Disjoint Partial Enumeration without Blocking Clauses
For SAT solvers and formal verification, this provides a more efficient method for disjoint model enumeration by eliminating blocking clauses.
The paper tackles the problem of enumerating disjoint propositional models (disjoint AllSAT) without using blocking clauses, which cause memory and performance issues. The proposed approach integrates CDCL, chronological backtracking, and implicant shrinking, and experiments show clear benefits over blocking-clause-based methods.
A basic algorithm for enumerating disjoint propositional models (disjoint AllSAT) is based on adding blocking clauses incrementally, ruling out previously found models. On the one hand, blocking clauses have the potential to reduce the number of generated models exponentially, as they can handle partial models. On the other hand, the introduction of a large number of blocking clauses affects memory consumption and drastically slows down unit propagation. We propose a new approach that allows for enumerating disjoint partial models with no need for blocking clauses by integrating: Conflict-Driven Clause-Learning (CDCL), Chronological Backtracking (CB), and methods for shrinking models (Implicant Shrinking). Experiments clearly show the benefits of our novel approach.