Synthesizing Implication Lemmas for Interactive Theorem Proving

Interactive theorem provers (ITP) enable programmers to formally verify properties of their software systems. One burden for users of ITPs is identifying the necessary helper lemmas to complete a proof, for example those that define key inductive invariants. Existing approaches to lemma synthesis for ITPs have limited, if any, support for synthesizing implications : lemmas of the form P 1 ∧ ⋯ ∧ P n ⇒ Q . In this paper, we propose a technique and associated tool for synthesizing useful implication lemmas. Our approach employs a form of data-driven invariant inference to explore strengthenings of the current proof state, based on sample valuations of the current goal and assumptions. We have implemented our approach in a Rocq tactic called dilemma. We demonstrate its effectiveness in synthesizing necessary helper lemmas for proofs from the Verified Functional Algorithms textbook as well as from prior benchmark suites for lemma synthesis.

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Journal
Proceedings of the ACM on Programming Languages
Published
2025-10-09
DOI
https://doi.org/10.1145/3763131
Primary Topic
Logic, programming, and type systems
Type
article
Field-Weighted Citation Impact
0.00
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article

Synthesizing Implication Lemmas for Interactive Theorem Proving

Todd Millstein, Ana Brendel, Aishwarya Sivaraman
Proceedings of the ACM on Programming Languages
Logic, programming, and type systems
article

Synthesizing Implication Lemmas for Interactive Theorem Proving

Todd Millstein, Ana Brendel, Aishwarya Sivaraman
article en

Abstract

Interactive theorem provers (ITP) enable programmers to formally verify properties of their software systems. One burden for users of ITPs is identifying the necessary helper lemmas to complete a proof, for example those that define key inductive invariants. Existing approaches to lemma synthesis for ITPs have limited, if any, support for synthesizing implications : lemmas of the form P 1 ∧ ⋯ ∧ P n ⇒ Q . In this paper, we propose a technique and associated tool for synthesizing useful implication lemmas. Our approach employs a form of data-driven invariant inference to explore strengthenings of the current proof state, based on sample valuations of the current goal and assumptions. We have implemented our approach in a Rocq tactic called dilemma. We demonstrate its effectiveness in synthesizing necessary helper lemmas for proofs from the Verified Functional Algorithms textbook as well as from prior benchmark suites for lemma synthesis.

Proceedings of the ACM on Programming LanguagesVol. 9(OOPSLA2)
University of California, Los Angeles (US)
Openalex Percentile: Top 85%
Logic, programming, and type systems
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