3 Search Results for "Le Gall, Tristan"

Document
DOI: 10.4230/LIPIcs.SAT.2025.32
Efficient Certified Reasoning for Binarized Neural Networks

Authors: Jiong Yang, Yong Kiam Tan, Mate Soos, Magnus O. Myreen, and Kuldeep S. Meel

Published in: LIPIcs, Volume 341, 28th International Conference on Theory and Applications of Satisfiability Testing (SAT 2025)

Abstract
Neural networks have emerged as essential components in safety-critical applications - these use cases demand complex, yet trustworthy computations. Binarized Neural Networks (BNNs) are a type of neural network where each neuron is constrained to a Boolean value; they are particularly well-suited for safety-critical tasks because they retain much of the computational capacities of full-scale (floating-point or quantized) deep neural networks, but remain compatible with satisfiability solvers for qualitative verification and with model counters for quantitative reasoning. However, existing methods for BNN analysis suffer from either limited scalability or susceptibility to soundness errors, which hinders their applicability in real-world scenarios. In this work, we present a scalable and trustworthy approach for both qualitative and quantitative verification of BNNs. Our approach introduces a native representation of BNN constraints in a custom-designed solver for qualitative reasoning, and in an approximate model counter for quantitative reasoning. We further develop specialized proof generation and checking pipelines with native support for BNN constraint reasoning, ensuring trustworthiness for all of our verification results. Empirical evaluations on a BNN robustness verification benchmark suite demonstrate that our certified solving approach achieves a 9× speedup over prior certified CNF and PB-based approaches, and our certified counting approach achieves a 218× speedup over the existing CNF-based baseline. In terms of coverage, our pipeline produces fully certified results for 99% and 86% of the qualitative and quantitative reasoning queries on BNNs, respectively. This is in sharp contrast to the best existing baselines which can fully certify only 62% and 4% of the queries, respectively.
Cite as

Jiong Yang, Yong Kiam Tan, Mate Soos, Magnus O. Myreen, and Kuldeep S. Meel. Efficient Certified Reasoning for Binarized Neural Networks. In 28th International Conference on Theory and Applications of Satisfiability Testing (SAT 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 341, pp. 32:1-32:22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{yang_et_al:LIPIcs.SAT.2025.32,
  author =	{Yang, Jiong and Tan, Yong Kiam and Soos, Mate and Myreen, Magnus O. and Meel, Kuldeep S.},
  title =	{{Efficient Certified Reasoning for Binarized Neural Networks}},
  booktitle =	{28th International Conference on Theory and Applications of Satisfiability Testing (SAT 2025)},
  pages =	{32:1--32:22},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-381-2},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{341},
  editor =	{Berg, Jeremias and Nordstr\"{o}m, Jakob},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SAT.2025.32},
  URN =		{urn:nbn:de:0030-drops-237665},
  doi =		{10.4230/LIPIcs.SAT.2025.32},
  annote =	{Keywords: Neural network verification, proof certification, SAT solving, approximate model counting}
}
Document
Experience Paper
DOI: 10.4230/LIPIcs.ECOOP.2025.37
RacerF: Lightweight Static Data Race Detection for C Code (Experience Paper)

Authors: Tomáš Dacík and Tomáš Vojnar

Published in: LIPIcs, Volume 333, 39th European Conference on Object-Oriented Programming (ECOOP 2025)

Abstract
We present RacerF, a novel static analyser for thread-modular data race detection. The approach behind RacerF exploits static analysis of sequential program behaviour whose results are generalised for multi-threaded programs using a combination of lightweight under- and over-approximating methods. The tool is implemented as a plugin of the Frama-C platform and can leverage several analysis backends, most notably the Frama-C’s abstract interpreter EVA. Although our methods are mostly heuristic without providing formal guarantees, our experimental evaluation shows that even for intricate programs, RacerF can provide very precise results competitive with more heavyweight approaches while being faster than them.
Cite as

Tomáš Dacík and Tomáš Vojnar. RacerF: Lightweight Static Data Race Detection for C Code (Experience Paper). In 39th European Conference on Object-Oriented Programming (ECOOP 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 333, pp. 37:1-37:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{dacik_et_al:LIPIcs.ECOOP.2025.37,
  author =	{Dac{\'\i}k, Tom\'{a}\v{s} and Vojnar, Tom\'{a}\v{s}},
  title =	{{RacerF: Lightweight Static Data Race Detection for C Code}},
  booktitle =	{39th European Conference on Object-Oriented Programming (ECOOP 2025)},
  pages =	{37:1--37:19},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-373-7},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{333},
  editor =	{Aldrich, Jonathan 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.ECOOP.2025.37},
  URN =		{urn:nbn:de:0030-drops-233298},
  doi =		{10.4230/LIPIcs.ECOOP.2025.37},
  annote =	{Keywords: concurrency, data race detection, static analysis}
}
Document
DOI: 10.4230/LIPIcs.FSTTCS.2012.224
Safety Verification of Communicating One-Counter Machines

Authors: Alexander Heußner, Tristan Le Gall, and Grégoire Sutre

Published in: LIPIcs, Volume 18, IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2012)

Abstract
In order to verify protocols that tag messages with integer values, we investigate the decidability of the reachability problem for systems of communicating one-counter machines. These systems consist of local one-counter machines that asynchronously communicate by exchanging the value of their counters via, a priori unbounded, FIFO channels. This model extends communicating finite-state machines (CFSM) by infinite-state local processes and an infinite message alphabet. The main result of the paper is a complete characterization of the communication topologies that have a solvable reachability question. As already CFSM exclude the possibility of automatic verification in presence of mutual communication, we also consider an under-approximative approach to the reachability problem, based on rendezvous synchronization.
Cite as

Alexander Heußner, Tristan Le Gall, and Grégoire Sutre. Safety Verification of Communicating One-Counter Machines. In IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2012). Leibniz International Proceedings in Informatics (LIPIcs), Volume 18, pp. 224-235, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2012)

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@InProceedings{heuner_et_al:LIPIcs.FSTTCS.2012.224,
  author =	{Heu{\ss}ner, Alexander and Le Gall, Tristan and Sutre, Gr\'{e}goire},
  title =	{{Safety Verification of Communicating One-Counter Machines}},
  booktitle =	{IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2012)},
  pages =	{224--235},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-939897-47-7},
  ISSN =	{1868-8969},
  year =	{2012},
  volume =	{18},
  editor =	{D'Souza, Deepak and Radhakrishnan, Jaikumar and Telikepalli, Kavitha},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.FSTTCS.2012.224},
  URN =		{urn:nbn:de:0030-drops-38614},
  doi =		{10.4230/LIPIcs.FSTTCS.2012.224},
  annote =	{Keywords: Counter Machines, FIFO Channels, Reachability Problem, Data Words}
}
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