Efficient and Complete FD-solving for extended array constraints

Abstract

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 consistencybased 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.

MCBAT: a practical tool for model counting constraints on bounded integer arrays

“…We find that the most closely related work to ours is that of Plazar, et. al [24]. While their work is focused primarily on satisfiability checking of array constraints over arbitrary value types, the bounded fragment of array theory that they focus on and the resulting algorithm bear resemblances to our approaches that focus on bounded integer arrays.…”

Constraint Programming for Dynamic Symbolic Execution of JavaScript

“…Further, because of aliasing, we cannot even determine statically which objects are being written to. To handle non-fixed indices, Plazar et al [39] exploit the observation that, because a finite sequence of reads and writes can only affect a bounded number of indices, it is possible to emulate an unbounded mapping with bounded arrays using an indirection.…”