Graph Algorithm Visualizer

Algorithm Selection

Breadth-First Search (BFS)

BFS explores the graph level by level, visiting all neighbors of a node before moving to the next level.

Complexity Analysis

Time Complexity: O(V + E)

Space Complexity: O(V)

Best For: Unweighted Shortest Path

Pseudocode ▼

function BFS(graph, start):
    queue = [start]
    visited = {start}
    
    while queue is not empty:
        node = queue.dequeue()
        visit(node)
        
        for neighbor in node.neighbors:
            if neighbor not visited:
                queue.enqueue(neighbor)
                visited.add(neighbor)

Applications & Use Cases ▼

Shortest path in unweighted graphs
Level-order traversal
Finding connected components
Web crawling

Key Points ▼

Uses Queue (FIFO) data structure
Guarantees shortest path in unweighted graphs
Explores all nodes at distance k before k+1
Memory intensive for wide graphs

Weighted Graph Directed Graph

Start Node: End Node:

Speed: 5x

Nodes: 0

Edges: 0

Step: 0

Ready

Welcome to Graph Algorithm Visualizer!

Study Mode: Algorithm Deep Dive