Matrix Questions at Samsung: What to Expect

Matrix questions appear in nearly 12% of Samsung’s coding problems. For a company that designs hardware, develops software, and builds massive networks, matrices are a natural data structure for modeling grids, maps, circuit boards, and display pixels. Success here demonstrates you can navigate and manipulate structured 2D data—a core skill for real-world Samsung projects involving image processing, memory arrays, or robot pathfinding.

What to Expect — Types of Problems

Samsung’s matrix problems typically fall into three categories. Grid Traversal questions ask you to move an agent (like a robot or pointer) through a matrix using rules (e.g., moving until hitting an obstacle). Flood Fill / Connected Components problems involve spreading through adjacent cells to label regions, simulate infections, or count islands. Pathfinding & Simulation questions are the most complex, often requiring BFS/DFS to find the shortest path or simulate multi-step processes on a grid, sometimes with changing states.

These problems are rarely abstract; they are presented as concrete engineering scenarios, such as cleaning a room with obstacles, escaping a maze, or spreading a virus in a network layout. Input is usually given as a matrix of integers or characters, and you must parse it, apply logic, and output a result like a number of steps, a final matrix state, or a yes/no decision.

How to Prepare — Study Tips with One Code Example

Master matrix navigation by internalizing movement patterns. Represent directions as arrays of (row, column) deltas. Always validate the next cell is within bounds before accessing it. Use a visited matrix to track cells you’ve already processed to avoid infinite loops. For shortest path problems, Breadth-First Search (BFS) with a queue is almost always the required approach.

A fundamental pattern is the 4-directional traversal. Here’s how to implement it across languages:

def traverse_four_directions(grid, start_row, start_col):
    rows, cols = len(grid), len(grid[0])
    directions = [(-1, 0), (1, 0), (0, -1), (0, 1)]  # up, down, left, right
    visited = [[False] * cols for _ in range(rows)]

    # Example: BFS queue initialization
    from collections import deque
    queue = deque([(start_row, start_col)])
    visited[start_row][start_col] = True

    while queue:
        r, c = queue.popleft()
        # Process cell (r, c) here
        for dr, dc in directions:
            nr, nc = r + dr, c + dc
            if 0 <= nr < rows and 0 <= nc < cols:
                if not visited[nr][nc] and grid[nr][nc] == 1:  # Example condition
                    visited[nr][nc] = True
                    queue.append((nr, nc))
    # Return result based on traversal

Recommended Practice Order

Start with basic traversal to build comfort moving in a grid. Then practice Flood Fill algorithms (like Number of Islands). Move on to simple agent simulation problems where movement rules are defined. Finally, tackle advanced BFS pathfinding, which is the most frequent pattern in Samsung’s harder matrix questions. Always diagram the problem on paper first to clarify movement rules and edge cases before coding.

Practice Matrix at Samsung