Clarify the validation rules and data model first, then design a processor that maintains account balances in a hash map while iterating through transactions in timestamp order. For each transaction, validate sender/receiver existence, positive amount, and sufficient sender balance; apply valid transactions atomically and return final balances. Discuss edge cases like self-transfers, duplicate IDs, and concurrency.
Pro tip: Emphasize idempotency and atomicity: in a real payment system, you'd need to handle duplicate transaction IDs and ensure that a failed validation doesn't partially update balances. Mentioning this shows production awareness beyond the basic algorithm.
Ask about the exact validation rules, whether accounts can be created on the fly, how to handle duplicate transaction IDs, and if transactions are guaranteed to be in timestamp order. Confirm the expected output format (e.g., map of account to balance).
Use a hash map to store account balances for O(1) lookups and updates. Optionally, maintain a set of valid accounts or a separate map for account metadata. Consider a set to track processed transaction IDs for idempotency.
Iterate through transactions in order. For each, check: sender and receiver exist, amount > 0, sender balance >= amount, and transaction ID not already processed. If all pass, deduct from sender and add to receiver; otherwise, skip or log the error.
Address self-transfers (sender == receiver), zero or negative amounts, insufficient balance, unknown accounts, and duplicate IDs. Decide whether to fail silently, throw exceptions, or collect errors, and discuss trade-offs.
State time complexity O(n) for n transactions and space O(m) for m accounts. For system design, discuss how to scale with sharding, concurrency control (e.g., locks or optimistic concurrency), and persistence.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
This is where things got interesting and also where I made a mess.
First, clarify the requirements and constraints, especially around how the platform debt should be tracked and reported. Then, propose a data model that extends the existing account structure to include a borrow balance, and outline the transaction flow that updates both sender balance and borrow amount. Finally, discuss trade-offs such as consistency, concurrency, and reporting implications.
Pro tip: Emphasize idempotency and atomicity in the transaction processing to avoid double-counting debts, and consider how this change affects downstream systems like reconciliation and reporting.
Ask questions to understand the scope: Is the debt per transaction or cumulative? Should the platform charge interest? How should the debt be returned in the API response?
Extend the account model with a 'platform_borrow_balance' field. Consider whether to track individual borrow transactions or just an aggregate balance.
Outline the steps: validate transaction, deduct from sender balance (allowing negative), calculate shortfall, increment platform borrow balance, and record the transaction.
Discuss how to ensure atomic updates to balances and borrow amounts, possibly using database transactions or optimistic locking.
Modify the response to include the borrow balance per account. Consider how this affects existing reports and reconciliation processes.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.