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Date
2020-06Type
- Conference Paper
Citations
Cited 23 times in
Web of Science
Cited 29 times in
Scopus
ETH Bibliography
yes
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Abstract
We introduce Semantic Fusion, a general, effective methodology for validating Satisfiability Modulo Theory (SMT) solvers. Our key idea is to fuse two existing equisatisfiable (i.e., both satisfiable or unsatisfiable) formulas into a new formula that combines the structures of its ancestors in a novel manner and preserves the satisfiability by construction. This fused formula is then used for validating SMT solvers. We realized Semantic Fusion as YinYang, a practical SMT solver testing tool. During four months of extensive testing, YinYang has found 45 confirmed, unique bugs in the default arithmetic and string solvers of Z3 and CVC4, the two state-of-the-art SMT solvers. Among these, 41 have already been fixed by the developers. The majority (29/45) of these bugs expose critical soundness issues. Our bug reports and testing effort have been well-appreciated by SMT solver developers. © 2020 ACM. Show more
Publication status
publishedExternal links
Book title
Proceedings of the 41st ACM SIGPLAN Conference on Programming Language Design and ImplementationPages / Article No.
Publisher
Association for Computing MachineryEvent
Subject
Fuzz testing; Semantic fusion; SMT solversOrganisational unit
09628 - Su, Zhendong / Su, Zhendong
Notes
Due to the Corona virus (COVID-19) the conference was conducted virtually.More
Show all metadata
Citations
Cited 23 times in
Web of Science
Cited 29 times in
Scopus
ETH Bibliography
yes
Altmetrics