A graph can be defined as a group of vertices and edges that are used to connect these vertices. A graph can be seen as a cyclic tree, where the vertices (Nodes) maintain any complex relationship among them instead of having a parent-child relationship. A graph G can be defined as an ordered set G(V, E) where V(G) represents the set of vertices and E(G) represents the set of edges that are used to connect these vertices.

Graph Algorithms – Data Structure and Algorithms

In this “Graph Algorithms – Data Structure and Algorithms” you will learn about the following topics:

  1. Introduction of Graph
  2. Graph Terminology
  3. Graph Representation
  4. Sequential Representation, Linked Representation
  5. Graph Algorithms
  6. Terminologies in Graph Algorithms
  7. Types of Graph Algorithms
  8. Breadth-First Search (BFS) Algorithm
  9. Implementation of Breadth First Search (BFS)
  10. Depth First Search (DFS) Algorithm
  11. Implementation of Depth First Search (DFS)
  12. Topological Sort
  13. Spanning Tree
  14. General Properties of Spanning Tree, Mathematical Properties of Spanning Tree
  15. Minimum Spanning Tree (MST)
  16. Kruskal's Algorithm, Prim's Algorithm
  17. Dijkstra's Algorithm
  18. How Dijkstra's Algorithm Works?
  19. Example of Dijkstra's Algorithm
  20. Implementation of Dijkstra’s Algorithm
  21. Network Flow Problems
  22. Residual Networks, Augmenting Path




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BCA 3rd Semester Data Structure and Algorithms (DSA) Notes Pdf: