Chain of Understanding: Supporting Code Understanding with Large Language Models

Abstract: Code auditing demands a robust understanding of codebases - an especially challenging task for end-user developers with limited expertise. To address this, we conducted formative interviews with experienced auditors and identified a Chain-of-Understanding approach, in which LLMs guide developers through hierarchical code comprehension - from high-level overviews to specific functions and variables. Building on this, we incorporated the Chain-of-Understanding concept into CodeMap, a system offering interactive visualizations, stepwise guided analysis, and context-aware chatbot support. Through within-subject user studies with 10 participants of diverse backgrounds and 5 expert and 2 novice interviews, CodeMap proved effective in reducing the manual effort of prompt engineering while enhancing engagement with visualization, outperforming both standalone LLMs and traditional static visualization tools.