Anchal Sharma’s Post

𝐈𝐦𝐩𝐨𝐫𝐭𝐚𝐧𝐭 𝐃𝐞𝐬𝐢𝐠𝐧 𝐏𝐚𝐭𝐭𝐞𝐫𝐧𝐬 – 𝐀𝐥𝐥 𝐢𝐧 𝐎𝐧𝐞 𝐏𝐥𝐚𝐜𝐞! I’ve recently joined Myntra(Flipkart). And these are the design patterns which I studied for my interviews at companies like Myntra, Flipkart, Amazon, Razorpay etc. And tbh, it's been a game-changer for my coding skills! I've started sharing my notes and code on various design patterns in my GitHub repository. More exciting content is coming soon, so stay tuned! Meanwhile, feel free to explore what's already there.  𝐋𝐢𝐧𝐤 is in the comments. Your feedback is always welcome! 𝐍𝐨𝐰, 𝐭𝐡𝐞 𝐪𝐮𝐞𝐬𝐭𝐢𝐨𝐧 𝐢𝐬: 𝐖𝐡𝐲 𝐋𝐋𝐃? [𝐆𝐞𝐭 𝐈𝐧𝐭𝐞𝐫𝐯𝐢𝐞𝐰 𝐑𝐞𝐚𝐝𝐲 𝐰𝐢𝐭𝐡 𝐦𝐞 𝐢𝐧 3 𝐦𝐨𝐧𝐭𝐡𝐬!!! ✨ 𝐋𝐢𝐧𝐤: https://lnkd.in/gaBqJxR3 𝐆𝐮𝐲𝐬, 𝐌𝐞 𝐚𝐧𝐝 Ikshit .. 𝐫𝐮𝐧 𝐚 𝐏𝐄𝐑𝐒𝐎𝐍𝐀𝐋 𝐆𝐔𝐈𝐃𝐀𝐍𝐂𝐄 𝐏𝐑𝐎𝐆𝐑𝐀𝐌 𝐰𝐡𝐞𝐫𝐞 𝐈 𝐦𝐲𝐬𝐞𝐥𝐟 𝐦𝐞𝐧𝐭𝐨𝐫 𝐣𝐮𝐬𝐭 50 𝐬𝐭𝐮𝐝𝐞𝐧𝐭𝐬/𝐛𝐚𝐭𝐜𝐡 𝐭𝐨 𝐜𝐫𝐚𝐜𝐤 𝐭𝐡𝐞 𝐒𝐃𝐄 𝐈𝐧𝐭𝐞𝐫𝐯𝐢𝐞𝐰𝐬. 𝐈 𝐰𝐢𝐥𝐥 𝐠𝐮𝐢𝐝𝐞 𝐲𝐨𝐮 𝐟𝐫𝐨𝐦 𝐭𝐡𝐞 𝐯𝐞𝐫𝐲 𝐬𝐜𝐫𝐚𝐭𝐜𝐡: 𝐥𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐩𝐫𝐨𝐠𝐫𝐚𝐦𝐦𝐢𝐧𝐠 𝐥𝐚𝐧𝐠𝐮𝐚𝐠𝐞, 𝐃𝐒𝐀, 𝐂𝐨𝐦𝐩𝐮𝐭𝐞𝐫 𝐂𝐨𝐧𝐜𝐞𝐩𝐭𝐬, 𝐋𝐋𝐃 + 𝐇𝐋𝐃, 𝐑𝐞𝐬𝐮𝐦𝐞 𝐑𝐞𝐯𝐢𝐞𝐰, 𝐏𝐫𝐨𝐣𝐞𝐜𝐭𝐬 𝐂𝐫𝐞𝐚𝐭𝐢𝐨𝐧 & 𝐚𝐭 𝐭𝐡𝐞 𝐞𝐧𝐝 𝐉𝐨𝐛 𝐇𝐮𝐧𝐭𝐢𝐧𝐠 𝐓𝐞𝐦𝐩𝐥𝐚𝐭𝐞𝐬 & 𝐓𝐫𝐢𝐜𝐤𝐬!!!  𝑨 𝒏𝒆𝒘 𝒃𝒂𝒕𝒄𝒉 𝒊𝒔 𝒄𝒐𝒎𝒊𝒏𝒈 𝒖𝒑 𝒊𝒏 𝑴𝒊𝒅-𝑶𝒄𝒕𝒐𝒃𝒆𝒓.] Tbh guys, It is a Must-Have Skill.  - Most companies now include LLD in their SDE-1 interviews. It's your chance to stand out from the crowd. - Better Coding Practices: LLD isn't just for interviews—it's essential for writing clean, efficient, and scalable code. - Mastering LLD helps you become a more versatile and skilled software engineer. 𝐇𝐨𝐰 𝐭𝐨 𝐩𝐫𝐨𝐜𝐞𝐞𝐝 𝐰𝐢𝐭𝐡 𝐋𝐋𝐃? - Get a solid grasp of OOPs(Encapsulation, Inheritance, Abstraction and Polymorphism). - Learn Design Patterns: Familiarise yourself with patterns like Singleton, Observer, and Factory and other important patterns to solve common design problems effectively. - Practice UML Diagrams: Use class and sequence diagrams to visualise your designs. - SOLID Principles: These principles ensure your code is maintainable and scalable. Don't get stuck on just Data Structures and Algorithms. Broaden your skill set and prepare for the real-world challenges in software development. Hope it helps!!! ❤️

