In this post, we will learn the difference between Depth-First Search (DFS) and Breadth-First Search (BFS) in Java. This is a frequently asked question in Java interviews for beginners. Let's dive into it.
Feature | Depth-First Search (DFS) | Breadth-First Search (BFS) |
---|---|---|
Approach | DFS explores as far as possible along each branch before backtracking. | BFS explores all the nodes at the current depth level before moving to the next depth level. |
Data Structure | DFS is typically implemented using a stack (either explicitly or implicitly using recursion). | BFS is typically implemented using a queue. |
Order of Exploration | DFS explores nodes in the order they are encountered along each branch. | BFS explores nodes level by level, visiting all nodes at the current level before moving to the next level. |
Completeness | DFS may not necessarily explore all nodes in the graph. It may get stuck in an infinite loop in cyclic graphs. | BFS always explores all nodes in the graph, ensuring completeness. |
Memory Usage | DFS typically uses less memory compared to BFS, as it explores deeply before backtracking. | BFS uses more memory as it needs to store all nodes at the current level before moving to the next level. |
Applications | DFS is often used for pathfinding, topological sorting, and graph traversal problems. | BFS is used for shortest path finding, finding connected components, and exploring all possible states in a state space. |
Time Complexity (for a graph with V vertices and E edges) | In general, DFS has a time complexity of O(V + E). However, it can vary based on the graph structure and the implementation used. | BFS has a time complexity of O(V + E), as it visits all vertices and edges in the graph once. |
Example |
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