Types of Graphs

Context: FIT1058_MOC · the simple graph (no loops, no parallel edges) is the default · richer classes add loops, multi-edges, weights, or direction

Quick Revision

  • 🎯 Objective: simple graph = no loops, no parallel edges ➔ the default.
  • 📦 Core Components: loop / multi-edge / weighted / directed generalisations.
  • ⚡ Key Constraint: edges-as-sets force simplicity; directed = ordered pairs (non-symmetric).

📝 Core

1. The Simple Graph

  • Definition ➔ no loops, no parallel edges (default here).
  • From sets ➔ edge has distinct vertices (no loop); a set (no repeat).

2. Richer Classes

  • Loop ➔ edge from a vertex to itself.
  • Multiple/parallel ➔ >1 edge between a pair.
  • Weighted ➔ each edge carries a number (cost/capacity).
  • Directed (digraph) ➔ ordered pairs , arcs; .

Key identities:

⚖️ Core Decision Matrix

ClassEdgesAdjacency
simpleunordered distinct pairssymmetric, irreflexive
loops allowedreflexive possible
multirepeated pairsmultiplicities
directedordered possibly non-symmetric

When It Flips: simple undirected graphs capture the main computational issues, so theorems transfer broadly; weights/directions add modelling power (road cost, one-way, flow) at the cost of more complex algorithms.

📊 Exam Execution Trace

Manual Execution Trace

Allowed in a simple graph?

Step / StateCandidateVerdict
0 (Init)
1loop — no
2parallel — no (one edge)
3directed — no

⚠️ Common Mistakes

  • 💡 Directed ≠ undirected ➔ a digraph uses ordered pairs, so adjacency need not be symmetric ( without ) — the general Binary Relation case.

🧠 Active Recall