Ayush Shaw

This really showcases the power that cloud-based IDEs can eventually provide the rest of the world, outside of Big Tech. Google, much like other large companies has tons of internal tooling for build systems (similar to Bazel or Buck), caching, version control, virtual file systems, dependency management, containerization, logging and monitoring, etc. Making tools like this more accessible outside of these companies with less maintenance required (meaning less engineering resources for tool development and maintenance) will be exponentially more powerful for engineering delivery as a whole. We are seeing this within many tools from GitHub, AWS, StackBlitz, GitPod, and many others. We are also seeing many Open-Source Build tools for monorepo management that rival these companies, such as Nx.dev, Turborepo by Vercel, Pants, Buck and Bazel. Docker and K8s has enabled containerization and scaling across the world via a single machine or multi-region + multi-cluster deployment strategy. We are now also seeing tech like WASM enter the space for building near-native applications that run in the browser. Soon, native desktop apps and developer experience will fully be automated by the cloud and I am excited to see this. #softwareengineering #devops #buildsystem #tooling

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𝐂𝐨𝐝𝐞𝐟𝐨𝐫𝐜𝐞𝐬 𝐑𝐨𝐮𝐧𝐝 983 : 𝐄𝐝𝐢𝐭𝐨𝐫𝐢𝐚𝐥 : 𝐀-𝐃 𝐀 - Minimum will be number of one’s mod 2.       For Maximum, if number of one’s is greater than is less than or equal to n, then answer will be number of one’s else the answer will be 2*n - no_of_ones. 𝐁 - if k is even then just break like 1, k, k+1 If k is odd then break like 1, 2, k, k+1, n 𝐂 - sort the array, start iterating from left to right get the rightmost index j for index i such that a[j]<a[i]+a[i+1], hence you don’t need to change anything in this window and have to change all the elements outside this window which will be first i-1 elements and last n-j elements, maintain a minimum and update for each i. 𝐃 - First get those nodes that are connected to 0 directly, after that maintain a set of leaf nodes, for any new number to check for its parent, First check with the biggest leaf node, if it turns out to be true, replace the biggest leaf node with the node for which you were checking as now it will be the leaf node Otherwise, start checking from smaller leaf nodes. If a leaf node you are checking now is not the parent of this current node, you just pop out this leaf node as the subtree of this branch is already over, and no new node will be connected to this in the future. Then, check for the next bigger leaf node until you find the parent, then repeat process 1.

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𝐇𝐞𝐚𝐝𝐥𝐢𝐧𝐞: 𝐄𝐦𝐛𝐫𝐚𝐜𝐞 𝐭𝐡𝐞 𝐉𝐨𝐮𝐫𝐧𝐞𝐲: 𝐇𝐚𝐫𝐝 𝐖𝐨𝐫𝐤 𝐀𝐥𝐰𝐚𝐲𝐬 𝐏𝐚𝐲𝐬 𝐎𝐟𝐟 💪 Navigating the competitive landscape of the software industry can be challenging, but the journey is full of valuable lessons and opportunities for growth. Here’s my story: 🔻🔻🔻🔻🔻🔻🔻🔻🔻🔻🔻🔻🔻🔻 In the past few months, I’ve appeared for more than 15 interviews. Some were successful, and others were learning experiences. Here’s a breakdown: 🙏Cleared the interview and machine coding round in 5 companies, but was ultimately rejected due to experience.👎 ❌❌Rejected from 5-6 interviews due to DSA, lack of technical skills, and other reasons.🔕🔕 ✍️Despite these setbacks, I’ve successfully cleared 4-5 interviews for roles including Frontend Developer, Cloud Engineer, and Service Desk.🙏💟 ⭐🌟Currently, I’m working as a Software Engineer but am actively seeking new opportunities, specifically in Frontend Development or MERN Stack Development.🎉 𝗞𝗲𝘆 𝗧𝗮𝗸𝗲𝗮𝘄𝗮𝘆𝘀 𝗳𝗿𝗼𝗺 𝗠𝘆 𝗜𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄 𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲 . . . For Startups_💪💪 Development and DSA are both crucial. DSA Topics to Focus On:☑️ Basics with loops➡️ Arrays➡️ Strings➡️ Hashmaps➡️ Linked Lists➡️ Stack➡️ Queues➡️ These topics will give you a solid foundation for startup roles. For Development_✅ HTML 👁️‍🗨️ CSS◼️ JavaScript (most important)◻️ React.js🔲 Node.js◻️ Database management👁️‍🗨️ My Journey Forward:👁️‍🗨️👁️‍🗨️👁️‍🗨️ I am actively looking for Frontend Developer and MERN Stack Developer roles. If you know of any opportunities or can provide assistance, I would be extremely grateful. follow Sanket Rahangdale for more ❤️

