Matrix Questions at DoorDash: What to Expect

Matrix questions appear in 14% of DoorDash’s technical interview problems. For a company that maps deliveries, optimizes routes, and manages logistics grids, matrices are a natural data structure. Success here demonstrates you can navigate 2D data—essential for real-world problems like delivery zone mapping, inventory grids, or simulating movement across a city layout.

What to Expect — Types of Problems

DoorDash matrix problems typically fall into three categories:

1. Grid Traversal and Pathfinding
   Problems involve moving through a matrix (e.g., representing a map or warehouse layout) using BFS, DFS, or dynamic programming. Common examples: shortest path in a grid, counting unique paths with obstacles, or finding connected regions.

2. Matrix Transformation and Simulation
   These questions ask you to modify the matrix in-place or simulate a process. Examples: rotating an image (matrix), the “game of life” simulation, or spreading changes across adjacent cells over time—similar to how delivery hotspots might propagate.

3. Search in Sorted Matrix
   While less frequent, some problems involve searching in a matrix sorted row-wise or column-wise, testing your ability to optimize beyond a naive O(m*n) scan.

Expect constraints around efficiency and edge cases, such as large matrices or in-place operation requirements.

How to Prepare — Study Tips with One Code Example

Focus on core patterns: BFS for shortest path, DFS for connected components, and in-place rotation techniques. Practice writing clean, bug-free code under time pressure. Always clarify the problem (e.g., input bounds, movement rules) before starting.

A key pattern is BFS for shortest path in a grid. Here’s a template for problems where you move up, down, left, right and need the shortest path length from a start to a target, avoiding obstacles:

from collections import deque

def shortest_path(grid, start, target):
    rows, cols = len(grid), len(grid[0])
    directions = [(1,0), (-1,0), (0,1), (0,-1)]
    queue = deque([(start[0], start[1], 0)])  # (row, col, distance)
    visited = set([(start[0], start[1])])

    while queue:
        r, c, dist = queue.popleft()
        if (r, c) == target:
            return dist
        for dr, dc in directions:
            nr, nc = r + dr, c + dc
            if 0 <= nr < rows and 0 <= nc < cols and grid[nr][nc] == 0 and (nr, nc) not in visited:
                visited.add((nr, nc))
                queue.append((nr, nc, dist + 1))
    return -1  # No path found

Recommended Practice Order

1. Start with fundamental traversals (DFS/BFS) on binary matrices.
2. Move to dynamic programming problems (e.g., unique paths, minimum path sum).
3. Practice in-place transformations (rotate, transpose).
4. Tackle advanced simulations (e.g., game of life, flood fill variations).
5. Finally, mix in search problems in sorted matrices.

Prioritize quality over quantity: solve each problem, then analyze time/space complexity and edge cases.

Practice Matrix at DoorDash