Justin Li

Computer Science Problem Solving


Someone once asked me if studying computer science changes the way I look at the world. I didn't think so at the time, but now I see that maybe there are some influences. I can't say whether it's a good or bad influence, but it definitely makes my thinking a lot more abstract.

Recently, my professor brought up an interesting viewpoint, that programmers are actually using a lot of known solutions in solving problems with the computer. The thought stuck in my mind, and the more I think about it, the more true it seems. Here are a couple analogies that map from computer science to the real world.

The example my professor gave was about traffic lights. Why do we have traffic lights, and what purpose do they serve? After asking a number of exploring questions, we arrive at that traffic lights are really there to ensure a fair sharing of resources, that resource being the intersection of two roads. Since the intersection technically belongs to both roads, it's impossible to say which cars have precedence. The traffic lights are to enforce which cars can go into the intersection at what time.

During the discussion, I eventually realized that traffic lights are actually mutual exclusion (mutex) locks, that prevent two different users from doing something at the same time. If one road's is passing through the intersection, the other road's can't. The whole idea of mutual exclusion, of course, is from memory sharing between processes, and how to prevent one program from overwriting another's work.

The professor then went on to other types of resource sharing, such as a talking stick, which shares the right to talk. Everyone sits in a circle, and who ever has the stick is allowed to talk. The computer analogy to that was a token ring network, which I'm not familiar with.

Here's another fun analogy: sorting. This is a pretty prevalent "problem" in computer science. By "problem" I mean it needs to be done all the time, even though we already know the best way to do it: quicksort. It is interesting to see a number of different types of sorting in real life, however.

For example, if I hand you a deck of cards, how would you sort it? You would probably go through and separate the diamonds from the clubs, hearts and spades, and then sort each one individually. Note however that when sorting each suit, you don't separate the cards into separate piles (say, less than 4, 4 to 8, larger than 8), but might pick out cards in ascending order. Another way to do the same within each suit is to go through the stack and when you get to an out of order card, put it in order in the part you've already gone through.

It turns out that there are algorithms that do all three of these sorting techniques. When the items are put into categories before being sorted, it's called a bucket sort. If you go through the items to pull out the next one in line, it's a selection sort. The last one, because the items are taken out and put into the correct position, is called insertion sort.

I'm sure if I take the time I can think of more examples. My point here though is that computer scientists use a lot of solutions to common problems that we've already solved. We've sorted things before, and have shared resources before, just not on computers. And if the base problem is the same, then why not move the solution over to the domain as well?

Going back to the original question: does studying computer science change the way one thinks? My answer is yes, but only in terms of abstracting out these patterns in life. People don't become bound to certain rules or boxed by their thinking in this way; it will only help by making more connections.