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Top 5 Must-Know DSA Patterns👇🏻👇🏻 DSA problems often follow recurring patterns. Mastering these patterns can make problem-solving more efficient and help you ace coding interviews. Here’s a quick breakdown: 1. Sliding Window • Use Case: Solves problems involving contiguous subarrays or substrings. • Key Idea: Slide a window over the data to dynamically track subsets. • Examples: • Maximum sum of subarray of size k. • Longest substring without repeating characters. 2. Two Pointers • Use Case: Optimizes array problems involving pairs or triplets of elements. • Key Idea: Use two pointers to traverse from opposite ends or incrementally. • Examples: • Pair with target sum in a sorted array. • Trapping rainwater problem. 3. Binary Search • Use Case: Efficiently solves problems with sorted data or requiring optimization. • Key Idea: Repeatedly halve the search space to narrow down the solution. • Examples: • Find an element in a sorted array. • Search in a rotated sorted array. 4. Dynamic Programming (DP) • Use Case: Handles problems with overlapping subproblems and optimal substructure. • Key Idea: Build solutions iteratively using a table to store intermediate results. • Examples: • 0/1 Knapsack problem. • Longest common subsequence. 5. Backtracking • Use Case: Solves problems involving all possible combinations, subsets, or arrangements. • Key Idea: Incrementally build solutions and backtrack when a condition is not met. • Examples: • N-Queens problem. • Sudoku solver. Why These Patterns? By focusing on patterns, you can identify the right approach quickly, saving time and improving efficiency in problem-solving.

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A common useState(); hook mistake that every beginner do, instead of declaring each variable again and again, we must use a single state variable to store all the values. As less the state variables are, more efficient the app is. If you enjoyed the content, please share with your circle. Follow Ahmad Raza Khokhar for more wonderful content.

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212. Word Search II Note: Use Tries and backtracking DFS to iterate over all the words. EndofWord is set to false during DFS to prevent duplicates but since we are using set() for result so technically the answer will be the same. TC: ~O(S * 3^L), where S is the number of cells on the board and L is the length of the longest word due to in DFS we only have 3 directions to search after the initial DFS. SC: O(N * L), where N is the number of words and L is the average length of the words.

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Do you really understand how cleanup functions works in useEffect ? This is a great article by Newton School which explains the working of useEffect and cleanup function in the simplest terms and with examples. A must read - https://lnkd.in/dC6fVk5M #reactjs #useEffect #article #newtonschool

