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Sharing the list of FREE resources I used to transition from TCS to Intuit 🚀 I have been asked many times about the resources I referred to for preparation. So, here it is.👇 𝐅𝐨𝐫 𝐃𝐒𝐀 👉 I used GeeksforGeeks to consistently solve problems everyday for 2-4 hours after work hours. 👉 Applying filters on the topic and top companies list helped. 👉 I did not have takeUforward during my time, but you have Raj Vikramaditya. So, you can refer to Striver’s SDE sheet for preparation. 𝐅𝐨𝐫 𝐒𝐲𝐬𝐭𝐞𝐦 𝐃𝐞𝐬𝐢𝐠𝐧 👉 System Design Interview book by Alex Xu 👉 Gaurav Sen’s playlist 𝐅𝐨𝐫 𝐉𝐚𝐯𝐚, 𝐒𝐩𝐫𝐢𝐧𝐠𝐁𝐨𝐨𝐭 👉 Wanna read? - javatpoint.com 👉 Binge watcher? - Navin Reddy’s Youtube channel - TELUSKO 𝐅𝐨𝐫 𝐜𝐨𝐫𝐞 𝐬𝐮𝐛𝐣𝐞𝐜𝐭𝐬 Sometimes, companies also ask questions on OOPS, SQL, OS and Networking. I had watched Ravindrababu Ravula sir’s videos during my college days and prepared notes. So, I used to revise them before every interview. And last but the most important thing - keep going. Stay consistent.. Lage raho, manzil mil hi jaegi.. 🙌 Do follow Akanksha Buchke for hirings, referrals, interview preparation content and please mention in the comments any other resource you found helpful. PS~ Join this group for all tech content (DSA, coding, System Design - interview preparation and resources) - https://lnkd.in/gUw9-G_u #interviewresources #interviewexperience #interviewpreparation #interviewtips #softwareengineer #softwaredeveloper #referral #intuit #jobswitch #networking #connections #reach #linkedin #linkedincommunity #akankshabuchke

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Intuit leveraged K8sGPT and GenAI in their on-call process, resulting in improved issue detection, debugging, and resolution. 🚀 On-call engineers often face frequent alerts, tedious log scanning, and multiple team handoffs to resolve issues. Often, few teams have high operations load and engineers face fatigue resulting in low productivity. 😌 Intuit was facing similar issues with their complex Kubernetes deployment comprising 325+ clusters and 7000 services. They came up with a methodical approach to solve the problem through GenAI. What were the goals of the project ? 👉 Reduce the Mean Time To Detect (MTTD) an issue 👉 Reduce the Mean Time To Remediate (MTTR) an issue How did they solve the problem ? 1️⃣ Golden cluster signals - Single view of cluster's health and availability. It helped engineers to detect the bad clusters quickly reducing MTTD. 2️⃣ Debugging with K8s GPT - Adopted open-source K8s GPT to analyze root cause of failures. K8s GPT has integration with Open AI and other models. 3️⃣ Remediation with GenAI - Since public LLMs don't have Intuit specific data, they hosted local models and augmented them with Intuit specific data (RAG) that suggested remediation Intuit is planning to extend the tool and use it for other use cases, such as traffic and Java virtual machine debugging. They have published a detailed blog on how they adopted K8s GPT and the challenges they faced. You can find the link in the first comment. 👇 On-call weeks are challenging, but investing in GenAI can streamline the process and improve work-life balance. Share in the comments if you've used GenAI to improve your on-call process. Also, explore how K8sGPT could boost your team's operational efficiency. Also, folks who are interested to know more about K8s GPT can go to the github link, understand the code and start contributing. 🔥 #chatGPT #GenAI #softwareengineering

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The SDE-2/SDE-3 position in some companies is just like SDE-1, so don't be too surprised. Don't make them gods of tech who are SDE-2/SDE-3 in these companies. They are not gods, they are just like you. PS: Even the compensation is just like to SDE-1. #AsheeshTalks #linkedin #SDE2 #SDE3

