3 Search Results for "Frenkel, Hadar"

Document
DOI: 10.4230/LIPIcs.CONCUR.2024.4
Centralized vs Decentralized Monitors for Hyperproperties

Authors: Luca Aceto, Antonis Achilleos, Elli Anastasiadi, Adrian Francalanza, Daniele Gorla, and Jana Wagemaker

Published in: LIPIcs, Volume 311, 35th International Conference on Concurrency Theory (CONCUR 2024)

Abstract
This paper focuses on the runtime verification of hyperproperties expressed in Hyper-recHML, an expressive yet simple logic for describing properties of sets of traces. To this end, we consider a simple language of monitors that observe sets of system executions and report verdicts w.r.t. a given Hyper-recHML formula. We first employ a unique omniscient monitor that centrally observes all system traces. Since centralised monitors are not ideal for distributed settings, we also provide a language for decentralized monitors, where each trace has a dedicated monitor; these monitors yield a unique verdict by communicating their observations to one another. For both the centralized and the decentralized settings, we provide a synthesis procedure that, given a formula, yields a monitor that is correct (i.e., sound and violation complete). A key step in proving the correctness of the synthesis for decentralized monitors is a result showing that, for each formula, the synthesized centralized monitor and its corresponding decentralized one are weakly bisimilar for a suitable notion of weak bisimulation.
Cite as

Luca Aceto, Antonis Achilleos, Elli Anastasiadi, Adrian Francalanza, Daniele Gorla, and Jana Wagemaker. Centralized vs Decentralized Monitors for Hyperproperties. In 35th International Conference on Concurrency Theory (CONCUR 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 311, pp. 4:1-4:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

Copy BibTex To Clipboard

@InProceedings{aceto_et_al:LIPIcs.CONCUR.2024.4,
  author =	{Aceto, Luca and Achilleos, Antonis and Anastasiadi, Elli and Francalanza, Adrian and Gorla, Daniele and Wagemaker, Jana},
  title =	{{Centralized vs Decentralized Monitors for Hyperproperties}},
  booktitle =	{35th International Conference on Concurrency Theory (CONCUR 2024)},
  pages =	{4:1--4:19},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-339-3},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{311},
  editor =	{Majumdar, Rupak and Silva, Alexandra},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CONCUR.2024.4},
  URN =		{urn:nbn:de:0030-drops-207763},
  doi =		{10.4230/LIPIcs.CONCUR.2024.4},
  annote =	{Keywords: Runtime Verification, hyperlogics, decentralization}
}
Document
DOI: 10.4230/LIPIcs.CONCUR.2024.10
Passive Learning of Regular Data Languages in Polynomial Time and Data

Authors: Mrudula Balachander, Emmanuel Filiot, and Raffaella Gentilini

Published in: LIPIcs, Volume 311, 35th International Conference on Concurrency Theory (CONCUR 2024)

Abstract
A regular data language is a language over an infinite alphabet recognized by a deterministic register automaton (DRA), as defined by Benedikt, Ley and Puppis. The later model, which is expressively equivalent to the deterministic finite-memory automata introduced earlier by Francez and Kaminsky, enjoys unique minimal automata (up to isomorphism), based on a Myhill-Nerode theorem. In this paper, we introduce a polynomial time passive learning algorithm for regular data languages from positive and negative samples. Following Gold’s model for learning languages, we prove that our algorithm can identify in the limit any regular data language L, i.e. it returns a minimal DRA recognizing L if a characteristic sample set for L is provided as input. We prove that there exist characteristic sample sets of polynomial size with respect to the size of the minimal DRA recognizing L. To the best of our knowledge, it is the first passive learning algorithm for data languages, and the first learning algorithm which is fully polynomial, both with respect to time complexity and size of the characteristic sample set.
Cite as