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If React is your daily jam, you'll dig this post. A while back, I shared some book recommendations. While I gave a quick rundown of each, I want to give a special shoutout to "𝘍𝘭𝘶𝘦𝘯𝘵 𝘙𝘦𝘢𝘤𝘵" (https://lnkd.in/dntjZ_N8) by Tejas Kumar. Let's get into why this book is so cool. 𝗛𝗲𝗮𝗱𝘀 𝗨𝗽: This book won't teach you React from the ground up, and that's not what it's for. If you're just starting with React, this one might not be for you (learning a framework from a book isn't usually the best way to go anyway). 𝗢𝗸𝗮𝘆, 𝗻𝗼𝘄 𝗳𝗼𝗿 𝘁𝗵𝗲 𝗴𝗼𝗼𝗱 𝘀𝘁𝘂𝗳𝗳. I've been working with React for a while (long enough to remember the days of class components 😉). I've read a ton of React books, but this one takes the cake when it comes to explaining what's happening behind the scenes. It's like having someone walk you through the source code and explain everything in plain English. 𝗪𝗵𝗮𝘁'𝘀 𝗶𝗻𝘀𝗶𝗱𝗲 𝘁𝗵𝗶𝘀 𝘁𝗿𝗲𝗮𝘀𝘂𝗿𝗲 𝘁𝗿𝗼𝘃𝗲? ▪️ A quick history of JSX and React ▪️ DOM and vDOM, plus why we need them ▪️ A deep dive into how React figures out what to update on your screen (every single step explained) ▪️ React patterns and the latest features (like concurrent React and SSR) ▪️ Meta frameworks like Next.js 𝗧𝗵𝗲 𝗯𝗼𝘁𝘁𝗼𝗺 𝗹𝗶𝗻𝗲: You don't need to know all this stuff to build awesome things with React. Most React devs don't know what goes on under the hood, and they do just fine. It's like driving a car – you don't need to know how the engine works, what a clutch is, or why we need an alternator. But if something breaks down, you'll need to call a mechanic (that's the dev who knows all the nitty-gritty). So, what are you waiting for? Go grab this book, you won't regret it.

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Day 5 Short polling Is used to check for updates or new data without continuously refreshing the entire page or resource by sending repeated requests. - Short-lived requests - Less resource-intensive - Scaling issues - Used in notifications etc #javascript #FrontEndDeveloper

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Most front-end developers lose interest in solving DSA because "They keep picking problems which do not follow any pattern". Let me explain 1. Let's solve a problem on arrays by using a two pointer approach. If that is your first time solving a 2 pointer approach problem. 2. Then do not pick your next problem where you use a new technique, ex: sliding window. 3. Solve problems similar to how you solve problems in college days. Solve a few related problems, so that you become conceptually strong. Once after you're conceptually strong about a technique, then move to the next technique. Same goes for the Data structure. But, once after you have solved a good number of problems, you start picking random problems to test your skills. Follow me and I will help you to find your dream job: Vasanth Bhat

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Chrome just released their Manifest V3, which attracted lots of eye balls. Because, it (finally) came with the ability to block all kinds of Ad-blockers. But this Manifests are initially designed to give Chrome Extensions more powers. And since we are discussing that : I have wrote a detailed blog piece on these Browser Extensions ➡️ How they work ➡️ Where they are mostly useful ➡️ How is the developer community Have a read and feel free to add your further thoughts 🙌🏻 (link in the first comment)

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Summer and elections in India have a lot in common. For starters, they're both scorching hot ♨️. As the immense saga of the Indian election draws to a close, let's applaud you for playing your part despite the smouldering heat waves. While India decides on its leadership for the next five years, let's take a look at the leading technologies from the Stack Overflow Developer Survey 2023. 🅹🅰🆅🅰🅲🆁🅸🅿🆃 continues to be the most popular language🌟📜💛. 🐻♥ 𝐏𝐨𝐬𝐭𝐠𝐫𝐞𝐒𝐐𝐋✌🍩 becomes most widely used database amongst pro-devs stealing the spotlight from MySQL. (っ◔◡◔)っ ♥ ReactJs and NodeJS ♥ reign supreme as the most popular web technologies. ⒶⓌⓈ remains the most used cloud platform for all respondents. ♔😈 ⓋⓈ ＣỖ𝔻Ẹ ☢🐣 is still the most popular IDE/Text Editor amongst all respondents. 💲😲 🆉🅸🅶 🎁💥 says bling as it is the highest paying language to know. https://lnkd.in/g8zyRSPf

