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Computer Science

657What is a Graph? Vertices and Edges
658Directed vs Undirected Graphs
659Weighted vs Unweighted Graphs
660Simple Graphs and Multigraphs
661Degree of a Vertex
662Paths and Walks
663Cycles and Acyclic Graphs
664Connected Graphs and Components
665Strongly Connected Components in Directed Graphs
666Complete, Bipartite, and Regular Graphs
667Subgraphs, Induced Subgraphs, and Spanning Subgraphs
668Graph Isomorphism
669Adjacency Matrix: Structure and Memory
670Adjacency Matrix: Operations and Complexity
671Adjacency Matrix: Space-Time Tradeoffs
672Adjacency List: Structure with Arrays
673Adjacency List: Structure with Linked Lists
674Adjacency List: Operations and Complexity
675Adjacency List: Memory Efficiency
676Edge List Representation
677Weighted Graph Representations
678Directed vs Undirected Graph Storage
679Incidence Matrix Representation
680Choosing Representation by Graph Density
681Representation Trade-offs for Common Operations
682Memory Layout and Cache Performance
683Hybrid and Compressed Representations
684Directed vs Undirected Graphs
685Weighted and Unweighted Graphs
686Simple Graphs and Multigraphs
687Self-Loops and Their Implications
688Complete Graphs
689Bipartite Graphs
690Cyclic and Acyclic Graphs
691Trees as Special Graphs
692Planar Graphs
693Graph Density and Sparsity

Computer Science

657What is a Graph? Vertices and Edges
658Directed vs Undirected Graphs
659Weighted vs Unweighted Graphs
660Simple Graphs and Multigraphs
661Degree of a Vertex
662Paths and Walks
663Cycles and Acyclic Graphs
664Connected Graphs and Components
665Strongly Connected Components in Directed Graphs
666Complete, Bipartite, and Regular Graphs
667Subgraphs, Induced Subgraphs, and Spanning Subgraphs
668Graph Isomorphism
669Adjacency Matrix: Structure and Memory
670Adjacency Matrix: Operations and Complexity
671Adjacency Matrix: Space-Time Tradeoffs
672Adjacency List: Structure with Arrays
673Adjacency List: Structure with Linked Lists
674Adjacency List: Operations and Complexity
675Adjacency List: Memory Efficiency
676Edge List Representation
677Weighted Graph Representations
678Directed vs Undirected Graph Storage
679Incidence Matrix Representation
680Choosing Representation by Graph Density
681Representation Trade-offs for Common Operations
682Memory Layout and Cache Performance
683Hybrid and Compressed Representations
684Directed vs Undirected Graphs
685Weighted and Unweighted Graphs
686Simple Graphs and Multigraphs
687Self-Loops and Their Implications
688Complete Graphs
689Bipartite Graphs
690Cyclic and Acyclic Graphs
691Trees as Special Graphs
692Planar Graphs
693Graph Density and Sparsity

← Computer Science

Lesson 675 of 2,872·16. Graphs: Representation and Basic ConceptsPro lesson

Adjacency List: Memory Efficiency

Understand why adjacency lists use O(V+E) space, making them ideal for sparse graphs.

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