21 Search Results for "Thankachan, Sharma V."

Document
DOI: 10.4230/LIPIcs.ESA.2024.16
Longest Common Substring with Gaps and Related Problems

Authors: Aranya Banerjee, Daniel Gibney, and Sharma V. Thankachan

Published in: LIPIcs, Volume 308, 32nd Annual European Symposium on Algorithms (ESA 2024)

Abstract
The longest common substring (also known as longest common factor) and longest common subsequence problems are two well-studied classical string problems. The former is solvable in optimal 𝒪(n) time for two strings of length m and n with m ≤ n, and the latter is solvable in 𝒪(nm) time, which is conditionally optimal under the Strong Exponential Time Hypothesis. In this work, we study the problem of longest common factor with gaps, that is, finding a set of at most k matching substrings obeying precedence conditions with maximum total length. For k = 1, this is equivalent to the longest common factor problem, and for k = m, this is equivalent to the longest common subsequence problem. Our work demonstrates that, for constant k, this problem can be solved in strongly subquadratic time, i.e., nm^{1 - Θ(1)}. Motivated by co-linear chaining applications in Computational Biology, we further demonstrate that the longest common factor with gaps results can be extended to the case where the matches are restricted to maximal exact matches (MEMs). To further demonstrate the applicability of our techniques, we show that a similar approach can be used for a restricted version of the episode matching problem where one seeks an ordered set of at most k matches whose concatenation equals a query pattern P and the length of the substring of T containing the matches is minimized. These solutions all run in strongly subquadratic time for constant k.
Cite as

Aranya Banerjee, Daniel Gibney, and Sharma V. Thankachan. Longest Common Substring with Gaps and Related Problems. In 32nd Annual European Symposium on Algorithms (ESA 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 308, pp. 16:1-16:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{banerjee_et_al:LIPIcs.ESA.2024.16,
  author =	{Banerjee, Aranya and Gibney, Daniel and Thankachan, Sharma V.},
  title =	{{Longest Common Substring with Gaps and Related Problems}},
  booktitle =	{32nd Annual European Symposium on Algorithms (ESA 2024)},
  pages =	{16:1--16:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-338-6},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{308},
  editor =	{Chan, Timothy and Fischer, Johannes and Iacono, John 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.2024.16},
  URN =		{urn:nbn:de:0030-drops-210877},
  doi =		{10.4230/LIPIcs.ESA.2024.16},
  annote =	{Keywords: Pattern Matching, Longest Common Subsequence, Episode Matching}
}
Document
DOI: 10.4230/LIPIcs.WABI.2024.17
A*PA2: Up to 19× Faster Exact Global Alignment

Authors: Ragnar Groot Koerkamp

Published in: LIPIcs, Volume 312, 24th International Workshop on Algorithms in Bioinformatics (WABI 2024)

Abstract
Motivation. Pairwise alignment is at the core of computational biology. Most commonly used exact methods are either based on O(ns) band doubling or O(n+s²) diagonal transition, where n is the sequence length and s the number of errors. However, as the length of sequences has grown, these exact methods are often replaced by approximate methods based on e.g. seed-and-extend and heuristics to bound the computed region. We would like to develop an exact method that matches the performance of these approximate methods. Recently, Astarix introduced the A* shortest path algorithm with the seed heuristic for exact sequence-to-graph alignment. A*PA adapted and improved this for pairwise sequence alignment and achieves near-linear runtime when divergence (error rate) is low, at the cost of being very slow when divergence is high. Methods. We introduce A*PA2, an exact global pairwise aligner with respect to edit distance. The goal of A*PA2 is to unify the near-linear runtime of A*PA on similar sequences with the efficiency of dynamic programming (DP) based methods. Like Edlib, A*PA2 uses Ukkonen’s band doubling in combination with Myers' bitpacking. A*PA2 1) uses large block sizes inspired by Block Aligner, 2) extends this with SIMD (single instruction, multiple data), 3) introduces a new profile for efficient computations, 4) introduces a new optimistic technique for traceback based on diagonal transition, 5) avoids recomputation of states where possible, and 6) applies the heuristics developed in A*PA and improves them using pre-pruning. Results. With the first 4 engineering optimizations, A*PA2-simple has complexity O(ns) and is 6× to 8× faster than Edlib for sequences ≥ 10 kbp. A*PA2-full also includes the heuristic and is often near-linear in practice for sequences with small divergence. The average runtime of A*PA2 is 19× faster than the exact aligners BiWFA and Edlib on >500 kbp long ONT (Oxford Nanopore Technologies) reads of a human genome having 6% divergence on average. On shorter ONT reads of 11% average divergence the speedup is 5.6× (avg. length 11 kbp) and 0.81× (avg. length 800 bp). On all tested datasets, A*PA2 is competitive with or faster than approximate methods.
Cite as

Ragnar Groot Koerkamp. A*PA2: Up to 19× Faster Exact Global Alignment. In 24th International Workshop on Algorithms in Bioinformatics (WABI 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 312, pp. 17:1-17:25, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{grootkoerkamp:LIPIcs.WABI.2024.17,
  author =	{Groot Koerkamp, Ragnar},
  title =	{{A*PA2: Up to 19× Faster Exact Global Alignment}},
  booktitle =	{24th International Workshop on Algorithms in Bioinformatics (WABI 2024)},
  pages =	{17:1--17:25},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-340-9},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{312},
  editor =	{Pissis, Solon P. and Sung, Wing-Kin},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2024.17},
  URN =		{urn:nbn:de:0030-drops-206610},
  doi =		{10.4230/LIPIcs.WABI.2024.17},
  annote =	{Keywords: Edit distance, Pairwise alignment, A*, Shortest path, Dynamic programming}
}
Document
DOI: 10.4230/LIPIcs.MFCS.2024.85
Approximate Suffix-Prefix Dictionary Queries

