Skip to yearly menu bar Skip to main content

Workshop: Advances in Programming Languages and Neurosymbolic Systems (AIPLANS)

Learning C to x86 Translation: An Experiment in Neural Compilation

Jordi Armengol-EstapĂ© · Michael O'Boyle


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.