10 Search Results for "Kokke, Wen"


Document
A Certified Proof Checker for Deep Neural Network Verification in Imandra

Authors: Remi Desmartin, Omri Isac, Grant Passmore, Ekaterina Komendantskaya, Kathrin Stark, and Guy Katz

Published in: LIPIcs, Volume 352, 16th International Conference on Interactive Theorem Proving (ITP 2025)


Abstract
Recent advances in the verification of deep neural networks (DNNs) have opened the way for a broader usage of DNN verification technology in many application areas, including safety-critical ones. However, DNN verifiers are themselves complex programs that have been shown to be susceptible to errors and numerical imprecision; this, in turn, has raised the question of trust in DNN verifiers. One prominent attempt to address this issue is enhancing DNN verifiers with the capability of producing certificates of their results that are subject to independent algorithmic checking. While formulations of Marabou certificate checking already exist on top of the state-of-the-art DNN verifier Marabou, they are implemented in C++, and that code itself raises the question of trust (e.g., in the precision of floating point calculations or guarantees for implementation soundness). Here, we present an alternative implementation of the Marabou certificate checking in Imandra - an industrial functional programming language and an interactive theorem prover (ITP) - that allows us to obtain full proof of certificate correctness. The significance of the result is two-fold. Firstly, it gives stronger independent guarantees for Marabou proofs. Secondly, it opens the way for the wider adoption of DNN verifiers in interactive theorem proving in the same way as many ITPs already incorporate SMT solvers.

Cite as

Remi Desmartin, Omri Isac, Grant Passmore, Ekaterina Komendantskaya, Kathrin Stark, and Guy Katz. A Certified Proof Checker for Deep Neural Network Verification in Imandra. In 16th International Conference on Interactive Theorem Proving (ITP 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 352, pp. 1:1-1:21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)


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@InProceedings{desmartin_et_al:LIPIcs.ITP.2025.1,
  author =	{Desmartin, Remi and Isac, Omri and Passmore, Grant and Komendantskaya, Ekaterina and Stark, Kathrin and Katz, Guy},
  title =	{{A Certified Proof Checker for Deep Neural Network Verification in Imandra}},
  booktitle =	{16th International Conference on Interactive Theorem Proving (ITP 2025)},
  pages =	{1:1--1:21},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-396-6},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{352},
  editor =	{Forster, Yannick and Keller, Chantal},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ITP.2025.1},
  URN =		{urn:nbn:de:0030-drops-246000},
  doi =		{10.4230/LIPIcs.ITP.2025.1},
  annote =	{Keywords: Neural Network Verification, Farkas Lemma, Proof Certification}
}
Document
Canonical for Automated Theorem Proving in Lean

Authors: Chase Norman and Jeremy Avigad

Published in: LIPIcs, Volume 352, 16th International Conference on Interactive Theorem Proving (ITP 2025)


Abstract
Canonical is a solver for type inhabitation in dependent type theory, that is, the problem of producing a term of a given type. We present a Lean tactic which invokes Canonical to generate proof terms and synthesize programs. The tactic supports higher-order and dependently-typed goals, structural recursion over indexed inductive types, and definitional equality. Canonical finds proofs for 84% of Natural Number Game problems in 51 seconds total.

Cite as

Chase Norman and Jeremy Avigad. Canonical for Automated Theorem Proving in Lean. In 16th International Conference on Interactive Theorem Proving (ITP 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 352, pp. 14:1-14:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)


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@InProceedings{norman_et_al:LIPIcs.ITP.2025.14,
  author =	{Norman, Chase and Avigad, Jeremy},
  title =	{{Canonical for Automated Theorem Proving in Lean}},
  booktitle =	{16th International Conference on Interactive Theorem Proving (ITP 2025)},
  pages =	{14:1--14:20},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-396-6},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{352},
  editor =	{Forster, Yannick and Keller, Chantal},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ITP.2025.14},
  URN =		{urn:nbn:de:0030-drops-246128},
  doi =		{10.4230/LIPIcs.ITP.2025.14},
  annote =	{Keywords: Automated Reasoning, Interactive Theorem Proving, Dependent Type Theory, Inhabitation, Unification, Program Synthesis, Formal Methods}
}
Document
Extended Abstract
Toward a Typed Intermediate Language for R (Extended Abstract)