Authors: Wiktor Zuba, Grigorios Loukides, Solon P. Pissis, and Sharma V. Thankachan

Published in: LIPIcs, Volume 306, 49th International Symposium on Mathematical Foundations of Computer Science (MFCS 2024)

Abstract
In the all-pairs suffix-prefix (APSP) problem [Gusfield et al., Inf. Process. Lett. 1992], we are given a dictionary R of r strings, S₁,…,S_r, of total length n, and we are asked to find the length SPL_{i,j} of the longest string that is both a suffix of S_i and a prefix of S_j, for all i,j ∈ [1..r]. APSP is a classic problem in string algorithms with applications in bioinformatics, especially in sequence assembly. Since r = |R| is typically very large in real-world applications, considering all r² pairs of strings explicitly is prohibitive. This is when the data structure variant of APSP makes sense; in the same spirit as distance oracles computing shortest paths between any two vertices given online. We show how to quickly locate k-approximate matches (under the Hamming or the edit distance) in R using a version of the k-errata tree [Cole et al., STOC 2004] that we introduce. Let SPL^k_{i,j} be the length of the longest suffix of S_i that is at distance at most k from a prefix of S_j. In particular, for any k = 𝒪(1), we show an 𝒪(nlog^k n)-sized data structure to support the following queries: - One-to-One^k(i,j): output SPL^k_{i,j} in 𝒪(log^k nlog log n) time. - Report^k(i,d): output all j ∈ [1..r], such that SPL^k_{i,j} ≥ d, in 𝒪(log^{k}n(log n/log log n+output)) time, where output denotes the size of the output. In fact, our algorithms work for any value of k not just for k = 𝒪(1), but the formulas bounding the complexities get much more complicated for larger values of k.
Cite as

Wiktor Zuba, Grigorios Loukides, Solon P. Pissis, and Sharma V. Thankachan. Approximate Suffix-Prefix Dictionary Queries. In 49th International Symposium on Mathematical Foundations of Computer Science (MFCS 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 306, pp. 85:1-85:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{zuba_et_al:LIPIcs.MFCS.2024.85,
  author =	{Zuba, Wiktor and Loukides, Grigorios and Pissis, Solon P. and Thankachan, Sharma V.},
  title =	{{Approximate Suffix-Prefix Dictionary Queries}},
  booktitle =	{49th International Symposium on Mathematical Foundations of Computer Science (MFCS 2024)},
  pages =	{85:1--85:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-335-5},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{306},
  editor =	{Kr\'{a}lovi\v{c}, Rastislav and Ku\v{c}era, Anton{\'\i}n},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.MFCS.2024.85},
  URN =		{urn:nbn:de:0030-drops-206416},
  doi =		{10.4230/LIPIcs.MFCS.2024.85},
  annote =	{Keywords: all-pairs suffix-prefix, suffix-prefix queries, suffix tree, k-errata tree}
}
Document
DOI: 10.4230/LIPIcs.CPM.2023.21
Suffix-Prefix Queries on a Dictionary

Authors: Grigorios Loukides, Solon P. Pissis, Sharma V. Thankachan, and Wiktor Zuba

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

Abstract
In the all-pairs suffix-prefix (APSP) problem, we are given a dictionary R of k strings, S_1,…,S_k, of total length n, and we are asked to find the length SPL_{i,j} of the longest string that is both a suffix of S_i and a prefix of S_j, for all i,j ∈ [1,k]. APSP is a classic problem in string algorithms with many applications in bioinformatics. When all strings of the dictionary are over an integer alphabet of size σ ≤ n^𝒪(1), APSP can be solved in the optimal 𝒪(n+k²) time with the use of the generalized suffix tree of the dictionary [Gusfield et al., Inf. Process. Lett. 1992]. In many bioinformatics applications, such as in sequence assembly, the size k of dictionary R is very large. In particular, k² usually dominates n, and thus the k² factor is the bottleneck both in the time and in the space complexity of such applications. We thus initiate a holistic study on several data structure variants of APSP. In particular, we consider the following types of queries: - One-to-One(i,j): output SPL_{i,j}. - One-to-All(i): output SPL_{i,j} for every j ∈ [1,k]. - Report(i,𝓁): output all distinct j ∈ [1,k] such that SPL_{i,j} ≥ 𝓁, where 𝓁 ≥ 0 is an integer. - Count(i,𝓁): output the number of distinct j ∈ [1,k] such that SPL_{i,j} ≥ 𝓁, where 𝓁 ≥ 0 is an integer. - Top(i,K): output K distinct j ∈ [1,k] with the highest values of SPL_{i,j} breaking ties arbitrarily. We assume the standard word RAM model of computation with word size w = Ω(log n) and an integer alphabet of size σ ≤ n^𝒪(1). We show the following upper bounds: Query | Space (words) | Query time | Note One-to-One(i,j) | 𝒪(n) | 𝒪(log log k) | Theorem 11 One-to-All(i) | 𝒪(n) | 𝒪(k) | Theorem 14 Report(i,𝓁) | 𝒪(n) | 𝒪(log n/log log n+output) | Theorem 19(i) Count(i,𝓁) | 𝒪(n) | 𝒪(log n/log log n) | Theorem 19(ii) Top(i,K) | 𝒪(n) | 𝒪(log² n/log log n+K) | Theorem 22 We also present efficient algorithms for constructing these data structures.
Cite as

