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Online Graph Algorithms Playground

Welcome to Graph Algo Visualizer! I built this application because I was interested in pathfinding/graph algorithms and wanted to learn more about them. I hope you enjoy playing around with this application as much as I had fun building it. You can access it via this link: Complete Project

Supported Algorithms

Dijkstra's Shortest Path Algorithm

Dijkstra's algorithm is a step-by-step algorithm one can implement in order to find the shortest path between two vertices in a weighted graph.

A Star Search Algorithm

A* Search is one of the best and popular techniques used in path-finding and graph traversal. It is widely used in games and mapping software. It could be though of as "smart" version of dijkstra's algorithm since it uses heuristics to find a path to the target node.

Greedy Best First Search

The idea of Best First Search is to use an evaluation function to decide which adjacent node the is most promising and then explore. Best First Search falls under the category of Heuristic Search or Informed Search.

Breadth First Search

My favorite graph traversal algorithm, utilizing a queue data structure for picking the next node to visit.

Depth First Search

A Graph traversal technique utilizing a stack data structure for picking the next node.

Floyd-Warshall Algorithm

An awesome algorithm that finds the closest distance and Path between ANY two vertices in a graph.

Bellman Ford Algorithm

This algorithm finds the shortest path between two vertices in a weighted graph. Moreover, it fixes Dijkstra's problem in that it finds the shortest path in a graph with negative weights.

Prim's Algorithm

Finds the Minimum Spanning tree of a graph.

Kruskal's Algorithm

Just like Prim's, this algorithm finds the Minimum Spanning tree of a graph.

In addition, I implemented a recursive division maze generating algorithm.


Other Features

  • You can move the target and start node at your leisure.

  • You can add walls by clicking on a valid cell.

  • Once the animation is complete, you can move the target node to further visualize the algorithm.