PaMpeR: Proof Method Recommendation System for Isabelle/HOL
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Abstract (arXiv)
Deciding which sub-tool to use for a given proof state requires expertise specific to each ITP. To mitigate this problem, we present PaMpeR, a Proof Method Recommendation system for Isabelle/HOL. Given a proof state, PaMpeR recommends proof methods to discharge the proof goal and provides qualitative explanations as to why it suggests these methods. PaMpeR generates these recommendations based on existing hand-written proof corpora, thus transferring experienced users' expertise to new users. Our evaluation shows that PaMpeR correctly predicts experienced users' proof methods invocation especially when it comes to special purpose proof methods.
Key facts. Cited by 7 papers in the map (data through 13 Oct 2026). First posted on arXiv 19 Jun 2018.
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Citing papers per year: 2021: 2; 2022: 1; 2023: 2; 2024: 1; 2025: 0; 2026: 1.
7 papers.
- 2023Baldur: Whole-Proof Generation and Repair with Large Language Modelscited by 119
- 2023Magnushammer: A Transformer-Based Approach to Premise Selectioncited by 50
- 2021The Role of Entropy in Guiding a Connection Provercited by 8
- 2021Online Machine Learning Techniques for Coq: A Comparisoncited by 7
- 2024Learning Guided Automated Reasoning: A Brief Surveycited by 7
- 2026Event-B Agent: Towards LLM Agent for Formal Model Synthesis and Repaircited by 3
- 2022Genetic Algorithm for Program Synthesiscited by 0
- 2026Event-B Agent: Towards LLM Agent for Formal Model Synthesis and Repair17 May 2026
- 2024Learning Guided Automated Reasoning: A Brief Survey6 Mar 2024
- 2023Baldur: Whole-Proof Generation and Repair with Large Language Models8 Mar 2023
- 2023Magnushammer: A Transformer-Based Approach to Premise Selection8 Mar 2023
- 2022Genetic Algorithm for Program Synthesis22 Nov 2022
- 2021The Role of Entropy in Guiding a Connection Prover31 May 2021
- 2021Online Machine Learning Techniques for Coq: A Comparison12 Apr 2021