Empirical results in CS papers I'm new to the CS field and I have noticed that in many of the papers that I read, there are no empirical results (no code, just lemmas and proofs). Why is that? Considering that Computer Science is a science, shouldn't it follow the scientific method?
Implementing algorithms well is a skill which takes a different set of tools than just proving theorems. Many algorithms which were discovered by the theory community have indeed been implemented in practice (although I would like to see the theory community take a bigger role in this process). Physics doesn't ask the same researchers to do theory and experiment, although it is expected that the two groups communicate. Why shouldn't you expect to see the same divide in computer science?

ADDED IN EDIT:

Expanding on my comment in answer to Suresh's about what I meant by "role" above, at Bell Labs and AT&amp;T Labs, researchers in algorithms were encouraged to talk to people in development. I didn't do as much of this as I probably should have, but I did get at least one paper out of it, and I think it would be good for the field if there were more communication between people in theory at universities and practitioners. This doesn't mean that I think everybody who comes up with an algorithm should code it (even if it's practical).

On the other hand, coding algorithms (or having a student code them) that you think might be practical can be useful in getting them adapted by practitioners. Consider one example. Lempel and Ziv wrote two technical papers in 1977 and 1978 on new data compression algorithms. Everybody ignored them. In 1984, Welch wrote a much less technical paper giving a slight twist on LZ78 that improved its performance somewhat, and gave the results of a small study comparing its performance with other data compression methods. It was published in a journal read by a number of programmers, and the algorithm was given by a few lines of pseudocode. The method was quickly adapted in a number of places, eventually resulting in an infamous intellectual property dispute.

Of course, one of the best ways for algorithms researchers to communicate with practice is to produce grad students who go off and work at Google, IBM, or other companies, and we're already doing that. Another way might be to answer practitioner's questions in this forum. Hopefully, we're doing a reasonable job of that as well.