The actual logic wasn't that complicated once I found the content check function buried in a separate file.
Start by clarifying requirements and edge cases, then design a modular content moderation service that can be easily integrated into the add and edit review endpoints. Implement the bad-word check, violation tracking, and flagging logic, ensuring existing unit tests pass and adding new tests for the moderation features.
Pro tip: Emphasize idempotency and performance: cache bad words and use efficient string matching to avoid slowing down review operations. Also, consider how to handle false positives and provide a way to appeal or review flags.
Ask questions to understand the scope: what constitutes a violation, how many violations trigger a flag, and whether moderation should be synchronous or asynchronous. Confirm the expected behavior for edge cases like partial matches or case sensitivity.
Propose a modular service (e.g., ContentModerator) that encapsulates bad-word checking and violation tracking. Consider using a trie or regex for efficient matching and a data store for user violation counts.
Wire the moderation service into the add and edit review endpoints. Ensure that on violation, the review is rejected, the user's violation count is incremented, and if the threshold is exceeded, the user is flagged.
Run existing unit tests to ensure no regressions. Add new tests for moderation scenarios: bad words, violation counting, flagging, and edge cases like empty reviews or multiple violations.
Explain trade-offs: synchronous vs asynchronous moderation, performance impact, and how to scale the solution. Mention potential improvements like using a dedicated moderation service or machine learning.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.