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Which all metrics needs to be monitored for restful webservices? 1. Response Time: Measure the time taken to process incoming requests and generate responses. Monitor average response time, percentiles (e.g., 90th, 95th, 99th), and trends over time to identify performance issues and bottlenecks. 2. Throughput: Monitor the rate of incoming requests and processed responses. Measure request and response rates per second or minute to understand traffic patterns, peak loads, and capacity utilization. 3. Error Rate: Track the percentage of requests that result in errors or failures. Monitor HTTP status codes (e.g., 4xx, 5xx) and error responses to identify issues such as client errors, server errors, or network issues. 4. Availability: Monitor the uptime and availability of the web service. Track service availability over time and calculate uptime percentage to ensure that the service meets reliability requirements and SLAs. 5. Latency: Measure network latency between clients and the web service endpoints. Monitor round-trip latency, DNS lookup time, TCP connection time, and time to first byte (TTFB) to identify network-related issues and optimize performance. 6. Concurrency: Monitor the level of concurrency or concurrent connections to the web service. Track the number of active connections, connection pool usage, and queue length to ensure that the service can handle concurrent requests efficiently. 7. Cache Hit Ratio: If caching is implemented, monitor the cache hit ratio to assess the effectiveness of caching strategies. Track the percentage of requests served from the cache versus the origin server to optimize cache performance and reduce response times. 8. API Usage Metrics: Monitor usage patterns and trends of API endpoints. Track the frequency of API calls, resource usage (e.g., CPU, memory), and API usage quotas to understand usage patterns and plan for capacity scaling. 9. Security Metrics: Monitor security-related metrics such as authentication failures, unauthorized access attempts, and anomalous behavior. Track security events, audit logs, and compliance metrics to ensure data protection and regulatory compliance. 10. Dependencies: Monitor dependencies and third-party integrations used by the web service. Track availability, latency, and error rates of external services, databases, and APIs to identify dependencies that may impact service reliability or performance. CONCLUSION:- By monitoring above mentioned metrics, issues can be detected, performance can be optimized, and ensure the reliability and availability of their RESTful web services. Some common tools available for monitoring these restful api are available like Prometheus , Grafana and many other. #backendEnineering #apis #systemdesign

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Senior developers can stay connected to the codebase, provide productive hands-on experience, maintain updated technical skills, and remain highly productive even without coding regularly. However, over time, not writing code or delivering key features can lead to a sense of moral high ground because they are not involved in meeting strict customer deadlines. On a personal note, I get little to no time to write code, but I ensure to contribute to at least one project per quarter, just for the love of it. It is one of the few job profiles that allows individual contributors to operate at such top levels. Making the most of it. Regardless, interesting read.

