Principles and Practices of Large-Scale Code Analysis at Ant Group: A Data- and Logic-Oriented Approach

Large-scale software development requires dynamic and multifaceted static code analysis that extend beyond the capabilities of traditional tools. Existing tools like CodeQL lack cross-language analysis capability and are time-consuming and resource-intensive. We present CodeFuse-Query, a data system tailored for large-scale code analysis. First, CodeFuse-Query adopts a Logic Oriented Computation Design, employing Datalog with a two-tiered schema(COREF) to convert source code into data facts, and Gödel to express complex analysis tasks in logical terms. Furthermore, CodeFuse-Query adopts Domain Optimized System Design. This approach optimizes resource utilization, prioritizes data reusability, applies incremental code extraction, and introduces tasks type characteristics specially for Code Change, underscoring its domain-optimized design.