Detecting Critical Bugs in SMT Solvers Using Blackbox Mutational Fuzzing

13 Apr 2020  ·  Muhammad Numair Mansur, Maria Christakis, Valentin Wüstholz, Fuyuan Zhang ·

Formal methods use SMT solvers extensively for deciding formula satisfiability, for instance, in software verification, systematic test generation, and program synthesis. However, due to their complex implementations, solvers may contain critical bugs that lead to unsound results. Given the wide applicability of solvers in software reliability, relying on such unsound results may have detrimental consequences. In this paper, we present STORM, a novel blackbox mutational fuzzing technique for detecting critical bugs in SMT solvers. We run our fuzzer on seven mature solvers and find 29 previously unknown critical bugs. STORM is already being used in testing new features of popular solvers before deployment.

PDF Abstract
No code implementations yet. Submit your code now

Categories


Software Engineering

Datasets


  Add Datasets introduced or used in this paper