Grigorios Loukides, Solon P. Pissis, Sharma V. Thankachan, and Wiktor Zuba. Suffix-Prefix Queries on a Dictionary. In 34th Annual Symposium on Combinatorial Pattern Matching (CPM 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 259, pp. 21:1-21:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{loukides_et_al:LIPIcs.CPM.2023.21,
  author =	{Loukides, Grigorios and Pissis, Solon P. and Thankachan, Sharma V. and Zuba, Wiktor},
  title =	{{Suffix-Prefix Queries on a Dictionary}},
  booktitle =	{34th Annual Symposium on Combinatorial Pattern Matching (CPM 2023)},
  pages =	{21:1--21:20},
  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.2023.21},
  URN =		{urn:nbn:de:0030-drops-179757},
  doi =		{10.4230/LIPIcs.CPM.2023.21},
  annote =	{Keywords: all-pairs suffix-prefix, suffix-prefix queries, internal pattern matching}
}
Document
DOI: 10.4230/LIPIcs.WABI.2022.17
Feasibility of Flow Decomposition with Subpath Constraints in Linear Time

Authors: Daniel Gibney, Sharma V. Thankachan, and Srinivas Aluru

Published in: LIPIcs, Volume 242, 22nd International Workshop on Algorithms in Bioinformatics (WABI 2022)

Abstract
The decomposition of flow-networks is an essential part of many transcriptome assembly algorithms used in Computational Biology. The addition of subpath constraints to this decomposition appeared recently as an effective way to incorporate longer, already known, portions of the transcript. The problem is defined as follows: given a weakly connected directed acyclic flow network G = (V, E, f) and a set ℛ of subpaths in G, find a flow decomposition so that every subpath in ℛ is included in some flow in the decomposition [Williams et al., WABI 2021]. The authors of that work presented an exponential time algorithm for determining the feasibility of such a flow decomposition, and more recently presented an O(|E| + L+|ℛ|³) time algorithm, where L is the sum of the path lengths in ℛ [Williams et al., TCBB 2022]. Our work provides an improved, linear O(|E| + L) time algorithm for determining the feasibility of such a flow decomposition. We also introduce two natural optimization variants of the feasibility problem: (i) determining the minimum sized subset of ℛ that must be removed to make a flow decomposition feasible, and (ii) determining the maximum sized subset of ℛ that can be maintained while making a flow decomposition feasible. We show that, under the assumption P ≠ NP, (i) does not admit a polynomial-time o(log |V|)-approximation algorithm and (ii) does not admit a polynomial-time O(|V|^{1/2-ε} + |ℛ|^{1-ε})-approximation algorithm for any constant ε > 0.
Cite as

Daniel Gibney, Sharma V. Thankachan, and Srinivas Aluru. Feasibility of Flow Decomposition with Subpath Constraints in Linear Time. In 22nd International Workshop on Algorithms in Bioinformatics (WABI 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 242, pp. 17:1-17:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

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@InProceedings{gibney_et_al:LIPIcs.WABI.2022.17,
  author =	{Gibney, Daniel and Thankachan, Sharma V. and Aluru, Srinivas},
  title =	{{Feasibility of Flow Decomposition with Subpath Constraints in Linear Time}},
  booktitle =	{22nd International Workshop on Algorithms in Bioinformatics (WABI 2022)},
  pages =	{17:1--17:16},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-243-3},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{242},
  editor =	{Boucher, Christina and Rahmann, Sven},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2022.17},
  URN =		{urn:nbn:de:0030-drops-170516},
  doi =		{10.4230/LIPIcs.WABI.2022.17},
  annote =	{Keywords: Flow networks, flow decomposition, subpath constraints}
}
Document
Track A: Algorithms, Complexity and Games
DOI: 10.4230/LIPIcs.ICALP.2022.65
Fully Functional Parameterized Suffix Trees in Compact Space

Authors: Arnab Ganguly, Rahul Shah, and Sharma V. Thankachan

Published in: LIPIcs, Volume 229, 49th International Colloquium on Automata, Languages, and Programming (ICALP 2022)

