I saw something that said “in industry basically 95% of what you do is just fancy CRUD operations”, and came to realize that held true for basically anything I’ve done in industry. It’s boring

I miss learning real computer science in school. Programming felt challenging, and rewarding when it was based in theory and math.

In most industry experience we use frameworks which abstract away a lot, and everything I’ve worked on can be (overly) simplified down to a user frontend that asks a backend for data from a database and displays it. It’s not like the apps aren’t useful, but they are nothing new, nothing that hasn’t been done before, and don’t require any complex thinking, science, or math in many ways.

In the early 90s I was given access to a transputer array (early parallel hardware) but I had to learn Occam to run code on it.

I know C is programing language. It is not architecture specific. One writes the source code and a compiler turns it into an executable depending on what settings you tell it. So the same source code would output different executables depending on what you want to run it on and what optimization options are on. Assembly languages on the other hand are architecture specific. Is C "Assembly-like"? To be honest I'm not sure what would be Assembly-like. I guess if a program written in multiple languages that have the same behavior, if the C version (using something like GNU C Compiler) looked closer to its assembly than, say its Java version (GraalVM), then that counts.

It would have functionally no use and would never be spoken. I still say we need a name for it.

For example, for me it's binary. It's not hard at all, and I know that, but for some reason handling and reading binary data just always hurts my brain for some reason and I mess up

If all computers just went out at the same time what would happen? Would all the data not stored on drives be lost? Would it be rebootable if that happened?

Anytime I talk to someone online or in person about comp sci they just complain about it I’m I the only one who genuinely likes programming or I’m I just a masochist

I'm currently making a list of some of the best/most influential/most well known computer science books to one day put on my shelf after reading them. I've currently got Knuths art of computer programming volumes 1-4b, structure and interpretation of computer programs (the wizzard book), compilers: principles, techniques, and tools (the dragon book), Tanenbaums operating systems design and implementation (the minix book), and the 3 unix books (the c programming language, design of the unix operating system, and the unix programming environment). I'm thinking of adding some of o'reillys more famous publications such as learning perl and programming perl (the lamma and camel books respectively), learning the vi and vim editors, sed and awk, and classic shell scripting. Is there anything I'm missing?

This is from a Python script I wrote. It runs the same size of array 10 times with random values and takes the mean of those values. I did this for arrays from size 1 to 500.

Eventually we can only shrink transistors to be so small. Once we get to the size of the atom; we are really done in terms of miniaturizing them

Does computing proficiency then end entirely or will there be workarounds to make even more advanced computers?

I dedicated three years, starting at the age of 16, to tackling the Travelling Salesman Problem (TSP), specifically the symmetric non-Euclidean variant. My goal was to develop a novel approach to finding the shortest path with 100% accuracy in polynomial time, effectively proving NP=P. Along the way, I uncovered fascinating patterns and properties, making the journey a profoundly rewarding experience.
Manually analyzing thousands of matrices on paper to observe recurring patterns, I eventually devised an algorithm capable of eliminating 98% of the values in the distance matrix, values guaranteed to never be part of the shortest path sequence with complete accuracy. Despite this breakthrough, the method remains insufficient for handling matrices with a large number of nodes.
One of my most significant realizations, however, is that the TSP transcends being merely a graph problem. At its core, it is fundamentally rooted in Number Theory, and any successful resolution proving NP=P will likely emerge from this perspective.
I was quite disappointed in not being able to find the ultimate algorithm, so I never published the findings I had, but it still remains one of the most beautiful problems I laid my eyes on.

Edit: I have some of the early papers of when I started here, I doubt it's understandable, most of my calculations were in my head so I didn't have to write properly: https://acrobat.adobe.com/id/urn:aaid:sc:us:c4b6aca7-cf9f-405e-acfc-36134357f2dd

Edit: I'm not trying to validate my findings on reddit, I was just discussing the general behaviour of TSP after observing thousands of matrices, I'm 20 now and have moved on from this problem and not working on it anymore.

Would you have preferred it to be different?

