3 papers
cs.SE2026
Decaf: Improving Neural Decompilation with Automatic Feedback and Search
Alexander Shypula, Osbert Bastani, Edward Schwartz
Decompilers are useful tools used in reverse engineering to understand compiled source code. Reconstructing source code from compiled binaries is a challenging task, because high-l…
cs.SE2025
Idioms: Neural Decompilation With Joint Code and Type Definition Prediction
Luke Dramko, Claire Le Goues, Edward J. Schwartz
Decompilers are important tools for reverse engineers that help them analyze software at a higher level of abstraction than assembly code. Unfortunately, because compilation is los…
cs.LG2025
Fast, Fine-Grained Equivalence Checking for Neural Decompilers
Luke Dramko, Claire Le Goues, Edward J. Schwartz
Neural decompilers are machine learning models that reconstruct the source code from an executable program. Critical to the lifecycle of any machine learning model is an evaluation…