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Self-correcting Neural Networks for Safe Classification.

, , , , , and . NSV/FoMLAS@CAV, volume 13466 of Lecture Notes in Computer Science, page 96-130. Springer, (2022)

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Symbolic Execution and Software Testing.. Engineering Dependable Software Systems, volume 34 of NATO Science for Peace and Security Series, D: Information and Communication Security, IOS Press, (2013)Property Inference for Deep Neural Networks., , , and . ASE, page 797-809. IEEE, (2019)Learning Techniques for Software Verification and Validation., and . ISoLA (1), volume 7609 of Lecture Notes in Computer Science, page 505-507. Springer, (2012)Finding Feasible Counter-examples when Model Checking Abstracted Java Programs., , and . TACAS, volume 2031 of Lecture Notes in Computer Science, page 284-298. Springer, (2001)Automated Circular Assume-Guarantee Reasoning with N-way Decomposition and Alphabet Refinement., , , and . CAV (1), volume 9779 of Lecture Notes in Computer Science, page 329-351. Springer, (2016)Verification of Java Programs Using Symbolic Execution and Invariant Generation., and . SPIN, volume 2989 of Lecture Notes in Computer Science, page 164-181. Springer, (2004)Test input generation for red-black trees using abstraction., , and . ASE, page 414-417. ACM, (2005)Symbolic Complexity Analysis Using Context-Preserving Histories., , and . ICST, page 58-68. IEEE Computer Society, (2017)Symbolic execution with mixed concrete-symbolic solving., , and . ISSTA, page 34-44. ACM, (2011)Learning Assumptions for Verifying Cryptographic Protocols Compositionally., , , and . FACS, volume 13077 of Lecture Notes in Computer Science, page 3-23. Springer, (2021)