Design Patterns for Software Engineers: Creational, Structural, and Behavioral

🔄 Continuing my Design Patterns journey… After exploring Creational and Structural patterns, today I focused on Behavioral Design Patterns — which define how objects communicate and interact with each other. 💡 Why Behavioral Patterns? They help manage complex communication between objects, making systems more flexible, maintainable, and easier to extend. 📌 Types of Behavioral Design Patterns (GoF – 11 patterns): 1️⃣ Strategy – Defines a family of algorithms and makes them interchangeable 2️⃣ Observer – Notifies multiple objects when one object changes 3️⃣ Command – Encapsulates a request as an object 4️⃣ Chain of Responsibility – Passes requests along a chain of handlers 5️⃣ State – Changes behavior when internal state changes 6️⃣ Template Method – Defines a skeleton of an algorithm with customizable steps 7️⃣ Mediator – Centralizes communication between objects 8️⃣ Iterator – Provides a way to access elements sequentially 9️⃣ Memento – Saves and restores object state 🔟 Visitor – Adds new operations without modifying existing classes 1️⃣1️⃣ Interpreter – Defines grammar and interprets expressions 🧠 Key takeaway: Behavioral patterns focus on how objects interact, helping reduce tight coupling and improving flexibility in code. 🚀 Tomorrow, I’ll implement these patterns with simple code examples. #DesignPatterns #BehavioralPatterns #ObjectOrientedDesign #Java #ProgrammingConcepts #SoftwareEngineering #CodingJourney

Majority of the problems tend to repeat while developing systems. I used to think that design patterns were nothing but complex templates to learn by heart. But while learning Low Level Design, something clicked. Design Patterns Are Born Because Design 𝐏𝐫𝐨𝐛𝐥𝐞𝐦𝐬 𝐑𝐞𝐩𝐞𝐚𝐭 𝐓𝐡𝐞𝐦𝐬𝐞𝐥𝐯𝐞𝐬. While developing software systems, developers face a lot of problems. • How to create objects? • How to avoid tight coupling? • How to make systems easy to extend? • How to make systems easy to maintain? At the initial stage, it feels like each problem is new and has to be addressed separately. But after a while, developers realized that they were not new problems. They were repetitive problems. Instead of solving them again and again, they found ways to solve them. And that is what we call design patterns. They are not meant to be learned by heart. They are meant to help developers create cleaner, easier, and maintainable code. Learning this concept made design patterns sound a lot more practical and a lot less theoretical. #LowLevelDesign #DesignPatterns #SoftwareEngineering #BuildInPublic #Java #ScalableSystems

Most developers use design patterns. Few know when not to use them. Early in my career, I was obsessed with patterns: Factory, Strategy, Singleton… everywhere. Every problem looked like a chance to “apply a pattern.” Until one day, a simple service turned into: • 6 classes • 3 interfaces • Endless abstraction For a problem that needed… 50 lines of code. ⸻ That’s when it clicked: 👉 Design patterns are tools, not goals. ⸻ Take the Strategy Pattern: Great when: • You have multiple interchangeable behaviors • Logic changes frequently Overkill when: • You have 2 simple conditions • Logic is unlikely to evolve ⸻ What I follow now: • Start simple • Refactor when complexity actually appears • Introduce patterns only when they remove pain ⸻ Big lesson: Bad code ignores patterns. Overengineered code worships them. Good code uses them when needed. ⸻ Before using any pattern, ask: “Am I solving a real problem… or just showing I know this pattern?” ⸻ #DesignPatterns #Java #SoftwareEngineering #CleanCode #BackendDevelopment #SystemDesign

Architects get teased for always answering questions with: “It depends.” Usually said like it’s a weakness. Like we’re dodging. Like we don’t know. But “it depends” is where the real thinking starts. Because most problems don’t live in isolation. They live in systems. And systems carry context. In architecture, “it depends” really means: * What constraints are we operating under? * What tradeoffs matter here? * What problem are we actually solving? A monolith can be the right answer. A distributed system can be the right answer. Same team. Same codebase. Different context. Programming has been showing us this for decades. Take PostScript. Yes, it’s stack-based. But it’s not just the stack. What a function does depends on: * What’s on the stack * The current transformation matrix (rotation, scaling, translation) * What’s defined in the dictionary stack * The current graphics state And here’s the part that sticks with me: You can save the entire state, change it—rotate, scale, redefine behavior— do your work inside that altered reality, and then restore it like nothing happened. Same code. Different world. Then back again. Or look at Ruby. Metaprogramming lets you shape behavior at runtime. Define methods on the fly. Change how objects respond based on context. You’re not just writing code. You’re shaping the rules the code lives by. That’s what “it depends” is really pointing at. Not uncertainty. Context. There are very few universal best practices. Only practices that fit a situation. “It depends” isn’t the end of the answer. It’s the start of a better one. It invites the real questions: * What are we optimizing for? * What are we willing to trade? * What context are we operating in? If your architecture never answers “it depends,” you’re probably not looking closely enough. Because context isn’t a nuisance. It’s the whole game. #ArchitectureMatters #ItDepends #SoftwareEngineering #SystemsThinking #Metaprogramming #PostScript #Ruby

