<p>It depends on your random graph model. The simplest model is the <a href="http://en.wikipedia.org/wiki/Erd%C5%91s%E2%80%93R%C3%A9nyi_model" rel="nofollow">Erdős–Rényi model</a>, where you specify the number of nodes and the probability of a link between any given pair. This is easy to generate but the resulting graphs will not be very interesting because they aren't at all similar to most networks observed in the real world. Real-world networks usually have power law degree distributions and higher clustering coefficients. There are a few other standard models you might be interested in that address this (<a href="http://en.wikipedia.org/wiki/Watts_and_Strogatz_model" rel="nofollow">Watts-Strogatz</a> or <a href="http://en.wikipedia.org/wiki/Barab%C3%A1si%E2%80%93Albert_model" rel="nofollow">Barabási–Albert</a>). I have also used the LFR model described in <a href="http://arxiv.org/pdf/0908.1062.pdf" rel="nofollow">this paper</a> which has source code available <a href="https://sites.google.com/site/andrealancichinetti/files" rel="nofollow">here</a>.</p>
Random adjacency list generator
<p>I am currently working on developing an application to find the maximum clique in a graph  for my final year project. I have most the project complete and am just starting to test the application. </p>

<p>The application currently uses an adjacency list as an input and I was wondering if anyone knew of an adjacency list random generator, so I can test my application?</p>

<p>Many thanks </p>