2 Search Results for "Trubiani, Catia"


Document
Improved Circular Dictionary Matching

Authors: Nicola Cotumaccio

Published in: LIPIcs, Volume 331, 36th Annual Symposium on Combinatorial Pattern Matching (CPM 2025)


Abstract
The circular dictionary matching problem is an extension of the classical dictionary matching problem where every string in the dictionary is interpreted as a circular string: after reading the last character of a string, we can move back to its first character. The circular dictionary matching problem is motivated by applications in bioinformatics and computational geometry. In 2011, Hon et al. [ISAAC 2011] showed how to efficiently solve circular dictionary matching queries within compressed space by building on Mantaci et al.’s eBWT and Sadakane’s compressed suffix tree. The proposed solution is based on the assumption that the strings in the dictionary are all distinct and non-periodic, no string is a circular rotation of some other string, and the strings in the dictionary have similar lengths. In this paper, we consider arbitrary dictionaries, and we show how to solve circular dictionary matching queries in O((m + occ) log n) time within compressed space using n log σ (1 + o(1)) + O(n) + O(d log n) bits, where n is the total length of the dictionary, m is the length of the pattern, occ is the number of occurrences, d is the number of strings in the dictionary and σ is the size of the alphabet. Our solution is based on an extension of the suffix array to arbitrary dictionaries and a sampling mechanism for the LCP array of a dictionary inspired by recent results in graph indexing and compression.

Cite as

Nicola Cotumaccio. Improved Circular Dictionary Matching. In 36th Annual Symposium on Combinatorial Pattern Matching (CPM 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 331, pp. 18:1-18:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)


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@InProceedings{cotumaccio:LIPIcs.CPM.2025.18,
  author =	{Cotumaccio, Nicola},
  title =	{{Improved Circular Dictionary Matching}},
  booktitle =	{36th Annual Symposium on Combinatorial Pattern Matching (CPM 2025)},
  pages =	{18:1--18:17},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-369-0},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{331},
  editor =	{Bonizzoni, Paola and M\"{a}kinen, Veli},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CPM.2025.18},
  URN =		{urn:nbn:de:0030-drops-231122},
  doi =		{10.4230/LIPIcs.CPM.2025.18},
  annote =	{Keywords: Circular pattern matching, dictionary matching, suffix tree, compressed suffix tree, suffix array, LCP array, Burrows-Wheeler Transform, FM-index}
}
Document
Probabilistic Analysis of Binary Sessions

Authors: Omar Inverso, Hernán Melgratti, Luca Padovani, Catia Trubiani, and Emilio Tuosto

Published in: LIPIcs, Volume 171, 31st International Conference on Concurrency Theory (CONCUR 2020)


Abstract
We study a probabilistic variant of binary session types that relate to a class of Finite-State Markov Chains. The probability annotations in session types enable the reasoning on the probability that a session terminates successfully, for some user-definable notion of successful termination. We develop a type system for a simple session calculus featuring probabilistic choices and show that the success probability of well-typed processes agrees with that of the sessions they use. To this aim, the type system needs to track the propagation of probabilistic choices across different sessions.

Cite as

Omar Inverso, Hernán Melgratti, Luca Padovani, Catia Trubiani, and Emilio Tuosto. Probabilistic Analysis of Binary Sessions. In 31st International Conference on Concurrency Theory (CONCUR 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 171, pp. 14:1-14:21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)


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@InProceedings{inverso_et_al:LIPIcs.CONCUR.2020.14,
  author =	{Inverso, Omar and Melgratti, Hern\'{a}n and Padovani, Luca and Trubiani, Catia and Tuosto, Emilio},
  title =	{{Probabilistic Analysis of Binary Sessions}},
  booktitle =	{31st International Conference on Concurrency Theory (CONCUR 2020)},
  pages =	{14:1--14:21},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-160-3},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{171},
  editor =	{Konnov, Igor and Kov\'{a}cs, Laura},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CONCUR.2020.14},
  URN =		{urn:nbn:de:0030-drops-128264},
  doi =		{10.4230/LIPIcs.CONCUR.2020.14},
  annote =	{Keywords: Probabilistic choices, session types, static analysis, deadlock freedom}
}
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