The greedy part clicked pretty fast: sort by price ascending, buy cheap orders first.
Clarify that orders are processed in the given order (or sorted by price if not), then iterate through each order, consuming as much quantity as the remaining budget allows. For each order, compute the maximum affordable quantity, subtract the cost from the budget, and accumulate the total XRP purchased. Stop when the budget is exhausted or all orders are processed.
Pro tip: Mention that in real trading systems, orders are typically sorted by price (best price first) to optimize the fill, but if the list is already in execution order, you must respect that. Also, discuss how to handle floating-point precision issues by using integer arithmetic (e.g., cents) or a tolerance.
Confirm whether the list is sorted by price or execution order, and whether partial fills are allowed only on the last order or on any order. Also, clarify if the budget must be fully used or if leftover is acceptable.
Decide if sorting is needed (e.g., by price ascending for best deal). Use a simple loop with O(n) time and O(1) space, or O(n log n) if sorting.
For each order, calculate the maximum quantity you can buy: min(order.quantity, remaining_budget / order.price). Update remaining budget and total XRP. If budget is insufficient for any quantity, break.
Consider zero budget, zero quantity orders, prices that don't divide evenly, and floating-point rounding. Use integer cents or a small epsilon for comparisons.
Walk through a small example, including a partial fill on the last order, and verify the total XRP and remaining budget. Discuss time and space complexity.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.