📔
Algorithms Analysis & Design
  • Algorithm Analysis & Design
  • 🚢Searching and Sorting
    • Introduction-Search
    • Linear Search
    • Binary Search
    • Interpolation Search
    • Introduction-Sorting
    • Bubble Sort
    • Selection Sort
    • Counting Sort
  • 💸Greedy Method
    • Introduction
    • Activity Selection
    • Fractional Knapsack Problem
    • Graph Colouring
  • 🚠Backtracking
    • Introduction
    • Hamiltonian Path/Cycle Problem
    • N Queen Problem
    • Rat in a Maze
    • Knight's Tour Problem
  • ⚔️Divide and Conquer
    • Introduction
    • Strassen's Matrix multiplication
    • Karatsuba algorithm
    • Tower of Hanoi
    • Closest Pair
  • 💣Dynamic Programming
    • Introduction
    • Longest Common Subsequence
    • Floyd-Warshall Algorithm
    • 0-1 Knapsack problem
    • Dice Throw
  • 📈Graph
    • Introduction
    • DFS
    • Dictionary Game
    • BFS
    • Flood Fill Algorithm
    • Minesweeper Lite
  • 🔢Number Theory
    • Introduction
    • GCD
    • Factorial
    • IsPrime | School Method
    • IsPrime | Fermat's Little Theorem
    • IsPrime | Miller-Rabin Method
  • 🌮References
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  1. 📈Graph

Introduction

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Last updated 3 years ago

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A graph data structure is a collection of nodes that have data and are connected to other nodes.

More precisely, a graph is a data structure (V, E) that consists of

  • A collection of vertices V

  • A collection of edges E, represented as ordered pairs of vertices (u,v)\

Graph Terminology

  • Adjacency: A vertex is said to be adjacent to another vertex if there is an edge connecting them. Vertices 2 and 3 are not adjacent because there is no edge between them.

  • Path: A sequence of edges that allows you to go from vertex A to vertex B is called a path. 0-1, 1-2 and 0-2 are paths from vertex 0 to vertex 2.

  • Directed Graph: A graph in which an edge (u,v) doesn't necessarily mean that there is an edge (v, u) as well. The edges in such a graph are represented by arrows to show the direction of the edge.