I started by trying to write separate logic for all four directions and immediately saw how messy that gets.
Clarify the rules and constraints, then design a solution that processes each row/column independently by extracting non-zero tiles, merging adjacent equal tiles once, and padding with zeros. Implement a generic slide-and-merge function and apply it to rows or columns based on direction, using rotation or reversal to handle all four directions uniformly.
Pro tip: Emphasize that each tile can merge only once per move (e.g., [2,2,2,2] becomes [4,4] not [8]), and discuss trade-offs between in-place modification and creating a new board, considering time/space complexity and potential follow-up questions about optimization.
Ask about board size, input format, whether the method should return a new board or modify in-place, and confirm merge rules (e.g., no double merges).
Decide whether to implement separate logic for each direction or use a generic approach with rotation/reversal to reduce code duplication.
Write a helper function that takes a list of tiles, removes zeros, merges adjacent equal values once, and pads with zeros to the original length.
For left/right, process each row; for up/down, process each column. Use rotation or reversal to reuse the same helper.
Walk through examples, including edge cases like all zeros or multiple merges, and state time/space complexity (O(n^2) time, O(n) extra space per line).
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
They asked this near the end and I kind of fumbled it.
First, clarify the game rules and the definition of a legal move. Then, propose an efficient check that avoids simulating all four full moves by using early termination and incremental state updates, such as tracking empty cells or precomputing move validity.
Pro tip: Mention that you can maintain a count of empty cells or a bitmask of available moves to make the check O(1) or O(log n) instead of O(n). This shows you think about performance and data structure design.
Ask or state the specific rules: what constitutes a legal move, how moves are generated, and what the board state looks like. This ensures the solution is tailored to the game.
Explain that simulating all four moves for each empty cell is O(n) per move and can be optimized by checking only necessary conditions or using incremental updates.
Suggest maintaining a data structure (e.g., count of empty cells, bitmask of possible moves) that allows quick detection of any legal move. Alternatively, use early termination: check if any move is possible by scanning until one is found.
Consider edge cases like full board, moves that merge tiles, or special rules. Ensure the check correctly returns true only when no legal move exists.
Discuss time and space complexity of your approach versus the naive method, and justify why your solution is efficient and maintainable.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Start by clarifying the context: the board is likely a 2048-like game where a move may or may not change the board. Propose that the move function returns a boolean indicating whether any tile moved or merged, and the caller uses that to decide whether to spawn a new tile. Emphasize that this keeps the API simple and avoids unnecessary state checks.
Pro tip: Mention that returning a boolean is a common pattern in game logic (e.g., 2048 implementations) and that it decouples the move logic from the spawning logic, making the code easier to test and maintain.
Restate the problem: after a move, the game needs to know if the board changed to decide whether to spawn a new tile. This avoids spawning a tile when the move was invalid or had no effect.
Propose returning a boolean from the move function, where true indicates the board changed. Alternatively, return a result object with a 'changed' flag and possibly other metadata.
Inside the move function, track whether any tile moved or merged. Set the flag accordingly and return it.
In the game loop, call the move function and check the returned value. If true, spawn a new tile; otherwise, do nothing.
Compare returning a boolean vs. an enum vs. a result object. Mention that a boolean is simple but may lack context; a result object can provide more information for future needs.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Start by clarifying the movement rules and the system under test, then outline a unit testing strategy that isolates the movement logic from dependencies. Focus on verifying both expected outcomes for valid moves and invariants that must hold across all moves, using a mix of example-based and property-based tests.
Pro tip: Emphasize that invariants are best tested with property-based testing (e.g., QuickCheck) to cover edge cases, and mention that you would also test invalid moves to ensure they are rejected without violating invariants.
Ask questions to understand the rules of movement, the state involved, and what constitutes a valid move. Identify the unit under test and its dependencies to isolate it properly.
List invariants that must always hold after any valid move, such as position bounds, no overlapping pieces, or conservation of resources. These will guide your test design.
Write specific test cases for typical valid moves, edge cases (e.g., moving to boundary), and invalid moves (e.g., out of bounds). Assert both the resulting state and that invariants are preserved.
Use property-based testing to generate random valid moves and verify that invariants hold across all of them. This catches subtle bugs that example-based tests might miss.
Explain how you balance thoroughness with test maintainability, and how you would handle flaky tests or performance concerns in property-based testing.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.