Abstract Syntax Tree

Abstract Syntax Trees (ASTs) are tree-like representations of source code that capture its grammatical structure, serving as a crucial tool for various code-related tasks. Current research focuses on leveraging ASTs within deep learning models, particularly transformer networks and graph neural networks, to improve code generation, analysis (including vulnerability detection and code summarization), and program understanding. This work is significant because effective AST-based methods enhance the accuracy and efficiency of automated software engineering tools, leading to improved code quality, faster development cycles, and more reliable software.