OK. So I’ve been looking at Conway’s game of life a little bit. And I was fascinated by the idea that it could be used to recursively imitate itself (look up OCTA’s supercell)

I was told that this is Turing complete, and I had to look up what that meant.

And it seems to mean that, in simple words, it’s a computer or system of computer rules that can model another computer.

Now, given that humans came up with all of these computers in the first place, and all of the rules, does this mean that we are Turing complete?

So the way it was explained to me, floats are prefered because they allow greater range, which makes a lot of sense.

Reasonably, in most games I imagine that the slowest an object can move is the equivalent of roughly 1 mm/second, and the fastest is equivalent to probably maximum bullet velocity, roughly 400 meter/second, i.e. 400,000 mm/second. This suggests that integers from 1 to 400,000 cover all reasonable speed ranges, i.e. 19 bits, and even if we allowed much greater ranges of numbers for other quantities, it is not immediately obvious to me why one would ever exceed a 32-bit signed integer, let alone a 64-bit int.

I'm guessing that this means that there are other considerations at play that I'm not taking into account. What am I missing folks?

EDIT: THANK EVERYBODY FOR THE DETAILED RESPONSES!

Don’t quantum computers require specialised super cooling that only exists in a few places around the world? How could some rogue hacker get a hold of that in the first place

Hey folks,

I’m working on a YouTube channel where I break down computer science and low-level programming concepts in a way that actually makes sense. No fluff, just clear, well-structured explanations.

I’ve noticed that a lot of topics in CS and software engineering are either overcomplicated, full of unnecessary jargon, or just plain hard to find good explanations for. So I wanted to ask:

What are some CS, low-level programming, or software engineering topics that you think are poorly explained?

• Maybe there’s a concept you struggled with in college or on the job.
• Maybe every resource you found felt either too basic or too academic.
• Maybe you just wish someone would explain it in a more visual or intuitive way.

I want to create videos that actually fill these gaps.
Thanks!

Update:

Thanks for all the amazing suggestions – you’ve really given me some great ideas! It looks like my first video will be about the booting process, and I’ll be breaking down each important part. I’m pretty excited about it!

I’ve got everything set up, and now I just need to finish the animations. I’m still deciding between Manim and Motion Canvas to make sure the visuals are as clear and engaging as possible.

Once everything is ready, I’ll post another update. Stay tuned!

Thanks again for all the input!

Obviously computer science is a very broad topic. What are some fields or sub-fields within a larger field where research has been stagnant or hit a dead end?

I think Assembly language is like LEGOs. You get raw, simple blocks like ADD and SUB, and you can build anything with them. These concepts are easily gamified and align well with how kids think. It isn't as complex as some people assume. Some might ask what the reason is, but I think it is a fun way to introduce them to computers.

Why are recursive functions sometimes used? If you want to do something multiple times, wouldn't a "while" loop in C and it's equivalent in other languages be enough? I am not talking about nested data structures like linked lists where each node has data and a pointed to another node, but a function which calls itself.

I am a Computer Science graduate and I have some background knowledge in CS in general but I am not really aware of the security field. I was reading a book called 'The Palestine Laboratory' which details how Israeli spywares have hacked into all kinds of devices. There was one incident of how Facebook sued NSO for exploiting a bug in their WhatsApp app they didn't have any easy fix to. I am wondering how come the security of our personal devices is so vulnerable and weak? And what is the future of cybersecurity and privacy in general? I know it can be a bit of a naive question, but any insights, comments on whether a research career in cybersecurity is worth it or how does it look like, etc?

This is the only place where college, career, and programming questions are allowed. They will be removed if they're posted anywhere else.

HOMEWORK HELP, TECH SUPPORT, AND PC PURCHASE ADVICE ARE STILL NOT ALLOWED!

There are numerous subreddits more suited to those posts such as:

/r/techsupport
/r/learnprogramming
/r/buildapc

Note: this thread is in "contest mode" so all questions have a chance at being at the top

Edit: For a little encouragement, anyone who gives a few useful answers in this thread will get a custom flair (I'll even throw some CSS in if you're super helpful)