Abstract Maximum Satisfiability (MaxSAT) is an optimization version of SAT, and many real
world applications can be naturally encoded as such. Solving MaxSAT is an important …

Satisfiability modulo theories (SMT) solving has become a critical part of many static
analyses, including symbolic execution, refinement type checking, and model checking. We …

Abstract Multi-Objective Combinatorial Optimization (MOCO) problems find a wide range of
practical application problems, some of which involving Boolean variables and constraints …

Propositional satisfiability (SAT) is a success story in Computer Science and Artificial
Intelligence: SAT solvers are currently used to solve problems in many different application …

We present BEE, a compiler which enables to encode finite domain constraint problems to
CNF. Using BEE both eases the encoding process for the user and also performs …

We introduce pairwise cardinality networks, networks of comparators, derived from pairwise
sorting networks, which express cardinality constraints. We show that pairwise cardinality …

We present an approach to propagation-based SAT encoding of combinatorial problems,
Boolean equi-propagation, where constraints are modeled as Boolean functions which …

The increasing popularity of the Semantic Web drove to a widespread adoption of
Description Logics (DLs) for modeling real world domains. To help the diffusion of DLs, a …

We present a new SAT backend for the B-Method to enable new applications of formal
methods. The new backend interleaves low-level SAT solving with high-level constraint …

A succinct SAT solver is presented that exploits the control provided by delay declarations to
implement watched literals and unit propagation. Despite its brevity the solver is surprisingly …