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Are we 𝐋𝐨𝐚𝐝 𝐁𝐚𝐥𝐚𝐧𝐜𝐢𝐧𝐠 𝐊𝐚𝐟𝐤𝐚 effectively until now? When it comes to load balancing in Kafka, many of us rely on well-established partitioning techniques. Isn’t it? However, there might be room for alternative methods worth considering. So here I am with educational mini-blog where we will explore traditional methods of Kafka load balancing and their bottlenecks. Next up is, we will dive into how Agoda uses a Lag-Aware Partitioning to load balance Kafka effectively. 𝐓𝐫𝐚𝐝𝐢𝐭𝐢𝐨𝐧𝐚𝐥 𝐌𝐞𝐭𝐡𝐨𝐝𝐬 𝐑𝐨𝐮𝐧𝐝 𝐑𝐨𝐛𝐢𝐧 The Round Robin method distributes messages evenly across partitions, similar to handing out candy one by one around a circle. This approach ensures that each partition gets an equal share of messages, based on the assumption that all Kafka brokers have similar capacity and performance. Bottleneck: Round Robin assumes uniformity in Kafka brokers' power and capacity. In reality, infrastructure often consists of heterogeneous VMs or pods, leading to inefficient processing as weaker machines become overloaded while stronger ones are under utilised. 𝐇𝐚𝐬𝐡-𝐁𝐚𝐬𝐞𝐝 Hash-Based partitioning assigns messages to partitions based on a hash of the key, such as a client name. This ensures that messages with the same key consistently go to the same partition, maintaining order and consistency in client-specific data streams. Bottleneck: Hash-Based partitioning can lead to uneven processing loads and skewed distribution. Some partitions may become overloaded with data, resulting in increased latency and performance bottlenecks. ! Next up is the 𝐩𝐫𝐨𝐭𝐚𝐠𝐨𝐧𝐢𝐬𝐭  of this blog, the algo that Agoda used ! 𝐏𝐫𝐨𝐝𝐮𝐜𝐞𝐫-𝐁𝐚𝐬𝐞𝐝 𝐋𝐚𝐠-𝐀𝐰𝐚𝐫𝐞 𝐏𝐚𝐫𝐭𝐢𝐭𝐢𝐨𝐧𝐢𝐧𝐠 This method involves the producer precomputing the queue size and directing messages to specific partitions based on this information. It helps optimise performance by preventing overloaded partitions. 𝐏𝐫𝐨𝐬: Optimises producer-side performance by balancing load based on queue size. 𝐂𝐨𝐧𝐬: May face scalability challenges with multiple consumer groups, as the precomputed data might not align perfectly for all consumers. 𝐂𝐨𝐧𝐬𝐮𝐦𝐞𝐫-𝐁𝐚𝐬𝐞𝐝 𝐋𝐚𝐠-𝐀𝐰𝐚𝐫𝐞 𝐏𝐚𝐫𝐭𝐢𝐭𝐢𝐨𝐧𝐢𝐧𝐠 Here, consumers are rebalanced when a partition experiences high load. This redistribution helps maintain even processing and reduce lag. 𝐏𝐫𝐨𝐬: Dynamically adjusts to current load, potentially reducing lag. 𝐂𝐨𝐧𝐬: Rebalancing can be costly and might cause some consumers to go down, disrupting processing. After all, it's essential to recognise that there isn't a one-size-fits-all solution. Each method has its pros and cons, and the best approach may vary depending on specific use cases and infrastructure.  On an ending note, A huge thanks to Yifan Huang for inspiring this post. Her blog (https://t.ly/QAsmj) offers more stats and a clearer understanding of how Agoda uses lag-aware partitioning. I highly recommend giving it a read! 

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Top Product-Based Companies expect SDEs and SDE2s to have solid fundamentals. 💪 This guide will help you build the CS foundation you need to crack these interviews! Huge Thanks to Bosscoder Academy for Sharing this Doc ⭐ Check here: https://bit.ly/4fZnqRx This guide covers → 🔹Crucial topics like: Computer Networks, Operating Systems & DBMS 🔹Most asked Interview Questions For those looking to go deeper, they also offer a structured learning path in DSA, System Design, and Full Stack Development, plus one-on-one mentorship and 24/7 support. #ad #sponsoredpost

