I started sketching a Board class and a Tile class, which is fine, but I immediately went down the road of writing four separate move handlers.
Start by clarifying requirements and constraints, then define the core classes (Board, Tile, Game) and their responsibilities. Walk through the move algorithm step-by-step, emphasizing the merge logic and direction handling, and discuss edge cases and extensibility.
Pro tip: Mention that you would separate the game logic from the UI to enable testing and reuse, and discuss how to handle moves in all four directions by transforming the board to a canonical orientation.
Ask about grid size (fixed or variable), win/lose conditions, scoring, and whether moves can be undone. Confirm that UI is out of scope.
Identify Board, Tile, and Game classes. Board manages the grid and move logic; Tile represents a cell with a value; Game handles overall state, score, and spawning new tiles.
Explain how to process a move in a given direction: compress non-empty tiles, merge adjacent equal values (each tile merges once per move), compress again, and update score. Use a canonical direction (e.g., left) and rotate/reflect the board for other directions.
After a move, check for win (2048 tile) or loss (no empty cells and no possible merges). Spawn a new tile (2 or 4) in a random empty cell. Discuss handling invalid moves (no change) and ensuring merges are not chained.
Mention how to extend for different grid sizes, add undo, or support different tile values. Emphasize unit testing the move logic with various board configurations.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Start by explaining the merge rule clearly: each tile can participate in at most one merge per move, so merges must be processed left-to-right (or in the direction of movement) without reusing a tile. Then walk through the example [2, 2, 2] to show that the leftmost two 2s merge into 4, leaving the third 2 untouched, resulting in [4, 2]. Finally, discuss how you'd implement this in code, such as using a flag or processing in a single pass.
Pro tip: Mention that the rule prevents chain reactions (e.g., [2,2,4] should not become [8] in one move) and that you'd handle it by iterating in the direction of movement and skipping the next index after a merge. This shows you understand the game's mechanics and can translate them into clean code.
State that each tile can merge at most once per move, meaning after a merge, the resulting tile cannot merge again in the same move.
Explain that you iterate through the line in the direction of movement (e.g., left-to-right for a left move) and merge adjacent equal tiles, then skip the next index to avoid double merging.
For [2, 2, 2], the first two 2s merge into 4, and the third 2 remains, giving [4, 2]. Emphasize that the new 4 does not merge with anything else in this move.
Describe how you'd code it: use a new array or in-place with a write index, and a flag to track whether the current tile has already merged.
Mention cases like [2,2,4] -> [4,4] (not [8]) and [4,4,4] -> [8,4] to reinforce the rule.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Start by acknowledging the need to separate randomness generation from game logic, then propose dependency injection of a random number generator (RNG) interface. Explain how this enables deterministic tests by substituting a seeded or mock RNG, and discuss trade-offs like testability vs. production randomness.
Pro tip: Mention that you'd also make the seed configurable for reproducible bug reports in production, showing you think beyond just unit tests.
List all places in the game logic where randomness is used (e.g., dice rolls, card shuffling, enemy AI).
Define an interface (e.g., RandomProvider) with methods like nextInt(), shuffle(), etc., to decouple game logic from concrete RNG.
Pass the RNG into game logic via constructor, method parameter, or a dependency injection framework, so it can be swapped.
Use a seeded RNG (e.g., java.util.Random with fixed seed) or a mock that returns preprogrammed sequences for predictable tests.
Explain that production uses a secure or true random source, while tests use deterministic ones; also mention logging seeds for reproducibility.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Snapshotting is simpler but costs O(N^2) memory per undo step.
Start by clarifying the requirements: what operations need to be undone, how deep the undo stack should be, and whether memory or latency is more critical. Then compare snapshotting and delta-based approaches across dimensions like time/space complexity, implementation complexity, and edge cases, and recommend a hybrid or context-specific solution.
Pro tip: Mention that many production systems (e.g., Asana) use a hybrid: periodic snapshots plus deltas for recent changes, to bound memory while keeping undo fast. Also, discuss how to handle non-reversible operations (e.g., random moves) and concurrency.
Ask about board size, move frequency, undo depth, memory limits, and whether undo must be persistent across sessions. This determines the trade-off space.
Explain that you store full board copies at each move. Highlight simplicity and fast undo, but note O(board size) memory per move and potential performance issues for large boards or deep undo stacks.
Explain that you record each move as a reversible operation (e.g., move piece from A to B, capture piece C). Highlight O(1) memory per move and scalability, but note complexity in implementing inverse operations and handling non-reversible moves.
Contrast time/space complexity, implementation effort, and edge cases (e.g., random events, concurrent edits). Discuss how each approach handles undo depth and memory growth.
Recommend a hybrid or context-specific approach, such as snapshots every N moves plus deltas in between, or deltas with periodic compaction. Explain how it balances memory, performance, and complexity.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Start by clarifying the game rules and board representation, then propose an incremental win-check that only examines lines through the last move, achieving O(1) per move. Finally, address whether 'board full' is sufficient by discussing draw conditions and edge cases like early wins.
Pro tip: Emphasize that checking only the last move's row, column, and diagonals is both efficient and correct, and mention that 'board full' alone is insufficient because a win can occur before the board is full.
Ask about the game (e.g., Tic-Tac-Toe, Connect Four), board size, and win condition to tailor your solution. Confirm whether moves are always valid and if the board can be partially filled.
Propose an incremental approach: after each move, check only the lines (row, column, diagonals) that include the last placed piece. This reduces time complexity to O(1) per move for fixed board sizes.
Explain that 'board full' is not sufficient for game-over because a player can win before the board is full. It only indicates a draw if no winner exists.
Discuss handling multiple win lines, early termination, and potential optimizations like maintaining counts of consecutive pieces for larger boards (e.g., Connect Four).
Reiterate that efficient detection checks only relevant lines after each move, and that 'board full' alone is insufficient; a win check must be performed independently.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Extract the merge predicate as a strategy or function passed into the merge routine.
Start by identifying the varying parts of the merge logic and abstracting them behind a strategy interface. Then, show how the slide logic can depend on this abstraction, allowing different merge rules (e.g., Fibonacci, target tile) to be plugged in without modifying the slide code. Emphasize the use of dependency injection and the Open/Closed Principle.
Pro tip: Mention that you would use a factory or configuration to select the merge strategy at runtime, and highlight how this improves testability and extensibility. Also, note that you'd keep the strategy stateless to avoid side effects.
Analyze the current merge rule and determine what changes when the condition changes (e.g., merging criteria, target value). Separate the invariant slide logic from the variant merge logic.
Create an interface (e.g., MergeStrategy) with a method like canMerge(tile1, tile2) and merge(tile1, tile2). This encapsulates the merge condition and result.
Provide implementations for different rules: standard 2048, Fibonacci, target tile, etc. Each strategy encapsulates its own logic.
Modify the slide logic to accept a MergeStrategy instance (via constructor or method parameter). The slide logic calls the strategy without knowing the details.
Use a factory or configuration to select the appropriate strategy at runtime. Write unit tests for each strategy and for the slide logic with a mock strategy.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.