ALASCA: Reasoning in Quantified Linear Arithmetic

Konstantin Korovin, Laura Kovács, Giles Reger, Johannes Schoisswohl, Andrei Voronkov

Abstract: Automated reasoning is routinely used in the rigorous construction and analysis of complex systems. Among different theories, arithmetic stands out as one of the most frequently used and at the same time one of the most challenging in the presence of quantifiers and uninterpreted function symbols. First-order theorem provers perform very well on quantified problems due to the efficient superposition calculus, but support for arithmetic reasoning is limited to heuristic axioms. In this paper, we introduce the \(\textsc {Alasca}\) calculus that lifts superposition reasoning to the linear arithmetic domain. We show that \(\textsc {Alasca}\) is both sound and complete with respect to an axiomatisation of linear arithmetic. We implemented and evaluated \(\textsc {Alasca}\) using the Vampire theorem prover, solving many more challenging problems compared to state-of-the-art reasoners.

External IDs:dblp:conf/tacas/KorovinKRSV23