Start by clarifying the problem: single buy and sell, maximize profit, and handle edge cases like empty or decreasing prices. Then explain a one-pass solution that tracks the minimum price seen so far and computes the maximum profit at each step. Finally, analyze time and space complexity and discuss potential variations.
Pro tip: At Apple, interviewers value clean, efficient code and clear communication. Before coding, briefly discuss the brute-force approach and its O(n^2) complexity to show you understand the trade-offs, then optimize to O(n) with a single pass.
Confirm that only one transaction is allowed, and ask about input constraints (e.g., array size, price range). Discuss edge cases: empty array, single element, strictly decreasing prices (no profit).
Mention the brute-force O(n^2) solution of checking all pairs. Then introduce the optimal O(n) one-pass approach: iterate through prices, keep track of the minimum price seen so far, and update max profit.
Use a small example like [7,1,5,3,6,4] to demonstrate how the algorithm works step by step, showing how min price and max profit are updated.
Implement the solution in your preferred language, using clear variable names and handling edge cases. For example, initialize min_price to infinity and max_profit to 0.
State that time complexity is O(n) and space is O(1). Test with edge cases and maybe discuss follow-ups like multiple transactions or handling large inputs.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.