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𝐀𝐟𝐭𝐞𝐫 𝐟𝐚𝐜𝐢𝐧𝐠 𝐫𝐞𝐣𝐞𝐜𝐭𝐢𝐨𝐧 𝐛𝐲 𝐈𝐧𝐭𝐮𝐢𝐭, 𝐈 𝐮𝐧𝐝𝐞𝐫𝐬𝐭𝐨𝐨𝐝 𝐡𝐨𝐰 𝐝𝐢𝐟𝐟𝐢𝐜𝐮𝐥𝐭 𝐭𝐞𝐜𝐡𝐧𝐢𝐜𝐚𝐥 𝐢𝐧𝐭𝐞𝐫𝐯𝐢𝐞𝐰𝐬 𝐜𝐚𝐧 𝐛𝐞🥲 . At Intuit, they divide interviews into 3 sections, out of which 1 was dedicated to computer networks. Unfortunately, I wasn’t prepared for it. I failed in that but I learned that you need to prepare all topics with a dedicated PLAN. → So, to crack technical interviews, each day I spent hours upskilling on core tech concepts! The result? 👉 Setting small targets & dividing my tasks helped me track my progress. 👉 Preparing on all topics led me to secure a position at a top PBC - Walmart🎊 In my case, I prepared for multiple months and while I was consistent, at times I felt directionless and had to pull myself out of that situation alone. However, it doesn’t have to be the same for you! You can seek help from top SDEs who will build customized roadmaps, solve your confusion and prepare you for the entire interview. Just book a FREE discussion call here - https://lnkd.in/g3HeJXX4 These SDEs have helped 500+ people get placed at MNCs like Uber, Oracle and Adobe with personalized mentorship. I’m sure they can help you, too. So, do connect with them!🌟 #interview #rejection #tech #collab #preplacedcollab

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Hi everyone,   🚀 Decoding Kafka — The Mystery 🚀   💡 Ever wondered how real-time tracking works on apps like Zomato or Uber? Imagine placing an order on Zomato and seeing the live location of your delivery agent, updating every few seconds. Or booking a cab on Uber and having various services like fare adjustments and analytics running in real-time. This seamless experience is powered by Kafka, ensuring that high volumes of data are processed efficiently and in real-time.   🔍 In my latest blog, I dive into: What Kafka is and where it’s being used. How Kafka integrates into our daily lives. Learning Kafka with real-world problem statements and examples. Kafka's robust architecture. Understanding Consumer Groups and Kafka's dual role as a Queue and Pub/Sub system.   🔗 Ready to dive deeper? Check out my full blog here: https://lnkd.in/geTGEKBh   Happy learning! 😊   #Kafka #DataStreaming #RealTimeData #TechBlog #SoftwareEngineering #TechInnovation #LearningJourney 

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Amazon is hiring Software Engineers. Sharing the list of most asked DSA questions in Amazon Check out the list of 20 questions you must solve before your DSA interview 1. Two Sum (Easy) 2. Merge Two Sorted Lists (Easy) 3. Best Time to Buy and Sell Stock (Easy) 4. Flood Fill (Easy) 5. Number of Islands (Medium) 6. Rotting Oranges (Medium) 7. LRU Cache (Medium) 8. Copy List with Random Pointer (Medium) 9. Word Break (Medium) 10. Group Anagrams (Medium) 11. Merge Intervals (Medium) 12. 3 Sum (Medium) 13. Longest Palindromic Substring (Medium) 14. All Nodes Distance K in Binary Tree (Medium) 15. Shortest Path in Binary Matrix (Medium) 16. Merge k Sorted Lists (Hard) 17. Trapping Rain Water (Hard) 18. Frog Jump (Hard) 19. Sliding Window Maximum (Hard) 20. Word Search II (Hard) Apply here :- 1+ years - https://lnkd.in/gsshGQiu https://lnkd.in/gKk-SzwK 3+ years - https://lnkd.in/gCmKR4kw https://lnkd.in/gYuYfdwM 5+ years - https://lnkd.in/gx-Z4mE9 6+ years - https://lnkd.in/gBwuWPS8 Hope this helps. Do let me know in the comments if you need a similar list for system design interview questions. You can follow Akanksha Buchke to stay updated with the latest hirings, referrals, DSA and system design content. #amazoninterviewquestions #amazon #faang #interviewexperience #hiring #jobs #akankshabuchke #connections

