Start by clarifying requirements and defining a clean interface for the logger with pluggable transformation behaviors. Then design the data structures and algorithms for efficient storage and search, discussing trade-offs between simplicity and performance. Finally, walk through an implementation sketch, covering edge cases and extensibility.
Pro tip: Emphasize the Strategy pattern for transformations and the importance of immutability and thread-safety in a logging system. Also, discuss how you would test each transformation and the search functionality.
Ask questions to understand expected message volume, concurrency needs, search complexity, and whether transformations are applied at log time or query time. Clarify if transformations are composable and configurable at runtime.
Define a Logger interface with methods like log(message) and search(query). Use the Strategy pattern for transformations, allowing them to be composed in a pipeline. Consider a builder or configuration object to specify which transformations to apply.
For in-memory storage, consider a list for simplicity or a more advanced structure like an inverted index for efficient substring search. Discuss trade-offs: list with linear scan vs. trie or suffix tree for faster search at the cost of memory and complexity.
Implement each transformation as a class with a transform method. For search, implement a method that iterates over stored messages (or uses an index) and returns matches. Ensure transformations are applied before storage if they are log-time, or during search if query-time.
Talk about performance vs. simplicity, thread-safety (e.g., using concurrent collections or locks), and how to add new transformations without modifying existing code. Outline a testing strategy for transformations and search.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Start by clarifying requirements and edge cases, then outline a modular design: parse input, evaluate hand category, sort hands, and compute weighted score. Emphasize extensibility for wildcard mode and discuss trade-offs between simplicity and performance.
Pro tip: Demonstrate foresight by discussing how to handle the wildcard mode without duplicating logic—e.g., parameterize the hand evaluation to treat J as wild. Also, mention that sorting stability matters when hands have equal ranks.
Ask about input format, hand size, card ranks/suits, and tiebreaking rules. Confirm wildcard behavior: J acts as best rank for category but lowest for tiebreaking.
Define a Hand class with cards, bid, and computed rank. Parse input into hands, validating format and handling errors.
Write a function to categorize a hand (e.g., five-of-a-kind, straight flush, etc.). For wildcard mode, treat J as wild and compute the best possible category.
Sort hands by category and tiebreakers (with J as lowest in wildcard mode). Compute weighted score by multiplying bid with rank position.
Write unit tests for edge cases (e.g., all wilds, multiple wilds). Discuss time complexity and potential optimizations.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.