When the graph is very deep and solutions are rare.
When you need to find the shortest path in an unweighted graph.
When memory usage is a concern.
When the graph is sparse.
Questions & Step-by-Step Solutions
In which scenario is BFS preferred over DFS?
Step 1: Understand what BFS (Breadth-First Search) and DFS (Depth-First Search) are. BFS explores all neighbors at the present depth before moving on to nodes at the next depth level, while DFS explores as far as possible along each branch before backtracking.
Step 2: Identify the type of graph you are working with. In this case, we are focusing on an unweighted graph, which means all edges have the same weight or cost.
Step 3: Determine what you need to find. If you need to find the shortest path from one node to another in an unweighted graph, BFS is the better choice.
Step 4: Understand why BFS is preferred for the shortest path. BFS explores all possible paths level by level, ensuring that the first time it reaches a node, it has found the shortest path to that node.
Step 5: Conclude that in scenarios where the shortest path is required in an unweighted graph, BFS is the preferred algorithm.
