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Graph Categories and Properties

Algorithmics (HESS)
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Graph Categories and Properties

Algorithmics (HESS)
01 May 2026

Categories of Graphs and Their Properties

1. Complete Graphs

A complete graph $K_n$ is an undirected graph with $n$ vertices where every pair of distinct vertices is connected by exactly one edge.

Properties

  • Number of edges: $\dfrac{n(n-1)}{2}$
  • Every vertex has degree $n - 1$
  • For $n = 4$: 6 edges; for $n = 5$: 10 edges

Significance

Complete graphs represent the worst-case scenario for many algorithms — every possible connection exists. The Travelling Salesman Problem considers complete weighted graphs.

KEY TAKEAWAY: $K_n$ has the maximum possible number of edges for $n$ vertices: $\dfrac{n(n-1)}{2}$.


2. Connected Graphs

A connected graph is an undirected graph in which there is a path between every pair of vertices.

Properties

  • No isolated vertices (every vertex can reach every other vertex)
  • Removing certain edges or vertices may disconnect the graph

Strongly vs. Weakly Connected (Directed Graphs)

Type Definition
Strongly connected Every vertex can reach every other vertex following edge directions
Weakly connected The underlying undirected graph (ignoring directions) is connected

Why It Matters

  • Prim’s algorithm requires a connected graph to produce a spanning tree.
  • BFS/DFS from a single source only reaches all vertices in a connected graph.

3. Directed Acyclic Graphs (DAGs)

A DAG is a directed graph with no directed cycles.

Properties

  • Has a topological ordering — vertices can be arranged so all edges point “forward”
  • Can model dependencies (task A must precede task B)

Applications

  • Task scheduling / project management (prerequisite tasks)
  • Build systems (file compilation order)
  • Decision trees and state graphs for planning
  • Dynamic programming problems (subproblem dependency structure)
  Compile A → Link A
  Compile B → Link A → Package

EXAM TIP: If a directed graph has a cycle, it cannot be a DAG and cannot be topologically sorted. Look for cycles when justifying whether a graph is a DAG.


4. Trees

A tree is a connected, undirected, acyclic graph.

Properties

  • $n$ vertices → exactly $n - 1$ edges
  • Exactly one path between any two vertices
  • Removing any edge disconnects the graph
  • Adding any edge creates a cycle

Rooted Trees

A tree with one designated root vertex. Vertices are called parents/children/leaves. Used in decision trees, parse trees, and binary search trees.

Spanning Trees

A spanning tree of a connected graph $G$ includes all $n$ vertices and exactly $n-1$ edges (no cycles). The minimum spanning tree (MST) is the spanning tree with minimum total weight — found by Prim’s algorithm.


Summary Comparison

Category Directed? Cycles? All pairs connected? Key Property
Complete graph No No Yes Maximum edges: $n(n-1)/2$
Connected graph No Possible Yes Path between all pairs
DAG Yes No Not required Topological ordering exists
Tree No No Yes $n$ vertices, $n-1$ edges

VCAA FOCUS: Know the formal definitions and be ready to classify a given graph into one or more categories. Properties (number of edges, connectivity, cycle-free) are frequently tested.

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