14 Search Results for "Bryant, Randal E."

Document
DOI: 10.4230/LIPIcs.STACS.2026.5
On the Complexity of Language Membership for Probabilistic Words

Authors: Antoine Amarilli, Mikaël Monet, Paul Raphaël, and Sylvain Salvati

Published in: LIPIcs, Volume 364, 43rd International Symposium on Theoretical Aspects of Computer Science (STACS 2026)

Abstract
We study the membership problem to context-free languages L (CFLs) on probabilistic words, that specify for each position a probability distribution on the letters (assuming independence across positions). Our task is to compute, given a probabilistic word, what is the probability that a word drawn according to the distribution belongs to L. This problem generalizes the problem of counting how many words of length n belong to L, or of counting how many completions of a partial word belong to L. We show that this problem is in polynomial time for unambiguous context-free languages (uCFLs), but can be #P-hard already for unions of two linear uCFLs. More generally, we show that the problem is in polynomial time for so-called poly-slicewise-unambiguous languages, where given a length n we can tractably compute an uCFL for the words of length n in the language. This class includes some inherently ambiguous languages, and implies the tractability of bounded CFLs and of languages recognized by unambiguous polynomial-time counter automata; but we show that the problem can be #P-hard for nondeterministic counter automata, even for Parikh automata with a single counter. We then introduce classes of circuits from knowledge compilation which we use for tractable counting, and show that this covers the tractability of poly-slicewise-unambiguous languages and of some CFLs that are not poly-slicewise-unambiguous. Extending these circuits with negation further allows us to show tractability for the language of primitive words, and for the language of concatenations of two palindromes. We finally show the conditional undecidability of the meta-problem that asks, given a CFG, whether the probabilistic membership problem for that CFG is tractable or #P-hard.
Cite as

Antoine Amarilli, Mikaël Monet, Paul Raphaël, and Sylvain Salvati. On the Complexity of Language Membership for Probabilistic Words. In 43rd International Symposium on Theoretical Aspects of Computer Science (STACS 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 364, pp. 5:1-5:21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

Copy BibTex To Clipboard

@InProceedings{amarilli_et_al:LIPIcs.STACS.2026.5,
  author =	{Amarilli, Antoine and Monet, Mika\"{e}l and Rapha\"{e}l, Paul and Salvati, Sylvain},
  title =	{{On the Complexity of Language Membership for Probabilistic Words}},
  booktitle =	{43rd International Symposium on Theoretical Aspects of Computer Science (STACS 2026)},
  pages =	{5:1--5:21},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-412-3},
  ISSN =	{1868-8969},
  year =	{2026},
  volume =	{364},
  editor =	{Mahajan, Meena and Manea, Florin and McIver, Annabelle and Thắng, Nguy\~{ê}n Kim},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.STACS.2026.5},
  URN =		{urn:nbn:de:0030-drops-254943},
  doi =		{10.4230/LIPIcs.STACS.2026.5},
  annote =	{Keywords: Automaton, probabilistic words, context-free grammar, membership problem}
}
Document
DOI: 10.4230/LIPIcs.TIME.2025.7
PDDL to DFA: A Symbolic Transformation for Effective Reasoning

Authors: Giuseppe De Giacomo, Antonio Di Stasio, and Gianmarco Parretti

Published in: LIPIcs, Volume 355, 32nd International Symposium on Temporal Representation and Reasoning (TIME 2025)

Abstract
ltl_f reactive synthesis under environment specifications, which concerns the automated generation of strategies enforcing logical specifications, has emerged as a powerful technique for developing autonomous AI systems. It shares many similarities with Fully Observable Nondeterministic (fond) planning. In particular, nondeterministic domains can be expressed as ltl_f environment specifications. However, this is not needed since nondeterministic domains can be transformed into deterministic finite-state automata (dfa) to be used directly in the synthesis process. In this paper, we present a practical symbolic technique for translating domains expressed in Planning Domain Definition Language (pddl) into dfas. The technique allows for the integration of the planning domain, reduced to dfa in a symbolic form, into current symbolic ltl_f synthesis tools. We implemented our technique in a new tool, pddl2dfa, and applied it to solve fond planning by using state-of-the-art reactive synthesis techniques in a tool called syft4fond. Our empirical results confirm the effectiveness of our approach.
Cite as

