What's Next?

What to Explore Next

More Graph Algorithms

  • A Search* — Dijkstra with a heuristic. Used for pathfinding in games and maps. Requires an admissible heuristic.
  • Floyd-Warshall — All-pairs shortest paths in O(V³). Great for dense graphs or when you need distances between all pairs.
  • Tarjan's SCC — Strongly Connected Components in a single DFS pass. More efficient than Kosaraju's.
  • Network Flow — Edmonds-Karp (BFS-based Ford-Fulkerson) for max flow / min cut problems.
  • Articulation Points & Bridges — Find critical infrastructure nodes/edges in a network.

Applications

  • Word Ladder — BFS on a graph where words are nodes and edges connect words differing by one letter.
  • Course Schedule — LeetCode 207/210: topological sort with cycle detection.
  • Number of Islands — DFS/BFS on a 2D grid graph.
  • Alien Dictionary — Topological sort from character ordering constraints.

Tools & Libraries

  • NetworkX — The Python graph library. Implements hundreds of algorithms, visualizes graphs, handles massive networks.
  • igraph — Fast graph analysis for Python and R.
  • Gephi — Graph visualization and exploration tool.
  • Neo4j — Graph database for storing and querying graph-structured data with Cypher query language.

Further Reading

  • Introduction to Algorithms (CLRS) — Chapters 22-25 cover all graph algorithms in depth.
  • Algorithm Design Manual by Steven Skiena — Practical graph algorithms with real-world applications.
  • CP-algorithms.com — Detailed explanations with implementations for competitive programming.
  • LeetCode Graph Problems — 200+ practice problems from easy to hard.
← Previous