Anitha Ramesh’s Post

🔥"𝐒𝐭𝐫𝐮𝐠𝐠𝐥𝐢𝐧𝐠 𝐰𝐢𝐭𝐡 𝐉𝐚𝐯𝐚? 𝐇𝐞𝐫𝐞’𝐬 𝐚 𝐪𝐮𝐢𝐜𝐤 𝐠𝐮𝐢𝐝𝐞 𝐭𝐨 𝐦𝐞𝐭𝐡𝐨𝐝𝐬 𝐰𝐢𝐭𝐡 𝟐 𝐬𝐢𝐦𝐩𝐥𝐞 𝐞𝐱𝐚𝐦𝐩𝐥𝐞𝐬! 🛠️" 🔥 Hello, Learners! 🔥 🌟 Today, let's uncover the basics of “Methods in Java” 🌟 📌 𝐖𝐡𝐚𝐭 𝐢𝐬 𝐚 𝐌𝐞𝐭𝐡𝐨𝐝? Ans : A method (also known as a function) allows code reusability and enables programmers to define a set of instructions. ✨ Where do methods live? Inside a class, where you can declare as many as needed. 🔍 𝐓𝐲𝐩𝐞𝐬 𝐨𝐟 𝐌𝐞𝐭𝐡𝐨𝐝𝐬 𝐢𝐧 𝐉𝐚𝐯𝐚: 1️⃣ Main Method -Executes automatically during program execution. -Has the highest priority when a program runs. 2️⃣ Regular Methods -Do not execute automatically. -Require a method call from the main method to run. 👉 𝐑𝐞𝐠𝐮𝐥𝐚𝐫 𝐦𝐞𝐭𝐡𝐨𝐝𝐬 𝐚𝐫𝐞 𝐟𝐮𝐫𝐭𝐡𝐞𝐫 𝐝𝐢𝐯𝐢𝐝𝐞𝐝 𝐢𝐧𝐭𝐨: I. Static Methods II. Non-Static Methods 🛠 How Methods Work: To execute regular methods (static or non-static), you must: ✅ Call the method from the main method. ❌ Without a call, they won't execute. ✨ Structure of a Method: 1️⃣ Method Declaration 2️⃣ Method Definition 📌 Static Methods: Include the keyword static in their declaration. 📌 Non-Static Methods: Exclude the static keyword. 💻 𝐄𝐱𝐚𝐦𝐩𝐥𝐞: 𝐔𝐧𝐝𝐞𝐫𝐬𝐭𝐚𝐧𝐝𝐢𝐧𝐠 𝐌𝐞𝐭𝐡𝐨𝐝𝐬 𝐢𝐧 𝐀𝐜𝐭𝐢𝐨𝐧 public class Demo { // Non-Static Method public void test() { System.out.println("This is a Non-Static Method"); } // Static Method public static void test1() { System.out.println("This is a Static Method"); } public static void main(String[] args) { Demo d = new Demo(); // Object Creation d.test(); // Calling Non-Static Method test1(); // Calling Static Method } } 📚 𝐖𝐡𝐚𝐭 𝐃𝐢𝐝 𝐖𝐞 𝐋𝐞𝐚𝐫𝐧? ✨ The difference between static and non-static methods. ✨ The importance of the main method in Java program execution. ✨ Practical application of methods through a simple program. 🌟 Let’s keep learning together! 🌟 💬 If you found this helpful: ✅ Like the post 💾 Save it for reference 🔄 Repost to help others 📌 Follow me Laxman Sapkale 🔍 for more Java knowledge and QA insights! 𝙅𝙤𝙞𝙣 𝙛𝙤𝙧 𝙏𝙚𝙨𝙩𝙞𝙣𝙜 𝙅𝙤𝙗 𝙐𝙥𝙙𝙖𝙩𝙚 𝙊𝙣 𝙢𝙮 𝙏𝙚𝙡𝙚𝙜𝙧𝙖𝙢 𝙖𝙣𝙙 𝙒𝙝𝙖𝙩𝙨𝘼𝙥𝙥 𝘾𝙝𝙖𝙣𝙣𝙚𝙡 #laxmansapkale #JavaBasics #SoftwareTesting #QA #LearningJourney

