Designing My Own Programming Language with LLVM and Compiler Concepts

🚀 Creating My Own Programming Language: A Technical Adventure In the world of programming, have you dreamed of designing your own language? Recently, I explored this fascinating process, inspired by tools like LLVM and compiler concepts. I share a summary of the key steps I followed to materialize this idea. 🔍 Initial Analysis and Design I started by defining the basic syntax, opting for a simple structure similar to Python but with unique twists to handle mathematical expressions and control flow. I used context-free grammars to model the language, ensuring it was extensible. ⚙️ Parser Implementation I developed a recursive descent parser in C++, integrating libraries like Flex and Bison for tokenization and syntactic analysis. This allowed for elegant error handling, with clear messages for debugging. 🛠️ Building the Interpreter The core was an interpreter that evaluates the generated AST (Abstract Syntax Tree). I incorporated an execution environment with support for dynamic variables and recursive functions, optimizing for performance in complex arithmetic operations. 📊 Testing and Optimizations I conducted exhaustive tests with edge cases, measuring execution times and fixing memory leaks. The result: a functional language that compiles and executes scripts in seconds, ready for quick prototypes. This experience highlights the importance of understanding compilers from scratch. Ideal for devs looking to deepen their knowledge in language theory! For more information visit: https://enigmasecurity.cl #ProgrammingLanguages #Compilers #SoftwareDevelopment #TechInnovation #Programming If you're passionate about cybersecurity and development, consider donating to the Enigma Security community for more news: https://lnkd.in/er_qUAQh Connect with me on LinkedIn to discuss more: https://lnkd.in/eXXHi_Rr 📅 Tue, 20 Jan 2026 07:53:52 GMT 🔗Subscribe to the Membership: https://lnkd.in/eh_rNRyt

Just published on Medium: "C++: The Powerhouse of High-Performance Programming (2026 Edition)" In a world where Python dominates AI and scripting, and Rust gains traction for safety, C++ is still the undisputed king when raw performance, low-level control, and zero-overhead abstractions matter most. Key takeaways from the article: ✅ Modern C++ (C++20/23) is expressive, safer, and more productive than ever — with concepts, ranges, modules, coroutines, and better tooling. ✅ It powers AAA games (Unreal Engine), high-frequency trading, browser engines, real-time simulations, and performance-critical AI inference. ✅ In early 2026 rankings: C++ holds strong in the top 5 (TIOBE ~8-9%, PYPL combined C/C++ ~15%), with massive legacy codebases and ongoing evolution keeping it relevant. ✅ The steep learning curve pays off: mastering modern C++ makes you a fundamentally better engineer in any language. Whether you're in game dev, systems programming, finance, or just want to understand computers at the deepest level, C++ remains essential. Read the full article here: https://lnkd.in/gqnHGCBB What about you? Still using C++ in 2026, or have you switched to newer alternatives? Drop your thoughts below, I'd love to hear! #C++ #Programming #SoftwareEngineering #HighPerformanceComputing #GameDev #Tech2026

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Ever wanted to build your own programming language? Here’s my step-by-step tutorial series. Introducing Pyxc (pronounced “Pixie”) — a compiled, Python-inspired language built from scratch with LLVM. Think of it as Python meets systems programming: familiar, readable syntax paired with the performance of compiled code. Why build yet another language? Because learning how compilers really work is one of the most rewarding skills a developer can master. And while the classic Kaleidoscope tutorial is a great start, I wanted something with a more modern, practical feel. So I’m writing Pyxc: My First Language Frontend with LLVM, a hands-on guide that walks you through creating a real, usable language—not just a toy. What you’ll build: ✅ A Python-like lexer and parser ✅ LLVM IR generation ✅ JIT compilation and optimization ✅ Control flow, variables, and user-defined operators ✅ Structs, classes, and a basic type system … and more, chapter by chapter. This isn’t just theory. You’ll end up with a working compiler for a language you designed yourself—perfect for a portfolio, a learning milestone, or just the thrill of creation. The first two chapters are live now: Chapter 1: Language and Lexer – tokenizing Python-like syntax Chapter 2: Parser and AST – building your abstract syntax tree 👉 Read and follow along here: https://lnkd.in/g4Dj_Rij New chapters drop frequently. Whether you’re a curious engineer, a student, or just someone who loves to build—come code a compiler with me. #Compilers #LLVM #ProgrammingLanguages #Python #Cpp #SoftwareEngineering #LearnToCode #OpenSource

🚀 Today I learned about Relational and Comparison Operators in programming. Relational operators are used to compare two values and determine the logical relationship between them. These operators always return a Boolean value — either True or False. The commonly used comparison operators are ==, !=, >, <, >=, and <=. The == operator checks whether two values are equal. The != operator verifies whether two values are not equal. The > and < operators determine greater than and less than relationships between operands. The >= and <= operators evaluate boundary conditions, including equality. These operators play a crucial role in decision-making statements like if-else, loops, and logical validations. Without comparison operators, implementing conditional logic in programs would not be possible. Mastering them strengthens logical reasoning and builds a strong foundation for advanced programming concepts. #Programming #Python #SoftwareDevelopment #Coding #AIML #LearningJourney #ComputerScience

