InCoder: A Generative Model for Code Infilling and Synthesis

Understand

Code is seldom written in a single left-to-right pass and is instead repeatedly edited and refined.

• We introduce InCoder, a unified generative model that can perform program synthesis (via left-to-right generation) as well as editing (via infilling).
• InCoder is trained to generate code files from a large corpus of permissively licensed code, where regions of code have been randomly masked and moved to the end of each file, allowing code infilling with bidirectional context.
• Our model is the first generative model that is able to directly perform zero-shot code infilling, which we evaluate on challenging tasks such as type inference, comment generation, and variable re-naming.