How to approach breadth first search problems in LeetCode?

Breadth-first search (BFS) is a popular algorithmic technique that can be used to solve a variety of problems on LeetCode. Here are the steps to solve a BFS problem in LeetCode:

  1. Understand the problem statement: Read the problem statement carefully to understand what the problem is asking for and what the input and output formats are.
  2. Determine the graph representation: Determine the graph representation of the problem. This could be an adjacency list, an adjacency matrix, or a set of edges.
  3. Implement the BFS algorithm: Use a queue to implement the BFS algorithm. Initialize a queue with the starting node or nodes, and mark them as visited. Then, while the queue is not empty, dequeue a node from the front of the queue, visit it, and enqueue its neighbors that haven’t been visited yet.
  4. Keep track of additional information: If the problem requires additional information, such as the shortest path or the number of connected components, keep track of it during the BFS algorithm.
  5. Handle edge cases: Consider any edge cases that may arise, such as when the graph is empty or disconnected.
  6. Test your solution: Test your solution on different test cases, including edge cases, to ensure that it is correct.

Overall, it’s important to carefully read and understand the problem statement, determine the graph representation, implement the BFS algorithm, keep track of additional information, and handle edge cases to solve BFS problems on LeetCode.