Program Representation

Program representation research focuses on transforming source code into machine-readable formats suitable for automated analysis and manipulation. Current efforts concentrate on developing sophisticated graph-based representations, often incorporating multiple views (e.g., control and data flow) and leveraging graph neural networks to capture complex program semantics and dependencies, improving upon simpler sequence or tree-based approaches. These advancements are crucial for improving various applications, including program analysis, performance optimization, and automated code generation, by enabling more effective machine learning models for tasks like bug detection and algorithm recognition.