Graph Traversal Visualizer
Explore BFS and DFS algorithms with interactive graph visualization
Graph Setup
Graph Type:
Undirected
Directed
Add Node:
Add Node
From:
Select node
To:
Select node
Add Edge
Generate Small Graph
Generate Large Graph
Clear Graph
Traversal Controls
Start Node:
Select node
Algorithm:
Breadth-First Search (BFS)
Depth-First Search (DFS)
Speed:
Slow
Medium
Fast
Very Fast
Start Traversal
Step
Reset
Graph Visualization
Nodes
0
Edges
0
Visited
0
Frontier
0
Traversal Order
Help
What are BFS and DFS?
Breadth-First Search (BFS):
Explores level by level using a queue
BFS visits all neighbors at distance k before visiting nodes at distance k+1
Guarantees shortest path in unweighted graphs
Depth-First Search (DFS):
Explores as deep as possible before backtracking
DFS uses a stack (or recursion) and explores one branch completely before trying others
Useful for cycle detection, topological sorting, and maze solving
How to Use
Add nodes by entering labels (A, B, C, etc.)
Connect nodes by selecting two nodes and clicking Add Edge
Choose directed or undirected graph type
Select a start node and traversal algorithm
Use Start to animate or Step to advance manually
Blue nodes are in the frontier, green nodes are visited, red is the current node
Key Differences
Data Structure:
BFS uses queue (FIFO), DFS uses stack (LIFO)
Exploration:
BFS goes wide, DFS goes deep
Optimality:
BFS finds shortest path, DFS does not guarantee it
Memory:
BFS uses more memory for wide graphs, DFS uses less
Use Cases:
BFS for shortest path, web crawling; DFS for topological sort, cycle detection