Okay, let's do something a little more complicated,
and something in which we've used in our homework assignments.
So in the assignments,
I talked about generating a random graph.
And the random graph has what's called a density, and
the density is roughly speaking how many edges per node are available.
So if I have a density of 0.5,
density will be between 0 and 1.
1 would mean that we have what's called the complete graph,
every possible edge is Is included in the graph.
0 would mean we would have a completely disconnected graph.
We would have nodes but no edges.
Half would mean that if I had a graph which had 100 nodes,
on average there would be 50 edges per node.
That would be a reasonably dense graph for something that large.
And it's very useful to use random generation techniques
because when you start applying graph algorithms
to hard problems, it's hard to get real world data.
So at University of California Santa Cruz,
my colleagues have a huge project in designing
the Internet in the sense of making Internet
connections reliable and optimal.