Mrudula Balachander, Emmanuel Filiot, and Raffaella Gentilini. Passive Learning of Regular Data Languages in Polynomial Time and Data. In 35th International Conference on Concurrency Theory (CONCUR 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 311, pp. 10:1-10:21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

Copy BibTex To Clipboard

@InProceedings{balachander_et_al:LIPIcs.CONCUR.2024.10,
  author =	{Balachander, Mrudula and Filiot, Emmanuel and Gentilini, Raffaella},
  title =	{{Passive Learning of Regular Data Languages in Polynomial Time and Data}},
  booktitle =	{35th International Conference on Concurrency Theory (CONCUR 2024)},
  pages =	{10:1--10:21},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-339-3},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{311},
  editor =	{Majumdar, Rupak and Silva, Alexandra},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CONCUR.2024.10},
  URN =		{urn:nbn:de:0030-drops-207829},
  doi =		{10.4230/LIPIcs.CONCUR.2024.10},
  annote =	{Keywords: Register automata, passive learning, automata over infinite alphabets}
}
Document
DOI: 10.4230/LIPIcs.CSL.2022.21
Inferring Symbolic Automata

Authors: Dana Fisman, Hadar Frenkel, and Sandra Zilles

Published in: LIPIcs, Volume 216, 30th EACSL Annual Conference on Computer Science Logic (CSL 2022)

Abstract
We study the learnability of symbolic finite state automata, a model shown useful in many applications in software verification. The state-of-the-art literature on this topic follows the query learning paradigm, and so far all obtained results are positive. We provide a necessary condition for efficient learnability of SFAs in this paradigm, from which we obtain the first negative result. The main focus of our work lies in the learnability of SFAs under the paradigm of identification in the limit using polynomial time and data. We provide a necessary condition and a sufficient condition for efficient learnability of SFAs in this paradigm, from which we derive a positive and a negative result.
Cite as

Dana Fisman, Hadar Frenkel, and Sandra Zilles. Inferring Symbolic Automata. In 30th EACSL Annual Conference on Computer Science Logic (CSL 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 216, pp. 21:1-21:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

Copy BibTex To Clipboard

@InProceedings{fisman_et_al:LIPIcs.CSL.2022.21,
  author =	{Fisman, Dana and Frenkel, Hadar and Zilles, Sandra},
  title =	{{Inferring Symbolic Automata}},
  booktitle =	{30th EACSL Annual Conference on Computer Science Logic (CSL 2022)},
  pages =	{21:1--21:19},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-218-1},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{216},
  editor =	{Manea, Florin and Simpson, Alex},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CSL.2022.21},
  URN =		{urn:nbn:de:0030-drops-157412},
  doi =		{10.4230/LIPIcs.CSL.2022.21},
  annote =	{Keywords: Symbolic Finite State Automata, Query Learning, Characteristic Sets}
}
  • Refine by Author
  • 1 Aceto, Luca
  • 1 Achilleos, Antonis
  • 1 Anastasiadi, Elli
  • 1 Balachander, Mrudula
  • 1 Filiot, Emmanuel
  • Show More...

  • Refine by Classification
  • 2 Theory of computation → Formal languages and automata theory
  • 1 Computing methodologies → Machine learning
  • 1 Theory of computation → Automata over infinite objects
  • 1 Theory of computation → Logic and verification
  • 1 Theory of computation → Modal and temporal logics
  • Show More...

  • Refine by Keyword
  • 1 Characteristic Sets
  • 1 Query Learning
  • 1 Register automata
  • 1 Runtime Verification
  • 1 Symbolic Finite State Automata
  • Show More...

  • Refine by Type
  • 3 document

  • Refine by Publication Year
  • 2 2024
  • 1 2022

Questions / Remarks / Feedback
X

Feedback for Dagstuhl Publishing


Thanks for your feedback!

Feedback submitted

Could not send message

Please try again later or send an E-mail
© 2023-2024 Schloss Dagstuhl – LZI GmbH Imprint Privacy Contact