Detecting Critical Bugs in SMT Solvers Using Blackbox Mutational Fuzzing
Software Engineering
2020-04-14 v1
Abstract
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.
Keywords
Cite
@article{arxiv.2004.05934,
title = {Detecting Critical Bugs in SMT Solvers Using Blackbox Mutational Fuzzing},
author = {Muhammad Numair Mansur and Maria Christakis and Valentin Wüstholz and Fuyuan Zhang},
journal= {arXiv preprint arXiv:2004.05934},
year = {2020}
}