US Patent 11836467 Code generation with reinforcement learning

A code generation system uses a non-terminal expansion model and a non-terminal selector model to generate a code sketch to complete a partially-formed source code snippet. The non-terminal expansion model is a neural transformer model trained on a supervised dataset through reinforcement learning to learn to predict the production rule to expand for a given non-terminal symbol. The non-terminal selector model is trained through reinforcement learning to predict the non-terminal symbol to expand given a partial-code state. The models are used in a two-step beam search to generate the top candidate code sketches, where a candidate code sketch may contain a hole that represents an unexpanded non-terminal symbol.