Authors: Mickaël Laurent, Jakob Hain, Filip Krikava, Sebastián Krynski, and Jan Vitek

Published in: OASIcs, Volume 134, Companion Proceedings of the 9th International Conference on the Art, Science, and Engineering of Programming (Programming 2025)


Abstract
Compilers for dynamic languages often rely on intermediate representations with explicit type annotations to facilitate writing program transformations. This paper documents the design of a new typed intermediate representation for a just-in-time compiler for the R programming language called FIŘ. Type annotations, in FIŘ, capture properties such as sharing, the potential for effects, and compiler speculations. In this extended abstract, we focus on the sharing properties that may be used to optimize away some copies of values.

Cite as

Mickaël Laurent, Jakob Hain, Filip Krikava, Sebastián Krynski, and Jan Vitek. Toward a Typed Intermediate Language for R (Extended Abstract). In Companion Proceedings of the 9th International Conference on the Art, Science, and Engineering of Programming (Programming 2025). Open Access Series in Informatics (OASIcs), Volume 134, pp. 24:1-24:4, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)


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@InProceedings{laurent_et_al:OASIcs.Programming.2025.24,
  author =	{Laurent, Micka\"{e}l and Hain, Jakob and Krikava, Filip and Krynski, Sebasti\'{a}n and Vitek, Jan},
  title =	{{Toward a Typed Intermediate Language for R}},
  booktitle =	{Companion Proceedings of the 9th International Conference on the Art, Science, and Engineering of Programming (Programming 2025)},
  pages =	{24:1--24:4},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-382-9},
  ISSN =	{2190-6807},
  year =	{2025},
  volume =	{134},
  editor =	{Edwards, Jonathan and Perera, Roly and Petricek, Tomas},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.Programming.2025.24},
  URN =		{urn:nbn:de:0030-drops-243086},
  doi =		{10.4230/OASIcs.Programming.2025.24},
  annote =	{Keywords: JIT, compilation, static typing, ownership, copy-on-write, dynamic language}
}
Document
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
Invited Talk
Vehicle: Bridging the Embedding Gap in the Verification of Neuro-Symbolic Programs (Invited Talk)

Authors: Matthew L. Daggitt, Wen Kokke, Robert Atkey, Ekaterina Komendantskaya, Natalia Slusarz, and Luca Arnaboldi

Published in: LIPIcs, Volume 337, 10th International Conference on Formal Structures for Computation and Deduction (FSCD 2025)


Abstract
Neuro-symbolic programs, i.e. programs containing both machine learning components and traditional symbolic code, are becoming increasingly widespread. Finding a general methodology for verifying such programs is challenging due to both the number of different tools involved and the intricate interface between the "neural" and "symbolic" program components. In this paper we present a general decomposition of the neuro-symbolic verification problem into parts, and examine the problem of the embedding gap that occurs when one tries to combine proofs about the neural and symbolic components. To address this problem we then introduce Vehicle - standing as an abbreviation for a "verification condition language" - an intermediate programming language interface between machine learning frameworks, automated theorem provers, and dependently-typed formalisations of neuro-symbolic programs. Vehicle allows users to specify the properties of the neural components of neuro-symbolic programs once, and then safely compile the specification to each interface using a tailored typing and compilation procedure. We give a high-level overview of Vehicle’s overall design, its interfaces and compilation & type-checking procedures, and then demonstrate its utility by formally verifying the safety of a simple autonomous car controlled by a neural network, operating in a stochastic environment with imperfect information.

