Abdul Raheem’s Post

𝗧𝗵𝗲 𝗜𝗻𝘁𝗲𝗿𝘀𝗲𝗰𝘁𝗶𝗼𝗻 𝗼𝗳 𝗙𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝗮𝗹 𝗮𝗻𝗱 𝗢𝗯𝗷𝗲𝗰𝘁-𝗢𝗿𝗶𝗲𝗻𝘁𝗲𝗱 𝗣𝗿𝗼𝗴𝗿𝗮𝗺𝗺𝗶𝗻𝗴 𝗶𝗻 𝗝𝗮𝘃𝗮𝗦𝗰𝗿𝗶𝗽𝘁 JavaScript supports multiple programming paradigms, including Object-Oriented Programming (OOP) and Functional Programming (FP). You can use both paradigms to create robust applications. Here are some key points about OOP and FP in JavaScript: - OOP revolves around objects and promotes encapsulation, inheritance, and polymorphism. - FP emphasizes the use of functions, immutability, and a declarative approach to data manipulation. - You can combine OOP and FP to create powerful applications. Let's look at an example: ```javascript is not allowed, using plain text instead You can define a class that uses functional approaches to manipulate its internal state. For example, a Counter class can have methods like increment, decrement, and reset. These methods can be implemented using arrow functions to ensure the correct context. You can also use function composition to combine multiple functions. For example, you can create a composed function that uppercases a string and appends an exclamation mark. When creating classes with methods, you can make these methods depend solely on the parameters they receive. This leads to more predictable and testable code. Here are some key differences between OOP and FP: - State Management: OOP uses objects to encapsulate state, while FP relies on immutability. - Code Reusability: OOP uses inheritance and polymorphism, while FP uses function composition. - Readability: OOP can have complex hierarchies, while FP can have less readable higher-order functions. - Testing: OOP requires knowledge of internal state, while FP has pure functions that are easier to test. - Performance: OOP can be slower due to state mutations, while FP is generally faster due to optimizations over immutability. You can use both OOP and FP in component-based frameworks like React and server-side applications like Express.js. When blending OOP and FP, consider performance characteristics like garbage collection, higher-order functions, and state mutations. Source: https://lnkd.in/g2ayw_kr

𝗧𝗵𝗲 𝗜𝗻𝘁𝗲𝗿𝘀𝗲𝗰𝘁𝗶𝗼𝗻 𝗼𝗳 𝗙𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝗮𝗹 𝗮𝗻𝗱 𝗢𝗯𝗷𝗲𝗰𝘁-𝗢𝗿𝗶𝗲𝗻𝘁𝗲𝗱 𝗣𝗿𝗼𝗴𝗿𝗮𝗺𝗺𝗶𝗻𝗴 𝗶𝗻 𝗝𝗮𝘃𝗮𝗦𝗰𝗿𝗶𝗽𝘁 JavaScript supports multiple programming paradigms, including Object-Oriented Programming (OOP) and Functional Programming (FP). You can use both paradigms to create robust applications. Here are some key points about OOP and FP in JavaScript: - OOP revolves around objects and promotes encapsulation, inheritance, and polymorphism. - FP emphasizes the use of functions, immutability, and a declarative approach to data manipulation. - You can combine OOP and FP to create powerful applications. Let's look at an example: ```javascript is not allowed, using plain text instead You can define a class that uses functional approaches to manipulate its internal state. For example, a Counter class can have methods like increment, decrement, and reset. These methods can be implemented using arrow functions to ensure the correct context. You can also use function composition to combine multiple functions. For example, you can create a composed function that uppercases a string and appends an exclamation mark. When creating classes with methods, you can make these methods depend solely on the parameters they receive. This leads to more predictable and testable code. Here are some key differences between OOP and FP: - State Management: OOP uses objects to encapsulate state, while FP relies on immutability. - Code Reusability: OOP uses inheritance and polymorphism, while FP uses function composition. - Readability: OOP can have complex hierarchies, while FP can have less readable higher-order functions. - Testing: OOP requires knowledge of internal state, while FP has pure functions that are easier to test. - Performance: OOP can be slower due to state mutations, while FP is generally faster due to optimizations over immutability. You can use both OOP and FP in component-based frameworks like React and server-side applications like Express.js. When blending OOP and FP, consider performance characteristics like garbage collection, higher-order functions, and state mutations. Source: https://lnkd.in/g2ayw_kr