Confused about what are companies asking DSA or Dev or System Design ? Many people are unsure whether to prioritize DSA, Development, or System Design for interviews 🤔 Lets clear the confusion once and for all. A typical way to look into this is to Divide the companies into below categories respectively - 🔍 𝐓𝐨𝐩 𝐏𝐫𝐨𝐝𝐮𝐜𝐭 𝐛𝐚𝐬𝐞𝐝 𝐌𝐍𝐂𝐬 𝐚𝐧𝐝 𝐓𝐞𝐜𝐡 𝐆𝐢𝐚𝐧𝐭𝐬 :  If you're aiming for big product-based companies, DSA is essential. You also need a solid grasp of System Design, especially for SDE-2 and above positions. Despite what some might say, DSA + System Design is crucial here. 💡 𝐕𝐞𝐫𝐲 𝐄𝐚𝐫𝐥𝐲 𝐬𝐭𝐚𝐠𝐞 𝐒𝐭𝐚𝐫𝐭𝐮𝐩𝐬 :  Interested in Dev ? If you're passionate about development, early-stage startups are for you. These companies don't usually require DSA but expect you to be excellent in core software engineering skills due to the fast-paced environment. 📢 𝐌𝐢𝐝 𝐒𝐢𝐳𝐞𝐝 𝐒𝐭𝐚𝐫𝐭𝐮𝐩𝐬 :  Focus here is mostly on development, but expect one DSA round and a few system design rounds. It's great for those looking to understand startup dynamics. 📝 𝐒𝐞𝐫𝐯𝐢𝐜𝐞 𝐁𝐚𝐬𝐞𝐝 𝐂𝐨𝐦𝐩𝐚𝐧𝐢𝐞𝐬 :  These companies focus on DSA and development/projects, but the difficulty level is generally lower. Exception are always there , IYKYK. Your target company determines what to focus on. Know where you want to work and prepare accordingly! 💪 Follow Gourav Roy for more such Amazing content 💚 👨💻 𝐂𝐨𝐧𝐧𝐞𝐜𝐭 𝐨𝐧 𝐈𝐧𝐬𝐭𝐚𝐠𝐫𝐚𝐦 - https://lnkd.in/dKdn2yeA 𝐈𝐟 𝐲𝐨𝐮 𝐰𝐚𝐧𝐭 𝐭𝐨 𝐤𝐧𝐨𝐰 𝐦𝐨𝐫𝐞 𝐚𝐛𝐨𝐮𝐭 𝐄𝐱𝐩𝐞𝐜𝐭𝐚𝐭𝐢𝐨𝐧 𝐚𝐧𝐝 𝐓𝐨𝐩𝐢𝐜𝐬 𝐟𝐨𝐫 𝐃𝐒𝐀, 𝐒𝐲𝐬𝐭𝐞𝐦 𝐃𝐞𝐬𝐢𝐠𝐧 𝐚𝐧𝐝 𝐅𝐫𝐨𝐧𝐭-𝐞𝐧𝐝 𝐈𝐧𝐭𝐞𝐫𝐯𝐢𝐞𝐰𝐬, 𝐆𝐞𝐭 𝐲𝐨𝐮𝐫 𝐑𝐞𝐬𝐮𝐦𝐞 𝐑𝐞𝐯𝐢𝐞𝐰𝐞𝐝, 𝐆𝐢𝐯𝐞 𝐚 𝐌𝐨𝐜𝐤 𝐈𝐧𝐭𝐞𝐫𝐯𝐢𝐞𝐰, 𝐟𝐞𝐞𝐥 𝐟𝐫𝐞𝐞 𝐭𝐨 𝐂𝐨𝐧𝐧𝐞𝐜𝐭 𝐰𝐢𝐭𝐡 𝐦𝐞 𝐡𝐞𝐫𝐞 : 👨💻 𝐂𝐨𝐧𝐧𝐞𝐜𝐭 𝐨𝐧 𝐭𝐨𝐩𝐦𝐚𝐭𝐞.𝐢𝐨 - https://lnkd.in/gyGxA7ut 👨💻 𝐏𝐫𝐞𝐩𝐥𝐚𝐜𝐞𝐝 𝐋𝐨𝐧𝐠 𝐓𝐞𝐫𝐦 𝐌𝐞𝐧𝐭𝐨𝐫𝐬𝐡𝐢𝐩 - https://lnkd.in/g75PrUXC #javascript #softwareengineering #leetcode #datastructures #algorithms

