Proceedings of the 41st ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages 2014
DOI: 10.1145/2535838.2535857
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Symbolic optimization with SMT solvers

Abstract: The rise in efficiency of Satisfiability Modulo Theories (SMT) solvers has created numerous uses for them in software verification, program synthesis, functional programming, refinement types, etc. In all of these applications, SMT solvers are used for generating satisfying assignments (e.g., a witness for a bug) or proving unsatisfiability/validity (e.g., proving that a subtyping relation holds). We are often interested in finding not just an arbitrary satisfying assignment, but one that optimizes (minimizes/… Show more

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Cited by 96 publications
(101 citation statements)
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“…SMT has become a cornerstone in the programming languages and in the verification community, with contributions to program synthesis [41], constraint programming [54], and symbolic optimization [58]. The combination of SMT and equivalence relations has been the subject of recent investigations.…”
Section: Introductionmentioning
confidence: 99%
“…SMT has become a cornerstone in the programming languages and in the verification community, with contributions to program synthesis [41], constraint programming [54], and symbolic optimization [58]. The combination of SMT and equivalence relations has been the subject of recent investigations.…”
Section: Introductionmentioning
confidence: 99%
“…In those experiments, we compare the results by OptiMathSAT [13], Z3 [3], and Symba [12]. We conclude there that OptiMathSAT provides the most stable performance and scales the best.…”
Section: Introductionmentioning
confidence: 90%
“…Similar approaches for template-based synthesis have been described, for instance, by Gawlitza and Seidl [2007], , and Li et al [2014]. However, these methods consider programs over mathematical integers.…”
Section: Reduction From Second-order To First-order Problemsmentioning
confidence: 97%