Case Guarantees. In 33rd Annual European Symposium on Algorithms (ESA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 351, pp. 64:1-64:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{gaede_et_al:LIPIcs.ESA.2025.64,
  author =	{G{\ae}de, Emil Toftegaard and van der Hoog, Ivor and Rotenberg, Eva and Stordalen, Tord},
  title =	{{A Dynamic Piecewise-Linear Geometric Index with Worst-Case Guarantees}},
  booktitle =	{33rd Annual European Symposium on Algorithms (ESA 2025)},
  pages =	{64:1--64:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-395-9},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{351},
  editor =	{Benoit, Anne and Kaplan, Haim and Wild, Sebastian and Herman, Grzegorz},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ESA.2025.64},
  URN =		{urn:nbn:de:0030-drops-245323},
  doi =		{10.4230/LIPIcs.ESA.2025.64},
  annote =	{Keywords: Algorithms Engineering, Data Structures, Indexing, Convex Hulls}
}
Document
DOI: 10.4230/LIPIcs.CPM.2023.4
Sliding Window String Indexing in Streams

Authors: Philip Bille, Johannes Fischer, Inge Li Gørtz, Max Rishøj Pedersen, and Tord Joakim Stordalen

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

Abstract
Given a string S over an alphabet Σ, the string indexing problem is to preprocess S to subsequently support efficient pattern matching queries, that is, given a pattern string P report all the occurrences of P in S. In this paper we study the streaming sliding window string indexing problem. Here the string S arrives as a stream, one character at a time, and the goal is to maintain an index of the last w characters, called the window, for a specified parameter w. At any point in time a pattern matching query for a pattern P may arrive, also streamed one character at a time, and all occurrences of P within the current window must be returned. The streaming sliding window string indexing problem naturally captures scenarios where we want to index the most recent data (i.e. the window) of a stream while supporting efficient pattern matching. Our main result is a simple O(w) space data structure that uses O(log w) time with high probability to process each character from both the input string S and any pattern string P. Reporting each occurrence of P uses additional constant time per reported occurrence. Compared to previous work in similar scenarios this result is the first to achieve an efficient worst-case time per character from the input stream with high probability. We also consider a delayed variant of the problem, where a query may be answered at any point within the next δ characters that arrive from either stream. We present an O(w + δ) space data structure for this problem that improves the above time bounds to O(log (w/δ)). In particular, for a delay of δ = ε w we obtain an O(w) space data structure with constant time processing per character. The key idea to achieve our result is a novel and simple hierarchical structure of suffix trees of independent interest, inspired by the classic log-structured merge trees.
Cite as

Philip Bille, Johannes Fischer, Inge Li Gørtz, Max Rishøj Pedersen, and Tord Joakim Stordalen. Sliding Window String Indexing in Streams. In 34th Annual Symposium on Combinatorial Pattern Matching (CPM 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 259, pp. 4:1-4:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{bille_et_al:LIPIcs.CPM.2023.4,
  author =	{Bille, Philip and Fischer, Johannes and G{\o}rtz, Inge Li and Pedersen, Max Rish{\o}j and Stordalen, Tord Joakim},
  title =	{{Sliding Window String Indexing in Streams}},
  booktitle =	{34th Annual Symposium on Combinatorial Pattern Matching (CPM 2023)},
  pages =	{4:1--4:18},
  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.2023.4},
  URN =		{urn:nbn:de:0030-drops-179587},
  doi =		{10.4230/LIPIcs.CPM.2023.4},
  annote =	{Keywords: String indexing, pattern matching, sliding window, streaming}
}
Document
DOI: 10.4230/LIPIcs.SWAT.2022.18
Predecessor on the Ultra-Wide Word RAM

Authors: Philip Bille, Inge Li Gørtz, and Tord Stordalen

Published in: LIPIcs, Volume 227, 18th Scandinavian Symposium and Workshops on Algorithm Theory (SWAT 2022)

Abstract
We consider the predecessor problem on the ultra-wide word RAM model of computation, which extends the word RAM model with ultrawords consisting of w² bits [TAMC, 2015]. The model supports arithmetic and boolean operations on ultrawords, in addition to scattered memory operations that access or modify w (potentially non-contiguous) memory addresses simultaneously. The ultra-wide word RAM model captures (and idealizes) modern vector processor architectures. Our main result is a simple, linear space data structure that supports predecessor in constant time and updates in amortized, expected constant time. This improves the space of the previous constant time solution that uses space in the order of the size of the universe. Our result is based on a new implementation of the classic x-fast trie data structure of Willard [Inform. Process. Lett. 17(2), 1983] combined with a new dictionary data structure that supports fast parallel lookups.
Cite as

Philip Bille, Inge Li Gørtz, and Tord Stordalen. Predecessor on the Ultra-Wide Word RAM. In 18th Scandinavian Symposium and Workshops on Algorithm Theory (SWAT 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 227, pp. 18:1-18:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

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@InProceedings{bille_et_al:LIPIcs.SWAT.2022.18,
  author =	{Bille, Philip and G{\o}rtz, Inge Li and Stordalen, Tord},
  title =	{{Predecessor on the Ultra-Wide Word RAM}},
  booktitle =	{18th Scandinavian Symposium and Workshops on Algorithm Theory (SWAT 2022)},
  pages =	{18:1--18:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-236-5},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{227},
  editor =	{Czumaj, Artur and Xin, Qin},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SWAT.2022.18},
  URN =		{urn:nbn:de:0030-drops-161786},
  doi =		{10.4230/LIPIcs.SWAT.2022.18},
  annote =	{Keywords: Ultra-wide word RAM model, predecessor, word-level parallelism}
}
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