Theory Exploration Powered by Deductive Synthesis

Author:

Singher Eytan,Itzhaky Shachar

Abstract

AbstractThis paper presents a symbolic method for automatic theorem generation based on deductive inference. Many software verification and reasoning tasks require proving complex logical properties; coping with this complexity is generally done by declaring and proving relevant sub-properties. This gives rise to the challenge of discovering useful sub-properties that can assist the automated proof process. This is known as the theory exploration problem, and so far, predominant solutions that emerged rely on evaluation using concrete values. This limits the applicability of these theory exploration techniques to complex programs and properties.In this work, we introduce a new symbolic technique for theory exploration, capable of (offline) generation of a library of lemmas from a base set of inductive data types and recursive definitions. Our approach introduces a new method for using abstraction to overcome the above limitations, combining it with deductive synthesis to reason about abstract values. Our implementation has shown to find more lemmas than prior art, avoiding redundant lemmas (in terms of provability), while being faster in most cases. This new abstraction-based theory exploration method is a step toward applying theory exploration to software verification and synthesis.

Publisher

Springer International Publishing

Cited by 12 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Proving Functional Program Equivalence via Directed Lemma Synthesis;Lecture Notes in Computer Science;2024-09-11

2. CCLemma: E-Graph Guided Lemma Discovery for Inductive Equational Proofs;Proceedings of the ACM on Programming Languages;2024-08-15

3. Automated Verification of Fundamental Algebraic Laws;Proceedings of the ACM on Programming Languages;2024-06-20

4. Survey of annotation generators for deductive verifiers;Journal of Systems and Software;2024-05

5. Equality Saturation Theory Exploration à la Carte;Proceedings of the ACM on Programming Languages;2023-10-16

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