Giuseppe De Giacomo, Antonio Di Stasio, and Gianmarco Parretti. PDDL to DFA: A Symbolic Transformation for Effective Reasoning. In 32nd International Symposium on Temporal Representation and Reasoning (TIME 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 355, pp. 7:1-7:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

Copy BibTex To Clipboard

@InProceedings{degiacomo_et_al:LIPIcs.TIME.2025.7,
  author =	{De Giacomo, Giuseppe and Di Stasio, Antonio and Parretti, Gianmarco},
  title =	{{PDDL to DFA: A Symbolic Transformation for Effective Reasoning}},
  booktitle =	{32nd International Symposium on Temporal Representation and Reasoning (TIME 2025)},
  pages =	{7:1--7:14},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-401-7},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{355},
  editor =	{Vidal, Thierry and Wa{\l}\k{e}ga, Przemys{\l}aw Andrzej},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.TIME.2025.7},
  URN =		{urn:nbn:de:0030-drops-244532},
  doi =		{10.4230/LIPIcs.TIME.2025.7},
  annote =	{Keywords: Fully Observable Nondeterministic Planning, Linear Temporal Logics on finite traces, Reactive Synthesis, DFA}
}
Document
DOI: 10.4230/LIPIcs.CONCUR.2025.4
Monitorability for the Modal Mu-Calculus over Systems with Data: From Practice to Theory

Authors: Luca Aceto, Antonis Achilleos, Duncan Paul Attard, Léo Exibard, Adrian Francalanza, Anna Ingólfsdóttir, and Karoliina Lehtinen

Published in: LIPIcs, Volume 348, 36th International Conference on Concurrency Theory (CONCUR 2025)

Abstract
Runtime verification consists in checking whether a system satisfies a given specification by observing the execution trace it produces. In the regular setting, the modal μ-calculus provides a versatile formalism for expressing specifications of the control flow of the system. This paper focuses on the data flow and studies an extension of that logic that allows it to express data-dependent properties, identifying fragments that can be verified at runtime and with what correctness guarantees. The logic studied here is closely related with register automata with guessing. That correspondence yields a monitor synthesis algorithm, and a strict hierarchy among the various fragments of the logic, in contrast to the regular setting. We then exhibit a fragment of the logic that can express all monitorable formulae in the logic without greatest fixed-points but not in the full logic, and show this is the best we can get.
Cite as

Luca Aceto, Antonis Achilleos, Duncan Paul Attard, Léo Exibard, Adrian Francalanza, Anna Ingólfsdóttir, and Karoliina Lehtinen. Monitorability for the Modal Mu-Calculus over Systems with Data: From Practice to Theory. In 36th International Conference on Concurrency Theory (CONCUR 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 348, pp. 4:1-4:21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

Copy BibTex To Clipboard

@InProceedings{aceto_et_al:LIPIcs.CONCUR.2025.4,
  author =	{Aceto, Luca and Achilleos, Antonis and Attard, Duncan Paul and Exibard, L\'{e}o and Francalanza, Adrian and Ing\'{o}lfsd\'{o}ttir, Anna and Lehtinen, Karoliina},
  title =	{{Monitorability for the Modal Mu-Calculus over Systems with Data: From Practice to Theory}},
  booktitle =	{36th International Conference on Concurrency Theory (CONCUR 2025)},
  pages =	{4:1--4:21},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-389-8},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{348},
  editor =	{Bouyer, Patricia and van de Pol, Jaco},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CONCUR.2025.4},
  URN =		{urn:nbn:de:0030-drops-239546},
  doi =		{10.4230/LIPIcs.CONCUR.2025.4},
  annote =	{Keywords: Runtime verification, monitorability, \muHML with data, register automata}
}
Document
DOI: 10.4230/LIPIcs.CP.2025.21
Practically Feasible Proof Logging for Pseudo-Boolean Optimization

