Scripting vs Programming: Understanding the Key Differences

Object Oriented Programming Fundamentals An object-oriented programming approach uses objects instead of step-by-step logic as in procedural programming. An object bundles data and behavior into a single unit. The introduction of such concepts extends OOP capabilities, making it simpler to use, more reusable, and easier to manage. Although this model still uses basic programming concepts such as control statements and functions, it addresses the limitations of procedural programming. The introduction of such concepts extends OOP capabilities, making it simpler to use, more reusable, and easier to manage. Object-oriented concepts offer practical, efficient solutions, particularly for modern applications. For more info, click on the link; https://lnkd.in/guZ_JzgB #differencebetweenproceduralandobjectorientedprogramming, #objectorientedprogramming, #oopprogramming, #OOPsconcepts, #introductiontoobjectorientedprogramming, #historyofoops,

ISO C23 for Systems Programming: Understanding the C Standard in Practice ======================== My first encounter with the C programming language dates back to 1989, when I began working with it using Borland’s Turbo C environment. At that time, C was demanding, unforgiving, and required a level of precision that was challenging for a beginner. A few years later, with the emergence of C++, the transition felt natural. Object-oriented programming, stronger abstraction mechanisms, and improved code organization made C++ an attractive evolution of C, and it became my primary professional language throughout the 1990s. With time and experience, however, it became increasingly clear that despite the rise of newer languages, C has never lost its central role in computing. While languages such as C++ and Rust continue to evolve and address different problem domains, C remains foundational in areas where predictability, minimal abstraction, and direct control over memory and execution are essential. C continues to dominate or strongly influence fields such as: • Operating Systems, where kernels and core subsystems rely on C for precise control and stable interfaces. • Embedded Systems, where limited resources and hardware proximity demand explicit and efficient code. • Compiler and Toolchain Development, where C’s simplicity and portability make it a natural implementation language. • Low-Level and Systems Programming, where understanding memory, calling conventions, and execution models is essential. These realities motivated the decision to write this book using the current ISO C standard, C23. The choice of C23 is not driven by novelty, but by correctness: it represents the most up-to-date, clarified, and officially standardized form of the C language. This book focuses on the domains where C has always been strongest, rather than attempting to reshape it into something it was never designed to be.

🚀 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

🚀 C# Async Best Practices: Handling Single & Multiple Task Exceptions ⚙️ Asynchronous programming in C# improves performance and responsiveness. But poorly structured exception handling can make async code hard to read, debug, and maintain 🐛 👉 In real-world scenarios, keeping exception handling simple is often the most professional choice. ================================================ 🔹 Single async operation — one task, one exception 🎯 When awaiting a single async operation, the exception is thrown directly. A single catch (Exception) is usually sufficient when the handling logic is the same. public async Task<Order> GetOrderAsync() {   try   {     return await _orderRepository.GetAsync();   }   catch (Exception ex)   {     _logger.LogError(ex, "Failed to retrieve order");     throw;   } } ✔️ Simple ✔️ Explicit ✔️ Clear responsibility boundaries 🧭 ================================================ 🔹 Multiple async operations — Task.WhenAll ⚡ When executing multiple tasks in parallel, all failures are grouped inside an AggregateException. Handle it explicitly to capture all individual errors. try {   await Task.WhenAll(     LoadCustomerAsync(),     LoadOrdersAsync(),     LoadPaymentsAsync()   ); } catch (AggregateException aggEx) {   foreach (var ex in aggEx.InnerExceptions)   {     Console.WriteLine($"Captured error: {ex.Message}");   } } 📌 Always handle the AggregateException to capture all errors and understand what really failed. ================================================ ✅ Key Takeaways 📋 🎯 Single task (await) → direct exception ⚡ Multiple tasks (Task.WhenAll) → AggregateException 🧼 Keep it simple = cleaner, more maintainable async code 💡 Clean async exception handling improves observability 🔍, reduces production bugs 🛠️, and keeps your codebase maintainable. #CSharp #DotNet #Async #AsynchronousProgramming #ExceptionHandling #CleanCode #SoftwareDevelopment #CodingTips #TechLeadership #SvetlanaVrabie