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Exciting News: Amazon is Hiring Again !! ✅ After a period of slowed hiring, Amazon has reopened opportunities for #SDE1 and #SDE2 positions. While 2024 was challenging for tech hiring, especially among top MNCs, 2025 is shaping up to be a promising year. Many companies are already planning their #hiring strategies for the upcoming year, making it an excellent time to consider switching roles. 😎 😎 ✅ If you're looking for referrals, feel free to reach out! Due to a high volume of messages in my DMs, it can be difficult to respond to everyone. If you're serious about getting noticed, you can book a call with me on topmate.io for personalised guidance. Link in my profile. #amazon #hiring #tech #jobs #referral #amazonhiring #techhiring #sdejobs #softwaredeveloper #techcareers #careeropportunities #jobsearchtips #2025hiring #jobreferrals #amazoncareers #techindustry #careertransition #sde1 #sde2 #jobopenings #softwareengineering

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“SDE ke liye system design aata hai” 🤔 Yes, they do ask. It’s often assumed to be something only senior engineers need to know, but many companies now include it in their interviews, even for junior and mid-level roles. If you’re preparing for an SDE interview, make system design part of your plan along with DSA, behavioral questions, and mock interviews. <> Start with the basics Understand the fundamentals of scalability, latency, throughput, and availability. You don’t need to be an expert, but knowing how these work and where to use them is crucial. <> Practice simple use cases Start with smaller problems like designing a URL shortener or a rate limiter. These are often asked in interviews and help you build confidence. <> Mock interviews Practice with peers or mentors. Even if you don’t know everything, explaining your thought process clearly can leave a good impression on the interviewer. Don’t brush it off as irrelevant—it could be the one thing that sets you apart. And if you're looking to boost your interview skills and achieve your career goals, consider Tutort Academy. Explore here-https://bit.ly/3CGlk9U The platform has helped over 1250 professionals like you to switch and crack top PBC, by offering 1:1 mentorship, mock interviews, resume-building sessions, salary negotiation tips, 100% Live interactive sessions from MAANG Mentors, and more they can also help you by joining their new batch start from 24 November, Sunday🚀 Don't waste your time start your preparation now. #interviewtips #sdeinterview #amazon #dreamcompany #upskilling #tutortacademy

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Famous SDE, EM behavioural question, "how did you work with cross-functional teams" is not about working. It's also not about the tools you use to work together. It is actually about handling vested interests. Why? Before that, lets first understand what is a cross-functional team. These are teams made of people from different functional expertise. For example, Product Manager, Developers, QA, UX, all in one team to solve a business problem. 3-4 developers + 1-2 PM + 2 QA + 1-2 UX Although these individuals are part of this team, but their managers are not same (in most of the cases). Meaning they are still reporting to their managers of their specific functional team. This is where challenges start to show. Each of these have their vested interests. Dev :- Use the latest and shiniest tech QA :- Make the entire product release a bug PM :- Keep squeezing in more and more features UX :- Become the most frustrated user of the product Shouldn't this lead to a better product? No, because while the team is cross-functional, they are only focused on their specific functions, instead of the specific problem because of which they all came together. Cherry on top is their managers are not same. So, how do you handle this situation at work and answer it in interviews. [1] If anyone deviates from original business problem due to their "best functional knowledge", bring them back by going back to business problem. [2] Communicate like you are talking to a 5 year old. Most of the problems start because we assume communication already happened and everyone is aware of the decisions. [3] Keep communication in written, you don't want to hear later, "oh, I meant that..." [4] Give respect to get respect. Escalate about those who keep disrespecting others. [5] If people disagree, understand where they are coming from. Try giving reasoning behind your stand with data. [6] After disagreement if the final decision in not in your favor, don't take it personally. [7] And finally, talk confidently, explain logically. Projects don't fail due to technology, they fail due to people. It gets worse, when people have vested interests with different reporting. If organisations wouldn't have people problem, then many of you and I won't be having the job we have today (we wouldn't need so many people at workforce). That's why behavioural interview are not hypothetical. They extract the best and worst of you from your own stories and serve it in a platter to interviewer. Need help with difficult behavioural interview questions? DM me COACH.