Cite as

Matthew L. Daggitt, Wen Kokke, Robert Atkey, Ekaterina Komendantskaya, Natalia Slusarz, and Luca Arnaboldi. Vehicle: Bridging the Embedding Gap in the Verification of Neuro-Symbolic Programs (Invited Talk). In 10th International Conference on Formal Structures for Computation and Deduction (FSCD 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 337, pp. 2:1-2:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)


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@InProceedings{daggitt_et_al:LIPIcs.FSCD.2025.2,
  author =	{Daggitt, Matthew L. and Kokke, Wen and Atkey, Robert and Komendantskaya, Ekaterina and Slusarz, Natalia and Arnaboldi, Luca},
  title =	{{Vehicle: Bridging the Embedding Gap in the Verification of Neuro-Symbolic Programs}},
  booktitle =	{10th International Conference on Formal Structures for Computation and Deduction (FSCD 2025)},
  pages =	{2:1--2:20},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-374-4},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{337},
  editor =	{Fern\'{a}ndez, Maribel},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.FSCD.2025.2},
  URN =		{urn:nbn:de:0030-drops-236172},
  doi =		{10.4230/LIPIcs.FSCD.2025.2},
  annote =	{Keywords: Neural Network Verification, Types, Interactive Theorem Provers}
}
Artifact
Software
vehicle-lang/vehicle

Authors: Matthew L. Daggitt, Wen Kokke, Robert Atkey, Ekaterina Komendantskaya, Natalia Slusarz, and Luca Arnaboldi


Abstract

Cite as

Matthew L. Daggitt, Wen Kokke, Robert Atkey, Ekaterina Komendantskaya, Natalia Slusarz, Luca Arnaboldi. vehicle-lang/vehicle (Software, Source Code). Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)


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@misc{AtkeyVehicleForm23,
   title = {{vehicle-lang/vehicle}}, 
   author = {Daggitt, Matthew L. and Kokke, Wen and Atkey, Robert and Komendantskaya, Ekaterina and Slusarz, Natalia and Arnaboldi, Luca},
   note = {Software, version 0.16.1., EPSRC grant AISEC: AI Secure and Explainable by Construction (EP/T026960/1, EP/T027037/1, EP/T026960/1), swhId: \href{https://archive.softwareheritage.org/swh:1:dir:0fa35e993030867ae24451f644c7c296c0f70f22;origin=https://github.com/vehicle-lang/vehicle;visit=swh:1:snp:a878c982596b8bfb093b9e4710463b94df33e699;anchor=swh:1:rev:9d607a0fffb599b31f53b13d06474dbdec41f2aa}{\texttt{swh:1:dir:0fa35e993030867ae24451f644c7c296c0f70f22}} (visited on 2025-07-07)},
   url = {https://github.com/vehicle-lang/vehicle},
   doi = {10.4230/artifacts.23126},
}
Document
Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees

Authors: Guanqin Zhang, Kota Fukuda, Zhenya Zhang, H.M.N. Dilum Bandara, Shiping Chen, Jianjun Zhao, and Yulei Sui

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


Abstract
The vulnerability of neural networks to adversarial perturbations has necessitated formal verification techniques that can rigorously certify the quality of neural networks. As the state-of-the-art, branch-and-bound (BaB) is a "divide-and-conquer" strategy that applies off-the-shelf verifiers to sub-problems for which they perform better. While BaB can identify the sub-problems that are necessary to be split, it explores the space of these sub-problems in a naive "first-come-first-served" manner, thereby suffering from an issue of inefficiency to reach a verification conclusion. To bridge this gap, we introduce an order over different sub-problems produced by BaB, concerning with their different likelihoods of containing counterexamples. Based on this order, we propose a novel verification framework Oliva that explores the sub-problem space by prioritizing those sub-problems that are more likely to find counterexamples, in order to efficiently reach the conclusion of the verification. Even if no counterexample can be found in any sub-problem, it only changes the order of visiting different sub-problems and so will not lead to a performance degradation. Specifically, Oliva has two variants, including Oliva^GR, a greedy strategy that always prioritizes the sub-problems that are more likely to find counterexamples, and Oliva^SA, a balanced strategy inspired by simulated annealing that gradually shifts from exploration to exploitation to locate the globally optimal sub-problems. We experimentally evaluate the performance of Oliva on 690 verification problems spanning over 5 models with datasets MNIST and CIFAR-10. Compared to the state-of-the-art approaches, we demonstrate the speedup of Oliva for up to 25× in MNIST, and up to 80× in CIFAR-10.

