I started with the data model and that turned out to be the right call.
Start by clarifying requirements and defining the transaction and fee rule models, then design a rule engine that resolves precedence and applies fee types. Emphasize extensibility through composition and configuration, and discuss trade-offs between flexibility and performance.
Pro tip: Show how you would test the rule engine with edge cases like overlapping rules and currency rounding, and mention how you'd version the rule schedule to avoid breaking changes.
Ask about supported transaction types, currencies, fee types, and expected scale. Confirm whether rules are static or dynamic, and if real-time calculation is needed.
Model Transaction with amount, type, currency, and attributes. Model FeeRule with conditions (type, currency, amount range), fee components (flat, percentage, tiered), and constraints (min, max).
Define a precedence order: specific overrides (per-type, per-currency) over general rules, and more specific conditions over less specific. Use a scoring system or ordered list to resolve conflicts.
Apply resolved rules to compute fees, handling tiered calculations, caps, and minimums. Ensure correct rounding and currency handling.
Use strategy pattern for fee types, configuration-driven rules, and versioning. Allow new fee types by adding new strategies without modifying core logic.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.