messy asf, a proper hobbiest system

mostly runs jellyfin for a group of about 30 users (2 or 3 on at most times). runs alpine on bare bones. the box was originally filled with foam cutouts from storing iPads in a school district I worked at. I figure it’s 20tbs of storage is a welcome upgrade. it stays cool cause I cutout half the side and put an AC fan in there. future upgrades involve the Nvidia k40 card I have, but I need to design an active cooling system for it before it can be installed as that thing gets HOT

I’m in the same boat. I was a kde neon person for a very long time, but I eventually got tired of some weird issues I was having that I couldn’t find a fix for. tried fedora on a bit of a whim and everything just worked. Nvidia drivers were a breeze to set up, gnome is very nice out of the box and doesn’t take the configuring I’m used to on kde, and even just having gnome boxes pre installed is super useful and I get to skip the virtualboxes setup. very impressed with it overall. never going back

yes, if you change the problem, you change the way we respond. that’s why there’s so many trolley problems spin offs in the first place

an entire section on race conditions I see

damn. that’s one hell of a family relic. sorry for your losses and I hope there’s a long time before you have to see it again.

true! connotation is a weird thing.

don’t get discouraged. sorting algorithms occur frequently in interviews, and yes you use them a decent amount (especially in languages without built in sorts like c) but they are one of the harder things to visualize in terms of how they work. I’d say avoid anything recursive for now until you can get selection and insertion down pat. check out geeksforgeeks articles on them, but also don’t be afraid to Google willy nilly, you’ll find the resource that makes it click eventually.

in terms of efficiency, it does become a little more difficult to grasp without some math background. big o is known as asymptomatic notation, and describes how a function grows. for example, if you graph f1(x)=15log(x) and f2(x)=x, you’ll notice that if x is bigger than 19, then f2(x) always has a higher output value than f1(x). in computer science terms, we’d say f1 is O(log(n)), meaning it has logarithmic growth, and f2 is O(n), or linear growth. the formal definition of big o is that f(x) is O(g(x)), if and only if (sometimes abbreviated as iff) there exists constants N and C such that |f(x)| <= C|g(x)| for all x>N. in our example, we can say that C = 1, and N>19, so that fulfills definition as |15log(x)| <= 1|x| whenever x>19. therefore, f1(x) is O(f2(x)). apologies for just throwing numbers at you, (or if you’ve heard all this before) but having even just the most basic grasp of the math is gonna help a lot. again, in terms of best resources, geeksforgeeks is always great and googling can help you find thousands of more resources. trust that you are not the first person to have trouble with these and most people before you have asked online about it as well.

I also highly reccomend grabbing a copy of discrete mathematics and it’s applications by Kenneth Rosen to dig farther into the math. there’s a few other types of asymptomatic notation such os big omega and big theta, even little o, that I didn’t mention here but are useful for comparing functions in slightly different ways. it’s a big book but it starts at the bottom and is generally pretty well written and well laid out.

feel free to dm me if you have questions, I’m always down to talk math and comp sci.

edit: in our example, we could also pick c =19 and n = 1, or probably a few other combinations as well. as long as it fills the definition it’s correct.

female as an adjective for clarification (like “oh you’re looking for that female doctor over there”) is ok, female as a noun is just weird

that’s how they get ya