Authors: Wietze Koops, Daniel Le Berre, Magnus O. Myreen, Jakob Nordström, Andy Oertel, Yong Kiam Tan, and Marc Vinyals

Published in: LIPIcs, Volume 340, 31st International Conference on Principles and Practice of Constraint Programming (CP 2025)

Abstract
Certifying solvers have long been standard for decision problems in Boolean satisfiability (SAT), allowing for proof logging and checking with very limited overhead, but developing similar tools for combinatorial optimization has remained a challenge. A recent promising approach covering a wide range of solving paradigms is pseudo-Boolean proof logging, but this has mostly consisted of proof-of-concept works far from delivering the performance required for real-world deployment. In this work, we present an efficient toolchain based on VeriPB and CakePB for formally verified pseudo-Boolean optimization. We implement proof logging for the full range of techniques in the state-of-the-art solvers RoundingSat and Sat4j, including core-guided search and linear programming integration with Farkas certificates and cut generation. Our experimental evaluation shows that proof logging and checking performance in this much more expressive paradigm is now quite close to the level of SAT solving, and hence is clearly practically feasible.
Cite as

Wietze Koops, Daniel Le Berre, Magnus O. Myreen, Jakob Nordström, Andy Oertel, Yong Kiam Tan, and Marc Vinyals. Practically Feasible Proof Logging for Pseudo-Boolean Optimization. In 31st International Conference on Principles and Practice of Constraint Programming (CP 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 340, pp. 21:1-21:27, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

Copy BibTex To Clipboard

@InProceedings{koops_et_al:LIPIcs.CP.2025.21,
  author =	{Koops, Wietze and Le Berre, Daniel and Myreen, Magnus O. and Nordstr\"{o}m, Jakob and Oertel, Andy and Tan, Yong Kiam and Vinyals, Marc},
  title =	{{Practically Feasible Proof Logging for Pseudo-Boolean Optimization}},
  booktitle =	{31st International Conference on Principles and Practice of Constraint Programming (CP 2025)},
  pages =	{21:1--21:27},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-380-5},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{340},
  editor =	{de la Banda, Maria Garcia},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CP.2025.21},
  URN =		{urn:nbn:de:0030-drops-238825},
  doi =		{10.4230/LIPIcs.CP.2025.21},
  annote =	{Keywords: proof logging, certifying algorithms, combinatorial optimization, certification, pseudo-Boolean solving, 0-1 integer linear programming}
}
Document
DOI: 10.4230/LIPIcs.SAT.2025.31
On Top-Down Pseudo-Boolean Model Counting

Authors: Suwei Yang, Yong Lai, and Kuldeep S. Meel

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

Abstract
Pseudo-Boolean model counting involves computing the number of satisfying assignments of a given pseudo-Boolean (PB) formula. In recent years, PB model counting has seen increased interest partly owing to the succinctness of PB formulas over typical propositional Boolean formulas in conjunctive normal form (CNF) at describing problem constraints. In particular, the research community has developed tools to tackle exact PB model counting. These recently developed counters follow one of the two existing major designs for model counters, namely the bottom-up model counter design. A natural question would be whether the other major design, the top-down model counter paradigm, would be effective at PB model counting, especially when the top-down design offered superior performance in CNF model counting literature. In this work, we investigate the aforementioned top-down design for PB model counting and introduce the first exact top-down PB model counter, PBMC. PBMC is a top-down search-based counter for PB formulas, with a new variable decision heuristic that considers variable coefficients. Through our evaluations, we highlight the superior performance of PBMC at PB model counting compared to the existing state-of-the-art counters PBCount, PBCounter, and Ganak. In particular, PBMC could count for 1849 instances while the next-best competing method, PBCount, could only count for 1773 instances, demonstrating the potential of a top-down PB counter design.
Cite as