𝐈𝐦𝐩𝐨𝐫𝐭𝐚𝐧𝐭 𝐃𝐞𝐬𝐢𝐠𝐧 𝐏𝐚𝐭𝐭𝐞𝐫𝐧𝐬 – 𝐀𝐥𝐥 𝐢𝐧 𝐎𝐧𝐞 𝐏𝐥𝐚𝐜𝐞! Hey Everyone, I've been studying Low-Level Design (LLD) lately, and it's been a game-changer for my coding skills! I've started sharing my notes and code on various design patterns in my GitHub repository. More exciting content is coming soon, so stay tuned! Meanwhile, feel free to explore what's already there.  𝐋𝐢𝐧𝐤: https://lnkd.in/gtxbdimE Your feedback is always welcome! 𝐍𝐨𝐰, 𝐭𝐡𝐞 𝐪𝐮𝐞𝐬𝐭𝐢𝐨𝐧 𝐢𝐬: 𝐖𝐡𝐲 𝐋𝐋𝐃? Tbh guys, It is a Must-Have Skill.  - Most companies now include LLD in their SDE-1 interviews. It's your chance to stand out from the crowd. - Better Coding Practices: LLD isn't just for interviews—it's essential for writing clean, efficient, and scalable code. - Mastering LLD helps you become a more versatile and skilled software engineer. 𝐇𝐨𝐰 𝐭𝐨 𝐩𝐫𝐨𝐜𝐞𝐞𝐝 𝐰𝐢𝐭𝐡 𝐋𝐋𝐃? - Get a solid grasp of OOPs(Encapsulation, Inheritance, Abstraction and Polymorphism). - Learn Design Patterns: Familiarise yourself with patterns like Singleton, Observer, and Factory and other important patterns to solve common design problems effectively. - Practice UML Diagrams: Use class and sequence diagrams to visualise your designs. - SOLID Principles: These principles ensure your code is maintainable and scalable. Don't get stuck on just Data Structures and Algorithms. Broaden your skill set and prepare for the real-world challenges in software development. Hope it helps!!! ❤️

For preparing for a software engineering role in a product-based company, here are two impactful project ideas that cover essential skills and give you hands-on experience with software engineering principles: 1. Full-Stack E-Commerce Web Application Description: Build a full-stack e-commerce application where users can browse products, add items to their cart, make payments, and track their orders. This project will help you learn about frontend, backend, and database development while also giving you exposure to authentication, data handling, and secure payment processing. Tech Stack: HTML, CSS, JavaScript, React (or Angular), Node.js (or Django), Express, MongoDB (or MySQL), and possibly a payment gateway API (like Stripe or Razorpay). Key Skills Learned: Frontend and backend integration. Database schema design and SQL/NoSQL management. User authentication and authorization. RESTful API development and deployment practices. Secure transactions and payment processing. 2. Scalable Microservices-Based Application Description: Develop an application using a microservices architecture, such as a simple ride-sharing or food delivery app. Divide it into separate services like user management, order processing, and location services. This will teach you how large-scale applications are structured in product-based companies. Tech Stack: Docker, Kubernetes, Node.js (or Python/Django), RabbitMQ (or Kafka), PostgreSQL, and REST/gRPC APIs. Key Skills Learned: Microservices architecture and communication between services. Containerization (Docker) and orchestration (Kubernetes). Inter-service communication and asynchronous messaging. API gateways and load balancing. Monitoring and logging in distributed systems. These projects will provide valuable experience with scalable system design, backend development, and deployment practices, which are crucial for a software engineering role at a product-based company.

