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Interactive graph algorithm visualization with step-by-step animation
Select algorithm and manage graph structure
4 nodes · 5 edges
BFS explores nodes level by level using a queue, finding shortest paths in unweighted graphs. DFS dives deep using a stack, ideal for connectivity checks, cycle detection, and topological ordering.
Dijkstra's and A* find shortest paths greedily. A* uses a heuristic to focus search. Bellman-Ford handles negative weights. Floyd-Warshall computes all-pairs paths in O(V³).
Kruskal's sorts edges by weight and adds cycle-free edges. Prim's grows the tree from a start vertex. Both yield the same MST but differ in efficiency characteristics.
Orders vertices of a DAG so directed edges go from earlier to later positions. Based on Kahn's algorithm (BFS on in-degrees). Used for build systems, task scheduling, and dependency resolution.
Finds all strongly connected components — maximal subgraphs where every vertex is reachable from every other. Uses a single DFS pass with a stack. Critical for web crawling and compiler analysis.
Graph algorithms power GPS navigation, social networks, web search (PageRank), compiler optimization, network routing, circuit design, and package dependency resolution.