Paper Info
Title
Detecting Critical Bugs in SMT Solvers Using Blackbox Mutational Fuzzing
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.
Year
DOI
Venue
2020
10.1145/3368089.3409763
ESEC/FSE '20: 28th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering Virtual Event USA November, 2020
DocType
ISBN
Citations 
Conference
978-1-4503-7043-1
2
PageRank 
References 
Authors
0.36
0
4
Name
Order
Citations
PageRank
Mansur Muhammad Numair120.36
Maria Christakis220016.69
Wüstholz Valentin320.70
Zhang Fuyuan420.70