You are given a list of financial transactions in CSV-like rows: ``` account_name, timestamp, currency, amount ``` - `account_name` is a string ID. - `timestamp` is an integer (not guaranteed to be sorted). - `currency` is a string like `"usd"`. - `amount` is an integer (positive = credit, negative = debit). Assume all arithmetic is integer. Unless otherwise stated, process transactions in increasing `timestamp` order (stable tie-breaker by input order). ## Part 1 — Final non-zero balances Compute each account’s final balance (you may assume all rows are the same currency, or treat balances independently per `(account_name, currency)`—state your assumption). Output all accounts with **non-zero** final balance. **Example** Input: ``` account_name, timestamp, currency, amount acct_123,1,usd,1000 acct_123,2,usd,500 acct_321,3,usd,400 acct_321,4,usd,-400 ``` Output: - `acct_123` has balance `1500` - `acct_321` is omitted (balance `0`) ## Part 2 — Reject debits that would overdraw Process transactions in time order while maintaining balances. A transaction is **rejected** if applying it would make the account’s balance negative (i.e., `balance + amount < 0`). Rejected transactions: - must be appended to `rejected_transactions` in the order encountered, - must **not** affect any balances. At the end, output: 1) `rejected_transactions` (full original rows for rejected ones), and 2) all accounts with **non-zero** final balance. **Example** Input: ``` account_name, timestamp, currency, amount acct_123,1,usd,1000 acct_123,2,usd,500 acct_321,3,usd,400 acct_321,4,usd,-500 ``` Output: - Non-zero balances: `acct_123 = 1500`, `acct_321 = 400` - `rejected_transactions = ["acct_321,4,usd,-500"]` ## Part 3(a) — Platform reserve can cover negatives You are also given a special `platform_id` account. Process transactions in time order with the following rule: - For any **non-platform** account, if applying a transaction would make its balance negative, the account may **borrow from the platform** just enough to bring its balance back to `0`. - This borrowing reduces the platform’s balance accordingly. - Track the platform’s **outstanding loans** (e.g., per account) so that when an account later receives credits, it repays its debt before increasing its own positive balance (state and apply a consistent repayment rule). - If the platform does not have enough available balance to cover the needed borrowing at that moment, then the transaction is **rejected** (and does not change balances or debts). Output three things: 1) `max_reserve`: the **maximum total outstanding amount borrowed from the platform at any time** (peak platform exposure), 2) `rejected_transactions`, 3) all accounts with **non-zero** final balance (including the platform if non-zero). **Example** (`platform_id = acct_123`) Input: ``` account_name, timestamp, currency, amount acct_123,1,usd,1000 acct_321,3,usd,400 acct_321,4,usd,-500 ``` Explanation: `acct_321` would go to `-100`, so it borrows `100` from the platform to return to `0`. Output: - `max_reserve = 100` - `rejected_transactions = []` - Non-zero balances include `acct_123 = 900` (and `acct_321` omitted if it ends at `0`) ### Constraints (you may assume) - Up to ~200k transactions. - Need an efficient solution (typically `O(n log n)` due to sorting, or `O(n)` if already sorted).