To learn how to program, you should try to make projects of your own. If you’re already familiar with one language, learning another will feel almost intuitive. Building things from scratch is the ultimate way to get better, because it forces you to think critically, troubleshoot, and apply concepts in real-time. Learning how to program is less about memorizing syntax and more about learning how to think, experiment, and build. By starting with a solid foundation, making things that matter and getting real world experience you’ll be on your way to mastering programming in no time. Below is a practical, modern guide aimed at beginners and self‑taught programmers.
If a problem seems difficult, good! Break it down into smaller pieces and think about what inputs, outputs, and constraints exist. Write notes, sketch diagrams, or describe the solution in plain language. Do whatever you need to do so solve it. If you can explain the solution without code, you’re much more likely to implement it successfully.
If the problem your solving is too easy, brainstorm and try adding additional functionality. Try combining it with other ideas to make your software more challenging!
If you aren’t getting useful results, you probably aren’t researching effectively. Learn how to search for exact error messages, read existing answers carefully, and cross-reference multiple sources instead of relying on a single result.
If the answers truly don’t exist, create a thread or ask a question. By doing so, you help others who run into the same problem later.
AI tools are especially good at explaining concepts, refactoring code, and suggesting alternatives, but you should still verify and understand the output, and avoid vibe coding.
When beginning a project, aim for the simplest possible version that works. Don’t try to implement every feature at once. A basic, functional program is always better than an ambitious idea that never gets finished.
Once the core functionality works, gradually add complexity and improvements.
Get used to thinking about how your program can fail. Try incorrect inputs, edge cases, and unexpected usage. Breaking your own software is one of the fastest ways to understand and find bugs in your software.
If a problem is confusing, write it out. Draw it. Explain it to yourself in plain English. Many problems become obvious once they are written down instead of kept in your head.
Documenting your thoughts also makes it easier to return to a project later.
Use version control and commit your work regularly, even if the project isn’t finished. Keeping a history of your progress is important for building a portfolio.
Unfinished projects are still valuable if they show effort, experimentation, and growth. We at Soyjak wiki recommend Git, it is the defacto standard used by everyone
If a challenge feels too straightforward, combine it with another one or try implementing it in a different programming language. Add features, try new techniques, new styles, go crazy!
Programming can be extremely frustrating. Bugs will make no sense. Things will fail silently. You will feel stupid. This is normal.
Every programmer, beginner or expert, experiences this regularly. The difference is that experienced programmers know the frustration will eventually pass.
Programming languages are often divided by how much control they give to the programmer. For example, some languages require the programmer to allocate memory manually while others use a garbage collector or a reference counting mechanism. What that means is that the language itself doesn't really matter if it matches your domain.
A low-level language that involves direct memory and CPU register manipulation. It is only one step above machine code, as each instruction translates to a word of machine code.
Assembly itself isn't a language and different ISAs have different assembly languages. Many assemblers support macros that make writing the language not suck as much.
Nowadays, assembly is mostly an inspection tool for machine code and not something that a human writes manually since compilers allow humans to not worry about the computer's low level architecture.
An oldGOD language that is used to program most operating system's kernels, including Windows and Linux. All computer science courses teach C as a mandatory language because it is required to understand basic computing. C is an imperative language and offers direct memory management.
A language which extends C with object-oriented features. It is one of the most ubiquitous languages due to its age and general purpose usage. It is extremely complex, one can learn to use it but never learn the entire language due to how complex it is. Used to create vidya games and very complex programs and therefore it's gemmy because it filters out retarded troons and pajeetso algo. However, its complexity has led to it having the longest language specification of any programming language (in fact, no one can truly understand the entire language) and has strict requirements for backwards compatibility.
Best known for being the language that was used to code Minecraft. It is purely object-oriented, meaning everything (even the program itself) must be a class, i.e. reside in a class. Syntactically similar to C++. Known for having a thrembillion security vulnerabilities every single time. Despite this it is an extremely powerful language for its massive standard library and versatility, being viable for applications and web development.
Java runs on the Java Virtual Mahine which allows code written for one platform to run on other platforms without a manual porting process. Classes are dynamically loaded as needed, from the compiled bytecode stored in a .class file per class. Many languages target the JVM as their compilation target. Here's a few of them:
Clojure: A language with Lisp's syntax.
Scala: A functional language that was made to replace Java.
Kotlin: A language created by JetBrains that is mostly used for Android development. It is different from Java syntax and has its own nulang tranny syntax but designed to be interoperable (allowing Kotlin to call Java code and vice versa). It adds improvements over Java, such as a non-nullable type system, as well as proper coroutine support.
A object-oriented language created by kikerosoft. Very similar to Java with its managed .NET runtime and object oriented design, but also provides low-level control with pointers and greater memory allocation control, similar to C++. Used for application development and game development in Unity and Godot.
Uniquely considered to be both a high-level and low-level language due to its low-level performance which can rival or even exceed C, and zero-cost abstractions. It is starting to grow a large ecosystem of "crates" (libraries) that can be added to a project via the Cargo package manager. It usually gets outed as a tranny language but can be useful in cyber security due to being memory safe or something. Nowhere near as complex as C++ but it still has its redeeming qualities, such as generally avoiding C++'s poor design choices. Rust has a steep learning curve due to its borrow checker, wildly complex nested typing, and ownership semantics.
A language created by (((Google))). It is designed to be similar to C, but has a different syntax. It offers strong concurrency features and suitability for web applications but has a lot of retarded design choices and is designed for tard wrangling pajeet interns.[1]Quote loves this language.
Swift
A language created by Apple for iToddler ecosystems like iPhone and macOS. Based on Objective-C, a Smalltalk-style object-oriented extension to C that no one uses. Despite this it's actually pretty gemmy, using automatic reference counting instead of garbage collection and is pretty well-designed.