Suwei Yang, Yong Lai, and Kuldeep S. Meel. On Top-Down Pseudo-Boolean Model Counting. In 28th International Conference on Theory and Applications of Satisfiability Testing (SAT 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 341, pp. 31:1-31:10, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

Copy BibTex To Clipboard

@InProceedings{yang_et_al:LIPIcs.SAT.2025.31,
  author =	{Yang, Suwei and Lai, Yong and Meel, Kuldeep S.},
  title =	{{On Top-Down Pseudo-Boolean Model Counting}},
  booktitle =	{28th International Conference on Theory and Applications of Satisfiability Testing (SAT 2025)},
  pages =	{31:1--31:10},
  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.2025.31},
  URN =		{urn:nbn:de:0030-drops-237658},
  doi =		{10.4230/LIPIcs.SAT.2025.31},
  annote =	{Keywords: Pseudo-Boolean, Model Counting, Constraint Satisfiability}
}
Document
DOI: 10.4230/LIPIcs.SAT.2025.3
Problem Partitioning via Proof Prefixes

Authors: Zachary Battleman, Joseph E. Reeves, and Marijn J. H. Heule

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

Abstract
Satisfiability solvers have been instrumental in tackling hard problems, including mathematical challenges that require years of computation. A key obstacle in efficiently solving such problems lies in effectively partitioning them into many, frequently millions of subproblems. Existing automated partitioning techniques, primarily based on lookahead methods, perform well on some instances but fail to generate effective partitions for many others. This paper introduces a powerful partitioning approach that leverages prefixes of proofs derived from conflict-driven clause-learning solvers. This method enables non-experts to harness the power of massively parallel SAT solving for their problems. We also propose a semantically-driven partitioning technique tailored for problems with large cardinality constraints, which frequently arise in optimization tasks. We evaluate our methods on diverse benchmarks, including combinatorial problems and formulas from SAT and MaxSAT competitions. Our results demonstrate that these techniques outperform existing partitioning strategies in many cases, offering improved scalability and efficiency.
Cite as

Zachary Battleman, Joseph E. Reeves, and Marijn J. H. Heule. Problem Partitioning via Proof Prefixes. In 28th International Conference on Theory and Applications of Satisfiability Testing (SAT 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 341, pp. 3:1-3:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

Copy BibTex To Clipboard

@InProceedings{battleman_et_al:LIPIcs.SAT.2025.3,
  author =	{Battleman, Zachary and Reeves, Joseph E. and Heule, Marijn J. H.},
  title =	{{Problem Partitioning via Proof Prefixes}},
  booktitle =	{28th International Conference on Theory and Applications of Satisfiability Testing (SAT 2025)},
  pages =	{3:1--3:18},
  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.2025.3},
  URN =		{urn:nbn:de:0030-drops-237378},
  doi =		{10.4230/LIPIcs.SAT.2025.3},
  annote =	{Keywords: Satisfiability solving, parallel computing, problem partitioning}
}
Document
DOI: 10.4230/LIPIcs.SAT.2025.8
Certifying Projected Knowledge Compilation

Authors: Randal E. Bryant, Yong Kiam Tan, and Marijn J. H. Heule

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

Abstract
Knowledge compilers convert Boolean formulas, given in conjunctive normal form (CNF), into representations that enable efficient evaluation of unweighted and weighted model counts, as well as a variety of other useful properties. With projected knowledge compilation, the generated representation describes the restriction of the formula to a designated set of data variables, with the remaining ones eliminated by existential quantification. Projected knowledge compilation has applications in a variety of domains, including formal verification and synthesis. This paper describes a formally verified proof framework for certifying the output of a projected knowledge compiler. It builds on an earlier clausal proof framework for certifying the output of a standard knowledge compiler. Extending the framework to projected compilation requires a method to represent Skolem assignments, describing how the quantified variables can be assigned, given an assignment for the data variables. We do so by extending the representation generated by the knowledge compiler to also encode Skolem assignments. We also refine the earlier framework, moving beyond purely clausal proofs to enable scaling certification to larger formulas. We present experimental results obtained by making small modifications to the D4 projected knowledge compiler and extensions of our earlier proof generator. We detail a soundness argument stating that a compiler output that passes our certifier is logically equivalent to the quantified input formula; the soundness argument has been formally validated using the HOL4 proof assistant. The checker also ensures that the compiler output satisfies the properties required for efficient unweighted and weighted model counting. We have developed two proof checkers for the certification framework: one written in C and designed for high performance and one written in CakeML and formally verified in HOL4.
Cite as

