Fuzzing Symbolic Expressions

Recent years have witnessed a wide array of results in software testing, exploring different approaches and methodologies ranging from fuzzers to symbolic engines, with a full spectrum of instances in between such as concolic execution and hybrid fuzzing. A key ingredient of many of these tools is S...

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Bibliographic Details
Published in:Proceedings / International Conference on Software Engineering pp. 711 - 722
Main Authors: Borzacchiello, Luca, Coppa, Emilio, Demetrescu, Camil
Format: Conference Proceeding
Language:English
Published: IEEE 01.05.2021
Subjects:
concolic execution
Distance measurement
Engines
Fuzzing
fuzzing testing
Hybrid power systems
SMT solver
Software engineering
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ISBN:1665402962, 9781665402965
ISSN:1558-1225
Online Access:Get full text
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Summary:Recent years have witnessed a wide array of results in software testing, exploring different approaches and methodologies ranging from fuzzers to symbolic engines, with a full spectrum of instances in between such as concolic execution and hybrid fuzzing. A key ingredient of many of these tools is Satisfiability Modulo Theories (SMT) solvers, which are used to reason over symbolic expressions collected during the analysis. In this paper, we investigate whether techniques borrowed from the fuzzing domain can be applied to check whether symbolic formulas are satisfiable in the context of concolic and hybrid fuzzing engines, providing a viable alternative to classic SMT solving techniques. We devise a new approximate solver, FUZZY-SAT, and show that it is both competitive with and complementary to state-of-the-art solvers such as Z3 with respect to handling queries generated by hybrid fuzzers.
ISBN:1665402962
9781665402965
ISSN:1558-1225
DOI:10.1109/ICSE43902.2021.00071