A few weeks ago I decided that I’ll be off to Indiana University in the fall to start a phd program in computer science. I’m very excited about the program, and I’m also excited about living in Bloomington. It seems like a great little town (that’s a bit warmer than Chicago!).
I’ve already started to study for my free shot at the written qualifiers. One of the suggested books was compared to what? by Gregory Rawlins, a professor at Indiana. Unfortunately the book is out of print (I picked up a used copy), but the first chapter has one of the most insightful introductions to algorithms analysis. It does an excellent job of explaining why we care about an algorithm’s running time and how our ‘model’ (i.e. what operations we are concerned with, what we are trying to optimize for, etc) greatly influences the analysis. I’ve stared at plenty of proofs and suffered through some big-oh notation, but it’s nice to step back and see what the point is. It actually makes algorithms more exciting.
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