Code Graph

Code graphs represent software code as interconnected nodes and edges, enabling machine learning models to analyze code structure and semantics more effectively than traditional sequential methods. Current research focuses on automatically generating these graphs from various code representations (e.g., abstract syntax trees, control flow), leveraging graph neural networks and graph representation learning to analyze their structural properties for tasks like bug prediction, code optimization, and improved interaction with large language models. This approach offers significant potential for advancing software engineering practices, improving code understanding, and automating complex software development tasks.