Start by clarifying the billing rules and status definitions, then design a data model that captures events and account state. Process events chronologically per account, applying rules to update status and record transitions. Finally, discuss scalability and edge cases.
Pro tip: Mention that you would make the rules configurable (e.g., grace periods, thresholds) to accommodate business changes without code changes. Also, highlight the importance of idempotency and handling out-of-order events in a distributed system.
Ask questions to understand the exact status definitions, time windows, grace periods, and payment allocation rules. Confirm expected output format and any constraints.
Define schemas for events (type, amount, timestamp) and account state (current status, last transition). Consider using an event-sourcing approach for auditability.
For each account, sort events by timestamp and process sequentially. Apply business rules to update the account's balance and status, recording transitions.
Address scenarios like partial payments, refunds, adjustments, and out-of-order events. Discuss how to scale for many accounts (e.g., batch processing, streaming).
Produce final status per account and list of transitions. Suggest validation steps, such as unit tests for rule scenarios and reconciliation with expected outcomes.
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