Randal E. Bryant, Yong Kiam Tan, and Marijn J. H. Heule. Certifying Projected Knowledge Compilation. In 28th International Conference on Theory and Applications of Satisfiability Testing (SAT 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 341, pp. 8:1-8:22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

Copy BibTex To Clipboard

@InProceedings{bryant_et_al:LIPIcs.SAT.2025.8,
  author =	{Bryant, Randal E. and Tan, Yong Kiam and Heule, Marijn J. H.},
  title =	{{Certifying Projected Knowledge Compilation}},
  booktitle =	{28th International Conference on Theory and Applications of Satisfiability Testing (SAT 2025)},
  pages =	{8:1--8:22},
  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.2025.8},
  URN =		{urn:nbn:de:0030-drops-237422},
  doi =		{10.4230/LIPIcs.SAT.2025.8},
  annote =	{Keywords: Knowledge Compilation, Propositional model counting, Proof checking}
}
Document
DOI: 10.4230/LIPIcs.SAT.2025.20
Scalable Precise Computation of Shannon Entropy

Authors: Yong Lai, Haolong Tong, Zhenghang Xu, and Minghao Yin

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

Abstract
Quantitative information flow analyses (QIF) are a class of techniques for measuring the amount of confidential information leaked by a program to its public outputs. Shannon entropy is an important method to quantify the amount of leakage in QIF. This paper focuses on the programs modeled in Boolean constraints and optimizes the two stages of the Shannon entropy computation to implement a scalable precise tool PSE. In the first stage, we design a knowledge compilation language called ADD[∧] that combines Algebraic Decision Diagrams and conjunctive decomposition. ADD[∧] avoids enumerating possible outputs of a program and supports tractable entropy computation. In the second stage, we optimize the model counting queries that are used to compute the probabilities of outputs. We compare PSE with the state-of-the-art probabilistic approximately correct tool EntropyEstimation, which was shown to significantly outperform the previous precise tools. The experimental results demonstrate that PSE solved 56 more benchmarks compared to EntropyEstimation in a total of 459. For 98% of the benchmarks that both PSE and EntropyEstimation solved, PSE is at least 10× as efficient as EntropyEstimation.
Cite as

Yong Lai, Haolong Tong, Zhenghang Xu, and Minghao Yin. Scalable Precise Computation of Shannon Entropy. In 28th International Conference on Theory and Applications of Satisfiability Testing (SAT 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 341, pp. 20:1-20:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

Copy BibTex To Clipboard

@InProceedings{lai_et_al:LIPIcs.SAT.2025.20,
  author =	{Lai, Yong and Tong, Haolong and Xu, Zhenghang and Yin, Minghao},
  title =	{{Scalable Precise Computation of Shannon Entropy}},
  booktitle =	{28th International Conference on Theory and Applications of Satisfiability Testing (SAT 2025)},
  pages =	{20:1--20:19},
  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.2025.20},
  URN =		{urn:nbn:de:0030-drops-237540},
  doi =		{10.4230/LIPIcs.SAT.2025.20},
  annote =	{Keywords: Knowledge Compilation, Algebraic Decision Diagrams, Quantitative Information Flow, Shannon Entropy}
}
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)

Copy BibTex To Clipboard

@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
DOI: 10.4230/LIPIcs.SAT.2025.27
Streamlining Distributed SAT Solver Design

