An Empirical Study of Bugs in the rustc Compiler

Rust is gaining popularity for its well-known memory safety guarantees and high performance, distinguishing it from C/C++ and JVM-based languages. Its compiler, rustc, enforces these guarantees through specialized mechanisms such as trait solving, borrow checking, and specific optimizations. However, Rust's unique language mechanisms introduce complexity to its compiler, resulting in bugs that are uncommon in traditional compilers. With Rust's increasing adoption in safety-critical domains, understanding these language mechanisms and their impact on compiler bugs is essential for improving the reliability of both rustc and Rust programs. Such understanding could provide the foundation for developing more effective testing strategies tailored to rustc. Improving the quality of rustc testing is essential for enhancing compiler reliability, which in turn strengthens the safety and correctness of all Rust programs, as compiler bugs can silently propagate into every compiled program. Yet, we still lack a large-scale, detailed, and in-depth study of rustc bugs. To bridge this gap, this work presents a comprehensive and systematic study of rustc bugs, specifically those originating in semantic analysis and intermediate representation (IR) processing, which are stages that implement essential Rust language features such as ownership and lifetimes. Our analysis examines issues and fixes reported between 2022 and 2024, with a manual review of 301 valid issues. We categorize these bugs based on their causes, symptoms, affected compilation stages, and test case characteristics. Additionally, we evaluate existing rustc testing tools to assess their effectiveness and limitations. Our key findings include: (1) rustc bugs primarily arise from Rust's type system and lifetime model, with frequent errors in the High-Level Intermediate Representation (HIR) and Mid-Level Intermediate Representation (MIR) modules due to complex checkers and optimizations; (2) bug-revealing test cases often involve unstable features, advanced trait usages, lifetime annotations, standard APIs, and specific optimization levels; (3) while both valid and invalid programs can trigger bugs, existing testing tools struggle to detect non-crash errors, underscoring the need for further advancements in rustc testing.