Nash AI·Software Engineer·Onsite - System Design / Architecture·Senior

SeniorPrefer not to say

Jun 2026Remote

Summary

Had a system design round at Nash AI for a software engineer role. The whole session was basically one big OOP design question about Minesweeper, which sounds toy-ish until you're actually in it trying to articulate class hierarchies and state machines on the spot.

Questions Asked (1)

Design an object-oriented Minesweeper game. The board is a grid of cells, and each cell has a probability of being a mine. Walk through how per-cell probabilities drive the initial mine layout, define the core classes and their responsibilities, describe how they relate to each other, and specify public APIs for printing the board and handling a user click. Also cover state transitions on a click, how you handle invalid or duplicate clicks, and how your design supports maintainability and testing.

System DesignAlgorithms & Data StructuresTechnical Trade-offs

Author's notes

I started with Cell, Board, Game and felt good about that for about two minutes.

Create a free account to read the full note

AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and assumptions, then walk through the probability-driven mine placement algorithm. Define the core classes (Board, Cell, Game) with clear responsibilities and relationships, and specify public APIs for printing and clicking. Finally, discuss state transitions, edge cases, and how the design supports testing and maintainability.

Pro tip: Emphasize separation of concerns: keep game logic independent of UI, and use dependency injection for the random number generator to make mine placement deterministic and testable.

1. Clarify requirements and assumptions

Ask about board size, mine probability, first-click safety, and whether probabilities are per-cell independent. State assumptions clearly.

2. Explain probability-driven mine placement

Describe iterating over each cell and placing a mine with probability p, using a random number generator. Mention seeding for reproducibility and handling edge cases like all mines or no mines.

3. Define core classes and relationships

Introduce Board (grid of Cells), Cell (state: hidden/revealed/flagged, adjacent mine count), Game (manages game state, win/loss). Explain composition and responsibilities.

4. Specify public APIs and state transitions

Define methods like printBoard() and click(row, col). Describe state transitions on click: reveal cell, flood-fill if zero adjacent mines, handle mine hit (game over), and invalid/duplicate clicks.

5. Discuss maintainability and testing

Highlight how separation of concerns, dependency injection, and clear interfaces enable unit testing (e.g., mock RNG) and future extensions (e.g., different board shapes).

Key Points to Mention

Probability-driven mine placement using independent Bernoulli trials per cell
Core classes: Board, Cell, Game with clear responsibilities and composition
Public APIs: printBoard() for display, click(row, col) for user interaction
State transitions: reveal, flood-fill for zero adjacent mines, game over on mine
Handling invalid clicks (out of bounds, already revealed) and duplicate clicks
Testability via dependency injection (e.g., Random interface) and separation of UI from logic

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.