Feels straightforward until you realize fees and multi-account updates mean you can't just do a simple running total per account.
Clarify the transaction format and constraints, then propose a hash map to track account balances, updating each account as transactions are processed. After processing, iterate through the map to collect accounts with non-zero balances, discussing time and space complexity.
Pro tip: Mention that you would use a hash map for O(1) average-time updates and that you'd only keep non-zero balances to save memory, showing awareness of real-world efficiency.
Ask about the transaction format, account identifier type, fee handling, and whether balances can be negative. Confirm if the stream is bounded or infinite.
Select a hash map (dictionary) to map account IDs to balances, enabling O(1) average-time updates. Consider if a balanced tree is needed for ordered output.
Iterate through each transaction: apply the fee (if any) and update the balances of all involved accounts. Remove accounts from the map if their balance becomes zero to optimize memory.
After processing all transactions, iterate through the map and return all accounts with a non-zero balance. If the map only contains non-zero balances, simply return its keys.
State the time complexity O(T + A) where T is number of transactions and A is number of accounts, and space O(A). Discuss edge cases like zero balances, negative balances, and duplicate accounts.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.