In this repository, you will find Depth-First Search (DFS: Useful for cycle detection, topological sort, and maze-solving) and Breadth-First Search (BFS: Good for shortest path in unweighted graphs) implementation with python.
WHY this repository !
1) Core to Understanding Graph Structures:
- Graph traversal algorithms help us explore all the nodes (vertices) and edges of a graph in a systematic way.
- This is essential for understanding the structure and properties of the graph.
2) Used in Many Real-World Applications:
- Social networks: Finding friends, influencers, or connections.
- Web crawling: Search engines use traversal to index web pages.
- Navigation and maps: GPS finds routes using traversal algorithms.
- Recommendation systems: Exploring similar users/items via a graph.
- Computer networks: Packet routing, connection analysis.
- AI and game development: Pathfinding (e.g., A* uses traversal principles).
3) Solves Important Computational Problems:
- Pathfinding: Finding shortest or all paths (e.g., Dijkstra, BFS).
- Cycle detection: Important in dependency resolution.
- Connected components: Identifying clusters or isolated parts.
- Topological sorting: Ordering tasks with dependencies.
- Searching: Locating specific nodes or values.
PS: We study graph traversal to explore, understand, and solve problems in graphs, which model relationships and structures in countless fields like computer science, AI, biology, social sciences, and engineering.