Cite as

Guanqin Zhang, Kota Fukuda, Zhenya Zhang, H.M.N. Dilum Bandara, Shiping Chen, Jianjun Zhao, and Yulei Sui. Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees. In 39th European Conference on Object-Oriented Programming (ECOOP 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 333, pp. 36:1-36:29, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)


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@InProceedings{zhang_et_al:LIPIcs.ECOOP.2025.36,
  author =	{Zhang, Guanqin and Fukuda, Kota and Zhang, Zhenya and Bandara, H.M.N. Dilum and Chen, Shiping and Zhao, Jianjun and Sui, Yulei},
  title =	{{Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees}},
  booktitle =	{39th European Conference on Object-Oriented Programming (ECOOP 2025)},
  pages =	{36:1--36:29},
  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.2025.36},
  URN =		{urn:nbn:de:0030-drops-233281},
  doi =		{10.4230/LIPIcs.ECOOP.2025.36},
  annote =	{Keywords: neural network verification, branch and bound, counterexample potentiality, simulated annealing, stochastic optimization}
}
Document
Contrasting Deadlock-Free Session Processes

Authors: Juan C. Jaramillo and Jorge A. Pérez

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


Abstract
Deadlock freedom is a crucial property for message-passing programs. Over the years, several different type systems for concurrent processes that ensure deadlock freedom have been proposed; this diversity raises the question of how they compare. We address this question, considering two type systems not covered in prior work: Kokke et al.’s HCP, a type system based on a linear logic with hypersequents, and Padovani’s priority-based type system for asynchronous processes, dubbed 𝖯. Their distinctive features make formal comparisons relevant and challenging. Our findings are two-fold: (1) the hypersequent setting does not drastically change the class of deadlock-free processes induced by linear logic, and (2) we relate the classes of deadlock-free processes induced by HCP and 𝖯. We prove that our results hold under both synchronous and asynchronous communication. Our results provide new insights into the essential mechanisms involved in statically avoiding deadlocks in concurrency.

Cite as

Juan C. Jaramillo and Jorge A. Pérez. Contrasting Deadlock-Free Session Processes. In 39th European Conference on Object-Oriented Programming (ECOOP 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 333, pp. 17:1-17:29, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)


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@InProceedings{jaramillo_et_al:LIPIcs.ECOOP.2025.17,
  author =	{Jaramillo, Juan C. and P\'{e}rez, Jorge A.},
  title =	{{Contrasting Deadlock-Free Session Processes}},
  booktitle =	{39th European Conference on Object-Oriented Programming (ECOOP 2025)},
  pages =	{17:1--17:29},
  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.2025.17},
  URN =		{urn:nbn:de:0030-drops-233103},
  doi =		{10.4230/LIPIcs.ECOOP.2025.17},
  annote =	{Keywords: session types, process calculi, deadlock freedom}
}
Document
Stay Safe Under Panic: Affine Rust Programming with Multiparty Session Types

Authors: Nicolas Lagaillardie, Rumyana Neykova, and Nobuko Yoshida

Published in: LIPIcs, Volume 222, 36th European Conference on Object-Oriented Programming (ECOOP 2022)


