Breadth-First Search (BFS) Calculator
This interactive calculator is designed to assist students, educators, and professionals in performing Breadth-First Search on graph structures. It simplifies the process of exploring graph nodes layer by layer, providing a clear, step-by-step demonstration of BFS traversal.
BFS Calculator
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Data Source and Methodology
The BFS algorithm is based on classical graph theory principles as outlined in authoritative computer science literature. All calculations rely strictly on these established methods.
The Formula Explained
The Breadth-First Search algorithm explores all of a graph's nodes at the present depth level before moving on to nodes at the next depth level.
Glossary of Terms
- Node: A point in the graph where lines intersect or branch.
- Adjacency List: A way to represent a graph as a collection of lists.
- BFS Traversal: The process of visiting all the nodes of a graph in breadth-wise motion.
How It Works: A Step-by-Step Example
Consider a graph with nodes connected as follows: 1 -> 2, 3; 2 -> 4, 5; 3 -> 5. Starting at node 1, BFS explores nodes in this order: 1, 2, 3, 4, 5.
Frequently Asked Questions (FAQ)
- What is BFS used for? BFS is used for finding the shortest path on unweighted graphs and for searching level by level.
- How does BFS differ from DFS? Unlike DFS, BFS explores all neighbors at the present depth prior to moving on to nodes at the next depth level.
- Can BFS be used on weighted graphs? BFS is typically used for unweighted graphs; for weighted graphs, Dijkstra's algorithm is more suitable.
- What is the time complexity of BFS? The time complexity of BFS is O(V + E), where V is the number of vertices and E is the number of edges.
- Is BFS a recursive algorithm? BFS is implemented using a queue and is not recursive.