Abstract
Two equal length strings are a parameterized match (p-match) iff there exists a one-to-one function that renames the symbols in one string to those in the other. The Parameterized Suffix Tree (PST) [Baker, STOC' 93] is a fundamental data structure that handles various string matching problems under this setting. The PST of a text T[1,n] over an alphabet Σ of size σ takes O(nlog n) bits of space. It can report any entry in (parameterized) (i) suffix array, (ii) inverse suffix array, and (iii) longest common prefix (LCP) array in O(1) time. Given any pattern P as a query, a position i in T is an occurrence iff T[i,i+|P|-1] and P are a p-match. The PST can count the number of occurrences of P in T in time O(|P|log σ) and then report each occurrence in time proportional to that of accessing a suffix array entry. An important question is, can we obtain a compressed version of PST that takes space close to the text’s size of nlogσ bits and still support all three functionalities mentioned earlier? In SODA' 17, Ganguly et al. answered this question partially by presenting an O(nlogσ) bit index that can support (parameterized) suffix array and inverse suffix array operations in O(log n) time. However, the compression of the (parameterized) LCP array and the possibility of faster suffix array and inverse suffix array queries in compact space were left open. In this work, we obtain a compact representation of the (parameterized) LCP array. With this result, in conjunction with three new (parameterized) suffix array representations, we obtain the first set of PST representations in o(nlog n) bits (when logσ = o(log n)) as follows. Here ε > 0 is an arbitrarily small constant. - Space O(n logσ) bits and query time O(log_σ^ε n); - Space O(n logσlog log_σ n) bits and query time O(log log_σ n); and - Space O(n logσ log^ε_σ n) bits and query time O(1). The first trade-off is an improvement over Ganguly et al.’s result, whereas our third trade-off matches the optimal time performance of Baker’s PST while squeezing the space by a factor roughly log_σ n. We highlight that our trade-offs match the space-and-time bounds of the best-known compressed text indexes for exact pattern matching and further improvement is highly unlikely.
Cite as

Arnab Ganguly, Rahul Shah, and Sharma V. Thankachan. Fully Functional Parameterized Suffix Trees in Compact Space. In 49th International Colloquium on Automata, Languages, and Programming (ICALP 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 229, pp. 65:1-65:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

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@InProceedings{ganguly_et_al:LIPIcs.ICALP.2022.65,
  author =	{Ganguly, Arnab and Shah, Rahul and Thankachan, Sharma V.},
  title =	{{Fully Functional Parameterized Suffix Trees in Compact Space}},
  booktitle =	{49th International Colloquium on Automata, Languages, and Programming (ICALP 2022)},
  pages =	{65:1--65:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-235-8},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{229},
  editor =	{Boja\'{n}czyk, Miko{\l}aj and Merelli, Emanuela and Woodruff, David P.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICALP.2022.65},
  URN =		{urn:nbn:de:0030-drops-164061},
  doi =		{10.4230/LIPIcs.ICALP.2022.65},
  annote =	{Keywords: Data Structures, Suffix Trees, String Algorithms, Compression}
}
Document
Invited Talk
DOI: 10.4230/LIPIcs.CPM.2022.3
Compact Text Indexing for Advanced Pattern Matching Problems: Parameterized, Order-Isomorphic, 2D, etc. (Invited Talk)

Authors: Sharma V. Thankachan

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

Abstract
In the past two decades, we have witnessed the design of various compact data structures for pattern matching over an indexed text [Navarro, 2016]. Popular indexes like the FM-index [Paolo Ferragina and Giovanni Manzini, 2005], compressed suffix arrays/trees [Roberto Grossi and Jeffrey Scott Vitter, 2005; Kunihiko Sadakane, 2007], the recent r-index [Travis Gagie et al., 2020; Takaaki Nishimoto and Yasuo Tabei, 2021], etc., capture the key functionalities of classic suffix arrays/trees [Udi Manber and Eugene W. Myers, 1993; Peter Weiner, 1973] in compact space. Mostly, they rely on the Burrows-Wheeler Transform (BWT) and its associated operations [Burrows and Wheeler, 1994]. However, compactly encoding some advanced suffix tree (ST) variants, like parameterized ST [Brenda S. Baker, 1993; S. Rao Kosaraju, 1995; Juan Mendivelso et al., 2020], order-isomorphic/preserving ST [Maxime Crochemore et al., 2016], two-dimensional ST [Raffaele Giancarlo, 1995; Dong Kyue Kim et al., 1998], etc. [Sung Gwan Park et al., 2019; Tetsuo Shibuya, 2000]- collectively known as suffix trees with missing suffix links [Richard Cole and Ramesh Hariharan, 2003], has been challenging. The previous techniques are not easily extendable because these variants do not hold some structural properties of the standard ST that enable compression. However, some limited progress has been made in these directions recently [Arnab Ganguly et al., 2017; Travis Gagie et al., 2017; Gianni Decaroli et al., 2017; Dhrumil Patel and Rahul Shah, 2021; Arnab Ganguly et al., 2021; Sung{-}Hwan Kim and Hwan{-}Gue Cho, 2021; Sung{-}Hwan Kim and Hwan{-}Gue Cho, 2021; Arnab Ganguly et al., 2017; Arnab Ganguly et al., 2022; Arnab Ganguly et al., 2021]. This talk will briefly survey them and highlight some interesting open problems.
Cite as

Sharma V. Thankachan. Compact Text Indexing for Advanced Pattern Matching Problems: Parameterized, Order-Isomorphic, 2D, etc. (Invited Talk). In 33rd Annual Symposium on Combinatorial Pattern Matching (CPM 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 223, pp. 3:1-3:3, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

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@InProceedings{thankachan:LIPIcs.CPM.2022.3,
  author =	{Thankachan, Sharma V.},
  title =	{{Compact Text Indexing for Advanced Pattern Matching Problems: Parameterized, Order-Isomorphic, 2D, etc.}},
  booktitle =	{33rd Annual Symposium on Combinatorial Pattern Matching (CPM 2022)},
  pages =	{3:1--3:3},
  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.2022.3},
  URN =		{urn:nbn:de:0030-drops-161300},
  doi =		{10.4230/LIPIcs.CPM.2022.3},
  annote =	{Keywords: Text Indexing, Suffix Trees, String Matching}
}
Document
Track A: Algorithms, Complexity and Games
DOI: 10.4230/LIPIcs.ICALP.2021.71
LF Successor: Compact Space Indexing for Order-Isomorphic Pattern Matching

