SICP: The only computer science book worth reading twice? (2010)

It’s interesting, SICP and other many other “classic” texts talk about designing programs, but these days I think the much more important skill is designing systems.

I don’t know if distributed systems is consider part of “Computer Science” but it is a much more common problem that I see needs to be solved.

I try to write systems in the simplest way possible and then use observability tools to figure out where the design is deficient and then maybe I will pull out a data structure or some other “computer sciency” thing to solve that problem. It turns out that big O notation and runtime complexity doesn’t matter the majority of the time and you can solve most problems with arrays and fast CPUs. And even when you have runtime problems you should profile the program to find the hot spots.

What computer science doesn’t teach you is how memory caching works in CPUs. Your fancy graph algorithm may have good runtime complexity but it completely hoses the CPU cache and you may have been able to go faster with an array with good cache usage.

The much more common problems I have is how to deal with fault tolerance, correctness in distributed locks and queues, and system scalability.

Maybe I am just biased because I have a computer/electrical engineering background.

I find books like SICP interesting and not very useful. I love reading them because I like this stuff, but I don’t get to apply their teachings in real world software. It’s a problem because naturally I want to spend my time reading these kind of books, but if I do that I would be jobless. I need to divide my time between reading pearls like SICP and boring Kafka/Postgres/Golang/K8s/AWS documentation.