Authors: Dominik Schreiber, Niccolò Rigi-Luperti, and Armin Biere

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

Abstract
Distributed clause-sharing SAT solvers have recently been established as powerful automated reasoning tools that can conquer previously infeasible instances. A common design of distributed SAT solvers is to run many off-the-shelf sequential solvers in parallel, employ some diversification (e.g., restart intervals or decision orders), and share conflict clauses among the solver threads. This approach, naïvely, adopts all best practices of sequential solver design for distributed solving, where these practices may be less useful or even actively detrimental. In this work we diagnose such shortcomings in the state-of-the-art system MallobSat and propose first effective mitigations. In particular, we replace the redundant pre- and inprocessing at all threads with single-core preprocessing that runs next to the parallel search, remove LBD values from the clause-sharing operation, and slim down solver diversification to very few lightweight and uniform methods. Experimental evaluations on up to 3072 cores (64 nodes) confirm that our measures improve performance while also drastically simplifying the SAT solving program that is run in parallel.
Cite as

Dominik Schreiber, Niccolò Rigi-Luperti, and Armin Biere. Streamlining Distributed SAT Solver Design. In 28th International Conference on Theory and Applications of Satisfiability Testing (SAT 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 341, pp. 27:1-27:23, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

Copy BibTex To Clipboard

@InProceedings{schreiber_et_al:LIPIcs.SAT.2025.27,
  author =	{Schreiber, Dominik and Rigi-Luperti, Niccol\`{o} and Biere, Armin},
  title =	{{Streamlining Distributed SAT Solver Design}},
  booktitle =	{28th International Conference on Theory and Applications of Satisfiability Testing (SAT 2025)},
  pages =	{27:1--27:23},
  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.2025.27},
  URN =		{urn:nbn:de:0030-drops-237615},
  doi =		{10.4230/LIPIcs.SAT.2025.27},
  annote =	{Keywords: Satisfiability, parallel SAT solving, distributed computing, preprocessing}
}
Document
DOI: 10.4230/LIPIcs.SAT.2025.29
Reencoding Unique Literal Clauses

Authors: Aeacus Sheng, Joseph E. Reeves, and Marijn J. H. Heule

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

Abstract
We present a lightweight reencoding technique that augments propositional formulas containing implicit or explicit exactly-one constraints with auxiliary variables derived from the order encoding. Our approach is based on the observation that many formulas contain clauses where each literal appears only in that clause, and that these unique literal clauses can be replaced by the corresponding sequential counter encoding of exactly-one constraints, which introduces the same variables as the order encoding. We implemented the reencoding in the state-of-the-art SAT solver CaDiCaL with support for proof logging and solution reconstruction. Experiments on SAT Competition benchmarks demonstrate that our technique enables solving dozens of additional formulas. We found that shuffling a formula before reencoding harms performance. To mitigate this issue, we introduce a method that sorts literals within clauses based on the formula structure before applying our reencoding. The same technique also predicts whether reencoding is likely to yield improvements.
Cite as

Aeacus Sheng, Joseph E. Reeves, and Marijn J. H. Heule. Reencoding Unique Literal Clauses. In 28th International Conference on Theory and Applications of Satisfiability Testing (SAT 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 341, pp. 29:1-29:21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

Copy BibTex To Clipboard

@InProceedings{sheng_et_al:LIPIcs.SAT.2025.29,
  author =	{Sheng, Aeacus and Reeves, Joseph E. and Heule, Marijn J. H.},
  title =	{{Reencoding Unique Literal Clauses}},
  booktitle =	{28th International Conference on Theory and Applications of Satisfiability Testing (SAT 2025)},
  pages =	{29:1--29:21},
  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.2025.29},
  URN =		{urn:nbn:de:0030-drops-237635},
  doi =		{10.4230/LIPIcs.SAT.2025.29},
  annote =	{Keywords: Satisfiability solving, auxiliary variables, graph coloring}
}
Document
DOI: 10.4230/LITES.10.1.2
Towards a Coq-verified Chain of Esterel Semantics

