Understanding this() and super() in Java

🧩 Thinking Beyond Code While learning backend development, I’m slowly realizing that building systems is not just about writing code, but about understanding how different parts work together. Things like: • communication between services • data flow • failure handling are just as important as individual features. Learning to think in terms of systems, one step at a time. #BackendDevelopment #SystemThinking #Java #SpringBoot #LearningInPublic

Me: Writes 5,000+ lines of backend code confidently. Also me: Opens Excel to write test cases… “I’ll do this later.” 😅 After working 2 months on a project, I realized something — Coding is the fun part. Testing and documentation are the responsibility part. And real engineering requires both. Working on improving that balance every day. #DeveloperLife #BackendEngineer #BuildInPublic #SoftwareDevelopment #Java #backend

Back to my roots: Java Backend After spending some time yesterday polishing my portfolio (Link in the comments!), I’m officially diving back into the world of Full-Stack Development, with a laser focus on the Backend. Design is great, but there’s something addictive about building the "brain" of an application. Day 1 of my Spring Boot Deep-Dive: Today wasn't just about 'Hello World'. I pushed myself to bridge the gap between simple code and scalable architecture. What’s under the hood today? => RESTful Architecture: Built endpoints to handle GET, POST, and DELETE requests. => Service Layer Pattern: Implemented @Service and @Autowired for clean, decoupled logic (No more messy Controllers!). => Data Flow: Mastered @RequestBody and @PathVariable to handle dynamic data from Postman. => In-Memory Storage: Managed state using ArrayLists before I move to persistent Databases tomorrow. The goal? To master enterprise-grade backend development and reach a high-impact role by August. The roadmap is set, the environment is configured, and the first few commits are live on GitHub. How did you start your dev journey? Let’s connect! 👇 #Java #SpringBoot #BackendDeveloper #WomenInTech #CodingJourney #SoftwareEngineering #Portfolio #BackendFocussed

𝗟𝗼𝗰𝗮𝗹𝗖𝗼𝗱𝗲, my self-hosted coding platform has now matured and is 𝗼𝗽𝗲𝗻 𝗳𝗼𝗿 𝗰𝗼𝗻𝘁𝗿𝗶𝗯𝘂𝘁𝗼𝗿𝘀 🚀 𝗟𝗼𝗰𝗮𝗹𝗖𝗼𝗱𝗲 lets you solve programming problems in a fully isolated environment: → Pick a problem → Write code → Submit → A Docker container runs it and disappears (no network, strict limits, zero noise) 🎥 The video shows it in action. I’m looking for contributors who want to: → Work on a real React + Spring Boot system → Solve design-level problems → Learn how platforms like LeetCode actually work under the hood 👉 Open issues are in the first comment. Pick one, comment that you’re taking it, and ship a PR. 𝗥𝗲𝗽𝗼 𝗟𝗶𝗻𝗸 https://lnkd.in/dxQy8eCa Shipping weekly. Early contributors shape the roadmap. #opensource #java #springboot #react #systemdesign #dsa

Small code style decisions matter more than we think. One habit I’ve consciously adopted in my backend work is avoiding wildcard imports and keeping imports explicit. Why it matters: - Improves readability for reviewers - Makes dependencies clear at a glance - Reduces accidental coupling - Avoids surprises during refactoring - Keeps diffs clean and predictable Tools help, such as IDEs and linters, but consistency is a team discipline. Over time, I’ve realized that senior engineering isn’t about writing more code; it’s about writing code that’s easier to understand, review, and maintain. #Java #BackendDevelopment #CleanCode #SoftwareEngineering #CodeQuality #EngineeringPractices #LearningInPublic

While solving problems on LeetCode with multiple tabs and frequent interactions, I encountered a temporary rate-limit response. From a Java backend system design perspective, this is a deliberate reliability mechanism. At scale, platforms like LeetCode must regulate request bursts early to protect backend services, maintain fairness, and ensure predictable latency. At the same time, this also highlights a practical limitation (trade-off) in the current design. Strict rate limiting can momentarily restrict legitimate high-frequency user workflows (such as parallel problem exploration), even though it effectively safeguards overall system stability. It got me thinking about how such systems could be improved to better differentiate between abusive traffic and valid bursty usage, without compromising reliability. Such systems are typically implemented using stateless services (e.g., Spring Boot) combined with fast in-memory tracking, request throttling policies, and clear rejection semantics (HTTP 429), rather than allowing uncontrolled traffic to cascade into failures. Rate limiting isn’t a failure — it’s a defensive design choice, but like all large-scale systems, it involves trade-offs that can be continuously refined. Open to thoughts or ideas on how you would design traffic control and backpressure handling for high-throughput platforms. #SystemDesign #Java #SpringBoot #BackendEngineering #DistributedSystems #Scalability #LeetCode #SDE #LearningInPublic #SoftwareEngineering #SystemDesign #Java #SpringBoot #BackendEngineering #DistributedSystems #Scalability #LeetCode #SDE #LearningInPublic #SoftwareEngineering

