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Enhancing Symbolic Execution of Heap-Based Programs with Separation Logic for Test Input Generation.

, , , , and . ATVA, volume 11781 of Lecture Notes in Computer Science, page 209-227. Springer, (2019)

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Concolic Testing Heap-Manipulating Programs., , , and . FM, volume 11800 of Lecture Notes in Computer Science, page 442-461. Springer, (2019)Learning Likely Invariants to Explain Why a Program Fails., , , , and . ICECCS, page 70-79. IEEE Computer Society, (2017)An Idealist's Approach for Smart Contract Correctness., , , and . ICFEM, volume 14308 of Lecture Notes in Computer Science, page 11-28. Springer, (2023)Enhancing Symbolic Execution of Heap-Based Programs with Separation Logic for Test Input Generation., , , , and . ATVA, volume 11781 of Lecture Notes in Computer Science, page 209-227. Springer, (2019)Towards an Effective and Interpretable Refinement Approach for DNN Verification., , , and . QRS, page 569-580. IEEE, (2023)Learning Likely Invariants to Explain Why a Program Fails., , , , and . CoRR, (2016)Verifying Neural Networks Against Backdoor Attacks., and . CAV (1), volume 13371 of Lecture Notes in Computer Science, page 171-192. Springer, (2022)SGUARD: Towards Fixing Vulnerable Smart Contracts Automatically., , and . SP, page 1215-1229. IEEE, (2021)Causality-Based Neural Network Repair., , , and . ICSE, page 338-349. ACM, (2022)Assertion generation through active learning., , and . ICSE (Companion Volume), page 155-157. IEEE Computer Society, (2017)