Efficient and Complete FD-solving for extended array constraints

Efficient and Complete FD-solving for extended array constraints

Quentin Plazar, Mathieu Acher, Sébastien Bardin, Arnaud Gotlieb

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence
Main track. Pages 1231-1238. https://doi.org/10.24963/ijcai.2017/171

Array constraints are essential for handling data structures in automated reasoning and software verification. Unfortunately, the use of a typical finite domain (FD) solver based on local consistency-based filtering has strong limitations when constraints on indexes are combined with constraints on array elements and size. This paper proposes an efficient and complete FD-solving technique for extended constraints over (possibly unbounded) arrays. We describe a simple but particularly powerful transformation for building an equisatisfiable formula that can be efficiently solved using standard FD reasoning over arrays, even in the unbounded case. Experiments show that the proposed solver significantly outperforms FD solvers, and successfully competes with the best SMT-solvers.
Keywords:
Knowledge Representation, Reasoning, and Logic: Automated Reasoning and Theorem Proving
Multidisciplinary Topics and Applications: Validation and Verification
Constraints and Satisfiability: Constraint Satisfaction