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Data structure & algorithms (Graph notes)

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This document provides a detailed overview of Graph data structures, a fundamental topic in computer science. It covers the basic terminology and explores all 13 types of graphs. The document also provides a comparison and analysis of graph representations, including adjacency matrices and adjacency lists, and discusses the advantages and disadvantages of each. It also details the basic operations on graphs and highlights the key differences between a tree and a graph. This is an excellent resource for students studying data structures and algorithms

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Uploaded on
September 6, 2025
Number of pages
21
Written in
2024/2025
Type
Class notes
Professor(s)
Dr.bilal ashfaq
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Class no.11

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Data Structures and Algorithm
(CC-2042)
Lecture 30
E N G R. D R B I L A L A S H FA Q A H M E D
S C H O O L O F S Y S T E M S A N D T E C H N O LO GY ( S S T )
C O M P U T E R S C I E N C E FA C U LT Y

, Graph
A graph is a nonlinear data structu
that models' relationships betwee
interconnected elements (often ca
nodes or vertices).
Graphs are widely used in comput
science to represent various types
problems and real-world systems—
as social networks, road maps, we
page links, and more—where enti
have pairwise relationships.




09/06/2025 DS

, Basic Terminology
Vertex (Node): A fundamental unit of a graph, representing an entity or
location (for example, a person in a social network or a city in a map).
Edge: A connection between two vertices. An edge can represent a
relationship (e.g., a “friendship” in a social network) or a path (e.g., a “road
between two cities).
Weight/Cost (optional): An attribute sometimes assigned to edges to
represent an associated value, such as distance, time, or capacity.
Degree of a Vertex: The number of edges connected to a vertex.


Graph is composed of a set of vertices( V ) and a set of edges( E ). The gra
is denoted by G(V, E).


09/06/2025 DS
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