I Knew BFS Existed but Couldn't Wire It Into a Grid Problem

The provided explanation and code for solving LeetCode problem "Minimum Path Sum" using Breadth-First Search (BFS) is actually addressing a different problem: finding the shortest path in a grid where each cell has a value representing some form of cost or distance. However, since you mentioned BFS and its application to various problems on grids, let's focus on understanding how to apply BFS correctly for such scenarios.

Key Concepts

1. BFS Basics:

   • BFS is used when we need to find the shortest path in an unweighted graph.
   • It explores all possible paths level by level (wave-by-wave).

2. Grid Traversal:

   • In a grid, each cell can be considered as a node with neighbors being adjacent cells (4-directional or 8-directional).
   • BFS uses a queue to explore nodes layer by layer.

3. Queue and Visited Set:

   • A deque is used for efficient popping from the front.
   • A set or list is used to keep track of visited nodes to avoid revisiting them.

4. Distance Propagation:

   • Each node in the queue holds its current distance (or cost) from the starting point

Read the full article at DEV Community

---

Want to create content about this topic? Use Nemati AI tools to generate articles, social posts, and more.