The logic itself isn't that bad once you map it out.
Start by clarifying requirements and constraints, then outline a modular design with a priority queue for letter coverage and a rate limiter. Discuss trade-offs between strict letter-first and random fallback, and how AI tools can accelerate implementation while ensuring correctness.
Pro tip: Mention that you would use AI tools to generate boilerplate and tests, but manually verify the priority logic and rate limiting to avoid subtle bugs. Also, discuss how to handle edge cases like pages with non-alphabetic titles.
Ask about rate limit specifics (e.g., requests per second), definition of 'title starts with a letter' (case sensitivity, non-ASCII), and whether the crawler should avoid revisiting pages.
Use a set to track visited letters and a priority queue or separate queues for each letter to prioritize unvisited letters. Maintain a visited set for URLs to avoid duplicates.
Use a token bucket or leaky bucket algorithm to enforce the rate limit, ensuring requests are spaced appropriately. Consider using a library or simple sleep-based approach.
While unvisited letters exist, prioritize fetching pages whose titles start with those letters. Once all letters are visited, switch to random crawling from a frontier of discovered links.
Use AI to generate initial code, unit tests, and documentation, but review and refine the priority logic and rate limiter manually to ensure correctness and efficiency.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.