0000000000422287
AUTHOR
Björn Beber
Improving Interpolants for Linear Arithmetic
Craig interpolation for satisfiability modulo theory formulas have come more into focus for applications of formal verification. In this paper we, introduce a method to reduce the size of linear constraints used in the description of already computed interpolant in the theory of linear arithmetic with respect to the number of linear constraints. We successfully improve interpolants by combining satisfiability modulo theory and linear programming in a local search heuristic. Our experimental results suggest a lower running time and a larger reduction compared to other methods from the literature.
Verification of linear hybrid systems with large discrete state spaces using counterexample-guided abstraction refinement
Abstract We present a counterexample-guided abstraction refinement ( CEGAR) approach for the verification of safety properties of linear hybrid automata with large discrete state spaces, such as naturally arising when incorporating health state monitoring and degradation levels into the controller design. Such models can – in contrast to purely functional controller models – not be analyzed with hybrid verification engines relying on explicit representations of modes, but require fully symbolic representations for both the continuous and discrete part of the state space. The presented abstraction methods directly work on a symbolic representation of arbitrary non-convex combinations of line…