Data Structures and Algorithms
with Object-Oriented Design Patterns in Python |

A graph is simply a set of points together with a set of lines connecting various points. Myriad real-world application problems can be reduced to problems on graphs.

Suppose you are planning a trip by airplane. From a map you have determined the distances between the airports in the various cities that you wish to visit. The information you have gathered can be represented using a graph as shown in Figure (a). The points in the graph represent the cities and the lines represent the distances between them. Given such a graph, you can answer questions such as ``What is the shortest distance between LAX and JFK?'' or ``What is the shortest route that visits all of the cities?''

**Figure:** Real-world examples of graphs.

An electric circuit can also be viewed as a graph as shown in Figure (b). In this case the points in the graph indicate where the components are connected (i.e., the wires) and the lines represent the components themselves (e.g, resistors and capacitors). Given such a graph, we can answer questions such as ``What are the mesh equations that describe the circuit's behavior?''

Similarly, a logic circuit can be reduced to a graph as shown in Figure (c). In this case the logic gates are represented by the points and arrows represent the signal flows from gate outputs to gate inputs. Given such a graph, we can answer questions such as ``How long does it take for the signals to propagate from the inputs to the outputs?'' or ``Which gates are on the critical path?''

Finally, Figure (d) illustrates that a graph can be used
to represent a *finite state machine*.
The points of the graph represent the states
and labeled arrows indicate the allowable state transitions.
Given such a graph, we can answer questions such as
``Are all the states reachable?''
or ``Can the finite state machine deadlock?''

This chapter is a brief introduction to the body
of knowledge known as *graph theory* .
It covers the most common data structures for the representation of graphs
and introduces some fundamental graph algorithms.

- Basics
- Implementing Graphs
- Graph Traversals
- Shortest-Path Algorithms
- Minimum-Cost Spanning Trees
- Application: Critical Path Analysis
- Exercises
- Projects

Copyright © 2003, 2004 by Bruno R. Preiss, P.Eng. All rights reserved.