Make OOP object-oriented again. A lot of "OOP" code is still just procedural code with classes around it. This: $catalogService->getCatalog('shoes', null, 35, 50, 100, 'asc'); passes values. This: $request = new GetCatalogRequest( ProductType::SHOES, Gender::BOTH, new AgeRange(30, 40), new PriceRange(50, 100), Order::ASC, ); $response = $catalogHandler->handle($request); passes meaning. Yes, more classes. But better modeling. A rich domain model vs anemic variables floating around. Try changing a rule or adding a new filter: one version scales, the other breaks silently. Good code doesn’t just work. It makes mistakes harder to write.

Renaming a symbol across a codebase with text search will break things. It matches strings, not definitions. A variable named user gets renamed alongside the class User. Import paths get touched. Comments get changed. Toolpack SDK ships 12 coding tools that work at the AST level. They understand the structure of your code, not just the text. coding.refactor_rename finds every reference to a symbol. The definition, every import, every usage. All renamed correctly. coding.find_references shows exactly which files are affected before you make the change. coding.get_diagnostics checks for new errors after. coding.multi_file_edit handles refactors that touch multiple files. All edits succeed or all of them roll back. No partial changes left behind. The navigation tools cover the other half. coding.find_symbol locates definitions. coding.get_call_hierarchy traces who calls what. coding.get_outline maps the structure of a file. Useful before making changes, not just during. JavaScript and TypeScript get full support through Babel. Python, Go, Rust, Java, C, and C++ get symbol navigation through Tree-sitter. All 12 tools available with tools: true. No external services. Wrote up all 12 with examples: https://lnkd.in/grcfacP6 #AI #LLM #TypeScript #DeveloperTools #OpenSource #SoftwareEngineering #AIAgents

I have been thinking about TypeScript generics wrong for years. Not the syntax. The mental model. I thought generics were about reusability — write once, use everywhere. That's true. But it's not the interesting part. I was reading Functional Programming in Scala (the creator of Claude Code mentioned it in a podcast) and came across this: "The more generic a function is, the fewer implementations it can have." That reframed everything. A fetchOrders function that quietly sorts your data by date. No one documented it. No one noticed — until someone needed a different order and spent hours wondering why the data came back pre-sorted. That's a function lying about what it does. A generic function can't lie like that. If it doesn't know what T is, it can't sort it, filter it, or touch it. The compiler takes that option away entirely. <T>(url: string) => { data: T | null, loading: boolean } This function is making a promise: I will not touch your data. And unlike a comment or a doc, the type system enforces it. Generics aren't just about reusability. They're how you write functions that are honest by construction.

Object-Oriented Programming (OOP) — a deeper, code-free view OOP is not mainly about syntax or specific features. It is a way of organizing thought before it becomes code. Instead of seeing a program as a long chain of instructions, you begin to see it as a world of interacting entities. Each entity has: an identity (what it is) attributes (what it has) behavior (what it does) boundaries (what others are allowed to access) This shift changes how you design everything. Modeling reality, but with discipline In real life, everything exists as a “thing”: a person, a car, a bank account. Each one carries its own data and controls its own behavior. OOP brings that same structure into software. You stop asking “what steps should I write?” and start asking “what kind of thing should handle this responsibility?” Why this matters The real challenge in programming is not writing code that works once — it’s writing code that continues to work as it grows. OOP helps by: Creating order instead of chaos Every part of the system has a clear role. Controlling complexity As systems grow, relationships multiply. OOP keeps parts separated and manageable. Making change safer You can modify one part without breaking everything else. The key mental shift Without OOP: “How do I do this step by step?” With OOP: “Who is responsible for doing this?” This small change leads to: clearer structure better readability fewer unintended side effects OOP as boundaries and contracts Each entity protects its internal details and exposes only what is necessary. This creates a kind of contract between parts of the system. Instead of everything knowing everything, each part knows only what it needs. That’s what keeps large systems from collapsing under their own complexity. More than a technique OOP is not just: classes constructors inheritance Those are tools. The real value is: thinking in terms of responsibility designing clear structures building systems that can evolve over time In one sentence OOP is a way to design software so that it remains understandable, flexible, and stable, even as it grows #flutter #MobileApplication #oop #Dart