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7 Techniques to Solve Array Problems Struggling with array problems? Here are 7 techniques to help you crack them efficiently: Two-Pointer Technique 🏃‍♂️🏃‍♀️ Use two pointers to traverse the array from different ends. Great for problems involving pairs or finding specific elements. Sliding Window 🪟 Ideal for problems that involve contiguous subarrays. Slide a window of fixed size over the array to find the maximum, minimum, or sum. Prefix Sum & Difference Array ➕➖ Calculate running totals or differences to quickly answer range queries or find subarray sums. Hash Maps 🗺️ Use hash maps for quick lookups, like checking if a complement exists for a target sum or finding duplicates. Sorting 🧮 Sorting the array can simplify problems, especially when combined with binary search or the two-pointer technique. Dynamic Programming 📈 Break down problems into subproblems and solve them recursively. This works well for finding maximum subarray sums or counting ways to split an array. Greedy Algorithms 🤑 Make the best possible decision at each step. Useful for problems where you need to find an optimal subarray or minimize/maximize some value. Master these techniques, and you'll be solving array problems like a pro! 💡 #Coding #ArrayProblems #Techniques #ProgrammingTips #LeetCode #DataStructures #AlgorithmSkills

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🚀 𝐀𝐝𝐯𝐞𝐧𝐭 𝐨𝐟 𝐂𝐨𝐝𝐞 𝟐𝟎𝟐𝟒: 9 Days of Non-Stop Coding! 🎄💻 I've been diving deep into Advent of Code 2024, and it's been an incredible journey so far! Starting with a global rank of 200K, I've managed to push my rank up to 16K in just 9 days! 🎉 Each day brings a new challenge, pushing my problem-solving skills and coding abilities to the next level. It's not just about the rank; it's about learning, growing, and embracing the joy of coding every single day. Still coding. Still improving. The grind doesn't stop! 🔥💪 #AdventOfCode #CodingJourney #LearningAndGrowing #25DaysOfCode #WinterCoder

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**LinkedIn Post** **System Design Problem: Real-time Collaborative Document Editing Tool** In today's fast-paced digital world, having tools that allow for seamless real-time collaboration has become indispensable. Imagine designing a platform that allows multiple users to edit documents in real time, concurrently. How would you ensure consistency, minimal latency, and robust conflict resolution? Key challenges include: 1. **Real-time Collaboration:** Ensuring that changes made by users are instantly visible to all collaborators with minimal delays. 2. **Conflict Resolution:** Implement a method to manage concurrent edits made by different users at the same time, ensuring document consistency. 3. **Scalability:** Support potentially thousands of concurrent users editing multiple documents simultaneously. 4. **Offline Editing and Syncing:** Allow users to make edits while offline and seamlessly integrate those changes once they reconnect. **Solution Proposal:** To tackle these challenges: - **Operational Transform (OT) or Conflict-free Replicated Data Types (CRDT):** Implement OT or CRDT algorithms to manage real-time editing conflicts. These allow concurrent modifications without blocking and ensure eventual consistency. - **Distributed Architecture:** Create a backend service using microservices architecture, distributed across multiple geographic locations to reduce latency. Utilize a publish/subscribe model (e.g., using WebSockets) to maintain live connections with clients for instant updates. - **Load Balancing and Autoscaling:** Use cloud-based solutions like AWS or GCP, integrating a load balancer and autoscaling groups to handle dynamic user loads and ensure high availability. - **Data Consistency & Persistence:** Utilize NoSQL databases like MongoDB or Firebase for flexible, real-time data storage. Implement logging and version control to rollback changes if necessary. - **Offline Capability:** Implement local storage on clients using IndexedDB or similar technologies to allow for offline edits. Develop sync mechanisms to merge changes once users come back online, focusing on minimal conflict generation and resolution. This approach balances the need for real-time collaboration with the robustness and scalability required for a wide user base. By leveraging mature algorithms and cloud services, we can create a system that empowers users to collaborate effortlessly, regardless of where they are in the world. #SystemDesign #CollaborationTools #TechInnovation #RealTimeEditing #SoftwareEngineering

