Matrix problems often involve traversals, dynamic programming, or search algorithms like BFS and DFS.

Matrix problems are common in competitive programming, and they often require efficient traversal techniques. Some problems may involve simple operations like row or column manipulation, while others may require dynamic programming (like finding the maximum sum path in a matrix). Search algorithms like BFS and DFS are often used for matrix problems involving grids, such as finding the shortest path in a maze or detecting connected components. Understanding how to efficiently traverse a matrix and how to apply dynamic programming to solve optimization problems will help you tackle a wide variety of matrix-related challenges.