{"id":155826,"date":"2008-01-01T00:00:00","date_gmt":"2008-01-01T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/using-dynamic-symbolic-execution-to-improve-deductive-verification\/"},"modified":"2018-10-16T20:08:02","modified_gmt":"2018-10-17T03:08:02","slug":"using-dynamic-symbolic-execution-to-improve-deductive-verification","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/using-dynamic-symbolic-execution-to-improve-deductive-verification\/","title":{"rendered":"Using Dynamic Symbolic Execution to Improve Deductive Verification"},"content":{"rendered":"<div class=\"asset-content\">\n<p>One of the most challenging problems in deductive program verification is to find inductive program invariants typically expressed using quantifiers. With strong-enough invariants, existing provers can often prove that a program satisfies its specification. However, provers by themselves do not find such invariants. We propose to automatically generate executable test cases from failed proof attempts using dynamic symbolic execution by exploring program code as well as contracts with quantifiers. A developer can analyze the test cases with a traditional debugger to determine the cause of the error; the developer may then correct the program or the contracts and repeat the process.<\/p>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>One of the most challenging problems in deductive program verification is to find inductive program invariants typically expressed using quantifiers. With strong-enough invariants, existing provers can often prove that a program satisfies its specification. However, provers by themselves do not find such invariants. 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