<p>Most people with a degree in CS will certainly know what <a href="http://www.nist.gov/dads/HTML/bigOnotation.html" rel="noreferrer">Big O stands for</a>.
It helps us to measure how well an algorithm scales. </p>

<p>But I'm curious, how do <em>you</em> calculate or approximate the complexity of your algorithms?</p>

Familiarity with the algorithms/data structures I use and/or quick glance analysis of iteration nesting.  The difficulty is when you call a library function, possibly multiple times - you can often be unsure of whether you are calling the function unnecessarily at times or what implementation they are using.  Maybe library functions should have a complexity/efficiency measure, whether that be Big O or some other metric, that is available in documentation or even
IntelliSense
.