My first instinct was to just nest two loops and call it done, which works but I spent way too long second-guessing whether they wanted something fancier.
Start by clarifying the requirements: what are the trigger types, how are rules defined, and what is the expected output format? Then design a data model and algorithm that efficiently evaluates all rules for each user on the given day, considering scalability and edge cases.
Pro tip: Discuss how you would handle time zones and daylight saving time, as these are common pitfalls in scheduling systems and demonstrate attention to real-world complexity.
Ask questions to understand the exact trigger types (e.g., days since creation, days until expiration, specific dates), the format of input data, and the expected output. Confirm assumptions about time zones, leap years, and whether notifications should be sent only once.
Define structures for user accounts (creation date, expiration date) and notification rules (trigger type, offset, template). Consider how to index or organize rules for efficient lookup.
For the given day, iterate through each user and evaluate each rule to determine if a notification should be triggered. Optimize by precomputing dates or using range queries if needed.
Address edge cases like users created or expiring on the given day, time zone conversions, and large datasets. Discuss potential optimizations like batch processing or caching.
Walk through examples, including boundary conditions, to verify correctness. Mention how you would test the solution, such as unit tests for each trigger type.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.