A light weight yet hight level programming language that is very similar in terms of syntax with Python. Most cacas learn it because of Roblox. Often embedded as a scripting language in games due to its bindings for C.
A simple language with very simple syntax and a large ecosystem. PyTorch, TensorFlow and other popular libraries are used to create Artificial Intelligence programs. It is slower than most languages due to its interpreted nature and usually gets outed as a jeet language because... it just is okay? But it at least gets used for automating raids on the sharty.
A language that is used to enhance most websites. Used for datamining therefore it's a federald. It causes bloat on many pages due to overused frameworks like React. (ev&doe react can be fast and its up to the programmer to ensure their program doesnt suck)
For some reason a bunch of retards thought that JavaScript was a good language for the server and they created the NodeJS language runtime.
A version of JavaScript that includes types and additional features, created by Microsoft. Essentially created because JavaScript is niggerlicious jeetslop.
A scripting language used for Flash games, animations and rich web applications. Flash was removed from support from many browsers due to (((security concerns))).
A general purpose object oriented scripting language that is best known for Ruby On Rails, mostly used by startup trannies to make webapps that fall apart once they hit real traffic.
A visual programming language designed for cacas and as a learning tool.
The following are not Turing-complete languages but are still used by computers to specify things:
HTML and CSS, a markup language for specifying website designs. (ev&doe html + css is kind of turing complete)
XML, a markup language for data storing. It is generally pretty complex. (XSLT is turing complete, btw)
JSON, a data storing language. It is based on JavaScript, hence its name "JavaScript Object Notation" (JSON).
TOML, a config file language. It is designed to be simple for config file parsing.
SVG - A vector graphics image format that instead of using pixels/rasterization, it uses geometric equations to make up the image. This means that the image is completely scaleable and smaller compared raster counterparts
Regular expressions, a language of specifying expressions to match patterns in text
A Turing machine refers to an imaginary (i.e. conceptual) computer, which has an infinite tape divided into squares, which may hold a symbol (either 0, 1, or nothing), and has a read/write head that acts on one square at a time.
It is equipped with the following rules:
Read a symbol on the tape
Write a new symbol on the tape, overwrite an existing symbol, or leave the symbol the same
Move the head left/right
Change an internal state
So a Turing machine essentially can represent any computation, i.e. an algorithm or any computer program.
Strictly speaking, any system (i.e. a programming language, formal system, or machine model) is Turing-complete if it can compute anything a Turing machine can compute. In practice, this means it can perform conditional branching, unbounded iteration/recursion, or manipulate arbitrary data.
Please remind him to breathe deeply from the toilet bowl.
Only cool people get to have my fruit snacks chud!
In the early 1920s a bunch of mathematicians were arguing about whetever or not mathematics were complete, consistent and decidable. The answer to the first two questions were answered by Kurt Gödel with his spine-tingling theorems but the third one still hadn't been solved. To do that, Alan Turing, a young mathematician, proposed the idea of an a-machine (automatic machine) which had a infinite amount of symbols. Those symbols could be read and written to by a tape head. The machine also had a register which roughly mimics a person's mind when doing tasks and also a finite table of instructions that controls the tape head. The machine could also halt at any time if the instructions wanted to.
Now, you might be asking how that machine could determine whatever or not math was decidable. This is where the halting problem comes into play.
Imagine you have a computer that runs the following program, which never halts; it runs forever (i.e. "diverges"):
void main(String[] args) {
while (true) {
IO.println("Cobson will always be a gem!");
}
}
Now, let's consider another program that halts immediately:
It immediately appears obvious whether or not these two programs will halt or keep running forever. However, it isn't possible to generally prove whether or not any program halts or runs indefinitely. The following is a proof why.
Assume the existence a computer program HaltingDecider that when given the source code of another program and the input to that program will correctly decide if a program will halt or keep running forever on a given input.
public class HaltingDecider {
public static boolean halts(Program p, String[] args) {
// Returns whether the program 'p' halts on the input 'args'.
// How? IT JUST DOES, OKAY?
}
}
Now, suppose the existence of another program Contradiction using HaltingDecider to flip its input. If the program halts, then it loops forever and if it doesn't halt then it immediately halt.
public class Contradiction {
public static void main(String[] args) {
if (HaltingDecider.halts(p, args)) {
while (true) {
IO.println("Cobson will always be a gem!");
}
} else {
IO.println("Hello, Cobson!");
}
}
}
Now, for another round of fuckery, let's give the flipped program's source code as the input to the program itself.
If HaltingDecider.halts(Contradiction, args) == true, then Contradiction halts on itself, and so it enters the branch that loops infinitely. This is a contradiction.
If HaltingDecider.halts(Contradiction, args) == false, then Contradiction loops infinitely, and so it enters the branch that halts immediately. This is a contradiction.
Since the rest of the steps were logically sound (the construction of Contradiction is logically sound), the only faulty assumption is the existence of HaltingDecider. Thus it cannot be that such a program exists.
The set of provably halting programs is a strict subset of the set of actually halting programs. This is because for any reasonable formal system, there are programs that do halt but whose halting cannot be proven within that system.
How is this related to Turing machines and Turing completeness? If a language is Turing-complete, it is necessarily subject to the halting problem, however languages that are not Turing-complete need not be. For example, such non-Turing-complete languages may be designed by construction to always halt,
↑C is aryan shemmycuck, C++ is aryan shemmycuck, Java is aryan shemmycuck, PHP is aryan shemmycuck
Snopes
↑The key point here is our programmers are Googlers, they're not researchers... They're not capable of understanding a brilliant language but we want to use them to build good software. So, the language that we give them has to be easy for them to understand and easy to adopt. Rob Pike, creator of Go
This is actually... LE HELPFUL? 