🔄 Continuing my Design patterns learning journey… After understanding Creational Design Patterns, today I explored Structural Design Patterns — which focus on how different components of a system are structured and connected. 💡 Why Structural Patterns? They simplify complex systems by organizing relationships between classes and objects, making them easier to scale, extend, and maintain. 📌 Key Structural Design Patterns: 1️⃣ Adapter – Helps incompatible interfaces work together 2️⃣ Bridge – Separates abstraction from implementation for flexibility 3️⃣ Composite – Treats individual objects and groups uniformly 4️⃣ Decorator – Adds new behavior dynamically without changing existing code 5️⃣ Facade – Provides a simple interface to a complex system 6️⃣ Flyweight – Optimizes memory usage by sharing common data 7️⃣ Proxy – Controls access to an object (e.g., security, caching, lazy loading) 🧠 These patterns are especially useful when building scalable systems where components need to interact efficiently without tight coupling. 🚀 Tomorrow, I’ll dive into code implementations. #DesignPatterns #Java #BackendDevelopment

🚀 Software Architecture (Part 1): SOLID Principles S — Single Responsibility A class should have only one reason to change. Keep responsibilities focused to make code easier to maintain and test. Visual: OrderService and OrderRepository as separate boxes with arrows showing delegation. O — Open/Closed Software entities should be open for extension but closed for modification. Add new behavior without breaking existing code. Visual: Discount base class with extensions like PercentageDiscount, SeasonalDiscount, and PriceCalculator untouched. L — Liskov Substitution Derived classes should be replaceable for their base classes without altering correctness. If it breaks expectations, it breaks design. Visual: Shape base class with Rectangle and Circle subclasses, and AreaPrinter working with both. I — Interface Segregation Prefer small, specific interfaces over large, general ones. Clients shouldn’t depend on methods they don’t use. Visual: Split interfaces (IWorkable, IEatable, ISleepable) with HumanWorker and RobotWorker implementing only what they need. D — Dependency Inversion Depend on abstractions, not concrete implementations. This reduces coupling and improves flexibility and testability. Visual: NotificationService depending on IMessageSender, with EmailSender and SmsSender injected. 💡 SOLID isn’t about over-engineering — it’s about writing code that survives change. #dotnet #csharp #softwareengineering #cleanarchitecture #softwarearchitecture #solidprinciples #designpatterns #backenddevelopment #webdevelopment #coding #programming #developer #devlife #bestpractices #scalability #maintainability #testability #architecture #microservices #api #engineering #SoftwareArchitecturePart1

𝗗𝗲𝘀𝗶𝗴𝗻 𝗧𝗵𝗶𝗻𝗸𝗶𝗻𝗴: 𝗔𝗯𝘀𝘁𝗿𝗮𝗰𝘁 𝗖𝗹𝗮𝘀𝘀 + 𝗦𝘁𝗮𝘁𝗶𝗰 𝗡𝗲𝘀𝘁𝗲𝗱 𝗖𝗹𝗮𝘀𝘀 (𝗝𝗮𝘃𝗮) — 𝗪𝗶𝘁𝗵 𝗘𝘅𝗮𝗺𝗽𝗹𝗲 Today I was exploring a design pattern used in many frameworks: **Abstract class with static nested class.** At first it looks like a simple Java feature, but actually this pattern is used for: * Hiding implementation * Controlled object creation * Wrapper design * Builder / Factory pattern * Framework-style API design ### Example ```java public abstract class PaymentProcessor { public abstract void processPayment(); // Static nested builder public static class Builder { public PaymentProcessor build() { return new DefaultPaymentProcessor(); } } // Hidden implementation private static class DefaultPaymentProcessor extends PaymentProcessor { @Override public void processPayment() { System.out.println("Processing payment..."); } } } ``` ### Usage ```java PaymentProcessor processor = new PaymentProcessor.Builder().build(); processor.processPayment(); ``` ### What this design tells User only sees: * PaymentProcessor (Abstraction) * Builder (Object creation) * processPayment() (API) User **cannot see or create DefaultPaymentProcessor directly**. Implementation is hidden and can be changed anytime without affecting users. This type of design is very common in frameworks and large systems where: **Abstraction is public, implementation is private, object creation is controlled.** ### Engineering Lesson In small projects we write code that works. In large systems we design code that: * Hides complexity * Controls object creation * Protects implementation * Exposes only abstraction * Allows future changes without breaking users **This is the difference between coding and software design.**

