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

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.

There are still jobs where people write frameworks, database engines or version control tools. Those jobs require heavy CS and algorithms, data structures day to day. But there are less of those jobs nowadays as no one is implementing db engine for their app they just use Postgres.

Other jobs that is vast majority is dealing with implementing business logic. Using database with understanding how it works in details is of course going to produce better outcomes. Yet one still can produce great amount of working software without knowing how indexes are stored on disk.

Also a lot of CS graduates fell into a trap where they think their job is to write a framework - where in reality they should just use frameworks and implement business logic- while using CS background to fully understand frameworks already existing.