🚀 Graph Tutorial 6: BFS & DFS Traversal For Disconnected Graph | Traversal | Data Structures | Graph

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In this video, I explain in detail how to implement BFS (Breadth-First Search) and DFS (Depth-First Search) traversal for disconnected graphs. Unlike a connected graph, where a single BFS or DFS call can explore the entire graph, a disconnected graph requires multiple traversal calls to ensure all components are visited. This video focuses only on disconnected graphs, as I have already covered BFS and DFS for connected graphs in a previous video.

Using clear visual animations and a complete line-by-line Java code walkthrough, I demonstrate how BFS and DFS work on disconnected graphs, ensuring a deep understanding of the process. You will also learn how to efficiently handle multiple components and why graph traversal for disconnected graphs is crucial when solving real-world graph problems.

► How is Graph Traversal Different for Disconnected Graphs?
In a connected graph, all nodes are part of a single component, meaning any node can reach every other node. As a result, a single BFS or DFS call from any node can explore the entire graph.
However, in a disconnected graph, there are multiple isolated components with no paths between them. To traverse the entire graph, we need to make multiple BFS or DFS calls, starting from each unvisited node to explore each component separately.

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By mastering BFS and DFS traversal for disconnected graphs, you can solve a wide range of graph problems efficiently, whether in coding interviews, competitive programming, or real-world applications.

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shrutakirtichakraborty