Choose efficient algorithms and appropriate data structures based on access patterns and computational requirements. Use built-in comparison methods like `cmp()` to avoid redundant checks, select data structures that match usage patterns (HashSet for lookups, Vec for iteration), and ensure algorithmic correctness by handling edge cases properly. Key practices: - Use `match` with `cmp()` for version/ordering comparisons instead of multiple if-else conditions - Choose HashSet over Vec when doing frequent containment checks: "Since we're just doing contains lookups, a hashset would be better, no?" - Ensure total ordering in comparison functions - consider topological sorting when dependencies exist: "You'll most likely have to do a topological sort, if the intention is to arrange the nodes in their dep order" - Handle edge cases in tree traversal algorithms, especially with zero-width nodes or empty ranges - Avoid brittle algorithmic assumptions like "the name field is always within the first three lines" - Implement iterator protocols correctly, ensuring `size_hint()` returns remaining elements count Example of efficient comparison: ```rust // Instead of multiple if-else conditions match new_version.cmp(¤t_version) { Ordering::Less => eprintln!("Warning: new version is lower than current!"), Ordering::Greater => println!("Bumping version {current_version} to {new_version}"), Ordering::Equal => println!("Keeping version {current_version}"), } ```