How Important are Good Method Names in Neural Code Generation? A Model Robustness Perspective

Understand

Pre-trained code generation models (PCGMs) have been widely applied in neural code generation which can generate executable code from functional descriptions in natural languages, possibly together with signatures.

• Despite substantial performance improvement of PCGMs, the role of method names in neural code generation has not been thoroughly investigated.
• In this paper, we study and demonstrate the potential of benefiting from method names to enhance the performance of PCGMs, from a model robustness perspective.
• Specifically, we propose a novel approach, named RADAR (neuRAl coDe generAtor Robustifier).