Authors: Arnab Ganguly, Dhrumil Patel, Rahul Shah, and Sharma V. Thankachan

Published in: LIPIcs, Volume 198, 48th International Colloquium on Automata, Languages, and Programming (ICALP 2021)

Abstract
Two strings are order isomorphic iff the relative ordering of their characters is the same at all positions. For a given text T[1,n] over an ordered alphabet of size σ, we can maintain an order-isomorphic suffix tree/array in O(nlog n) bits and support (order-isomorphic) pattern/substring matching queries efficiently. It is interesting to know if we can encode these structures in space close to the text’s size of nlogσ bits. We answer this question positively by presenting an O(nlog σ)-bit index that allows access to any entry in order-isomorphic suffix array (and its inverse array) in t_{SA} = {O}(log²n/logσ) time. For any pattern P given as a query, this index can count the number of substrings of T that are order-isomorphic to P (denoted by occ) in {O}((|P|logσ+t_{SA})log n) time using standard techniques. Also, it can report the locations of those substrings in additional O(occ ⋅ t_{SA}) time.
Cite as

Arnab Ganguly, Dhrumil Patel, Rahul Shah, and Sharma V. Thankachan. LF Successor: Compact Space Indexing for Order-Isomorphic Pattern Matching. In 48th International Colloquium on Automata, Languages, and Programming (ICALP 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 198, pp. 71:1-71:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)

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@InProceedings{ganguly_et_al:LIPIcs.ICALP.2021.71,
  author =	{Ganguly, Arnab and Patel, Dhrumil and Shah, Rahul and Thankachan, Sharma V.},
  title =	{{LF Successor: Compact Space Indexing for Order-Isomorphic Pattern Matching}},
  booktitle =	{48th International Colloquium on Automata, Languages, and Programming (ICALP 2021)},
  pages =	{71:1--71:19},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-195-5},
  ISSN =	{1868-8969},
  year =	{2021},
  volume =	{198},
  editor =	{Bansal, Nikhil and Merelli, Emanuela and Worrell, James},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICALP.2021.71},
  URN =		{urn:nbn:de:0030-drops-141400},
  doi =		{10.4230/LIPIcs.ICALP.2021.71},
  annote =	{Keywords: Succinct data structures, Pattern Matching}
}
Document
DOI: 10.4230/LIPIcs.STACS.2021.35
Finding an Optimal Alphabet Ordering for Lyndon Factorization Is Hard

Authors: Daniel Gibney and Sharma V. Thankachan

Published in: LIPIcs, Volume 187, 38th International Symposium on Theoretical Aspects of Computer Science (STACS 2021)

Abstract
This work establishes several strong hardness results on the problem of finding an ordering on a string’s alphabet that either minimizes or maximizes the number of factors in that string’s Lyndon factorization. In doing so, we demonstrate that these ordering problems are sufficiently complex to model a wide variety of ordering constraint satisfaction problems (OCSPs). Based on this, we prove that (i) the decision versions of both the minimization and maximization problems are NP-complete, (ii) for both the minimization and maximization problems there does not exist a constant approximation algorithm running in polynomial time under the Unique Game Conjecture and (iii) there does not exist an algorithm to solve the minimization problem in time poly(|T|) ⋅ 2^o(σlog σ) for a string T over an alphabet of size σ under the Exponential Time Hypothesis (essentially the brute force approach of trying every alphabet order is hard to improve significantly).
Cite as

Daniel Gibney and Sharma V. Thankachan. Finding an Optimal Alphabet Ordering for Lyndon Factorization Is Hard. In 38th International Symposium on Theoretical Aspects of Computer Science (STACS 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 187, pp. 35:1-35:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)

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@InProceedings{gibney_et_al:LIPIcs.STACS.2021.35,
  author =	{Gibney, Daniel and Thankachan, Sharma V.},
  title =	{{Finding an Optimal Alphabet Ordering for Lyndon Factorization Is Hard}},
  booktitle =	{38th International Symposium on Theoretical Aspects of Computer Science (STACS 2021)},
  pages =	{35:1--35:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-180-1},
  ISSN =	{1868-8969},
  year =	{2021},
  volume =	{187},
  editor =	{Bl\"{a}ser, Markus and Monmege, Benjamin},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.STACS.2021.35},
  URN =		{urn:nbn:de:0030-drops-136809},
  doi =		{10.4230/LIPIcs.STACS.2021.35},
  annote =	{Keywords: Lyndon Factorization, String Algorithms, Burrows-Wheeler Transform}
}
Document
DOI: 10.4230/LIPIcs.ESA.2020.15
On the Complexity of BWT-Runs Minimization via Alphabet Reordering

Authors: Jason W. Bentley, Daniel Gibney, and Sharma V. Thankachan

Published in: LIPIcs, Volume 173, 28th Annual European Symposium on Algorithms (ESA 2020)

