Module 3: Graph Algorithms & Network Analysis
This page aggregates the generated reference routes used by the learner-facing module.
- Semester:
semester-02-algorithms - App:
foundations
Read only if stuck
- ADM: Graph Traversal overview
- ADM: Flavors of Graphs
- ADM: The Friendship Graph
- ADM: Design Graphs, Not Algorithms
- ADM: Graph Data Structures
- CLRS 20.1: Representations of Graphs
- Sedgewick: Elementary Graph Algorithms (Part 1)
- Competitive Programming: Graph
- Competitive Programming: Special Graphs
- ADM: Traversing a Graph
- ADM: Breadth-First Search
- ADM: Applications of BFS
- ADM: Depth-First Search
- ADM: Applications of DFS
- ADM: DFS on Directed Graphs
- ADM: Strongly Connected Components
- CLRS 20.2: Breadth-First Search
- CLRS 20.3: Depth-First Search
- CLRS 20.4: Topological Sort
- CLRS 20.5: Strongly Connected Components
- Sedgewick: Connectivity
- Sedgewick: Directed Graphs
- Competitive Programming: BFS
- Competitive Programming: Finding SCCs
- Competitive Programming: Kosaraju's Algorithm
- ADM: Dijkstra's Algorithm
- ADM: All-Pairs Shortest Paths
- ADM: Dialing for Documents war story
- CLRS 22.1: Bellman-Ford Algorithm
- CLRS 22.2: SSSP on DAGs
- CLRS 22.3: Dijkstra's Algorithm
- CLRS 22.5: Proofs of Shortest-Paths Properties
- CLRS 23.2: Floyd-Warshall Algorithm
- CLRS 23.3: Johnson's Algorithm for Sparse Graphs
- Competitive Programming: SSSP on weighted graphs
- Competitive Programming: SSSP with negative cycles
- Competitive Programming: All-Pairs Shortest Paths
- Competitive Programming: Shortest Path Faster Algorithm
- ADM: Minimum Spanning Trees
- ADM: Kruskal's Algorithm
- ADM: Union-Find Data Structure
- ADM: MST Variations
- ADM: Nothing But Nets war story
- CLRS 19.1: Disjoint-Set Operations
- CLRS 19.3: Disjoint-Set Forests
- CLRS 19.4: Analysis of Union by Rank with Path Compression
- CLRS 21.1: Growing a Minimum Spanning Tree
- CLRS 21.2: Kruskal and Prim
- Competitive Programming: Minimum Spanning Tree
- Competitive Programming: Prim's Algorithm
- Competitive Programming: MST Applications
- ADM: Network Flows and Bipartite Matching
- CLRS 24.1: Flow Networks
- CLRS 24.2: Ford-Fulkerson Method
- CLRS 24.3: Maximum Bipartite Matching
- CLRS 25.1: Maximum Bipartite Matching Revisited
- CLRS 25.3: The Hungarian Algorithm
- Sedgewick: Network Flow
- Sedgewick: Matching
- Competitive Programming: Network Flow
- Competitive Programming: Ford-Fulkerson's Method
- Competitive Programming: Edmonds-Karp's Algorithm
- Competitive Programming: Dinic's Algorithm
- Competitive Programming: Graph Matching
- Competitive Programming: Hopcroft-Karp Algorithm
Optional deep dive
- ADM: Chapter Notes - Minimum Spanning Trees
- CLRS 22.4: Difference Constraints and Shortest Paths
- CLRS 23.1: Shortest Paths and Matrix Multiplication
- CLRS 25.2: The Stable Marriage Problem
- CLRS 19.4: Analysis of Union by Rank with Path Compression
- Competitive Programming: Min Path Cover on DAG
- Sedgewick: Elementary Graph Algorithms (Part 2)
- ADM: Graph Traversal Exercises