CoqPyt: Proof Navigation in Python in the Era of LLMs

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Detalles Bibliográficos
Publicado en:arXiv.org (May 7, 2024), p. n/a
Autor principal: Carrott, Pedro
Otros Autores: Saavedra, Nuno, Thompson, Kyle, Lerner, Sorin, Ferreira, João F, First, Emily
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Cornell University Library, arXiv.org
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022 |a 2331-8422 
024 7 |a 10.1145/3663529.3663814  |2 doi 
035 |a 3052222220 
045 0 |b d20240507 
100 1 |a Carrott, Pedro 
245 1 |a CoqPyt: Proof Navigation in Python in the Era of LLMs 
260 |b Cornell University Library, arXiv.org  |c May 7, 2024 
513 |a Working Paper 
520 3 |a Proof assistants enable users to develop machine-checked proofs regarding software-related properties. Unfortunately, the interactive nature of these proof assistants imposes most of the proof burden on the user, making formal verification a complex, and time-consuming endeavor. Recent automation techniques based on neural methods address this issue, but require good programmatic support for collecting data and interacting with proof assistants. This paper presents CoqPyt, a Python tool for interacting with the Coq proof assistant. CoqPyt improves on other Coq-related tools by providing novel features, such as the extraction of rich premise data. We expect our work to aid development of tools and techniques, especially LLM-based, designed for proof synthesis and repair. A video describing and demonstrating CoqPyt is available at: https://youtu.be/fk74o0rePM8. 
653 |a Data collection 
653 |a Tools 
700 1 |a Saavedra, Nuno 
700 1 |a Thompson, Kyle 
700 1 |a Lerner, Sorin 
700 1 |a Ferreira, João F 
700 1 |a First, Emily 
773 0 |t arXiv.org  |g (May 7, 2024), p. n/a 
786 0 |d ProQuest  |t Engineering Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3052222220/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch 
856 4 0 |3 Full text outside of ProQuest  |u http://arxiv.org/abs/2405.04282