This paper presents optimizations for verifying systems with complex time-invariant constraints. These constraints arise naturally from modeling physical systems, e.g., in establishing the relationship between different components in a system. To verify constraint-rich systems, we propose two new optimizations. The first optimization is a simple, yet powerful, extension of the conjunctivepartitioning algorithm. The second is a collection of BDD-based macro-extraction and macro-expansion algorithms to remove state variables. We showthat these two optimizations are essential in verifying constraint-rich problems; in particular, this work has enabled the verification of fault diagnosis models of the Nomad robot (an Antarctic meteorite explorer) and of the NASA Deep Space One spacecraft.
['Bwolen Yang', 'Reid G. Simmons', 'Randal E. Bryant', "David R. O'Hallaron"]
Optimizing Symbolic Model Checking for Constraint-Rich Models