Building Custom Programming Languages: A Developer's Journey

🚀 Discovering the World of Custom Programming Languages In the fascinating universe of software development, creating your own programming language represents an exciting challenge that combines creativity and deep technical expertise. Recently, I explored an article that details the step-by-step process of a developer who built their own language from scratch, inspired by the need to simplify specific tasks and experiment with innovative paradigms. 💻 The Origin and Initial Motivation It all began with the idea of solving everyday problems more efficiently. The author, motivated by curiosity and the desire to understand the fundamentals of compilers, decided to embark on this personal project. Using accessible tools like LLVM for the backend, they avoided reinventing the wheel and focused on the essentials: a simple lexer and a recursive descent parser. 🔧 Key Steps in Development - Lexer and Tokenization: The first stage involved breaking down the source code into tokens, handling basic expressions and operators with precision to avoid common errors. - Parser and Syntax Tree: Building an AST (Abstract Syntax Tree), the grammatical rules were translated into manageable data structures, allowing for quick evaluations. - Code Generation: Integrating with LLVM IR, the language generated optimized machine code, supporting primitive types and recursive functions. - Testing and Debugging: Constant iterations revealed challenges such as scope handling and garbage collection, resolved through exhaustive unit tests. This approach not only resulted in a functional language for simple scripts but also offered valuable lessons about the underlying complexity of languages like Python or C++. It's a reminder that innovation in programming arises from practical experimentation. For more information visit: https://enigmasecurity.cl #SoftwareDevelopment #ProgrammingLanguages #Compilers #TechInnovation #Programming Support Enigma Security by donating here for more technical news: https://lnkd.in/er_qUAQh Connect with me on LinkedIn to discuss more about these topics: https://lnkd.in/eXXHi_Rr 📅 Sat, 17 Jan 2026 08:22:04 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

Compiled vs Interpreted Programming Languages: Choosing the Right One for Your Project We're excited to share our latest infographic explaining the key differences between Compiled and Interpreted programming languages in a simple, visual way. The infographic covers: How compiled languages convert source code into machine code How interpreted languages execute code line-by-line Performance vs portability comparison Error handling, security, and development speed differences Real-world examples like C/C++, Python, JavaScript, and Java’s hybrid approach Key takeaway: There is no “one-size-fits-all” language. Compiled languages are ideal when performance and efficiency matter. Interpreted languages help with rapid development and flexibility. Hybrid approaches (like Java) aim to balance both worlds. We're created this to help students, developers, and tech enthusiasts quickly understand how language execution models impact real projects. Which approach do you prefer for your projects — compiled, interpreted, or hybrid? Let’s discuss in the comments #Programming #SoftwareDevelopment #Coding #ComputerScience #Java #Python #JavaScript #Cpp #TechEducation #Developers #RoyalResearch

🚀 Day 36/100 of My LeetCode Challenge: Mastering Greedy & Dynamic Programming! Just solved LeetCode 3507: Minimum Pair Removal to Sort Array I – an interesting problem that beautifully blends greedy operations with dynamic programming thinking! 🧠 🔍 The Challenge: Given an array, repeatedly replace the adjacent pair with the minimum sum until the array becomes non-decreasing. Return the minimum number of such operations required. 💡 Key Insights: This isn't just about blindly following the operation description (selecting minimum sum pairs) The optimal solution requires recognizing this as a dynamic programming problem We need to find the minimum operations to partition the array into segments that can be merged while maintaining the non-decreasing property Each merge operation happens only when the left segment's sum exceeds the right segment's sum 🛠️ My Approach: Implemented a memoized DP solution that explores all possible partition points For each possible split position, recursively solve left and right subarrays Add a merge cost when the left segment's sum is greater than the right segment's sum Use memoization to avoid redundant computations for O(n²) time complexity 📊 Performance: Runtime: 66.06% Memory: 44.62 MB Beats: 32.51% of Java submissions 🎯 Why This Matters: This problem is a great example of how: Problem understanding matters more than just following instructions Dynamic programming can elegantly solve what seems like a greedy problem Memoization dramatically improves performance for recursive solutions Real-world scenarios often require transforming problem statements into solvable patterns ✨ The Journey Continues: Every day of this 100-day challenge brings new learning opportunities. Today reinforced that sometimes the direct approach isn't optimal, and we need to think one level deeper about the underlying structure of the problem. #LeetCode #CodingChallenge #100DaysOfCode #ProblemSolving #DynamicProgramming #GreedyAlgorithms #Java #SoftwareEngineering #TechCareer #DeveloperJourney #Algorithm #DataStructures #CodingInterview #Programming

Asynchronous programming sounds scary at first—but once it clicks, it completely changes how you think about software. I used to write code that waited. Wait for the API. Wait for the database. Wait for the file to load. And while my program was waiting… everything else was frozen. That’s when asynchronous programming started to make sense. Instead of blocking the whole application, async code says: “Start this task, and while it’s running, go do something useful.” This is why modern apps feel fast and responsive. Your UI doesn’t freeze. Your server handles thousands of users at the same time. Your app feels alive, not stuck. Whether it’s async/await in Dart, JavaScript, Python, or C#, the idea is the same: Do work in the background Don’t waste time waiting Handle results when they’re ready Asynchronous programming isn’t about writing more complex code. It’s about writing smarter code that respects time, performance, and user experience. Once you truly understand async, there’s no going back. #Programming #AsynchronousProgramming #AsyncAwait #SoftwareDevelopment #CleanCode #LearningJourney

What Is a Programming Language? A Beginner’s Complete Guide Every app you use, every website you visit, and every system that powers modern businesses runs on one fundamental concept: programming languages. But what exactly is a programming language? Simply put, it’s a structured way for humans to communicate with machines. It allows developers to write instructions that computers can translate into executable actions through compilers or interpreters. Here’s a quick breakdown: Low-Level Languages – Machine & Assembly (closer to hardware) High-Level Languages – Python, Java, C++, JavaScript (closer to human language) Domain-Specific Languages – SQL, HTML, CSS (built for specific tasks) Over the decades, programming languages have evolved to support: Automation Scalability Problem-solving Innovation across industries For beginners, the best way to start: Pick a beginner-friendly language like Python or JavaScript Practice consistently Build small projects Engage with developer communities Programming languages are not just tools they are the foundation of modern software development. If you understand how they work, you understand how the digital world works. Read More: https://lnkd.in/gAV4dSKp Podcast: https://lnkd.in/gfGvm8bQ #Programming #SoftwareDevelopment #Coding #TechEducation #ComputerScience #Python #JavaScript #LearningToCode #RoyalResearch

🚀 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

Getting Started with Prolog: The Foundation of Logic Programming Prolog stands at the crossroads of logic and computation—a programming language that doesn’t tell the computer how to do something, but rather what constitutes a logical relationship or goal. For newcomers, Prolog offers a unique way to express solutions using facts and rules rather than procedural instructions.

Getting Started with Prolog: The Foundation of Logic Programming Prolog stands at the crossroads of logic and computation—a programming language that doesn’t tell the computer how to do something, but rather what constitutes a logical relationship or goal. For newcomers, Prolog offers a unique way to express solutions using facts and rules rather than procedural instructions.