Start by clarifying the requirements: what kind of data store (in-memory, database, etc.), what operations are needed (add, remove), and any constraints (e.g., duplicates, ordering). Then design a simple, efficient solution using appropriate data structures, and implement the functions with clean, testable code. Discuss trade-offs and potential optimizations.
Pro tip: Demonstrate awareness of real-world concerns like concurrency, error handling, and scalability, even if not explicitly asked. Mentioning these shows maturity and can set you apart.
Ask questions to understand the data store type, expected operations, constraints (e.g., uniqueness, ordering), and performance needs. This ensures you solve the right problem.
Select appropriate data structures (e.g., hash map for O(1) add/remove, linked list for ordering) based on requirements. Explain your choice and trade-offs.
Define function signatures, return types, and error handling (e.g., what happens when removing a non-existent record). Consider edge cases.
Write clean, efficient code for add and remove. Include comments and handle edge cases. If time permits, discuss optimizations.
Walk through test cases (normal, edge, error) and discuss potential improvements, scalability, and concurrency if relevant.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.