Object-Oriented Programming (OOP) has been around for decades, yet it remains one of the most powerful ways to design scalable and maintainable systems. At its core, OOP is about modeling real-world concepts in code. Instead of thinking in isolated functions, you think in terms of objects that bundle data and behavior together. The four pillars still matter: • Encapsulation: Keep data safe and expose only what’s necessary • Abstraction: Hide complexity behind simple interfaces • Inheritance: Reuse and extend existing behavior • Polymorphism: Write flexible and interchangeable code But here’s the thing, OOP isn’t just about following principles. It’s about making code easier to reason about, evolve, and collaborate on. Great engineers don’t just “use OOP.” They know when not to. Sometimes a simple functional approach beats deep class hierarchies. The real skill is choosing the right paradigm for the problem, not forcing one. Clean design > strict ideology.

Most projects don’t fail because of bad developers… They fail because of bad systems. No clear structure No proper planning No scalability in mind Just code… on top of code… on top of code. And eventually — everything breaks. Here’s what actually makes a project successful 👇 ✔ Clear architecture ✔ Proper data flow ✔ Scalable backend structure ✔ Clean separation of logic Because good code is not enough. 👉 Systems matter more than syntax That’s something I’ve been learning deeply while working with Laravel and backend systems. What do you think causes most projects to fail? 👇 #Laravel #SoftwareDevelopment #BackendDevelopment #SystemDesign #CleanCode #Developers #Programming #TechInsights #WebDevelopment #Coding

I just published a new blog post: Refactoring OO Toward Functional Style. A lot of codebases are not going to jump from object-oriented to functional overnight, and that is fine. What matters is finding practical ways to move in that direction step by step. In this post, I share some thoughts on how to evolve OO code toward a more functional style through refactoring, with a focus on making code simpler, clearer, and easier to reason about. Read it here: https://lnkd.in/eibamTdd Have you made this kind of transition in your own code?

Yesterday we had a group discussion on OOP (Java) and we covered some very practical scenario-based questions instead of just theory. Here are the questions we discussed: 1. How would you design a system where an employee’s salary cannot be accessed or modified directly, but only through controlled methods? 2. Car and Bike share common properties like speed and fuel. How would you design your classes to avoid code duplication? 3. In a system with multiple payment methods (UPI, Card, NetBanking), how would you ensure the same method call behaves differently for each type? 4. How would you design a payment system where the user only sees the “pay” action, but the internal implementation is hidden? 5. How would you design a calculator that supports the same method name for different input types (int, double)? 6. In an Animal system, Dog and Cat produce different sounds. How would you ensure the correct behavior is executed at runtime? 7. How would you secure sensitive data like passwords or salary while still allowing controlled access? 8. An application supports multiple login methods (Google, Email, OTP). How would you structure this using OOP principles? 9. How would you model the relationship between Car and Engine? Would you use inheritance or another approach? 10. How would you prevent a class from being extended or modified? 💡 This discussion really helped me understand how OOP concepts like Encapsulation, Inheritance, Polymorphism, and Abstraction are used in real-world systems, not just in theory. Good learning session and looking forward to more such discussions 🚀 #Java #OOP #SoftwareEngineering #Polymorphism #Encapsulation  #LearningInPublic #DeveloperJourney #BackendDeveloper  #TechCommunity #Programming #GrowthMindset #SDE