Abstract
The Burrows-Wheeler Transform (BWT) has been an essential tool in text compression and indexing. First introduced in 1994, it went on to provide the backbone for the first encoding of the classic suffix tree data structure in space close to entropy-based lower bound. Within the last decade, it has seen its role further enhanced with the development of compact suffix trees in space proportional to "r", the number of runs in the BWT. While r would superficially appear to be only a measure of space complexity, it is actually appearing increasingly often in the time complexity of new algorithms as well. This makes having the smallest value of r of growing importance. Interestingly, unlike other popular measures of compression, the parameter r is sensitive to the lexicographic ordering given to the text’s alphabet. Despite several past attempts to exploit this fact, a provably efficient algorithm for finding, or approximating, an alphabet ordering which minimizes r has been open for years. We help to explain this lack of progress by presenting the first set of results on the computational complexity of minimizing BWT-runs via alphabet reordering. We prove that the decision version of this problem is NP-complete and cannot be solved in time poly(n)⋅ 2^o(σ) unless the Exponential Time Hypothesis fails, where σ is the size of the alphabet and n is the length of the text. Moreover, we show that the optimization variant is APX-hard. In doing so, we relate two previously disparate topics: the optimal traveling salesperson path of a graph and the number of runs in the BWT of a text. In addition, by relating recent results in the field of dictionary compression, we illustrate that an arbitrary alphabet ordering provides an O(log² n)-approximation. Lastly, we provide an optimal linear-time algorithm for a more restricted problem of finding an optimal ordering on a subset of symbols (occurring only once) under ordering constraints.
Cite as

Jason W. Bentley, Daniel Gibney, and Sharma V. Thankachan. On the Complexity of BWT-Runs Minimization via Alphabet Reordering. In 28th Annual European Symposium on Algorithms (ESA 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 173, pp. 15:1-15:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)

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@InProceedings{bentley_et_al:LIPIcs.ESA.2020.15,
  author =	{Bentley, Jason W. and Gibney, Daniel and Thankachan, Sharma V.},
  title =	{{On the Complexity of BWT-Runs Minimization via Alphabet Reordering}},
  booktitle =	{28th Annual European Symposium on Algorithms (ESA 2020)},
  pages =	{15:1--15:13},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-162-7},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{173},
  editor =	{Grandoni, Fabrizio and Herman, Grzegorz and Sanders, Peter},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ESA.2020.15},
  URN =		{urn:nbn:de:0030-drops-128819},
  doi =		{10.4230/LIPIcs.ESA.2020.15},
  annote =	{Keywords: BWT, NP-hardness, APX-hardness}
}
Document
DOI: 10.4230/LIPIcs.ESA.2020.61
The Fine-Grained Complexity of Median and Center String Problems Under Edit Distance

Authors: Gary Hoppenworth, Jason W. Bentley, Daniel Gibney, and Sharma V. Thankachan

Published in: LIPIcs, Volume 173, 28th Annual European Symposium on Algorithms (ESA 2020)

Abstract
We present the first fine-grained complexity results on two classic problems on strings. The first one is the k-Median-Edit-Distance problem, where the input is a collection of k strings, each of length at most n, and the task is to find a new string that minimizes the sum of the edit distances from itself to all other strings in the input. Arising frequently in computational biology, this problem provides an important generalization of edit distance to multiple strings and is similar to the multiple sequence alignment problem in bioinformatics. We demonstrate that for any ε > 0 and k ≥ 2, an O(n^{k-ε}) time solution for the k-Median-Edit-Distance problem over an alphabet of size O(k) refutes the Strong Exponential Time Hypothesis (SETH). This provides the first matching conditional lower bound for the O(n^k) time algorithm established in 1975 by Sankoff. The second problem we study is the k-Center-Edit-Distance problem. Here also, the input is a collection of k strings, each of length at most n. The task is to find a new string that minimizes the maximum edit distance from itself to any other string in the input. We prove that the same conditional lower bound as before holds. Our results also imply new conditional lower bounds for the k-Tree-Alignment and the k-Bottleneck-Tree-Alignment problems studied in phylogenetics.
Cite as

Gary Hoppenworth, Jason W. Bentley, Daniel Gibney, and Sharma V. Thankachan. The Fine-Grained Complexity of Median and Center String Problems Under Edit Distance. In 28th Annual European Symposium on Algorithms (ESA 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 173, pp. 61:1-61:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)

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@InProceedings{hoppenworth_et_al:LIPIcs.ESA.2020.61,
  author =	{Hoppenworth, Gary and Bentley, Jason W. and Gibney, Daniel and Thankachan, Sharma V.},
  title =	{{The Fine-Grained Complexity of Median and Center String Problems Under Edit Distance}},
  booktitle =	{28th Annual European Symposium on Algorithms (ESA 2020)},
  pages =	{61:1--61:19},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-162-7},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{173},
  editor =	{Grandoni, Fabrizio and Herman, Grzegorz and Sanders, Peter},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ESA.2020.61},
  URN =		{urn:nbn:de:0030-drops-129278},
  doi =		{10.4230/LIPIcs.ESA.2020.61},
  annote =	{Keywords: Edit Distance, Median String, Center String, SETH}
}
Document
DOI: 10.4230/LIPIcs.CPM.2020.13
FM-Index Reveals the Reverse Suffix Array

Authors: Arnab Ganguly, Daniel Gibney, Sahar Hooshmand, M. Oğuzhan Külekci, and Sharma V. Thankachan

