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“A Taxonomy of C Decompiler Fidelity Issues”
by Luke Dramko, Jeremy Lacomis, Edward J. Schwartz, Bogdan Vasilescu, and Claire Le Goues.
In Proceedings of the USENIX Security Symposium, 2024.
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“DIRE and its Data: Neural Decompiled Variable Renamings with Respect to Software Class”
by Luke Dramko, Jeremy Lacomis, Pengching Yin, Edward J. Schwartz, Miltiadis Allamanis, Graham Neubig, Bogdan Vasilescu, and Claire Le Goues.
{ACM} Transactions on Software Engineering and Methodology, vol. 32, no. 2, 2022.
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“VarCLR: Variable Semantic Representation Pre-training via Contrastive Learning”
by Qibin Chen, Jeremy Lacomis, Edward J. Schwartz, Graham Neubig, Bogdan Vasilescu, and Claire Le Goues.
In Proceedings of the International Conference on Software Engineering, 2022.
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“Augmenting Decompiler Output with Learned Variable Names and Types”
by Qibin Chen, Jeremy Lacomis, Edward J. Schwartz, Claire Le Goues, Graham Neubig, and Bogdan Vasilescu.
In Proceedings of the USENIX Security Symposium, 2022.
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“A Generic Technique for Automatically Finding Defense-Aware Code Reuse Attacks”
by Edward J. Schwartz, Stephanie M. Schwartz, Cory F. Cohen, and Jeffrey S. Gennari.
In Proceedings of the ACM Conference on Computer and Communications Security, 2020.
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“DIRE: A Neural Approach to Decompiled Identifier Naming”
by Jeremy Lacomis, Pengcheng Yin, Edward J. Schwartz, Miltiadis Allamanis, Claire Le Goues, Graham Neubig, and Bogdan Vasilescu.
In Proceedings of the IEEE/ACM International Conference on Automated Software Engineering, 2019.
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“Using Logic Programming to Recover C++ Classes and Methods from Compiled Executables”
by Edward J. Schwartz, Cory F. Cohen, Michael Duggan, Jeffrey Gennari, Jeffrey S. Havrilla, and Charles Hines.
In Proceedings of the ACM Conference on Computer and Communications Security, 2018.
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“Meaningful Variable Names for Decompiled Code: A Machine Translation Approach”
by Alan Jaffe, Jeremy Lacomis, Edward J. Schwartz, Claire Le Goues, and Bogdan Vasilescu.
In Proceedings of the IEEE/ACM International Conference on Program Comprehension, 2018.
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“Executable Counterexamples in Software Model Checking”
by Jeffrey Gennari, Arie Gurfinkel, Temesghen Kahsai, Jorge A. Navas, and Edward J. Schwartz.
In Proceedings of the Working Conference on Verified Software: Theories, Tools, and Experiments, 2018.
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“Can Knowledge of Technical Debt Help Identify Software Vulnerabilities?”
by Robert L. Nord, Ipek Ozkaya, Edward J. Schwartz, Forrest Shull, and Rick Kazman.
In Proceedings of the USENIX Workshop on Cyber Security Experimentation and Test, 2016.
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“Abstraction Recovery for Scalable Static Binary Analysis”
by Edward J. Schwartz.
Ph.D. dissertation, Carnegie Mellon University, 2014.
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“Automatic Exploit Generation”
by Thanassis Avgerinos, Sang Kil Cha, Alexandre Rebert, Edward J. Schwartz, Maverick Woo, and David Brumley.
Communications of the Association for Computing Machinery, vol. 57, no. 2, Feb. 2014, pp. 74-84.
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“Native x86 Decompilation using Semantics-Preserving Structural Analysis and Iterative Control-Flow Structuring”
by Edward J. Schwartz, JongHyup Lee, Maverick Woo, and David Brumley.
In Proceedings of the USENIX Security Symposium, 2013.
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“Q: Exploit Hardening Made Easy”
by Edward J. Schwartz, Thanassis Avgerinos, and David Brumley.
In Proceedings of the USENIX Security Symposium, 2011.
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“BAP: A Binary Analysis Platform”
by David Brumley, Ivan Jager, Thanassis Avgerinos, and Edward J. Schwartz.
In Proceedings of the Conference on Computer Aided Verification, 2011.
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“All You Ever Wanted to Know About Dynamic Taint Analysis and Forward Symbolic Execution (but might have been afraid to ask)”
by Edward J. Schwartz, Thanassis Avgerinos, and David Brumley.
In Proceedings of the IEEE Symposium on Security and Privacy, 2010.
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“A Contractual Anonymity System”
by Edward J. Schwartz, David Brumley, and Jonathan M. McCune.
In Proceedings of the Network and Distributed System Security Symposium, 2010.
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