The Only 10 Books You Need to Become a Better Software Engineer. A Must-Read List for SDE 2 and SDE 3 :- 01. Clean Code: A Handbook of Agile Software Craftsmanship by Robert C. Martin   - This book emphasizes writing clean, readable and maintainable code. It's a must-read for building a strong foundation in coding practices. 02. Refactoring: Improving the Design of Existing Code by Martin Fowler   - Refactoring teaches how to improve the design of existing code by making small, systematic changes. This is crucial for maintaining and enhancing codebases. 03. Design Patterns: Elements of Reusable Object-Oriented Software by Erich Gamma, Richard Helm, Ralph Johnson and John Vlissides (Gang of Four)   - This classic book introduces common design patterns that help solve recurring design problems, making your code more flexible and reusable. 04. The Pragmatic Programmer: Your Journey to Mastery by Andrew Hunt and David Thomas   - This book covers a wide range of topics to help you think critically, adopt best practices and stay adaptable in your programming career. 05. Introduction to Algorithms by Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest and Clifford Stein   - A comprehensive textbook on algorithms, essential for understanding the theoretical foundations of computer science and problem-solving. 06. Designing Data-Intensive Applications (DDIA) by Martin Kleppmann   - DDIA is a deep dive into modern data systems, covering the challenges of building and maintaining reliable, scalable and maintainable systems. 07. Building Microservices: Designing Fine-Grained Systems by Sam Newman   - This book provides practical advice on how to build microservices, a modern approach to designing scalable and maintainable systems. 08. Understanding Distributed Systems by Roberto Vitillo   - An accessible introduction to the principles and challenges of distributed systems, a must-read for engineers building scalable systems. 09. Database Internals: A Deep Dive into How Distributed Data Systems Work by Alex Petrov   - This book explores the inner workings of database systems, offering insights into their architecture, algorithms and performance. 10. Web Scalability for Startup Engineers by Artur Ejsmont   - A practical guide to designing scalable web applications, this book is particularly useful for engineers working in fast-paced startup environments. How many of you have read these books and do you have any other recommendations?

Devin AI VS Software Engineering 🚀 **The Journey of Jyoti, A Engineering Student: How Devin AI Became Her Trusted Companion on the Software Engineering Path** 🚀 Once upon a recent time, in a bustling college filled with ambitious minds, there was a B.Tech student named Jyoti. Like many of you, Jyoti dreamt of conquering the world of software engineering, armed only with her laptop and an insatiable curiosity. 👩💻 As the semesters unfolded, Jyoti encountered the mythical beast known as "coding complexity"—a challenge every software engineer must face. She grappled with algorithms that twisted and turned like serpents, and debugged lines of code that seemed like a labyrinth designed by Daedalus himself. 🌟 Then one day, as she navigated the dense forest of Stack Overflow threads, Maya stumbled upon a legend whispered among her peers—the tale of Devin AI. Devin AI wasn't like any other tool she had used before. It was said to be born from the minds of those who had danced with code and emerged enlightened. With Devin AI by her side, Jyoti could: ✨ *Translate her thoughts into flawless code with ease.* ✨ *Refactor the Gordian knots in her scripts with a few keystrokes.* ✨ *Predict the outcomes of her programs with the foresight of an oracle.* Curiosity piqued, Jyoti invoked Devin AI, and before her eyes, the screen lit up with possibilities. Each session with Devin AI was like a dialogue with a mentor who possessed infinite patience and knowledge. 🔍 Through Devin AI, Jyoti learned to see patterns in chaos and elegance in solutions. She began to share her journey with Devin AI on LinkedIn, inspiring her fellow students with tales of how: 📈 *Her productivity soared like a rocket.* 🤖 *Her understanding of complex concepts solidified like ancient ruins standing against time.* 🎓 *Her projects became masterpieces that told of her growth and her partnership with Devin AI.* So, dear future software engineering maestros, I share with you the saga of Jyoti and Devin AI. Whether you're battling bugs or architecting the next breakthrough app, remember—Devin AI can be your ally, your guide, and your friend in this digital odyssey. 👇 Are you ready to write your own legend with Devin AI? Share your thoughts, or better yet, your own stories with Devin AI in the comments! #SoftwareEngineering #DevinAI #CodingJourney #TechTales #BtechLife #Innovation #AI #FutureOfCoding

