Reviews: Write, Execute, Assess: Program Synthesis with a REPL

Neural Information Processing Systems 

This paper provides a method for Deep RL-based program synthesis, which exploits a SMC sampler during inference progressively decode into an executable program. The reviewers were enthusiastic about this method and found the experimental support for the proposal convincing. Without much need for further comment, I find the paper of acceptable standard for the conference. The authors are encouraged to take note of the suggestions made by the reviewers, especially R2 and R3, when improving the paper for eventual publication.