A Learning-Based Fact Selector for Isabelle/HOL

Sledgehammer integrates automatic theorem provers in the proof assistant
Isabelle/HOL. A key component, the fact selector, heuristically ranks the thousands of facts
(lemmas, definitions, or axioms) available and selects a subset, based on syntactic similarity
to the current proof goal. We introduce MaSh, an alternative that learns from successful
proofs. New challenges arose from our “zero click” vision: MaSh integrates seamlessly with
the users’ workflow, so that they benefit from machine learning without having to install
software, set up servers, or guide the learning. MaSh outperforms the old fact selector on
large formalizations.