🧬 What is Inheritance in OOP? ❓ 1️⃣ Question What is inheritance in Object-Oriented Programming? 💡 2️⃣ Answer Inheritance is an OOP concept where a child (subclass) acquires the properties and behaviors of a parent (superclass), promoting code reuse and hierarchy. 🔒 3️⃣ Private Variable Private variables belong only to the parent class and cannot be accessed directly by the child class, ensuring data protection. 🧩 4️⃣ Public Method Public methods of the parent class can be accessed and reused by the child class, allowing consistent behavior across classes. 🙈 5️⃣ Data Hiding Inheritance works alongside data hiding, where sensitive data remains hidden in the parent class while exposing only necessary functionalities. ✨ 6️⃣ Benefits of Inheritance ✅ Code reusability ♻️ ✅ Reduced duplication 🧹 ✅ Easy maintenance 🛠️ ✅ Clear class hierarchy 🌳 ✅ Supports method overriding 🔁 🚀 Inheritance helps build scalable and extensible applications by reusing existing logic instead of rewriting it. 💬 Which inheritance type do you use most in real-time projects? Let’s discuss 👇🔥 #Inheritance #OOP #Java #ObjectOrientedProgramming #SoftwareDevelopment #CleanCode #DeveloperLife #TechConcepts

🚀 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

🚀 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/evtXjJTA Connect with me on LinkedIn to discuss more about these topics: https://lnkd.in/ex7ST38j 📅 Sat, 17 Jan 2026 08:22:04 GMT 🔗Subscribe to the Membership: https://lnkd.in/eh_rNRyt

Most developers stop at the "4 Pillars" of OOP. But if you want true architectural mastery, you need the full 7. Object-Oriented Programming isn't just about syntax. It is the blueprint for flexibility and reusability at scale. Here is the cheat sheet to level up your software design: 📦 Encapsulation Data hiding. Keep your state safe within the unit. 🎭 Abstraction Show the feature, hide the messy implementation details. 🧬 Inheritance Don't repeat yourself. Inherit behaviors from parent classes. 🦎 Polymorphism flexibility. Treat different objects as the same type. 🧩 Composition The unsung hero. Combine small objects to build complex ones (often better than inheritance!). 🔗 Association Understanding how objects depend on one another. 🔄 Dependency Inversion Decouple your high-level logic from low-level details. Mastering these principles turns you from a "Coder" into a "Software Engineer." Which of these 7 do you find most difficult to implement correctly? #SoftwareEngineering #OOP #CleanCode #Programming

💡 The Day OOP Finally Made Sense ☺️ When I first learned Object-Oriented Programming, it felt like four definitions to memorize 😁: ✔Encapsulation. ✔Abstraction. ✔Inheritance. ✔Polymorphism. But working on real .NET projects changed that. I realized these aren’t concepts. They’re architectural decisions. 🔹 When I made fields private and exposed only methods, I wasn’t just writing code — I was protecting state. (Encapsulation) 🔹 When controllers depended on interfaces instead of concrete classes, I wasn’t just following patterns — I was designing loose coupling. (Abstraction) 🔹 When a derived class reused base functionality, I wasn’t copying code — I was building extensibility. (Inheritance) 🔹 When the same method behaved differently depending on the object, I wasn’t being clever — I was enabling flexibility at runtime. (Polymorphism) That’s when it clicked. 🙂 OOP isn’t academic theory. It’s the foundation of scalable and maintainable systems. The stronger the fundamentals, the cleaner the architecture. Still learning. Still refining. 🚀 #DotNet #CSharp #OOP #BackendDevelopment #SoftwareEngineering #CleanCode #LearningInPublic

🚀 Understanding OOP: Why It Matters Object-Oriented Programming (OOP) isn’t just a buzzword – it’s a way to write code that’s organized, maintainable, and scalable. By modeling real-world objects as classes, we can: Encapsulate data and protect it from invalid access Reuse code with inheritance Flexibly extend behavior through polymorphism Keep our systems clean with clear responsibilities #oop #programming #softwareengineering