I am AdventOfCoding this year in ("modern") Java, posting solutions into this repository: https://lnkd.in/eTGyesQS I would like to expand briefly here on a remark at the end of my notes for Day 1: "Sometimes in AOC the thing you do to make life easier in part 1 serendipitously helps you out in part 2, and sometimes it...doesn't". One of the great virtues of AOC, in my view, is that it trains the spidey-sense that tells you when You Might Need It After All. We spend a lot of time telling more junior engineers not to get ahead of themselves; to work incrementally towards a solution, learning step by step what is needed, rather than building castles in the air out of abstractions that have yet to prove their worth. This is a useful teaching, because at a certain point in a programmer's development they are liable to be bewitched by the powers of abstraction at their fingertips, and it's important to cultivate good sense around not getting carried away by one's own far-sighted cleverness, or desire to hedge against every possible extension of a program when one doesn't really have any feeling at all for which way things are *likely* to go. No, we tell them, YAGNI: just solve the problem at hand and use the guide-rails of TDD to bring the next thing, and the thing after that, into view. But if you watch a seasoned programmer at work, you will often see them quietly pre-empting problems that they can see just around the corner. We may pretend we're not doing it, but we are. We make lucky guesses around the approach we take right now because we sense that a little work sketching out a model with helpful affordances will pay off when the time comes to cut the data diagonally. We bet the other way to YAGNI: that it will be easier to simplify something that turns out to be slightly over-artificed if it turns out a really basic for-loop will do just as well, than it will be to turn an over-fitted implementation inside-out to fit requirements we could reasonably have seen coming. AOC teaches this.

"If you watch a seasoned programmer at work, you will often see them quietly pre-empting problems that they can see just around the corner. We may pretend we're not doing it, but we are. We make lucky guesses around the approach we take right now because we sense that a little work sketching out a model with helpful affordances will pay off when the time comes to cut the data diagonally. We bet the other way to YAGNI" Exactly. "sketching out a model with helpful affordances" is a great way to describe the craft of technical design. So nice (and crucially important) to see this being called out boldly in the face of "build only what is specifically asked for" nonsense, which results in mountains of crippling technical debt that will never be resolved. #Software #Technology #Technical #Design #TechnicalDesign #Architecture #Business #Experience #Communication #Order #Chaos #Discipline #Wisdom #Ontology #Taxonomy #Development #SoftwareDevelopment #Engineering #SoftwareEngineering #Document #Diagram #Context #Documentation #Quality #Interface #Module #Dependency #Inheritance #SOLID #GangOfFour #GOF #Coupling #Component #UnifiedModelingLanguage #UML #Structure #Matrix #Cohesive #TechnicalDebt #OpenSource #Standard