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The trend of Design Patterns in LLD interviews: Once upon a time only knowing Gof creational design patterns (mostly Singleton) was expected Then came a time when knowing Strategy pattern in addition to creational was acceptable Currently, it's expected that one must also be well versed with practical usages of Gof structural and behaviour patterns.

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Layoffs in past have proved that An average engineer in a high priority team is more valuable than a top engineer in a low priority team. Most of the layoffs are not relevant to performance but have a direct correlation with the projects team is working on. It is equally important to pick the right team along with the company. #softwareengineering #layoffs #programming

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Leetcode Problem Of The Day : Shortest Subarray With OR at Least K II Approach: 1. Initialize Variables: Use count to store the count of set bits (1s) for each bit position from 0 to 31 across the current subarray. Use start and end to represent the window boundaries. Use min to keep track of the minimum subarray length that satisfies the condition. 2. Expand the Window (end pointer): For each end in nums, add nums[end] to the window. Update count using the updateBits method to record the contribution of nums[end] in terms of bits. 3. Contract the Window (start pointer): While the combined OR value (computed by getVal) of the elements in the current window is at least k, calculate the current window length end - start + 1. If the current length is less than min, update min. Move the start pointer forward, removing nums[start] from the window, and update count by decrementing its bit contributions. 4. Return Result: If min is still Integer.MAX_VALUE, return -1 (no valid subarray was found). Otherwise, return min. Helper Methods : 1. updateBits(int[] count, int num, int val): This method iterates over each bit position (0 to 31). For each bit in num, if it is set (i.e., 1), it increments or decrements the count at that bit position by val. 2. getVal(int[] count): This method calculates the combined bitwise OR of the current subarray by checking each bit in count. If a bit position in count is greater than zero, it means at least one element in the current window has this bit set, so it adds this bit to the OR result. Time Complexity : O(n) Space Complexity : O(1) Problem Link : https://shorturl.at/8eIHK #Coding #CompetitiveProgramming #dsa #DatastructuresAndAlgorithms #Leetcode #Consistency #Programming #CodingChallenge

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20 DSA questions frequently asked by service based and mid level product companies 📌 Arrays & Strings 1. Two Sum - https://lnkd.in/gUUp8UtD 2. Longest Substring Without Repeating Characters - https://lnkd.in/gAcpdxsU 3. Container With Most Water - https://lnkd.in/gxaATtTY 4. Maximum Subarray (Kadane's Algorithm) - https://lnkd.in/gTPYuKwg 📌 Linked Lists 5. Reverse a Linked List - https://lnkd.in/gQ6tjhMe 6. Merge Two Sorted Lists - https://lnkd.in/gHk6ZbFT 7. Linked List Cycle - https://lnkd.in/gEMZCNTf 8. Intersection of Two Linked Lists - https://lnkd.in/g4y3FSPu 📌 Stacks & Queues 9. Valid Parentheses - https://lnkd.in/gJ_qZ6UD 10. Min Stack - https://lnkd.in/gQmZBX8h 11. Implement Queue using Stacks - https://lnkd.in/gWP5sfPm 📌 Trees 12. Binary Tree Inorder Traversal - https://lnkd.in/gsrJwvZV 13. Lowest Common Ancestor of a Binary Tree - https://lnkd.in/gxW4-bgH 14. Maximum Depth of Binary Tree - https://lnkd.in/g-BHqnjP 📌 Heaps 15. Top K Frequent Elements - https://lnkd.in/gP8Rbrj2 16. Kth Largest Element in an Array - https://lnkd.in/gdbYa5HT 📌 Graphs 17. Number of Islands - https://lnkd.in/g4uHsTiP 18. Graph Cycle Detection (Course Schedule) - https://lnkd.in/gutn9zeX 📌 Dynamic Programming (Least probability) 19. Climbing Stairs - https://lnkd.in/ge9NE8XB 20. Longest Increasing Subsequence - https://lnkd.in/gDaV8FpY Get the complete list of MOST IMPORTANT DSA questions here - https://lnkd.in/gZDApNar Do follow Akanksha Buchke for hiring updates, referrals, DSA, Java, system design content. #jobs #freshers #hiring #interviews #placements #tech #interview #softwareengineer #techjobs #connections #programming #careers

