Skip to main content
Course/Module 11/Topic 4 of 4Advanced

Graph Algorithms

Implement graph data structures and algorithms — BFS, DFS, shortest paths, minimum spanning trees, and topological sorting.

50 minBy Priygop TeamLast updated: Feb 2026

Graph Representation & Traversal

  • Adjacency Matrix: 2D array — graph[i][j] = 1 if edge exists. O(V²) space. O(1) edge check. Best for dense graphs or when V is small
  • Adjacency List: Array of linked lists — each vertex stores list of its neighbors. O(V+E) space. Better for sparse graphs (most real-world graphs)
  • BFS (Breadth-First Search): Use queue — visit all neighbors before going deeper. Finds shortest path in unweighted graphs. O(V+E) time. Level-order exploration
  • DFS (Depth-First Search): Use stack or recursion — go as deep as possible before backtracking. Detects cycles, topological sort, connected components. O(V+E)
  • Dijkstra's Algorithm: Shortest path from source to all vertices in weighted graph (non-negative weights). Uses priority queue (min-heap). O((V+E) log V)
  • Bellman-Ford: Shortest path with negative weights. Relax all edges V-1 times. Detects negative cycles on Vth iteration. O(V×E). Slower but more versatile than Dijkstra

Try It Yourself: Bubble Sort

Try It Yourself: Bubble SortC
C Editor
✓ ValidTab = 2 spaces
C|34 lines|681 chars|✓ Valid syntax
UTF-8

Quick Quiz — Algorithms

Chat on WhatsApp
Priygop - Leading Professional Development Platform | Expert Courses & Interview Prep