Learning C to x86 Translation: An Experiment in Neural Compilation

08/17/2021
by   Jordi Armengol-Estapé, et al.
0

Deep learning has had a significant impact on many fields. Recently, code-to-code neural models have been used in code translation, code refinement and decompilation. However, the question of whether these models can automate compilation has yet to be investigated. In this work, we explore neural compilation, building and evaluating Transformer models that learn how to produce x86 assembler from C code. Although preliminary results are relatively weak, we make our data, models and code publicly available to encourage further research in this area.

READ FULL TEXT

Please sign up or login with your details

Forgot password? Click here to reset