Matrix Questions at Zepto: What to Expect

Matrix questions appear in 1 out of every 7 problems at Zepto, making them a significant part of their technical interview. For a company that builds a hyperlocal 10-minute delivery platform, efficient matrix operations are not academic—they’re practical. Real-time inventory grids, delivery route mapping, and store location data are often modeled as matrices. Your ability to traverse, transform, and analyze 2D arrays directly reflects your capacity to handle core data structures in their logistics and mapping systems.

What to Expect — Types of Problems

Zepto’s matrix problems typically focus on applied algorithms rather than abstract math. Expect these categories:

• Traversal Variations: Spiral, diagonal, or zigzag traversal, often used for processing grid-based data like store layouts or delivery zones.
• Search and Pathfinding: Searching in a row-wise and column-wise sorted matrix, or finding the shortest path in a grid with obstacles, analogous to routing through a delivery network.
• Dynamic Programming on Grids: Problems involving calculating minimum cost paths or maximal squares, which can model optimization problems in inventory or resource allocation.
• In-place Modification: Rotating or transposing a matrix, relevant for image processing or data transformation tasks.

The constraints usually emphasize optimal time and space complexity, with a strong preference for in-place operations where possible.

How to Prepare — Study Tips with One Code Example

Master a few core patterns rather than memorizing problems. Practice writing clean, bug-free traversal code using precise loop boundaries. Always sketch a small 3x3 example to verify your indices. A fundamental pattern is Depth-First Search (DFS) on a grid, used for problems like "Number of Islands" or flood-fill. The key is to mark visited cells to avoid cycles.

Here is a template for DFS on a matrix to count connected components:

def count_islands(grid):
    if not grid:
        return 0
    rows, cols = len(grid), len(grid[0])
    count = 0

    def dfs(r, c):
        if r < 0 or c < 0 or r >= rows or c >= cols or grid[r][c] != '1':
            return
        grid[r][c] = '#'  # Mark visited
        # Explore neighbors
        dfs(r+1, c)
        dfs(r-1, c)
        dfs(r, c+1)
        dfs(r, c-1)

    for r in range(rows):
        for c in range(cols):
            if grid[r][c] == '1':
                count += 1
                dfs(r, c)
    return count

Recommended Practice Order

1. Start with traversal fundamentals: practice printing a matrix in spiral order and searching in a sorted matrix.
2. Move to DFS/BFS applications: "Number of Islands," "Rotting Oranges," and "Word Search" to build recursive comfort on grids.
3. Tackle dynamic programming problems: "Unique Paths" and "Minimum Path Sum" to handle optimization.
4. Finally, attempt in-place operations: rotate image and set matrix zeroes, focusing on constant space solutions.

Practice Matrix at Zepto