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Directed Weighted Graph Edge List Representation

A directed weighted graph can be stored as a pair of lists: every vertex in one list, and every edge as a three-part tuple of start node, end node, and weight. Replacing the node values with indexes into the vertex list lets you jump to those nodes in constant time after you find an edge.

mike September 13, 2026

Computer Science Data Structures Graphs

How to Represent Undirected Weighted Graphs Using Edge Lists

Learn the edge list representation for undirected weighted graphs. Build a vertex list and an edge list of triples that store both endpoints and the weight of each edge. Convert the list to use indexes so node lookups become constant time when the vertices are stored in a vector or array. This approach keeps each undirected edge only once and improves the speed of operations that need both edges and nodes.

mike August 26, 2026

Computer Science Data Structures Graphs

How to Represent an Unweighted Undirected Graph with an Edge List

Represent an unweighted undirected graph as a tuple of a vertex list and an edge list. Store nodes as indexable objects and list each edge once as a pair of indexes so you can reach any vertex in constant time.

mike August 15, 2026

Computer Science Data Structures Graphs

Graph Paths Explained: Node vs Edge Based, Simple Paths, Cycles and DAGs

Paths in a graph show how to travel from a start node to a destination. Node-based paths list the nodes visited but cannot distinguish parallel edges with different weights. Edge-based paths use tuples of start node, destination node and weight so every route is exact. Simple paths repeat no edges or vertices. Cyclic paths start and end on the same node and prove the graph is cyclic. A DAG is a directed acyclic graph with no cycles. These ideas prepare for graph algorithms.

mike August 5, 2026

Computer Science Data Structures Graphs

Graph Connectedness Explained: Connected Strongly Connected and Weakly Connected

This video explains graph connectedness for both undirected and directed graphs. For undirected graphs a connected graph means every node can reach every other node through a path. Disconnected graphs have nodes that cannot reach others and may contain separate subgraphs. For directed graphs the terms change to strongly connected where every node reaches every other node following edge directions and weakly connected where the graph is connected if directions are ignored. Step by step examples show how adding edges turns a graph from not connected to weakly connected and finally to strongly connected.

mike July 25, 2026

Computer Science Data Structures Graphs

Graph Basics in Data Structures: Nodes, Edges, and Representations

Graphs are collections of nodes and edges, or vertices and edges. In this tutorial we implement them as template classes in C++ so you can use custom data types for nodes and edge weights. We cover undirected unweighted graphs, then add directions and weights to show path costs between cities or network nodes.

mike July 14, 2026

Computer Science Data Structures Graphs

4 Graph Types: Undirected vs Directed, Weighted vs Unweighted

A graph is basically a collection of nodes, also known as vertices, and edges, which are the lines that connect nodes to each other. The four types of graphs are undirected unweighted, undirected weighted, directed unweighted, and directed weighted. Graphs help represent relationships between things like computers in a network or cities and airports.

mike July 6, 2026

AVL Trees Binary Search Trees Computer Science

AVL Trees: Adding Linear Data and Performing Rotations

In this AVL tree example we add linear data starting with 12 then 21 30 38 42 and 55. After each insertion we update balance factors and when we hit imbalance we select the XYZ trinode and perform rotations to restore the AVL property. The tree stays balanced despite the bad input data.

mike June 27, 2026

AVL Trees Binary Search Trees Computer Science

AVL Tree Rotations Practice: Balancing a Huge Linear Tree Step by Step

Learn how to perform AVL tree rotations on a completely linear binary search tree. This step-by-step practice video shows multiple rotations, balance factor updates, and how to transform an unbalanced O(n) tree into a balanced O(log n) AVL tree.

mike June 16, 2026

AVL Trees Binary Search Trees Computer Science

How to Perform AVL Tree Rotations – Step By Step Example

Learn how to rotate an AVL tree in this detailed example. We identify imbalance using balance factors, locate X Y Z nodes, and apply a double right rotation to restore the self-balancing property of the binary search tree.

mike June 8, 2026