#Contributing to Rust Clippy: Fixing the useless_conversion Lint

#Introduction

January 2025 marked a significant milestone in my open source journey—my first merged PR into rust-lang/rust-clippy. This contribution tackled a subtle but impactful issue in the useless_conversion lint that was generating incorrect suggestions for nested references.

#The Problem

The useless_conversion lint is designed to catch unnecessary type conversions in Rust code. However, it had a blind spot when dealing with nested references. Consider this code:

let x: &&T = ...;
let y = x.into_iter();  // Clippy incorrectly suggested removing this

The lint would suggest removing the .into_iter() call, but this would actually change the semantics of the code. The issue stemmed from how the lint handled over-borrowed patterns—situations where you have multiple levels of references.

#The Solution

After diving deep into Clippy’s internals and the Rust type inference system, I discovered that the lint wasn’t accounting for automatic dereferencing that happens with .into_iter(). The fix involved:

1. Enhanced Reference Tracking: Modified the lint to properly track nested reference levels
2. Type Inference Integration: Better integration with Rust’s type inference to understand when conversions are actually needed
3. Test Coverage: Added comprehensive tests covering various nested reference scenarios

// The fix ensures these patterns are correctly handled
let nested: &&Vec<i32> = &&vec![1, 2, 3];
let iter = nested.into_iter();  // No false positive anymore

#Impact on the Rust Ecosystem

This might seem like a small fix, but it has broad implications:

• Fewer False Positives: Developers won’t see incorrect warnings that could lead to broken code
• Better Type Safety: The lint now respects Rust’s borrowing semantics more accurately
• Learning Opportunity: Understanding this required deep knowledge of Rust’s type system

#What I Learned

#Rust Compiler Internals

Contributing to Clippy forced me to understand:

• How the High-Level Intermediate Representation (HIR) works
• Type inference and unification algorithms
• The relationship between borrowing, dereferencing, and trait implementations

#Open Source Process

The rust-lang organization has an impressive review process:

• Detailed code reviews with constructive feedback
• Emphasis on test coverage and edge cases
• Documentation requirements for maintainability

#Looking Forward

This contribution has inspired me to continue diving deeper into Rust compiler internals. I’m particularly interested in:

• Type inference optimizations
• More sophisticated lint patterns
• Contributing to rustc itself

If you’re interested in contributing to Rust tooling, I highly recommend starting with Clippy. The team is welcoming, and you’ll learn an incredible amount about how Rust works under the hood.

#Resources

• My PR on GitHub
• Clippy Contributing Guide
• Rust Compiler Development Guide

Have you contributed to Rust tooling? What was your experience? Let me know in the comments below!