Learning Semantic Program Embeddings with Graph Interval Neural Network

Understand

Learning distributed representations of source code has been a challenging task for machine learning models.

• Earlier works treated programs as text so that natural language methods can be readily applied.
• Unfortunately, such approaches do not capitalize on the rich structural information possessed by source code.
• Of late, Graph Neural Network (GNN) was proposed to learn embeddings of programs from their graph representations.