First, clarify the operation types and how value is computed for each checkout (e.g., based on current book value at checkout time). Then design a data structure to track book values and process operations in order, accumulating checkout values into a result list.
Pro tip: Discuss how you would handle edge cases like checking out a book that hasn't been acquired or reclassifying a non-existent book, and mention that you'd confirm these with the interviewer to avoid assumptions.
Ask about the exact format of operations, how book value is determined (e.g., acquisition cost, reclassification updates), and what to do with invalid operations.
Use a hash map to store the current value of each book by its ID, and a list to collect checkout values in order.
Iterate through the operations, updating the book value on acquisition or reclassification, and for checkout, retrieve the current value and append it to the result list.
Decide on behavior for missing books or invalid operations (e.g., skip, error, or default value) and ensure the solution handles them gracefully.
State the time and space complexity (O(n) time, O(m) space where m is number of unique books) and walk through a small example to verify correctness.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.