Doppel Software Engineer First Round Interview Experience

Context Doppel, a Series B startup focused on detecting and mitigating social engineering attacks, utilizes the following multi-stage technical problem during their interview process. **Problem St

Context Doppel, a Series B startup focused on detecting and mitigating social engineering attacks, utilizes the following multi-stage technical problem during their interview process. Problem Statement: Conway's Game of Life The core task is to simulate a cellular automaton on an M x N grid. Each cell is either live ('O') or dead ('.') and interacts with its eight horizontal, vertical, and diagonal neighbors. The state of the board evolves in generations based on four simultaneous rules: * Under-population: A live cell with fewer than two live neighbors dies. * Survival: A live cell with two or three live neighbors remains live. * Overpopulation: A live cell with more than three live neighbors dies. * Reproduction: A dead cell with exactly three live neighbors becomes live. Interview Stages 1. Implementation The candidate must write the logic to simulate the game for K generations, printing the state of the board after each update. This tests basic array manipulation and the ability to handle simultaneous state changes (requiring a buffer or distinct current/next state). 2. Pattern Recognition The interviewer provides specific starting configurations (seeds). The candidate runs the simulation to identify behavior patterns, such as "still lifes" (static patterns) or "oscillators" (repeating patterns). The candidate must explain the logic behind why these patterns stabilize or loop. 3. The Infinite Board The constraints change from a fixed M x N grid to an infinite board. The candidate must design a solution to handle an unbounded grid using finite memory. The standard solution involves moving away from 2D arrays to a sparse storage approach, such as using a Hash Set to store only the coordinates of "live" cells, treating all unstored coordinates as dead. 4. Optimization Building on the patterns observed in stage 2, the candidate must optimize the engine. This involves identifying stable regions of the board that do not require recalculation or detecting cycles to skip generations. Candidate Experience This interview focuses on engineering fundamentals and critical thinking rather than abstract algorithmic brainteasers. The problem allows for a collaborative discussion regarding system design (infinite scaling) and performance optimization, scaling in difficulty based on the candidate's seniority.