🌟 Mastering Object-Oriented Programming (OOP) in Java 🌟 Object-Oriented Programming (OOP) is at the heart of Java development. It's a design paradigm that helps in building robust, maintainable, and scalable applications. Whether you're working on large enterprise systems or mobile apps, mastering OOP is essential for writing clean and efficient Java code. 🔹 What is OOP? OOP in Java focuses on designing software based on objects - instances of classes that combine data (fields) and behavior (methods). Each object in Java can interact with others through methods, making your code modular and reusable. 🔹 Key OOP Principles: Encapsulation : Binding data and methods that manipulate data into a single unit (class). This hides internal implementation details and ensures data integrity. Abstraction : Exposing only relevant details and hiding complexity through abstract classes and interfaces. Inheritance : Reusing code by inheriting properties and methods from a base class, allowing hierarchical relationships. Polymorphism : Enabling one interface to be used for a general class of actions, typically achieved via method overloading and overriding. 🔹 Core Java OOP Topics: Interfaces vs Abstract Classes : Understanding when to use interfaces (complete abstraction) and abstract classes (partial abstraction). Composition over Inheritance : Leveraging composition for flexibility and maintaining a loose coupling between classes. SOLID Principles : Writing maintainable and scalable object-oriented code by following the SOLID principles. Design Patterns : Familiarize yourself with popular patterns like Singleton, Factory, and Observer, which provide proven solutions to recurring problems in software design. 🔹 Why Focus on OOP in Java? OOP enables you to write scalable, maintainable, and reusable code. In the real world, it’s essential for creating complex systems where different components interact through well-defined interfaces. Understanding and mastering OOP principles in Java makes you a better developer, helping you write cleaner and more robust code. What’s your experience with OOP in Java? Have you used any specific patterns or principles that significantly improved your design? Let’s exchange insights! #Java #OOP #ObjectOrientedProgramming #SoftwareDevelopment #CoreJava #DesignPatterns #SOLIDPrinciples #Coding

🚀 Day 15: Consistent Coding Challenge - Add Binary in Java 🚀 Today's challenge was an exciting deep dive into binary arithmetic with the Add Binary problem! The task is to add two binary strings and return their sum as a binary string, which showcases how important it is to be comfortable working with different number bases. Problem Statement: Given two binary strings `a` and `b`, the task is to return their sum, also in binary form. Solution Approach: 1. BigInteger Class: Java’s `BigInteger` class makes it easy to work with binary numbers. By converting the binary strings to `BigInteger`, we can add them directly and then convert the result back to binary. 2. Base Conversion: We convert the strings `a` and `b` from base-2 to decimal using `BigInteger`, perform the addition, and then convert the result back to a binary string using `toString(2)`. Key Insights: - BigInteger Class: Java’s `BigInteger` class handles arbitrarily large integers, making it perfect for adding binary numbers that could be quite large. - Binary Arithmetic: The challenge provides a simple introduction to binary addition, highlighting how useful it is to manipulate numbers in different bases. - Efficiency: The `BigInteger` class efficiently handles large calculations, simplifying what could be a more complex problem if we implemented binary addition manually. 🔄 Reflections: This challenge was a great opportunity to explore number bases and the built-in tools Java provides for handling binary arithmetic. The `BigInteger` class really simplifies working with large numbers in different bases, making it a go-to for similar problems. 💡 Tip: When dealing with binary or other base systems, Java’s `BigInteger` class is your best friend! It handles the conversions and operations seamlessly, helping you focus more on problem-solving. Let’s keep the coding momentum strong! 🚀 #Java #BinaryAddition #BigInteger #BaseConversion #ProblemSolving #Algorithms #CodingChallenge #Consistency #LearningJourney

What Are the Benefits of Groovy Programming Language for Building Domain Specific Languages Groovy is a dynamic, object-oriented programming language for the JVM (Java Virtual Machine). It is widely used for building Domain-Specific Languages (DSLs) due to its flexibility, simplicity, and integration capabilities. Here are the benefits of using Groovy for DSL development: Ease of Syntax and Readability Groovy offers a concise and human-readable syntax that closely resembles natural language. This makes it ideal for DSLs, where simplicity and clarity are key. The language supports optional typing, reducing boilerplate code and making DSL scripts more intuitive. Seamless Integration with Java Groovy is fully interoperable with Java, allowing DSLs to leverage Java libraries and frameworks seamlessly. Java developers can quickly learn and use Groovy, speeding up the adoption of DSLs in Java- based ecosystems. Dynamic Typing and Metaprogramming Groovy supports dynamic typing, which enables developers to create highly flexible and customizable DSLs. With metaprogramming, developers can define methods and properties dynamically, tailoring the language to specific domains without modifying the core language. Built-in Support for Closures Groovy's closures (anonymous blocks of code) simplify implementing concise and expressive DSLs. Closures make it easy to define and execute domain-specific behaviors within a compact syntax. Embedded DSLs Groovy excels at creating embedded DSLs, which are DSLs written directly within Groovy code. This is achieved without requiring additional tools or compilers, making it convenient for developers. String Interpolation and Command Chains Groovy’s string interpolation allows for embedding dynamic expressions within strings, which is useful for creating readable DSLs. Command chain syntax lets developers build clean and natural-looking DSLs that read like declarative scripts. Rich Ecosystem and Tools Groovy’s ecosystem includes tools like Gradle (a build automation tool built with Groovy), showcasing how effective Groovy is for DSLs. The language's libraries and frameworks support developing and executing DSLs. Runtime Flexibility Groovy supports runtime compilation, enabling DSLs to be written, modified, and executed dynamically without recompilation. This feature is handy for prototyping and iteratively refining DSLs. XML and JSON Support Groovy simplifies working with XML and JSON, making it suitable for creating DSLs for data processing, configuration management, and service orchestration. Active Community and Support Groovy has an active community and extensive documentation, which is helpful for developers building DSLs. #GroovyProgrammingLanguage #DomainSpecificLanguages #DSLs

𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗝𝗮𝘃𝗮 𝗠𝗲𝘁𝗵𝗼𝗱𝘀 : 𝗠𝘆 𝗟𝗮𝘁𝗲𝘀𝘁 𝗕𝗹𝗼𝗴 𝗨𝗽𝗱𝗮𝘁𝗲! 🌟 I have uploaded 𝗽𝗮𝗿𝘁 𝟴 of my Java Learning Series. This time, we're diving into Java methods, which is very important for code reusability, readability, maintainability, and abstraction, enabling efficient problem-solving and cleaner code. 𝗧𝗼𝗽𝗶𝗰𝘀 𝗖𝗼𝘃𝗲𝗿𝗲𝗱: 🔹 Understanding the basics and significance of methods 🔹 Passing Objects as Parameters 🔹 Parameter Passing in Java 🔹 Method Overloading 🔹 Variable Arguments (Varargs) 🔹 Recursion Check out the blog here: https://lnkd.in/eUMy8vbu I hope you find it helpful and informative. Feel free to share your thoughts, questions, or feedback in the comments. Let's learn and grow together! Happy coding! 💻 PS: Don't forget to stay hydrated! #Java #Methods #Coding #LearningJourney #SoftwareDevelopment #Programming #LearnToTeach

[How I Learned Java Programming in a Day with Support from AI Chatbot] So, I recently had the chance to dive into several Java projects. Full disclosure: I had never learned Java before. I knew that both Python and Java are Object-Oriented Programming (OOP) languages, so to make things easier for myself, I decided to learn some Java. 𝑵𝒐𝒕 𝒂𝒊𝒎𝒊𝒏𝒈 𝒕𝒐 𝒃𝒆𝒄𝒐𝒎𝒆 𝒂𝒏 𝒆𝒙𝒑𝒆𝒓𝒕 𝒐𝒗𝒆𝒓𝒏𝒊𝒈𝒉𝒕, 𝒃𝒖𝒕 𝒂𝒕 𝒍𝒆𝒂𝒔𝒕 𝒈𝒆𝒕 𝒄𝒐𝒎𝒇𝒐𝒓𝒕𝒂𝒃𝒍𝒆 𝒓𝒆𝒂𝒅𝒊𝒏𝒈 𝒂𝒏𝒅 𝒕𝒘𝒆𝒂𝒌𝒊𝒏𝒈 𝒕𝒉𝒆 𝒄𝒐𝒅𝒆. I started with ChatGPT-4o (because I have an OpenAI subscription, but Claude or Gemini or other powerful open-source LLMs would work too). I kicked things off with the prompt, "𝑰 𝒂𝒎 𝒔𝒕𝒂𝒓𝒕𝒊𝒏𝒈 𝒕𝒐 𝒍𝒆𝒂𝒓𝒏 𝑱𝒂𝒗𝒂, 𝒑𝒍𝒆𝒂𝒔𝒆 𝒑𝒓𝒐𝒗𝒊𝒅𝒆 𝒎𝒆 𝒆𝒙𝒂𝒎𝒑𝒍𝒆𝒔 𝒕𝒉𝒂𝒕 𝒄𝒐𝒗𝒆𝒓 𝒕𝒉𝒆 𝒎𝒐𝒔𝒕 𝒇𝒖𝒏𝒅𝒂𝒎𝒆𝒏𝒕𝒂𝒍 𝒄𝒐𝒏𝒄𝒆𝒑𝒕𝒔." Boom! I got around 10 .java files as examples (you can find them in the repo link below under the fundamentals/folder). Next, I got curious about how Java handles inheritance—being an OOP language and all. It gave me examples showing the basics of inheritance syntax. I followed up with a few questions, leveraging my knowledge from other programming languages, like how to import packages, write loops, and so on. Afterward, I asked ChatGPT-4o what other aspects I might be missing. It helped me list out topics, and I named folders accordingly. Then, I asked for a few examples under each topic, and voilà, I got several ready-to-use examples. Whenever I faced issues while reading or modifying the code, GitHub Copilot came to the rescue with direct suggestions and comments. For instance, I was puzzled about the differences between private, protected, public, and default, 𝑰 𝒋𝒖𝒔𝒕 𝒘𝒓𝒐𝒕𝒆 // 𝑻𝒉𝒆 𝒅𝒊𝒇𝒇𝒆𝒓𝒆𝒏𝒄𝒆... 