Clarify requirements first, then choose a data structure that balances O(1) title lookup with efficient positional moves, such as a doubly linked list plus a hash map. Implement the class with clean APIs, handle edge cases, and write tests covering normal operations, boundary conditions, and error cases.
Pro tip: Explicitly discuss the trade-offs between using an array (O(n) moves) and a linked list (O(1) moves but O(n) lookup) to show you understand performance implications, and mention that in a real system you might use a balanced tree or order-statistic tree for O(log n) operations.
Ask about expected input sizes, whether positions are 0-indexed or 1-indexed, and what should happen when removing or moving a non-existent book. Confirm that titles are unique and that moving a book to its current position is a no-op.
Select a combination like a hash map for O(1) title-to-node lookup and a doubly linked list for O(1) insertion, removal, and repositioning. Explain why this beats a simple array or a single list.
Write methods addBook(title), removeBook(title), and moveBook(title, newPosition). Handle edge cases such as empty shelf, invalid position, and duplicate titles. Ensure moveBook correctly updates links.
Create at least three tests: one for adding and removing books, one for moving a book to the front/back/middle, and one for error conditions like removing a non-existent book or moving to an invalid position.
State time and space complexity for each operation. Mention potential optimizations like using an order-statistic tree for O(log n) moves if positions are frequent, or a skip list for simpler implementation.
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