Compiled vs Interpreted Programming Languages: Key Differences

It turns out that a programming language optimized for developer happiness is also optimized for Large Language Models. #RubyLang #Ruby https://lnkd.in/gfA7VWCf

We have actually spent years thinking and debating which is the best programming language . Either python , Java or C++ and so many more . But I just saw somewhere that in today’s world it’s neither of these languages . You know what is the most powerful coding language ? ITS ENGLISH . With the right prompt we can design systems , generate production ready code, automate workflows , debug errors , write tests and even document the architecture and all of these without even touching the traditional syntax first . From moving from “how to code” to “how to correctly describe a problem”. Clarity >>> syntax Best developers won’t just be good coders but also be great communicators . #Ai #PromptEngineering #FutureOfWork #Coding #Innovation

Programming languages are just wrappers. Logic is the core. 🍫💻 JavaScript. Python. Java. C#. PHP. Different syntax. Different ecosystems. But underneath? Same fundamentals. 👉 Variables 👉 Loops 👉 Conditions 👉 Data structures 👉 Algorithms You can switch languages. You can switch frameworks. But if your fundamentals are weak, the wrapper won’t save you. C++ in this image is symbolic — it represents core programming concepts. Master the core once, and every new language becomes easier. Stop chasing languages. Start mastering problem-solving. #Programming #Coding #DeveloperMindset #LearnToCode #DSA #ComputerScience #SoftwareEngineering #FullStackDeveloper #TechLife #CodeWithMishu 🚀

Do LLMs change the energy trade-off in coding? While LLMs make dynamic languages like Python faster to write, research shows compiled languages (C, C++, Rust) remain far more energy-efficient at runtime. In high-scale systems, runtime efficiency usually outweighs development speed. The best balance? Python for productivity, Rust/C++ for performance. Sources 1. Pereira et al., Energy Efficiency Across Programming Languages: How Do Energy, Time, and Memory Relate?, ACM (2017) — https://lnkd.in/eHYUCp6v 2. Which Programming Language Is Best for Claude Code? — https://lnkd.in/eJungxPN

# Understanding Code: A Communication Analogy Code is essentially our communication style with computers. Think of Python as akin to English – widely known, readable, and accessible. Java, on the other hand, is like German – highly technical, precise, and specific in its requirements. JavaScript, much like spoken Spanish, is fast-paced, vibrant, and fluid. It allows for rapid development, powering much of the modern web. Each language has its own rhythm and purpose, enabling diverse forms of digital creation. Ultimately, the same message can be conveyed in multiple ways across different languages, highlighting the nuance in how we instruct machines. #Programming #TechExplained #CodingLanguages #Python #JavaScript #Java

💻 Understanding Function Overloading vs Function Overriding While learning Object-Oriented Programming, two important concepts that every developer should understand are Function Overloading and Function Overriding. Both improve code flexibility and reusability, but they work in different ways. 🔹 Function Overloading Function Overloading allows multiple functions to have the same name but different parameters (different number or type of arguments). It helps developers write cleaner and more readable code by performing similar tasks using the same function name. 🔹 Function Overriding Function Overriding happens when a child class provides a specific implementation of a method that is already defined in its parent class. It is a key concept of runtime polymorphism and helps achieve dynamic behavior in object-oriented programming. 📌 Key Difference: • Overloading → Same function name, different parameters (Compile-time polymorphism) • Overriding → Same method in parent and child class with same signature (Runtime polymorphism) Mastering these concepts helps developers build scalable, reusable, and maintainable applications. #Programming #OOP #SoftwareDevelopment #CodingConcepts #Java #CSharp #Python #LearningJourney

How much does it cost to to generate code in different programming languages? As LLMs write increasing amounts of our code, I started wondering: what is the impact of the language choice on the token cost? I ran an experiment to find out: 8 languages, 2 OpenAI models, 7 programming tasks, all output validated by compilation. The differences can be substantial. Java's error handling costs 533 tokens because the model has to generate an entire generic Result class. Rust does it in 256 tokens. C needs 1,025 tokens for word frequency counting while Python does it in 489. It turns out that built-in abstractions and low-ceremony syntax consistently cut token costs in half. I also threw in Glyph, a compiled language that I'm developing, with a design goal of reducing model token cost while maintaining human legibility. Current models don't know about it, so every prompt needs a ~1k token description, and it still lands mid-pack overall, and has token costs that are similar to Rust and Go. For full results and all generated code see: https://lnkd.in/gM8nmdu7

Coding in C++ is nice. I've been playing around with writing something in C++, and I've come to realize just how powerful this language is. I do most of my work in TypeScript, which is a super super high level language. C++ is a whole different beast. Not just the actual programming aspect of it. I've definitely gotten better from not being able to parse compiler errors (AI helps a lot with that), but I still can't rap my head around installing libraries. Like it took me several hours to build boost. It may be a symptom of my Windows usage, but alas. Anyway, C++ is nice to write. Today, I was using it to write some code to create splines, which are basically mathematical expressions to draw a curve between some points. I got to write out the derivation, and then I could just write that derivation out in code because I could just create a custom vector implementation (not std::vector, but a mathematical vector) with operators and what not, and then just write out the math. It's very elegant and makes me very happy. I also appreciate the class system, though its much more complicated than TypeScript or Java. It force you to make good design decisions. In this project, I haven't gotten to any points of serious memory management, but I imagine there will be lots of learning there. Also, sidenote... why not Rust? One word: CUDA. Rust, despite being more memory safe, is not good for scientific computing, and I'm working on a simulation tool, so I'll have to deal with the memory management when it comes.

🚀 Demystifying the "this" Pointer in C++ While exploring Object-Oriented Programming in C++, I revisited a small but powerful concept — the "this" pointer. In C++, every non-static member function has access to a hidden pointer called "this", which points to the "current object" that invoked the function. But why is this important? Consider a constructor where the parameter names are the same as the class attributes. Without "this", the compiler cannot distinguish between them. That’s where "this" becomes useful. class Teacher { private: double salary; public: string name; string dept; string subject; Teacher(string name, string dept, string subject, double salary) { this->name = name; this->dept = dept; this->subject = subject; this->salary = salary; } }; Here: this->name → refers to the class member variable name → refers to the constructor parameter So the statement: this->name = name; means: 👉 Assign the parameter value to the object's member variable. 💡 Key Insight The "this" pointer always refers to the object that calls the member function. Example: Teacher t1("Dhiraj","CSE","DSA",35400); Inside the constructor, this points to t1. 📌 Why developers use this ✔ Resolves naming conflicts between variables ✔ Improves code readability ✔ Helps in method chaining ✔ Essential for advanced OOP concepts 🔍 Takeaway Small concepts like the this pointer are the building blocks of deeper C++ understanding. Mastering these fundamentals makes it much easier to understand advanced patterns in Object-Oriented Programming. #Cplusplus #CPP #Programming #OOP #CodingJourney #SoftwareDevelopment

🧠 The Skill That Matters More Than Any Programming Language In tech, people often ask: “Which language should I learn next?” Python? Java? SQL? Go? But over time, many professionals realize something important. Languages change. Tools evolve. Frameworks come and go. The real skill that stays valuable is problem solving. Being able to understand a problem, break it into smaller parts, and think through a solution is what truly makes someone effective in tech. The language you use is just the tool. Two people can know the same programming language, but the one who understands the problem better will almost always build the better solution. That is why experienced developers often focus less on tools and more on thinking. Because once you understand the problem well, learning the tool becomes much easier. 💬 Question What skill do you think has helped you the most in your tech journey? #TechCareers #ProblemSolving