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𝐃𝐨 𝐓𝐡𝐞𝐬𝐞 𝐐𝐮𝐞𝐬𝐭𝐢𝐨𝐧𝐬 𝐨𝐧 𝐓𝐫𝐞𝐞𝐬 𝐛𝐞𝐟𝐨𝐫𝐞 𝐲𝐨𝐮𝐫 𝐍𝐞𝐱𝐭 𝐃𝐒𝐀 𝐈𝐧𝐭𝐞𝐫𝐯𝐢𝐞𝐰 I have given a lot of Interviews in Top Product Based Companies and found out Trees to be one of the most important Data Structure. Sharing some Frequently asked questions on Trees - 𝐓𝐫𝐚𝐯𝐞𝐫𝐬𝐚𝐥 𝐏𝐫𝐨𝐛𝐥𝐞𝐦𝐬 𝐨𝐧 𝐓𝐫𝐞𝐞𝐬 : Preorder Traversal - https://lnkd.in/dgBBRpu7 Inorder Traversal - https://lnkd.in/dS42eEGm Postorder Traversal - https://lnkd.in/dpQp2w9B Level Order Traversal - https://lnkd.in/dyqDcZiz Boundary Traversal - https://lnkd.in/dW-y-RWV Zig Zag Traversal - https://lnkd.in/dnifzee2 𝐕𝐢𝐞𝐰 𝐁𝐚𝐬𝐞𝐝 𝐏𝐫𝐨𝐛𝐥𝐞𝐦𝐬 𝐨𝐧 𝐓𝐫𝐞𝐞𝐬 : Top View of Tree - https://lnkd.in/djTZJS3c Bottom View of Tree - https://lnkd.in/ducG6vXj Right/Left View of Tree - https://lnkd.in/ddw9y2jM Vertical Order Traversal - https://lnkd.in/dkq2EdGj 𝐌𝐞𝐝𝐢𝐮𝐦 𝐏𝐫𝐨𝐛𝐥𝐞𝐦𝐬 𝐨𝐧 𝐓𝐫𝐞𝐞𝐬 : Height/Depth Of Binary Tree - https://lnkd.in/dKvy5A2a Diameter Of Binary Tree - https://lnkd.in/dCE5WtBu Maximum Path Sum - https://lnkd.in/d-r7Aa7T Find if Two Trees are identical - https://lnkd.in/dRNfXS5Q Symmetric Binary Tree - https://lnkd.in/dMvK7tBb 𝐇𝐚𝐫𝐝 𝐏𝐫𝐨𝐛𝐥𝐞𝐦𝐬 𝐨𝐧 𝐓𝐫𝐞𝐞𝐬 : Root to Leaf Path - https://lnkd.in/dQSC8sgq Lowest Common Ancestor - https://lnkd.in/dEj_kiC5 Children Sum Property - https://lnkd.in/dsXTsd9z Time Taken to Burn a Binary Tree - https://lnkd.in/dS7g3fwP Serialize and Deserialize a Tree - https://lnkd.in/dsWSsYEr Follow Gourav Roy for more such Amazing content 💚 👨‍💻 𝐂𝐨𝐧𝐧𝐞𝐜𝐭 𝐨𝐧 𝐈𝐧𝐬𝐭𝐚𝐠𝐫𝐚𝐦 - https://lnkd.in/dKdn2yeA #datastructures #trees #softwareengineering #linkedincommunity

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