Abstract

Multiway Decision Graph (MDG) is a canonical representation of a subset of many-sorted first-order logic. It generalizes the logic of equality with abstract types and uninterpreted function symbols. The area of Satisfiability (SAT) has been the subject of intensive research in recent years, with significant theoretical and practical contributions. From a practical perspective, a large number of very effective SAT solvers have recently been proposed, most of which based on improvements made to the original Davis-Putnam algorithm. Local search algorithms have allowed solving extremely large satisfiable instances of SAT. The combination between various verification methodologies will enhance the capabilities of each and overcome their limitations. In this thesis, we introduce a methodology and propose a new design verification tool integrating MDG and SAT, to check the safety of a design by invariant checking. Using MDG to encode the set of states provide powerful mean of abstraction. We use SAT solver searching for paths of reachable states violating the property under certain encoding constraints. In addition, we also introduce an automated conversion-verification methodology to convert a Directed Formula (DF) into Conjunctive Normal Form (CNF) formula that can be fed to a SAT solver. The formal verification of this conversion is conducted within the HOL theorem prover. Finally, we implement and conduct experiment on some examples along with a case study to show the correctness and the efficiency of our approach.