Explanation-Based Generalization of Infeasible Path

Abstract

Recent code-based test input generators based on dynamic symbolic execution increase path coverage by solving path condition with a constraint or an SMT solver. When the solver considers path condition produced from an infeasible path, it tries to show unsatisfiability, which is a useless time-consuming process. In this paper, we propose a new method that takes opportunity of the detection of a single infeasible path to generalize to a (possibly infinite) family of infeasible paths, which will not have to be considered in further path conditions solving. The method exploits non-intrusive constraint-based explanations, a technique developed in Constraint Programming to explain unsatisfiability. Experimental results obtained with our prototype tool IPEG show that, whatever is the underlying constraint solving procedure (IC, Colibri and the SMT solver Z3), this approach can save considerable computational time.