Logico-Numerical Abstract Acceleration and Application to the Verification of Data-Flow Programs
Abstract
Acceleration methods are commonly used for speeding up the convergence of loops in reachability analysis of counter machine models. Applying these methods to synchronous data-flow programs with Boolean and numerical variables, e.g., Lustre programs, requires the enumeration of the Boolean states in order to obtain a control flow graph (CFG) with numerical variables only. Our goal is to apply acceleration techniques to data-flow programs without resorting to this exhaustive enumeration. To this end, we present (1) logico-numerical abstract acceleration methods for CFGs with Boolean and numerical variables and (2) partitioning techniques that make logical-numerical abstract acceleration effective. Experimental results show that incorporating these methods in a verification tool based on abstract interpretation provides not only significant advantage in terms of accuracy, but also a gain in performance in comparison to standard techniques.
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