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Invariant Synthesis for Incomplete Verification Engines
[chapter]
2018
Lecture Notes in Computer Science
We propose a framework for synthesizing inductive invariants for incomplete verification engines, which soundly reduce logical problems in undecidable theories to decidable theories. Our framework is based on the counter-example guided inductive synthesis principle (CEGIS) and allows verification engines to communicate non-provability information to guide invariant synthesis. We show precisely how the verification engine can compute such non-provability information and how to build effective
doi:10.1007/978-3-319-89960-2_13
fatcat:saysfl3slnbn3mktsvtqk7mnlm