Authors: Lionel Rieg and Gérard Berry

Published in: LITES, Volume 10, Issue 1 (2025). Leibniz Transactions on Embedded Systems, Volume 10, Issue 1

Abstract
This article focuses on formally specifying and verifying the chain of formal semantics of the Esterel synchronous programming language using the Coq proof assistant. In particular, in addition to the standard logical (LBS) semantics, constructive semantics (CBS) and constructive state semantics (CSS), we introduce a novel microstep semantics that gets rid of the Must/Can potential function pair of the constructive semantics and can be viewed as an abstract version of Esterel’s circuit semantics used by compilers to generate software code and hardware designs. The article also comes with formal proofs in Coq of the equivalence between the CBS and CSS semantics and of the refinement of the CSS by the microstep semantics, except for the loop construct of Esterel.
Cite as

Lionel Rieg and Gérard Berry. Towards a Coq-verified Chain of Esterel Semantics. In LITES, Volume 10, Issue 1 (2025). Leibniz Transactions on Embedded Systems, Volume 10, Issue 1, pp. 2:1-2:54, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

Copy BibTex To Clipboard

@Article{rieg_et_al:LITES.10.1.2,
  author =	{Rieg, Lionel and Berry, G\'{e}rard},
  title =	{{Towards a Coq-verified Chain of Esterel Semantics}},
  journal =	{Leibniz Transactions on Embedded Systems},
  pages =	{2:1--2:54},
  ISSN =	{2199-2002},
  year =	{2025},
  volume =	{10},
  number =	{1},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LITES.10.1.2},
  URN =		{urn:nbn:de:0030-drops-230144},
  doi =		{10.4230/LITES.10.1.2},
  annote =	{Keywords: Esterel programming language, formal verification, Coq proof assistant}
}
Document
DOI: 10.4230/LIPIcs.ICDT.2025.30
An FPRAS for Model Counting for Non-Deterministic Read-Once Branching Programs

Authors: Kuldeep S. Meel and Alexis de Colnet

Published in: LIPIcs, Volume 328, 28th International Conference on Database Theory (ICDT 2025)

Abstract
Non-deterministic read-once branching programs, also known as non-deterministic free binary decision diagrams (nFBDD), are a fundamental data structure in computer science for representing Boolean functions. In this paper, we focus on #nFBDD, the problem of model counting for non-deterministic read-once branching programs. The #nFBDD problem is #P-hard, and it is known that there exists a quasi-polynomial randomized approximation scheme for #nFBDD. In this paper, we provide the first FPRAS for #nFBDD. Our result relies on the introduction of new analysis techniques that focus on bounding the dependence of samples.
Cite as

Kuldeep S. Meel and Alexis de Colnet. An FPRAS for Model Counting for Non-Deterministic Read-Once Branching Programs. In 28th International Conference on Database Theory (ICDT 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 328, pp. 30:1-30:21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

Copy BibTex To Clipboard

@InProceedings{meel_et_al:LIPIcs.ICDT.2025.30,
  author =	{Meel, Kuldeep S. and de Colnet, Alexis},
  title =	{{An FPRAS for Model Counting for Non-Deterministic Read-Once Branching Programs}},
  booktitle =	{28th International Conference on Database Theory (ICDT 2025)},
  pages =	{30:1--30:21},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-364-5},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{328},
  editor =	{Roy, Sudeepa and Kara, Ahmet},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICDT.2025.30},
  URN =		{urn:nbn:de:0030-drops-229717},
  doi =		{10.4230/LIPIcs.ICDT.2025.30},
  annote =	{Keywords: Approximate model counting, FPRAS, Knowledge compilation, nFBDD}
}
Document
DOI: 10.4230/LIPIcs.SAT.2023.6
Certified Knowledge Compilation with Application to Verified Model Counting

