Automated Conjecturing in QuickSpec
Paper i proceeding, 2021

A key component of mathematical reasoning is the ability to formulate interesting conjectures about a problem domain at hand. This task has not yet been widely studied by the automated reasoning and AI communities, but we believe interest is growing. In this paper, we give a brief overview of a theory exploration system called QuickSpec, able to automatically discover interesting conjectures about a given set of functions. QuickSpec works by interleaving term generation with random testing to form candidate equational conjectures. This is made tractable by starting from small sizes and ensuring that only terms that are irreducible with respect to already discovered equalities are considered. QuickSpec has been successfully applied to generate lemmas for automated inductive theorem proving as well as to generate specifications of functional programs. We also give a small survey of different approaches to conjecture discovery, and speculate about future directions combining symbolic methods and machine learning.


Moa Johansson

Chalmers, Data- och informationsteknik, Formella metoder

Nicholas Smallbone

Chalmers, Data- och informationsteknik, Funktionell programmering

1 st Mathematical Reasoning in General Artificial Intelligence Workshop, ICLR 2021.

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