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DOI: 10.4230/LIPIcs.CSL.2025.10

The Complexity of Second-Order HyperLTL

Authors: Hadar Frenkel and Martin Zimmermann

Published in: LIPIcs, Volume 326, 33rd EACSL Annual Conference on Computer Science Logic (CSL 2025)

Abstract

We determine the complexity of second-order HyperLTL satisfiability, finite-state satisfiability, and model-checking: All three are equivalent to truth in third-order arithmetic. We also consider two fragments of second-order HyperLTL that have been introduced with the aim to facilitate effective model-checking by restricting the sets one can quantify over. The first one restricts second-order quantification to smallest/largest sets that satisfy a guard while the second one restricts second-order quantification further to least fixed points of (first-order) HyperLTL definable functions. All three problems for the first fragment are still equivalent to truth in third-order arithmetic while satisfiability for the second fragment is Σ₁¹-complete, i.e., only as hard as for (first-order) HyperLTL and therefore much less complex. Finally, finite-state satisfiability and model-checking are in Σ₂² and are Σ₁¹-hard, and thus also less complex than for full second-order HyperLTL.

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Hadar Frenkel and Martin Zimmermann. The Complexity of Second-Order HyperLTL. In 33rd EACSL Annual Conference on Computer Science Logic (CSL 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 326, pp. 10:1-10:23, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{frenkel_et_al:LIPIcs.CSL.2025.10,
  author =	{Frenkel, Hadar and Zimmermann, Martin},
  title =	{{The Complexity of Second-Order HyperLTL}},
  booktitle =	{33rd EACSL Annual Conference on Computer Science Logic (CSL 2025)},
  pages =	{10:1--10:23},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-362-1},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{326},
  editor =	{Endrullis, J\"{o}rg and Schmitz, Sylvain},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CSL.2025.10},
  URN =		{urn:nbn:de:0030-drops-227679},
  doi =		{10.4230/LIPIcs.CSL.2025.10},
  annote =	{Keywords: HyperLTL, Satisfiability, Model-checking}
}

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.

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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)

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@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}
}

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Documents authored by Frenkel, Hadar

The Complexity of Second-Order HyperLTL

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Inferring Symbolic Automata

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