I'd add that evolution works for organisms because they have evolved evolvability. By this I mean that the source code isn't fragile, so that you can take the source code from two organisms of the same (sexually reproducing) species, mix and match them together, and the resulting DNA codes for a viable organism. This even works for closely related species as the existance of mules demonstrates.
Programs written by humans in the sort of programming languages we use do not have this characteristic of robustness.
Genetic programming would work better using languages specifically designed to be robust in this sense.
I used a genetic algorithm to optimize a signal processing routine in my research (I'm a grad student in biological engineering, the project is sizing nanoparticles). It took me 3 days to write and debug a mutation algorithm, a fitness score, and a backbone that iterates breeding a new generation of code and keeping the most fit offspring. I started running the code on a Friday and by Monday morning, at around 500 generations, the fitness score had improved 60%. Colleagues of ours working on a very similar problem spent 3 months doing the same thing manually and only got to about 55% improvement.
I spent that weekend sailing and thinking, I'm glad my computer is doing my work for me right now.