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Automated web application testing is a critical component of modern software development, with frameworks like Selenium widely adopted for validating functionality through browser automation. Among the essential aspects of such testing is…

Proof engineering is notoriously labor-intensive: proofs that are straightforward on paper often require lengthy scripts in theorem provers. Recent advances in large language models (LLMs) create new opportunities for proof automation:…

编程语言 · 计算机科学 2026-01-08 Yichen Xu , Martin Odersky

Automatic software verification tools help to find hard-to-detect faults in programs checked against specified requirements non-interactively. Besides, they can prove program correctness formally under certain assumptions. These…

软件工程 · 计算机科学 2023-09-29 Ilja Zakharov , Evgeny Novikov , Ilya Shchepetkov

Researchers have recently designed a number of application-specific fault tolerance mechanisms that enable applications to either be naturally resilient to errors or include additional detection and correction steps that can bring the…

编程语言 · 计算机科学 2018-05-17 Brett Boston , Zoe Gong , Michael Carbin

Large language models (LLMs) are increasingly explored as general-purpose reasoners, particularly in agentic contexts. However, their outputs remain prone to mathematical and logical errors. This is especially challenging in open-ended…

人工智能 · 计算机科学 2025-05-30 Agnieszka Mensfelt , Kostas Stathis , Vince Trencsenyi

We propose an approach for modular verification of programs written in an object-oriented language where, like in C++, the same virtual method call is bound to different methods at different points during the construction or destruction of…

编程语言 · 计算机科学 2023-07-18 Niels Mommen , Bart Jacobs

Software correctness is ensured mathematically through formal verification, which involves the resources of generating formal requirement specifications and having an implementation that must be verified. Tools such as model-checkers and…

软件工程 · 计算机科学 2025-08-29 Arshad Beg , Diarmuid O'Donoghue , Rosemary Monahan

We introduce SimulBench, a benchmark designed to evaluate large language models (LLMs) across a diverse collection of creative simulation scenarios, such as acting as a Linux terminal or playing text games with users. While these simulation…

计算与语言 · 计算机科学 2024-09-13 Qi Jia , Xiang Yue , Tianyu Zheng , Jie Huang , Bill Yuchen Lin

This paper proposes the use of Large Language Models (LLMs) for translating Request for Comments (RFC) protocol specifications into a format compatible with the Cryptographic Protocol Shapes Analyzer (CPSA). This novel approach aims to…

密码学与安全 · 计算机科学 2024-02-05 Martin Duclos , Ivan A. Fernandez , Kaneesha Moore , Sudip Mittal , Edward Zieglar

Local grammars can be represented in a very convenient way by automata. This paper describes and illustrates an efficient algorithm for the application of local grammars put in this form to lemmatized texts.

cmp-lg · 计算机科学 2008-02-03 Mehryar Mohri

Implementing a complex concept as an executable model in a strongly typed, purely functional language hits a sweet spot between mere simulation and formal specification. For research and education it is often desirable to enrich the…

编程语言 · 计算机科学 2020-08-31 Baltasar Trancón y Widemann , Markus Lepper

We recommend a programming construct - availability check - for programs that need to automatically adjust to presence or absence of segments of code. The idea is to check the existence of a valid definition before a function call is…

编程语言 · 计算机科学 2007-05-23 Joy Mukherjee , Srinidhi Varadarajan

Large Language Models (LLMs) are increasingly used to automatically generate optimized CUDA kernels, substantially improving developer productivity. However, despite rapid generation, these kernels often contain subtle correctness bugs and…

软件工程 · 计算机科学 2026-03-19 Bodhisatwa Chatterjee , Drew Zagieboylo , Sana Damani , Siva Hari , Christos Kozyrakis

Algorithm portfolio and selection approaches have achieved remarkable improvements over single solvers. However, the implementation of such systems is often highly customised and specific to the problem domain. This makes it difficult for…

人工智能 · 计算机科学 2014-05-01 Lars Kotthoff

Large language models (LLMs) are becoming more advanced and widespread and have shown their applicability to various domains, including cybersecurity. Static malware analysis is one of the most important tasks in cybersecurity; however, it…

密码学与安全 · 计算机科学 2024-11-25 Shota Fujii , Rei Yamagishi

Automated characterization of porous materials has the potential to accelerate materials discovery, but it remains limited by the complexity of simulation setup and force field selection. We propose a multi-agent framework in which…

人工智能 · 计算机科学 2025-09-15 Marko Petković , Vlado Menkovski , Sofía Calero

We study induction on the program structure as a proof method for bisimulation-based compiler correctness. We consider a first-order language with mutually recursive function definitions, system calls, and an environment semantics. The…

编程语言 · 计算机科学 2016-11-30 Sigurd Schneider , Gert Smolka , Sebastian Hack

The application of automatic theorem provers to discharge proof obligations is necessary to apply formal methods in an efficient manner. Tools supporting formal methods, such as Atelier~B, generate proof obligations fully automatically.…

软件工程 · 计算机科学 2017-01-31 Lilian Burdy , David Déharbe , Étienne Prun

Functional simulation is an essential step in digital hardware design. Recently, there has been a growing interest in leveraging Large Language Models (LLMs) for hardware testbench generation tasks. However, the inherent instability…

软件工程 · 计算机科学 2024-11-14 Ruidi Qiu , Grace Li Zhang , Rolf Drechsler , Ulf Schlichtmann , Bing Li

While LLM-Based agents, which use external tools to solve complex problems, have made significant progress, benchmarking their ability is challenging, thereby hindering a clear understanding of their limitations. In this paper, we propose…

计算与语言 · 计算机科学 2024-11-07 Chuyu Zhang , Songyang Zhang , Yingfan Hu , Haowen Shen , Kuikun Liu , Zerun Ma , Fengzhe Zhou , Wenwei Zhang , Xuming He , Dahua Lin , Kai Chen