2,246 papers · page 18 of 113
Jonas Kastberg Hinrichsen, Jules Jacobs, Robbert Krebbers
We introduce Multris, a separation logic for verifying functional correctness of programs that combine multiparty message-passing communication with shared-memory concurrency. The foundation of our work is a novel concept of multiparty protocol consistency, which guarantees safe …
Wolf Honoré, Longfei Qiu, Yoonseung Kim, Ji-Yong Shin, Jieung Kim, Zhong Shao
Achieving consensus is a challenging and ubiquitous problem in distributed systems that is only made harder by the introduction of malicious byzantine servers. While significant effort has been devoted to the benign and byzantine failure models individually, no prior work has con…
Seungmin Jeon, Kyeongmin Cho, Chan Gu Kang, Janggun Lee, Hakjoo Oh, Jeehoon Kang
Probabilistic model checking (PMC) is a verification technique for analyzing the properties of probabilistic systems. However, existing techniques face challenges in verifying large systems with high accuracy. PMC struggles with state explosion, where the number of states grows e…
Keith J. C. Johnson, Rahul Krishnan, Thomas W. Reps, Loris D'Antoni
In top-down enumeration for program synthesis, abstraction-based pruning uses an abstract domain to approximate the set of possible values that a partial program, when completed, can output on a given input. If the set does not contain the desired output, the partial program and …
Michael Jungmair, Alexis Engelke, Jana Giceva
Data science workloads frequently include Python code, but Python's dynamic nature makes efficient execution hard. Traditional approaches either treat Python as a black box, missing out on optimization potential, or are limited to a narrow domain. However, a deep and efficient in…
Anan Kabaha, Dana Drachsler-Cohen
Neural networks are successful in various applications but are also susceptible to adversarial attacks. To show the safety of network classifiers, many verifiers have been introduced to reason about the local robustness of a given input to a given perturbation. While successful, …
Chan Gu Kang, Joonghoon Lee, Hakjoo Oh
We present a new technique for accelerating quantum program testing. Given a quantum circuit with an input/output specification, our goal is to check whether executing the program on the input state produces the expected output. In quantum computing, however, it is impossible to …
Ryan Kavanagh, Brigitte Pientka
We present Most, a process language with message-observing session types. Message-observing session types extend binary session types with type-level computation to specify communication protocols that vary based on messages observed on other channels. Hence, Most allows us to ex…
Caleb Kim, Pai Li, Anshuman Mohan, Andrew Butt, Adrian Sampson, Rachit Nigam
Compilers for accelerator design languages (ADLs) translate high-level languages into application-specific hardware. ADL compilers rely on a hardware control interface to compose hardware units. There are two choices: static control, which relies on cycle-level timing; or dynamic…
Lutz Klinkenberg, Christian Blumenthal, Mingshuai Chen, Darion Haase, Joost-Pieter Katoen
We present an exact Bayesian inference method for inferring posterior distributions encoded by probabilistic programs featuring possibly unbounded loops. Our method is built on a denotational semantics represented by probability generating functions, which resolves semantic intri…
David Klopp, Sebastian Erdweg, André Pacak
Modern usages of Datalog exceed its original design purpose in scale and complexity. In particular, Datalog lacks abstractions for code organization and reuse, making programs hard to maintain. Is it possible to exploit abstractions and design patterns from object-oriented progra…
David Klopp, Sebastian Erdweg, André Pacak
The resurgence of Datalog in the last two decades has led to a multitude of new Datalog systems. These systems explore novel ideas for improving Datalog's programmability and performance, making important contributions to the field. Unfortunately, the individual systems progress …
Anastasiya Kravchuk-Kirilyuk, Gary Feng, Jonas Iskander, Yizhou Zhang, Nada Amin
Many obstacles stand in the way of modular, extensible code. Some language constructs, such as pattern matching, are not easily extensible. Inherited code may not be type safe in the presence of extended types. The burden of setting up design patterns can discourage users, and pa…
Ada Lamba, Max Taylor, Vincent Beardsley, Jacob Bambeck, Michael D. Bond, Zhiqiang Lin
Information flow control (IFC) provides confidentiality by enforcing noninterference, which ensures that high-secrecy values cannot affect low-secrecy values. Prior work introduces fine-grained IFC approaches that modify the programming language and use non-standard compilation t…
Callista Le, Kiran Gopinathan, Koon Wen Lee, Seth Gilbert, Ilya Sergey
Design of an efficient thread-safe concurrent data structure is a balancing act between its implementation complexity and performance. Lock-based concurrent data structures, which are relatively easy to derive from their sequential counterparts and to prove thread-safe, suffer fr…
Edward Lee, Yaoyu Zhao, Ondrej Lhoták, James You, Kavin Satheeskumar, Jonathan Immanuel Brachthäuser
Type qualifiers offer a lightweight mechanism for enriching existing type systems to enforce additional, desirable, program invariants. They do so by offering a restricted but effective form of subtyping. While the theory of type qualifiers is well understood and present in many …
Maxime Legoupil, June Rousseau, Aïna Linn Georges, Jean Pichon-Pharabod, Lars Birkedal
WebAssembly offers coarse-grained encapsulation guarantees via its module system, but does not support fine-grained sharing of its linear memory. MSWasm is a recent proposal which extends WebAssembly with fine-grained memory sharing via handles, a type of capability that guarante…
Haonan Li, Yu Hao, Yizhuo Zhai, Zhiyun Qian
While static analysis is instrumental in uncovering software bugs, its precision in analyzing large and intricate codebases remains challenging. The emerging prowess of Large Language Models (LLMs) offers a promising avenue to address these complexities. In this paper, we present…
Ningke Li, Yuekang Li, Yi Liu, Ling Shi, Kailong Wang, Haoyu Wang
Large language models (LLMs) have revolutionized language processing, but face critical challenges with security, privacy, and generating hallucinations — coherent but factually inaccurate outputs. A major issue is fact-conflicting hallucination (FCH), where LLMs produce content …
Zikun Li, Jinjun Peng, Yixuan Mei, Sina Lin, Yi Wu, Oded Padon, Zhihao Jia
Optimizing quantum circuits is challenging due to the very large search space of functionally equivalent circuits and the necessity of applying transformations that temporarily decrease performance to achieve a final performance improvement. This paper presents Quarl, a learning-…