It's easy enough in elementary treatments of probability to say what is meant by random variables X and Y are independent. And in both theory and applications

It's easy enough in elementary treatments of probability to say what is meant by random variables X and Y are independent. And in both theory and applications, independence is just crucial. Well, what about uncountably infinite collections A and B of random variables being independent? Also, random variables that are functions of independent random variables are independent, etc. The sigma algebra generated by a random variable, or a collection of such, is important to be able to work with. E.g., just in the Poisson process, that is, the vanilla arrival process, need to talk about the time to the next arrival being independent of all of the past of the process. > Linux kernel Difficult? Right. No doubt by now it's huge, and I have to believe has many patches. And I have to suspect that it's not well documented. And people that use it especially want it for high end work where they make modifications, and then the problems of complexity, documentation, testing, etc. get much worse. Difficult? Yes. Leading edge, not in the usual sense of knowledge. More broadly, tough to make progress in any sense if still have to spend much effort with the Linux kernel -- we're supposed to be past that by now. This may be wrong for some niche need, but people should try to keep their careers out of such niches. Linux kernel performance? Might want some math there!