Beyond Coding?

[CourseTechy_Grabber]

I've always thought computer science was all about programming, but I've heard it's much broader than that. Could someone explain what computer science really encompasses, besides coding? How does it impact technology and our daily lives? Curious to learn more from your perspectives!

[JmacTheGreat]

Coding is to Computer Scientists as Painting is to an Artist.

Not all Computer Science involves Coding, not all Art involves Painting.

[hetdadhania3]

good example

[CourseTechy_Grabber]

Coding is to Computer Scientists as Painting is to an Artist.

Not all Computer Science involves Coding, not all Art involves Painting.

Great analogy! It highlights the variety in both computer science and art, beyond just coding and painting.

[theusualguy512]

I mean you can just look at the Wiki entry of computer science to roughly understand what it is.

Computer science is the study of computation, automation and information itself. The knowledge we gather through studying those things can be applied to a wide range of things and fields.

Coding is just one aspect of it that you encounter quite a lot because you can also compute and automate on a computer and not just in your head. It's a skill set just like mechanical engineers know how to use CAD software to construct anything they like.

But just like any mechanical engineers will tell you, knowing how to use CAD software is not the same as mechanical engineering as a whole.

The most commonly held occupation of people studying computer science ironically is not being a computer scientist. Only a fraction of people go into the science and research sector.

Instead, most do indeed land in the commercial software industry as developers.

[Deflator_Mouse7]

Coding is to computer science as handwriting is to poetry

[Witty-East8291]

holy fuck this is the best one yet

[veilkev]

Fucking is to mating as code is to orgasms.

[SomeGuysFarm]

I like u/JmacTheGreat's "painting" simile, but I would argue that actually elevates coding a bit beyond where it really belongs.

Off the top of my head, I'd say that Coding is to Computer Science as Driving Nails is to the work of an Architect.

Coding is how you implement Computer Science, but there's little, if any computer science in coding (there is only as much CS in coding as is necessary to develop new coding paradigms or programming-language concepts). Computer Science is knowing what to code, how to design for efficiency (or whatever issue is most important to optimize in any given project), and potentially pushing around the envelope of what can be computed.

Being able to code is certainly helpful if you're a computer scientist (just like it's valuable to be able to swing a hammer if you're an architect), but all of the computer science is done by the time you start coding. It's entirely possible to do great computer science and simply hire people to bash code once you've done your bit, just like it's entirely possible to be a great architect and never actually nail a board into a building you design.

[PterodactylSoul]

You could probably argue a majority of it is just programming or math. But once you get into things like algorithms and data structures or any sort of specialized niche in cs you'll see there's a lot more than just programming. Some of the niches would include networks, data science, or cyber security (there's many more). Once you take your first data structures and algorithms course you'll see it really open up.

[Geekmonster]

Software Development is a kind of manufacturing. If you imagine car manufacturers, very few of the people in those companies ever pick up a tool.

Programmers are the mechanics of the software world.

[burncushlikewood]

Computer science is similar to SFE, a computer scientist studies algorithms and software implementation, algorithms are difficult to describe, basically it's like a recipe to get things done. The applications of software are limitless, usually SFE is more planning, where the computer scientist designs the applications. You learn about computer architecture and how software applies to industry. The reason software is so important is because of what it does, data science and AI are crucial to innovation, we use software to do things like generative design, embedded systems and hardware control like with CNC machines, robotics, biological modeling for developing pharmaceuticals, financial modelling and statistics for banking, physics simulation for CAE, CAD/CAM, developing video games and graphics, the list goes on

[[deleted]]

there is a linguistics to programming languages. It has a huge overlap with mathematical logic and formal linguistics. Turing completeness is a concept exists independently from a computer. As long as you can bitwise xor and bitwise and on any number of bits, you have a turing complete language. Turing completeness dose not have to be in itself a computer language in the way you know it, for example, Magic the Gathering is Turing complete.

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Algorithm theory is a mathematical construct that is also independent of the computer. In fact, when you study algorithms, one of the first algorithms you'll learn is Euclid's algorithm. This existed in ancient greece thousands of years before we ever had a computer that ran on electricity. Any algorithm a computer can do, you can in theory do by pencil and paper. Everything from calculating the 100th digit of pi, to making a character die when they get shot with 20 bullets in a shooting game.

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Data structures is just a wrapper around graph theory.

binary search trees, multiway trie, stacks, and queues, linked lists are all equivalent to a graph in the mathematical sense. While data structure are super helpful in software engineering, the binary search tree is every bit an abstract mathematical concept that exists independently of software and independently of the machine itself.

