Inferring Invariants with Quantifier Alternations: Taming the Search Space Explosion
Jason R. Koenig, Oded Padon, Sharon Shoham, Alex Aiken

TL;DR
This paper introduces a novel algorithm for finding inductive invariants with quantifier alternations, improving scalability and effectiveness in complex distributed protocol verification by combining a breadth-first search and a new syntactic form.
Contribution
The paper presents a new PDR/IC3 algorithm that efficiently searches for inductive invariants with quantifier alternations using a combined breadth-first strategy and a specialized syntactic form.
Findings
Successfully solves more complex distributed protocol examples than existing methods.
Demonstrates improved scalability and effectiveness on a benchmark suite.
Introduces a syntactic form that manages the search space for quantified invariants.
Abstract
We present a PDR/IC3 algorithm for finding inductive invariants with quantifier alternations. We tackle scalability issues that arise due to the large search space of quantified invariants by combining a breadth-first search strategy and a new syntactic form for quantifier-free bodies. The breadth-first strategy prevents inductive generalization from getting stuck in regions of the search space that are expensive to search and focuses instead on lemmas that are easy to discover. The new syntactic form is well-suited to lemmas with quantifier alternations by allowing both limited conjunction and disjunction in the quantifier-free body, while carefully controlling the size of the search space. Combining the breadth-first strategy with the new syntactic form results in useful inductive bias by prioritizing lemmas according to: (i) well-defined syntactic metrics for simple quantifier…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsDistributed systems and fault tolerance · Topic Modeling · Parallel Computing and Optimization Techniques
