Beyond k-Limiting: Pointer-Flow-Guided Context Sensitivity for Scalable and Precise Rust Pointer Analysis

Abstract

Pointer analysis for Rust faces unique challenges arising from its ownership-based memory model and layered abstractions, which complicate how heap-allocated objects flow across functions. Existing k-limited callsite abstractions - designed for earlier languages - are both imprecise and inefficient on large Rust programs. We present Rceus, a Rust-oriented pointer-analysis technique that mitigates points-to set explosion and resource exhaustion caused by cross-function pointer conflation under deep heap encapsulation, a scalability bottleneck that conventional k-limiting cannot address. Rceus performs a fast, coarse-grained pointer-flow pre-analysis to identify precision-critical functions and the essential callsites within their calling contexts. This selective context construction distinguishes parameter-derived flows while avoiding unnecessary expansion. As a result, Rceus cleanly partitions intertwined pointer flows, eliminating context explosion and improving both scalability and precision. On 16 real-world Rust applications, Rceus outperforms state-of-the-art techniques - standard k-limiting, selective k-limiting for Java, and stack-filtered k-limiting for Rust - in both precision and efficiency. The evaluation includes Wasmtime, a WebAssembly runtime with 669K lines of code, where the benefits increase with program size. Rceus also composes with existing techniques, providing a practical and extensible foundation for scalable, precise Rust pointer analysis.