I Stopped Writing “Working Code.” I Started Designing Systems. When I first started learning Java, my goal was simple: 👉 Make the code run. If it compiled and gave output — I was happy. But backend development taught me something different. Working code is not enough. Good backend code must be: • Structured • Scalable • Maintainable • Secure That’s when OOP started making real sense. Encapsulation is not just theory. It protects state. Abstraction is not just a keyword. It hides complexity. Polymorphism is not for exams. It enables flexibility. The shift from “solving problems” to “designing systems” changes everything. Still learning. But now thinking like a backend developer. #Java #BackendDevelopment #OOPS #SpringBoot #SoftwareEngineering

Understanding Bean Lifecycle in Spring (Quick Read) Ever wondered what really happens to a Spring Bean behind the scenes? Here’s the Bean Lifecycle in simple steps: 1️⃣ Instantiation – Spring creates the bean 2️⃣ Populate Properties – Dependencies are injected 3️⃣ Aware Interfaces – Bean gets context info (BeanName, ApplicationContext, etc.) 4️⃣ BeanPostProcessor (before init) 5️⃣ Initialization – @PostConstruct / afterPropertiesSet() 6️⃣ BeanPostProcessor (after init) 7️⃣ Bean Ready to Use 🚀 8️⃣ Destruction – @PreDestroy / destroy() 👉 Why this matters: • Customize initialization logic • Handle resource setup/cleanup • Debug tricky startup issues • Write cleaner, production-ready Spring apps Mastering the bean lifecycle = better control over your application. #SpringBoot #Java #SpringFramework #BackendDevelopment #Microservices #CleanCode

𝗝𝗮𝘃𝗮 𝗮𝗻𝗱 𝗞𝗼𝘁𝗹𝗶𝗻: 𝗪𝗵𝘆 𝗽𝗶𝗰𝗸𝗶𝗻𝗴 𝘀𝗶𝗱𝗲𝘀 𝗶𝘀𝗻'𝘁 𝗻𝗲𝗰𝗲𝘀𝘀𝗮𝗿𝘆 After spending time with both languages, one thing becomes clear: This isn't about choosing a winner. It's about using the right tool for the moment. 𝗝𝗮𝘃𝗮 𝗿𝗲𝗺𝗮𝗶𝗻𝘀 𝗳𝗼𝘂𝗻𝗱𝗮𝘁𝗶𝗼𝗻𝗮𝗹. The ecosystem is massive, the community has solved basically every problem imaginable, and there's something reassuring about code that's been battle-tested for decades. When stability and extensive libraries matter, Java delivers. 𝗞𝗼𝘁𝗹𝗶𝗻 𝗯𝗿𝗶𝗻𝗴𝘀 𝗺𝗼𝗱𝗲𝗿𝗻 𝗰𝗼𝗻𝘃𝗲𝗻𝗶𝗲𝗻𝗰𝗲𝘀. When writing new features or moving fast, Kotlin's conciseness helps. Less boilerplate means focusing on solving the actual problem. The null safety is nice too, fewer defensive checks to write. 𝗧𝗵𝗲𝘆 𝘄𝗼𝗿𝗸 𝘄𝗲𝗹𝗹 𝘁𝗼𝗴𝗲𝘁𝗵𝗲𝗿. This is the part that doesn't get talked about enough. Critical backend services can stay in Java (why mess with what works?) while newer APIs or features use Kotlin. It's not dramatic it just works. 𝗗𝗶𝗳𝗳𝗲𝗿𝗲𝗻𝘁 𝘀𝘁𝗿𝗲𝗻𝗴𝘁𝗵𝘀, 𝘀𝗮𝗺𝗲 𝗽𝗹𝗮𝘁𝗳𝗼𝗿𝗺. Java excels at enterprise-scale systems where predictability matters. Kotlin shines when developer productivity and modern syntax make a difference. Both compile to the same bytecode anyway. The reality? It's not about "migrating away" from Java or being "fully committed" to Kotlin. It's about using both where they make sense. Some days call for Java. Some days call for Kotlin. Either way, the JVM provides solid options. 𝗛𝗼𝘄 𝗱𝗼 𝘆𝗼𝘂 𝗯𝗮𝗹𝗮𝗻𝗰𝗲 𝗝𝗮𝘃𝗮 𝗮𝗻𝗱 𝗞𝗼𝘁𝗹𝗶𝗻 𝗶𝗻 𝘆𝗼𝘂𝗿 𝘄𝗼𝗿𝗸? 𝗢𝗿 𝗮𝗿𝗲 𝘆𝗼𝘂 𝗳𝗼𝗰𝘂𝘀𝗲𝗱 𝗼𝗻 𝗼𝗻𝗲? 𝗪𝗵𝗮𝘁 𝗱𝗿𝗶𝘃𝗲𝘀 𝘁𝗵𝗮𝘁 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻? 👇 #Java #Kotlin #JVM #SoftwareDevelopment #Programming #BackendDevelopment