CodeFuse-Query: A Data-Centric Static Code Analysis System for Large-Scale Organizations

• DOI: 10.48550/arxiv.2401.01571
• Publication Date: 2024-01-01
• Authors: Xiaoheng Xie; Gang Fan; Xiaojun Lin; Ang Zhou; Shijie Li; Xunjin Zheng; Yinan Liang; Yu Zhang; Na Yu; Haokun Li; Xinyu Chen; Yingzhuang Chen; Yi Zhen; Dejun Dong; Xianjin Fu; Jinzhou Su; Fuxiong Pan; Pengshuai Luo; Youzheng Feng; Ruoxiang Hu; Jing Fan; Jinguo Zhou; Xiao Xiao; Peng Di
• Keywords: Datalog

In the domain of large-scale software development, demands for dynamic and multifaceted static code analysis exceed capabilities traditional tools. To bridge this gap, we present CodeFuse-Query, a system that redefines through fusion Domain Optimized System Design Logic Oriented Computation Design. CodeFuse-Query reimagines as data computation task, support scanning over 10 billion lines daily more than 300 different tasks. It optimizes resource utilization, prioritizes reusability, applies incremental extraction, introduces tasks types specially Code Change, underscoring its domain-optimized design. The system's logic-oriented facet employs Datalog, utilizing unique two-tiered schema, COREF, to convert source into facts. Through Godel, distinctive language, enables formulation complex logical expressions, harnessing Datalog's declarative prowess. This paper provides empirical evidence CodeFuse-Query's transformative approach, demonstrating robustness, scalability, efficiency. We also highlight real-world impact diverse applications, emphasizing potential reshape landscape in context development.Furthermore, spirit collaboration advancing field, our project is open-sourced repository available public access