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

Abstract
Given a text T[1,n] over an alphabet Σ of size σ, the suffix array of T stores the lexicographic order of the suffixes of T. The suffix array needs Θ(nlog n) bits of space compared to the n log σ bits needed to store T itself. A major breakthrough [FM - Index, FOCS'00] in the last two decades has been encoding the suffix array in near-optimal number of bits (≈ log σ bits per character). One can decode a suffix array value using the FM-Index in log^{O(1)} n time. We study an extension of the problem in which we have to also decode the suffix array values of the reverse text. This problem has numerous applications such as in approximate pattern matching [Lam et al., BIBM' 09]. Known approaches maintain the FM - Index of both the forward and the reverse text which drives up the space occupancy to 2nlog σ bits (plus lower order terms). This brings in the natural question of whether we can decode the suffix array values of both the forward and the reverse text, but by using nlog σ bits (plus lower order terms). We answer this question positively, and show that given the FM - Index of the forward text, we can decode the suffix array value of the reverse text in near logarithmic average time. Additionally, our experimental results are competitive when compared to the standard approach of maintaining the FM - Index for both the forward and the reverse text. We believe that applications that require both the forward and reverse text will benefit from our approach.
Cite as

Arnab Ganguly, Daniel Gibney, Sahar Hooshmand, M. Oğuzhan Külekci, and Sharma V. Thankachan. FM-Index Reveals the Reverse Suffix Array. In 31st Annual Symposium on Combinatorial Pattern Matching (CPM 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 161, pp. 13:1-13:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)

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@InProceedings{ganguly_et_al:LIPIcs.CPM.2020.13,
  author =	{Ganguly, Arnab and Gibney, Daniel and Hooshmand, Sahar and K\"{u}lekci, M. O\u{g}uzhan and Thankachan, Sharma V.},
  title =	{{FM-Index Reveals the Reverse Suffix Array}},
  booktitle =	{31st Annual Symposium on Combinatorial Pattern Matching (CPM 2020)},
  pages =	{13:1--13:14},
  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.2020.13},
  URN =		{urn:nbn:de:0030-drops-121388},
  doi =		{10.4230/LIPIcs.CPM.2020.13},
  annote =	{Keywords: Data Structures, Suffix Trees, String Algorithms, Compression, Burrows - Wheeler transform, FM-Index}
}
Document
DOI: 10.4230/LIPIcs.ESA.2019.51
On the Hardness and Inapproximability of Recognizing Wheeler Graphs

Authors: Daniel Gibney and Sharma V. Thankachan

Published in: LIPIcs, Volume 144, 27th Annual European Symposium on Algorithms (ESA 2019)

Abstract
In recent years several compressed indexes based on variants of the Burrows-Wheeler transformation have been introduced. Some of these are used to index structures far more complex than a single string, as was originally done with the FM-index [Ferragina and Manzini, J. ACM 2005]. As such, there has been an increasing effort to better understand under which conditions such an indexing scheme is possible. This has led to the introduction of Wheeler graphs [Gagie et al., Theor. Comput. Sci., 2017]. Gagie et al. showed that de Bruijn graphs, generalized compressed suffix arrays, and several other BWT related structures can be represented as Wheeler graphs, and that Wheeler graphs can be indexed in a way which is space efficient. Hence, being able to recognize whether a given graph is a Wheeler graph, or being able to approximate a given graph by a Wheeler graph, could have numerous applications in indexing. Here we resolve the open question of whether there exists an efficient algorithm for recognizing if a given graph is a Wheeler graph. We present: - The problem of recognizing whether a given graph G=(V,E) is a Wheeler graph is NP-complete for any edge label alphabet of size sigma >= 2, even when G is a DAG. This holds even on a restricted, subset of graphs called d-NFA’s for d >= 5. This is in contrast to recent results demonstrating the problem can be solved in polynomial time for d-NFA’s where d <= 2. We also show the recognition problem can be solved in linear time for sigma =1; - There exists an 2^{e log sigma + O(n + e)} time exact algorithm where n = |V| and e = |E|. This algorithm relies on graph isomorphism being computable in strictly sub-exponential time; - We define an optimization variant of the problem called Wheeler Graph Violation, abbreviated WGV, where the aim is to remove the minimum number of edges in order to obtain a Wheeler graph. We show WGV is APX-hard, even when G is a DAG, implying there exists a constant C >= 1 for which there is no C-approximation algorithm (unless P = NP). Also, conditioned on the Unique Games Conjecture, for all C >= 1, it is NP-hard to find a C-approximation; - We define the Wheeler Subgraph problem, abbreviated WS, where the aim is to find the largest subgraph which is a Wheeler Graph (the dual of the WGV). In contrast to WGV, we prove that the WS problem is in APX for sigma=O(1); The above findings suggest that most problems under this theme are computationally difficult. However, we identify a class of graphs for which the recognition problem is polynomial time solvable, raising the open question of which parameters determine this problem’s difficulty.
Cite as

Daniel Gibney and Sharma V. Thankachan. On the Hardness and Inapproximability of Recognizing Wheeler Graphs. In 27th Annual European Symposium on Algorithms (ESA 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 144, pp. 51:1-51:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)