Authors: Randal E. Bryant, Wojciech Nawrocki, Jeremy Avigad, and Marijn J. H. Heule

Published in: LIPIcs, Volume 271, 26th International Conference on Theory and Applications of Satisfiability Testing (SAT 2023)

Abstract
Computing many useful properties of Boolean formulas, such as their weighted or unweighted model count, is intractable on general representations. It can become tractable when formulas are expressed in a special form, such as the decision-decomposable, negation normal form (dec-DNNF) . Knowledge compilation is the process of converting a formula into such a form. Unfortunately existing knowledge compilers provide no guarantee that their output correctly represents the original formula, and therefore they cannot validate a model count, or any other computed value. We present Partitioned-Operation Graphs (POGs), a form that can encode all of the representations used by existing knowledge compilers. We have designed CPOG, a framework that can express proofs of equivalence between a POG and a Boolean formula in conjunctive normal form (CNF). We have developed a program that generates POG representations from dec-DNNF graphs produced by the state-of-the-art knowledge compiler D4, as well as checkable CPOG proofs certifying that the output POGs are equivalent to the input CNF formulas. Our toolchain for generating and verifying POGs scales to all but the largest graphs produced by D4 for formulas from a recent model counting competition. Additionally, we have developed a formally verified CPOG checker and model counter for POGs in the Lean 4 proof assistant. In doing so, we proved the soundness of our proof framework. These programs comprise the first formally verified toolchain for weighted and unweighted model counting.
Cite as

Randal E. Bryant, Wojciech Nawrocki, Jeremy Avigad, and Marijn J. H. Heule. Certified Knowledge Compilation with Application to Verified Model Counting. In 26th International Conference on Theory and Applications of Satisfiability Testing (SAT 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 271, pp. 6:1-6:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

Copy BibTex To Clipboard

@InProceedings{bryant_et_al:LIPIcs.SAT.2023.6,
  author =	{Bryant, Randal E. and Nawrocki, Wojciech and Avigad, Jeremy and Heule, Marijn J. H.},
  title =	{{Certified Knowledge Compilation with Application to Verified Model Counting}},
  booktitle =	{26th International Conference on Theory and Applications of Satisfiability Testing (SAT 2023)},
  pages =	{6:1--6:20},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-286-0},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{271},
  editor =	{Mahajan, Meena and Slivovsky, Friedrich},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SAT.2023.6},
  URN =		{urn:nbn:de:0030-drops-184685},
  doi =		{10.4230/LIPIcs.SAT.2023.6},
  annote =	{Keywords: Propositional model counting, Proof checking}
}
  • Refine by Type
  • 14 Document/PDF
  • 12 Document/HTML

  • Refine by Publication Year
  • 1 2026
  • 12 2025
  • 1 2023

  • Refine by Author
  • 4 Heule, Marijn J. H.
  • 3 Meel, Kuldeep S.
  • 3 Tan, Yong Kiam
  • 2 Bryant, Randal E.
  • 2 Lai, Yong
  • Show More...

  • Refine by Series/Journal
  • 13 LIPIcs
  • 1 LITES

  • Refine by Classification
  • 4 Theory of computation → Automated reasoning
  • 4 Theory of computation → Logic and verification
  • 2 Hardware → Theorem proving and SAT solving
  • 2 Theory of computation → Constraint and logic programming
  • 1 Computer systems organization → Real-time languages
  • Show More...

  • Refine by Keyword
  • 2 Knowledge Compilation
  • 2 Proof checking
  • 2 Propositional model counting
  • 2 Satisfiability solving
  • 1 0-1 integer linear programming
  • Show More...

Any Issues?
X

Feedback on the Current Page

CAPTCHA

Thanks for your feedback!

Feedback submitted to Dagstuhl Publishing

Could not send message

Please try again later or send an E-mail
© 2023-2026 Schloss Dagstuhl – LZI GmbH Schloss Dagstuhl – LZI GmbH About DROPS Imprint Privacy Contact