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**LinkedIn Post:** **System Design Challenge: Real-Time Ride-Sharing Platform** **Problem Statement:** Design a scalable system for a real-time ride-sharing platform similar to Uber or Lyft. The platform should efficiently match riders with drivers in near real-time, ensure low latency for ride requests, and handle peak traffic smoothly. Key features include: 1. Real-time location tracking for drivers and riders. 2. Efficient driver allocation based on proximity and availability. 3. Scalable architecture to handle millions of concurrent users. 4. Dynamic pricing for surge times. 5. Robust data storage and retrieval for ride history and user profiles. 6. Reliable payment processing and transaction logging. **Solution:** To tackle this problem, we can leverage a microservices architecture to ensure scalability, fault tolerance, and maintainability. Heres a high-level overview of the system design: 1. **Microservices Architecture**: Split the system into microservices such as User Management, Ride Matching, Location Tracking, Payment Processing, and Pricing. This allows easy scaling and independent deployment. 2. **Data Storage**: Use a mix of databases to cater to different needs. A NoSQL database like MongoDB or Cassandra for user profiles and ride history, an in-memory data store like Redis for transient data like current ride status, and a relational database like PostgreSQL for transactions and payment logs. 3. **Real-time Communication**: Utilize WebSockets or gRPC to maintain persistent connections with clients for real-time tracking and updates. This reduces latency and enhances the user experience. 4. **Load Balancing & Scaling**: Employ cloud-based load balancers (e.g., AWS Elastic Load Balancing) and auto-scaling groups to handle varying traffic loads efficiently. This ensures stability, especially during peak demand. 5. **Dynamic Pricing Algorithm**: Implement a machine learning model to adjust pricing based on factors like demand, supply, location, and time. This helps in managing surge pricing and driver incentives. 6. **Efficient Matching**: Use geospatial indexing and algorithms to quickly match riders with the nearest available drivers. This can be further optimized with predictive analytics to pre-position drivers in high-demand areas. 7. **Monitoring & Logging**: Deploy robust monitoring using tools like Prometheus and Grafana for system health and reliability. Use centralized logging with tools like ELK Stack for debugging and auditing. By designing a system with these components, we build a platform that is robust, scalable, and capable of offering a seamless service to both drivers and riders around the clock. #SystemDesign #Architecture #RideSharing #Microservices #Scalability #RealTime #Uber #Lyft

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To participate in the Har Ghar Tiranga campaign, I've created a tutorial demonstrating how to build a Spring Boot MVC app. By accessing the URL, you can virtually hoist the Tiranga flag. You might think you need to build the entire app yourself, but don't worry—I've already deployed my app on Render, and it will remain live until midnight on August 15th. For now, you can hoist the flag using the deployed app, and later, you can create your own version. Links are provided in the description. #Harghartiranga

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ChAI Talk #3: LLMs and Tokens (Word Chunks) ☕️🧩 ☕️ 𝗧𝗼𝗱𝗮𝘆'𝘀 𝘀𝗶𝗽: LLMs Learn New Words Just Like Us! 🧠💡 Remember learning 'play' + 'ground' = 'playground'? LLMs do the same with 'tokens' (word parts). Why use tokens? 1. Speed: Process language faster 2. Smarts: Understand new words easily How it works: • LLM recognizes parts: 'play', 'ing', 'er', 'sing' from known words ('playing', 'singer') • LLM combines parts: Learns new word 'play' + 'er' = 'player', 'sing' + 'ing' = 'singing'. Result: Huge vocab from fewer parts! 🤯 𝗠𝗶𝗻𝗱-𝗯𝗼𝗴𝗴𝗹𝗶𝗻𝗴 𝗳𝗮𝗰𝘁: GPT-3 covers all English with a 50,000-token vocabulary, from 𝘵𝘦𝘢 to 𝘱𝘯𝘦𝘶𝘮𝘰𝘯𝘰𝘶𝘭𝘵𝘳𝘢𝘮𝘪𝘤𝘳𝘰𝘴𝘤𝘰𝘱𝘪𝘤𝘴𝘪𝘭𝘪𝘤𝘰𝘷𝘰𝘭𝘤𝘢𝘯𝘰𝘤𝘰𝘯𝘪𝘰𝘴𝘪𝘴! 👇 𝗬𝗼𝘂𝗿 𝘁𝘂𝗿𝗻: Play around with https://lnkd.in/e3cw3Gmc to see how words break into tokens! Share your experience below! #ChAI #ChAITalk #ChAITalk03 #LLM #NLP #ML #AI #OpenAI #GPT3

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