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Automated Environment Generation for Software Model Checking.

, , and . ASE, page 116-129. IEEE Computer Society, (2003)

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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)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)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)DifFuzz: differential fuzzing for side-channel analysis., , and . ICSE, page 176-187. IEEE / ACM, (2019)On reliability of patch correctness assessment., , , , , and . ICSE, page 524-535. IEEE / ACM, (2019)NEUROSPF: A Tool for the Symbolic Analysis of Neural Networks., , , , and . ICSE (Companion Volume), page 25-28. IEEE, (2021)Rule-Based Testing of Neural Networks., , , and . SE4SafeML@SIGSOFT FSE, page 1-5. ACM, (2023)