Abstract
Communicating systems comprise diverse software components across networks. To ensure their robustness, modern programming languages such as Rust provide both strongly typed channels, whose usage is guaranteed to be affine (at most once), and cancellation operations over binary channels. For coordinating components to correctly communicate and synchronise with each other, we use the structuring mechanism from multiparty session types, extending it with affine communication channels and implicit/explicit cancellation mechanisms. This new typing discipline, affine multiparty session types (AMPST), ensures cancellation termination of multiple, independently running components and guarantees that communication will not get stuck due to error or abrupt termination. Guided by AMPST, we implemented an automated generation tool (MultiCrusty) of Rust APIs associated with cancellation termination algorithms, by which the Rust compiler auto-detects unsafe programs. Our evaluation shows that MultiCrusty provides an efficient mechanism for communication, synchronisation and propagation of the notifications of cancellation for arbitrary processes. We have implemented several usecases, including popular application protocols (OAuth, SMTP), and protocols with exception handling patterns (circuit breaker, distributed logging).

Cite as

Nicolas Lagaillardie, Rumyana Neykova, and Nobuko Yoshida. Stay Safe Under Panic: Affine Rust Programming with Multiparty Session Types. In 36th European Conference on Object-Oriented Programming (ECOOP 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 222, pp. 4:1-4:29, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)


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@InProceedings{lagaillardie_et_al:LIPIcs.ECOOP.2022.4,
  author =	{Lagaillardie, Nicolas and Neykova, Rumyana and Yoshida, Nobuko},
  title =	{{Stay Safe Under Panic: Affine Rust Programming with Multiparty Session Types}},
  booktitle =	{36th European Conference on Object-Oriented Programming (ECOOP 2022)},
  pages =	{4:1--4:29},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-225-9},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{222},
  editor =	{Ali, Karim and Vitek, Jan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECOOP.2022.4},
  URN =		{urn:nbn:de:0030-drops-162324},
  doi =		{10.4230/LIPIcs.ECOOP.2022.4},
  annote =	{Keywords: Rust language, affine multiparty session types, failures, cancellation}
}
Document
Separating Sessions Smoothly

Authors: Simon Fowler, Wen Kokke, Ornela Dardha, Sam Lindley, and J. Garrett Morris

Published in: LIPIcs, Volume 203, 32nd International Conference on Concurrency Theory (CONCUR 2021)


Abstract
This paper introduces Hypersequent GV (HGV), a modular and extensible core calculus for functional programming with session types that enjoys deadlock freedom, confluence, and strong normalisation. HGV exploits hyper-environments, which are collections of type environments, to ensure that structural congruence is type preserving. As a consequence we obtain a tight operational correspondence between HGV and HCP, a hypersequent-based process-calculus interpretation of classical linear logic. Our translations from HGV to HCP and vice-versa both preserve and reflect reduction. HGV scales smoothly to support Girard’s Mix rule, a crucial ingredient for channel forwarding and exceptions.

Cite as

Simon Fowler, Wen Kokke, Ornela Dardha, Sam Lindley, and J. Garrett Morris. Separating Sessions Smoothly. In 32nd International Conference on Concurrency Theory (CONCUR 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 203, pp. 36:1-36:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)


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@InProceedings{fowler_et_al:LIPIcs.CONCUR.2021.36,
  author =	{Fowler, Simon and Kokke, Wen and Dardha, Ornela and Lindley, Sam and Morris, J. Garrett},
  title =	{{Separating Sessions Smoothly}},
  booktitle =	{32nd International Conference on Concurrency Theory (CONCUR 2021)},
  pages =	{36:1--36:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-203-7},
  ISSN =	{1868-8969},
  year =	{2021},
  volume =	{203},
  editor =	{Haddad, Serge and Varacca, Daniele},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CONCUR.2021.36},
  URN =		{urn:nbn:de:0030-drops-144138},
  doi =		{10.4230/LIPIcs.CONCUR.2021.36},
  annote =	{Keywords: session types, hypersequents, linear lambda calculus}
}
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