𝒂𝒏𝒅 𝑪𝒐𝒑𝒊𝒍𝒐𝒕 𝒇𝒊𝒍𝒍𝒆𝒅 𝒊𝒏 𝒕𝒉𝒆 𝒓𝒆𝒔𝒕, 𝒆𝒙𝒑𝒍𝒂𝒊𝒏𝒊𝒏𝒈 𝒆𝒗𝒆𝒓𝒚𝒕𝒉𝒊𝒏𝒈 𝒑𝒆𝒓𝒇𝒆𝒄𝒕𝒍𝒚. In the end, I asked ChatGPT-4o how to package the Java repo. I mentioned that in Python, I use setup.py / pyproject.toml with pip / poetry. It suggested Gradle or Maven. After a little research, I picked Gradle and asked ChatGPT-4o to help finish the setup and even write the README follow my guidance. Now, I can read through many Java projects without much trouble. And if I do hit a snag, I can quickly ask my assistant (either GPT or another chatbot) for help. Overall, I just want to say that with AI, we can all learn so much faster. It has completely transformed my learning experience and made me way more productive at work and in life. Even if you don't know how to build AI, knowing how to use it can already set you apart. Cheers! Repo: https://lnkd.in/gwFQwngt

Excited to share my latest learning project: Codex DI Framework! 🚀 Over the past few weeks, I've been working on developing a basic, lightweight Dependency Injection and ORM framework for Java applications. This project, while simple, has been an incredible learning journey, pushing me to explore core Java concepts and software design principles. Key features of this basic Codex DI Framework: ✅ Simple Dependency Injection container ✅ Basic ORM capabilities with schema generation ✅ Annotation-based configuration What I've learned through this mini-project: 1. Fundamentals of Java reflection and annotations 2. Basic principles of Dependency Injection 3. Introduction to ORM design and database interaction 4. Maven project structure and dependency management 5. The importance of clean code and modular design Building this basic framework from scratch has given me a new appreciation for the complexities behind professional tools we often use. It's been challenging but incredibly rewarding to see even a simple version come together. The framework is now available on GitHub as a learning resource. I welcome any feedback or suggestions for improvement from the community. Check it out here: https://lnkd.in/e9haemcg #Java #DependencyInjection #ORM #LearningJourney #OpenSource Have you worked on any learning projects recently? I'd love to hear about your experiences and what you've learned!