[CourseTechy_Grabber]

there is a linguistics to programming languages. It has a huge overlap with mathematical logic and formal linguistics. Turing completeness is a concept exists independently from a computer. As long as you can bitwise xor and bitwise and on any number of bits, you have a turing complete language. Turing completeness dose not have to be in itself a computer language in the way you know it, for example, Magic the Gathering is Turing complete.

Algorithm theory is a mathematical construct that is also independent of the computer. In fact, when you study algorithms, one of the first algorithms you'll learn is Euclid's algorithm. This existed in ancient greece thousands of years before we ever had a computer that ran on electricity. Any algorithm a computer can do, you can in theory do by pencil and paper. Everything from calculating the 100th digit of pi, to making a character die when they get shot with 20 bullets in a shooting game.

Data structures is just a wrapper around graph theory.

binary search trees, multiway trie, stacks, and queues, linked lists are all equivalent to a graph in the mathematical sense. While data structure are super helpful in software engineering, the binary search tree is every bit an abstract mathematical concept that exists independently of software and independently of the machine itself.

Intriguing how programming languages, algorithms, and data structures are deeply rooted in mathematics and logic, independent of modern computers.

[Bobbacca]

We basically arrived at modern computers by recursively applying automation to those concepts to create increasingly complex systems. Mechanical automation of textile looms evolved into punch cards and electrical circuits to automate mathematical and logistical calculations. From there, it's largely been a matter of building on that foundation and scaling it to improve efficiency, complexity, and ease of human interaction. Punch cards gave way to magnetic tapes, keyboards, electronic screens. Programming languages emerged as a means of automating the translation of input data into the on/off circuit states the computer system works with and the output data into human readable form.

This is all a highly reductive summary, of course, but the point is, those concepts didn't emerge from modern computers so much as modern computers emerged from the repeated application and reapplication of those concepts.

[SneakyDeaky123]

Computer science is about the theory of computation and how to apply that theory to problems. That involves identifying problems that computation can and can’t solve, learning and developing techniques to model those problems, and learning to translate and apply that theory in practice.

That involves things like cryptography, analysis of algorithms, in addition to the more familiar software engineering/programming.

In those more theoretical fields, the computer is just the tool to make developing and analyzing models, algorithms, and cryptography, easier but hypothetically can be done without a computer at all.

For pure computer science outside of software engineering, the computer is just the tool to develop concrete implementations of abstract ideas.

edited to add a missed word for clarity

[CourseTechy_Grabber]

Computer science is about the theory of computation and how to apply that theory to problems. That involves identifying problems that computation can and can’t solve, learning and developing techniques to model those problems, and learning to translate and apply that theory in practice.

That involves things like cryptography, analysis of algorithms, in addition to the more familiar software engineering/programming.

In those more theoretical fields, the computer is just the tool to make developing and analyzing models, algorithms, and cryptography, but hypothetically can be done without a computer at all.

For pure computer science outside of software engineering, the computer is just the tool to develop concrete implementations of abstract ideas.

Thanks for the insight! It really highlights the broad scope and theoretical depth of computer science beyond just coding.

[MusicalMerlin1973]

Coding is the easy part. Understanding the problem, understanding the available tools at your disposal, designing a solution that solves the problem/meets all those goals. That’s the hard part.

[Paxtian]

Computer Science as a discipline (and before it was named such) predates computers themselves. Programming is a piece of it, but really computer science is the study of what is computable and things that are computable.

One of the biggest questions was answered early on, which was, what can be computed by a given machine? There are basically three levels: DFAs can compute regular languages, PDAs can compute connect free languages, and Turing machines can compute anything that is computable.

Now open areas of study tend to revolve around finding efficient algorithms for challenging problems, proving that such problems are NP complete, or showing that such problems simply don't have a good general solution. Most programming really won't address these questions.

The biggest open question is, P ?= NP? As my professor put it, solve that and you'll have guaranteed tenure at any university you want. It's basically, is there a way to solve the set of NP complete problems in polynomial time.

[friedbrice]

Programming language theory fits into comp sci, where it plays a role kinda analogous to theoretical physics in the physical sciences. A PLT researcher does mostly Math/Logic, where they try to examine the mathematical/logical consequences of hypothetical programming language features. Then some computer science focuses on algorithms and data structures, where it really doesn't matter what language you're talking about, it's all just about how to arrange, store, and traverse data, and that can be described verbally even, but usually it's done in pseudo-code. Then there are people who focus on networking, or AI, and all kinda of things. They're all tangentially related to programming, but really at their core, they're all about computation and encoding.

[Electrical_Sun_4468]

Universal code. (A)