Too many if conditions in your service? It’s not bad coding. It’s bad design. I’ve seen this in real systems (and I’ve written it too 👀): 👉 Different user types 👉 Different behaviors 👉 And suddenly… your service becomes a decision machine if (user instanceof PrimeUser) { ... } if (user instanceof InternationalUser) { ... } if (user instanceof GuestUser) { ... } At first, it feels normal. But slowly, your system starts asking: “Which type of user is this?” That’s where things break. Because now, not every user can be safely used everywhere. And that’s exactly what the Liskov Substitution Principle warns us about. 👉 A subclass should replace its parent 👉 Without breaking the system So what’s the fix? Stop checking types. Start trusting behavior. Instead of handling logic in the service, push it into the user itself. Now: ✔ No if conditions ✔ No type checks ✔ Clean, extensible design And most importantly — any User can replace another User safely. That’s real LSP. — If this made you rethink your design, follow for more real-world backend concepts 🚀 Next: Interface Segregation Principle (ISP) #systemdesign #backenddevelopment #java #cleanarchitecture #solidprinciples #softwareengineering

Most engineers set up 1 layer out of 4. Then wonder why Claude feels useless. Here's the cheatsheet changed how I use Claude Code. Sharing it because it should change yours, too. Most people set up Claude Code like this: Run /init → get a generic CLAUDE.md → start prompting. Claude has no idea how your project works. So it hallucinates structure. Misses context. Again. Here's what actually matters: ▪️ CLAUDE.md = Claude's persistent memory. Loaded every session. ▪️ Add your tech stack, architecture, build commands. ▪️ Add gotchas Claude can't infer on its own. ▪️ Keep each file under 200 lines. Subfolder files append context. ▪️ Never overwrite parent context. Here's (exactly) how to set it up: 1. Install Claude Code → Requires Node 18+ → Run: curl -fsSL https://lnkd.in/d6x7eeDK | bash → cd your-project → claude → /init → It scans your codebase. Creates a starter memory file. 2. Build your CLAUDE.md properly → What: tech stack, directory map, architecture → Why: purpose of each module, design decisions → How: build/test/lint commands, workflows, gotchas 3. Add Skills (the real superpower) → Skills = markdown guides Claude auto-invokes → Project skill: .claude/skills/<name>/SKILL.md → Description field is critical for auto-activation → Use for: code-review, testing patterns, commit messages 4. Set up Hooks → Hooks = deterministic callbacks. PreToolUse / PostToolUse / Notification → Exit code 0 = allow. Code 2 = block. → Use for: security scripts, auto-lint, safety gates 5. Daily Workflow → cd project && claude → Shift + Tab + Tab → Plan Mode → Describe feature intent → Shift + Tab → Auto Accept → /compact → Esc Esc → rewind → Commit frequently. Start new session per feature. The 4-layer architecture behind it all: L1 – CLAUDE.md: persistent context and rules L2 – Skills: auto-invoked knowledge packs L3 – Hooks: safety gates and automation L4 – Agents: subagents with their own context Most developers use Layer 1 and wonder why it feels basic. Set up all 4. One afternoon. Then you'll understand why engineers switched. _________________________________ Want to go deeper on AI tools like this? Here you can find FREE Guides and Courses on AI workflows, agentic systems, and practical implementation. → https://lnkd.in/d6XFUESR ♻️ Repost to help your team stop winging Claude Code. Image credits: Brij Kishore Pandey #ClaudeCode #Engineering #DeveloperTools #AI #Productivity #Anthropic

This Claude Code workflow cheat sheet is one of the better mental models I’ve seen recently. What stood out isn’t just the commands, it’s the shift in how to think about AI in development: → From “ask for code” → to structured workflows → From one-off prompts → to reusable systems (CLAUDE.md, skills, hooks) → From assistant → to something closer to an operating layer for your dev process A lot of people are still using tools like Claude at surface level. But the real leverage comes from designing workflows: • Analyze → Plan → Execute → Iterate • Persist context (CLAUDE.md) instead of repeating yourself • Break work into agent-like steps instead of dumping one big prompt That’s when it starts compounding. The gap right now isn’t access to AI — it’s workflow design. Curious how others are structuring their setups — are you still prompting, or actually building systems around it?