Data-driven lemma synthesis for interactive proofs

Abstract

Interactive proofs of theorems often require auxiliary helper lemmas to prove the desired theorem. Existing approaches for automatically synthesizing helper lemmas fall into two broad categories. Some approaches are goal-directed, producing lemmas specifically to help a user make progress from a given proof state, but they have limited expressiveness in terms of the lemmas that can be produced. Other approaches are highly expressive, able to generate arbitrary lemmas from a given grammar, but they are completely undirected and hence not amenable to interactive usage.

Document Details

Document Type
Pub Defense Publication
Publication Date
Oct 31, 2022
Source ID
10.1145/3563306

Entities

People

  • Aishwarya Sivaraman
  • Alex Sanchez-Stern
  • Bretton Chen
  • Sorin Lerner
  • Todd Millstein

Organizations

  • Defense Advanced Research Projects Agency
  • National Science Foundation
  • University of California, Los Angeles
  • University of California, San Diego
  • University of Massachusetts Amherst

Tags

Readers

  • Computational Linguistics
  • Graph Algorithms and Convex Optimization.