Identify code paths that execute frequently (loops, hot functions, repeated calls) and optimize them by avoiding redundant computations, expensive operations, and unnecessary allocations. Key optimization strategies: - **Reorder conditions** for short-circuiting: Place cheaper or more likely-to-fail conditions first - **Cache expensive computations**: Store results of function calls that are used multiple times - **Choose efficient APIs**: Prefer operations like `fs::rename()` over `fs::copy() + fs::remove_file()` - **Avoid repeated allocations**: Use `Vec::push()` and `join()` instead of repeated `format!()` calls - **Reuse objects**: Don't recreate expensive objects like `Regex` instances in loops Example of avoiding redundant calls: ```rust // Before: calling node.is_named() twice fn caller() { if node.is_named() { render_node_range(cursor, node.is_named()); // redundant call } } // After: cache the result fn caller() { let is_named = node.is_named(); if is_named { render_node_range(cursor, is_named); } } ``` Focus especially on optimizing code that processes large datasets, handles user input, or runs in tight loops where small inefficiencies compound into significant performance impacts.