Code Reviews Are Meant to Build You Up, Not Tear You Down In our coding journeys, many of us will encounter confronting code reviews that seem daunting. Where your work gets scrutinized line by line. Where instead of celebrating success, more gets focused on what's wrong versus what's right. It's understandable to feel discouraged in such situations. To take criticism of your code too personally and have it hurt your confidence. Code reviews often feel like a report card grading our worth. But their true intent is to build your skills and contribute to collective gains. Reviewers aim to share constructive suggestions that amplify strengths and refine shortcomings - with sensitivity and care. That said, not all feedback gets delivered thoughtfully at first. Mentors have to hedge unfiltered feedback for juniors. And teammates confront unfamiliar styles. With mutual empathy and communication, code review conversations become less about proving correctness but more about how we can uplift each other. Rather than tearing down blindly, we thoughtfully offer better alternatives. Reflect sincerely on whether there is merit to ideas that challenge your own. Be receptive to techniques that may lift the collective bar higher. Advice coming from care should not be confused for condemnation.  With the right support, code reviews become symbols of a team's pursuit of excellence. Of holding each other to the highest standards with compassion and respect. #codereview #developer #softwaretesting #softwaredevelopment #developer #cloud #devops #dsa #freshers #jobs #hiring

As software engineers, we're constantly at the forefront of technological evolution, witnessing remarkable shifts that redefine how we craft and innovate. Let's take a moment to reflect on this journey, from the early days of low-level programming to the transformative era of AI integration. In the 60s and 70s, software engineering was basic low-level programming, where every line of code had to be crafted to perform specific tasks. It was hard and complex to understand and develop, but it also did automate a lot of manual jobs at the time. Over the decades, new languages and tools emerged and simplified the work on different tasks like web development and networking, and languages like C++, Java, etc. provided those functionalities out of the box. Fast forward to today, and we've got all these cool programming languages like JavaScript, Python, Go, you name it. These languages make our lives a whole lot simpler and let us build stuff way faster. Plus, there are tons of handy tools and frameworks out there that help us work smarter, not harder. Some of them are barely in the native language but provide all those abstractions that you don’t even know how they are working to build software with them, and the core concepts that they are using underneath this abstraction are the same ones developed in the previous decades. Up until now, software engineering jobs are in high demand and have been constantly increasing compared to the 70s, 80s, or even the 2000s. Now, let's talk about AI. You might've heard about it in the news or seen it in movies, but it's not just science fiction anymore. Recently, the CEO of Nvidia gave a speech about how AI is changing the game for us software folks. He said that AI could even start doing some of the coding for us and people should not learn to code anymore, which is pretty wild when you think about it. And then there's Devin AI – it's being called the world's first AI software engineer. It's a super smart computer program that can help us write code, check its quality, and suggest improvements. It's like having a coding buddy who never gets tired or makes mistakes. Still... In my daily development cycle, I already use Copilot or other tools that help me develop faster. It is just that, develop faster. It means that they gave suggestions and auto-completion, but never gave the exact solution that I was searching for. Sometimes I ended up spending more time debugging, than developing the thing from scratch. Looking ahead to the next decade, we anticipate significant changes in the development process, for better or worse. However, I doubt that it will become so autonomous that human interaction won't be necessary. Until then, we will still be here!   #SoftwareEngineering #AI #Innovation #FutureOfWork #TechEvolution

Is the ticket to AI success hidden in the line between perfection and good enough? Is big picture thinking all it takes to unlock the the value of this new tech? It’s obviously much easier to imagine conceptually than practically, but I do think it’s worth consideration… #genai #modernsoftwaredev

We have aggregated, and #developed some great material here at #PagerTree to help those getting started on their #Docker journey and to help those who could benefit from some great resources. Learn more at https://buff.ly/4aopnDn #Devops #Coding #develpment #Developers