Model-guided synthesis of inductive lemmas for FOL with least fixpoints

Adithya Murali, Lucas Peña, Eion Blanchard, Christof Löding, P. Madhusudan

Research output: Contribution to journalArticlepeer-review

Abstract

Recursively defined linked data structures embedded in a pointer-based heap and their properties are naturally expressed in pure first-order logic with least fixpoint definitions (FO+lfp) with background theories. Such logics, unlike pure first-order logic, do not admit even complete procedures. In this paper, we undertake a novel approach for synthesizing inductive hypotheses to prove validity in this logic. The idea is to utilize several kinds of finite first-order models as counterexamples that capture the non-provability and invalidity of formulas to guide the search for inductive hypotheses. We implement our procedures and evaluate them extensively over theorems involving heap data structures that require inductive proofs and demonstrate the effectiveness of our methodology.

Original languageEnglish (US)
Article number191
JournalProceedings of the ACM on Programming Languages
Volume6
Issue numberOOPSLA2
Early online dateOct 31 2022
DOIs
StatePublished - Oct 31 2022

Keywords

  • Counterexample-Guided Inductive Synthesis
  • First Order Logic with Least Fixpoints
  • Inductive Hypothesis Synthesis
  • Learning Logics
  • Verifying Linked Data Structures

ASJC Scopus subject areas

  • Software
  • Safety, Risk, Reliability and Quality

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