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Q: Exploit Hardening Made Easy., , and . USENIX Security Symposium, USENIX Association, (2011)Can Knowledge of Technical Debt Help Identify Software Vulnerabilities?, , , , and . CSET @ USENIX Security Symposium, USENIX Association, (2016)Augmenting Decompiler Output with Learned Variable Names and Types., , , , , and . CoRR, (2021)Native x86 Decompilation Using Semantics-Preserving Structural Analysis and Iterative Control-Flow Structuring., , , and . USENIX Security Symposium, page 353-368. USENIX Association, (2013)How to model a TCP/IP network using only 20 parameters., , and . WSC, page 849-860. IEEE, (2010)VarCLR: Variable Semantic Representation Pre-training via Contrastive Learning., , , , , and . ICSE, page 2327-2339. ACM, (2022)Statistical Machine Translation Is a Natural Fit for Automatic Identifier Renaming in Software Source Code., , , , and . AAAI Workshops, volume WS-18 of AAAI Technical Report, page 771-774. AAAI Press, (2018)Meaningful variable names for decompiled code: a machine translation approach., , , , and . ICPC, page 20-30. ACM, (2018)Automatic exploit generation., , , , , and . Commun. ACM, 57 (2): 74-84 (2014)The Danger of Unrandomized Code.. login Usenix Mag., (2011)