✅ Day 37 of 100 Days LeetCode Challenge Problem: 🔹 #322 – Coin Change 🔗 https://lnkd.in/gtfVrvhV Learning Journey: 🔹 Today’s problem focused on finding the minimum number of coins needed to make up a given amount. 🔹 I used Dynamic Programming with a bottom-up approach, building solutions for smaller amounts first. 🔹 A DP array tracks the minimum coins required for each value from 0 up to the target amount. 🔹 For every amount, I iterated through all coin denominations to compute the optimal solution. Concepts Used: 🔹 Dynamic Programming 🔹 Bottom-Up DP 🔹 Optimization Problems 🔹 State Transition Key Insight: 🔹 Breaking problems into smaller subproblems makes optimization manageable. 🔹 Initializing with infinity helps represent unreachable states clearly. 🔹 Iterative DP ensures efficient computation and avoids repeated work. #LeetCode #DataStructures #Algorithms #CodingInterview #SoftwareEngineering #SoftwareDeveloper #ProblemSolving #Programming #ComputerScience #TechCareers #100DaysOfCode #DailyCoding #Consistency #LearningInPublic #Python #BackendDevelopment #InterviewPreparation #TechCommunity

After more than a decade of building things in Python, automation is not new to me. If something needs to be done, my instinct is still to write a script. That’s why I was a bit skeptical when I started experimenting with n8n v2.0 for some personal file workflows. On paper, Python can already do everything. And it still can. But what surprised me wasn’t *capability*. It was *friction*. When I automate something in Python, I’m also signing up for structure, retries, logging, scheduling, failure notifications, and future maintenance. None of those are hard, but together they add weight. For small, recurring workflows, that overhead starts to feel unnecessary. With n8n, I found myself thinking less about scaffolding and more about intent. I could visually model the flow, handle edge cases, and see exactly where things break without wiring up extra tooling. The logic was still mine, but the plumbing came for free. One personal workflow I set up handles recurring file processing end-to-end. What used to be a “I’ll do it later” task now runs quietly in the background and just lets me know if something needs attention. This didn’t replace Python for me. It changed *where* I use it. I still reach for code when I need deep logic or performance. But for glue work, orchestration, and long-running automations, tools like n8n remove a lot of unnecessary effort. Sometimes the most valuable optimization isn’t execution speed. It’s cognitive load. Curious how others with a strong coding background decide where code ends and orchestration begins. #Automation #Python #n8n #EngineeringExperience #WorkflowDesign

The most powerful programming language of the future isn’t C++ or Python. It’s English. Jensen Huang from NVidia: “Why program in Python? So weird.” You won’t write code anymore. You’ll describe what you want. If the result isn’t right, you won’t debug. You’ll just tell it to fix itself. The barrier to controlling computers is hitting zero. We’re shifting from syntax to intent. You don’t need to know how to write a script to modify a system. You need to know how to explain what should happen. Huang: “English is the best programming language of the future.” Prompt engineering is just clear communication with a new audience. How you talk to people and how you talk to machines is becoming the same competency. If you can articulate what you need clearly, you’re a developer. If you can refine through conversation, you can ship products. The coder is obsolete. The orchestrator is everything. The skill isn’t syntax anymore. It’s clarity. Knowing what to build, how to ask for it, and how to direct until it’s exactly right.

𝐅𝐫𝐨𝐦 𝐂𝐨𝐧𝐟𝐮𝐬𝐢𝐨𝐧 𝐭𝐨 𝐂𝐥𝐚𝐫𝐢𝐭𝐲 🐍✨ At the start, choosing a programming language was confusing 🤯 — there were so many options—C, C++, Java, JavaScript—each claiming to be the best. That’s when I discovered 𝐏𝐲𝐭𝐡𝐨𝐧 🐍 Python stood out for its simplicity, powerful features, and wide range of applications 🚀 From 📊 Data Science and 🤖 Machine Learning to 🌐 Web Development, ⚙️ Automation, and 🧠 AI — Python does it all. Today, Python is not just a language for me 💡 It’s a tool to build, explore, and innovate 🔥 And this is just the beginning 🚀✨ #Python #Programming #LearningJourney #Tech #DataScience #MachineLearning #AI #WebDevelopment #Automation #DeveloperJourney

📌 Today’s DSA Series Topic: Array An array is a linear data structure that stores elements of the same data type in contiguous memory locations. It uses 0-based indexing, enabling constant-time access O(1). 🔹 CRUD Operations on Arrays: 👉 See the operations explained in the image below. 📊 Time Complexity Summary Access / Update: O(1) Insertion / Deletion: O(n) 💬 If you want to learn this concept in any specific programming language (C, C++, Java, Python, JavaScript, etc.), please let me know in the comments. I’ll explain it with examples in that particular language. 🚀 Keep learning, keep growing. #DSASeries #Arrays #DataStructures #CRUD #TimeComplexity #Programming #SoftwareEngineering