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@InProceedings{gibney_et_al:LIPIcs.ESA.2019.51,
  author =	{Gibney, Daniel and Thankachan, Sharma V.},
  title =	{{On the Hardness and Inapproximability of Recognizing Wheeler Graphs}},
  booktitle =	{27th Annual European Symposium on Algorithms (ESA 2019)},
  pages =	{51:1--51:16},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-124-5},
  ISSN =	{1868-8969},
  year =	{2019},
  volume =	{144},
  editor =	{Bender, Michael A. and Svensson, Ola 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.2019.51},
  URN =		{urn:nbn:de:0030-drops-111728},
  doi =		{10.4230/LIPIcs.ESA.2019.51},
  annote =	{Keywords: Burrows–Wheeler transform, string algorithms, suffix trees, NP-completeness}
}
Document
DOI: 10.4230/LIPIcs.ICDT.2019.9
Categorical Range Reporting with Frequencies

Authors: Arnab Ganguly, J. Ian Munro, Yakov Nekrich, Rahul Shah, and Sharma V. Thankachan

Published in: LIPIcs, Volume 127, 22nd International Conference on Database Theory (ICDT 2019)

Abstract
In this paper, we consider a variant of the color range reporting problem called color reporting with frequencies. Our goal is to pre-process a set of colored points into a data structure, so that given a query range Q, we can report all colors that appear in Q, along with their respective frequencies. In other words, for each reported color, we also output the number of times it occurs in Q. We describe an external-memory data structure that uses O(N(1+log^2D/log N)) words and answers one-dimensional queries in O(1 +K/B) I/Os, where N is the total number of points in the data structure, D is the total number of colors in the data structure, K is the number of reported colors, and B is the block size. Next we turn to an approximate version of this problem: report all colors sigma that appear in the query range; for every reported color, we provide a constant-factor approximation on its frequency. We consider color reporting with approximate frequencies in two dimensions. Our data structure uses O(N) space and answers two-dimensional queries in O(log_B N +log^*B + K/B) I/Os in the special case when the query range is bounded on two sides. As a corollary, we can also answer one-dimensional approximate queries within the same time and space bounds.
Cite as

Arnab Ganguly, J. Ian Munro, Yakov Nekrich, Rahul Shah, and Sharma V. Thankachan. Categorical Range Reporting with Frequencies. In 22nd International Conference on Database Theory (ICDT 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 127, pp. 9:1-9:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)

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@InProceedings{ganguly_et_al:LIPIcs.ICDT.2019.9,
  author =	{Ganguly, Arnab and Munro, J. Ian and Nekrich, Yakov and Shah, Rahul and Thankachan, Sharma V.},
  title =	{{Categorical Range Reporting with Frequencies}},
  booktitle =	{22nd International Conference on Database Theory (ICDT 2019)},
  pages =	{9:1--9:19},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-101-6},
  ISSN =	{1868-8969},
  year =	{2019},
  volume =	{127},
  editor =	{Barcelo, Pablo and Calautti, Marco},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICDT.2019.9},
  URN =		{urn:nbn:de:0030-drops-103115},
  doi =		{10.4230/LIPIcs.ICDT.2019.9},
  annote =	{Keywords: Data Structures, Range Reporting, Range Counting, Categorical Range Reporting, Orthogonal Range Query}
}
Document
DOI: 10.4230/LIPIcs.CPM.2018.8
Non-Overlapping Indexing - Cache Obliviously

Authors: Sahar Hooshmand, Paniz Abedin, M. Oguzhan Külekci, and Sharma V. Thankachan

Published in: LIPIcs, Volume 105, 29th Annual Symposium on Combinatorial Pattern Matching (CPM 2018)

Abstract
The non-overlapping indexing problem is defined as follows: pre-process a given text T[1,n] of length n into a data structure such that whenever a pattern P[1,p] comes as an input, we can efficiently report the largest set of non-overlapping occurrences of P in T. The best known solution is by Cohen and Porat [ISAAC, 2009]. Their index size is O(n) words and query time is optimal O(p+nocc), where nocc is the output size. We study this problem in the cache-oblivious model and present a new data structure of size O(n log n) words. It can answer queries in optimal O(p/(B)+log_B n+nocc/B) I/Os, where B is the block size.
Cite as

Sahar Hooshmand, Paniz Abedin, M. Oguzhan Külekci, and Sharma V. Thankachan. Non-Overlapping Indexing - Cache Obliviously. In 29th Annual Symposium on Combinatorial Pattern Matching (CPM 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 105, pp. 8:1-8:9, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)

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@InProceedings{hooshmand_et_al:LIPIcs.CPM.2018.8,
  author =	{Hooshmand, Sahar and Abedin, Paniz and K\"{u}lekci, M. Oguzhan and Thankachan, Sharma V.},
  title =	{{Non-Overlapping Indexing - Cache Obliviously}},
  booktitle =	{29th Annual Symposium on Combinatorial Pattern Matching (CPM 2018)},
  pages =	{8:1--8:9},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-074-3},
  ISSN =	{1868-8969},
  year =	{2018},
  volume =	{105},
  editor =	{Navarro, Gonzalo and Sankoff, David and Zhu, Binhai},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CPM.2018.8},
  URN =		{urn:nbn:de:0030-drops-87009},
  doi =		{10.4230/LIPIcs.CPM.2018.8},
  annote =	{Keywords: Suffix Trees, Cache Oblivious, Data Structure, String Algorithms}
}
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