How to Improve Technical Pattern Recognition and Code Reading Skills

I'm often asked what to do if one can't solve a coding problem after pondering it for 15-20 minutes. People often hit a wall while preparing for coding interviews. I did too. Here are my suggestions: 👉𝐏𝐫𝐚𝐜𝐭𝐢𝐜𝐞 𝐀𝐜𝐭𝐢𝐯𝐞𝐥𝐲: Instead of passively reading the explanation after 15-20 minutes, try to struggle with the problem a bit longer. This is where the learning really happens. If you can't solve it, try to identify which part of the problem you find challenging. Is it the initial approach? Is it a tricky corner case? Once you've identified your weak point, you can then focus on solutions to that specific issue. 👉𝐔𝐧𝐝𝐞𝐫𝐬𝐭𝐚𝐧𝐝 𝐭𝐡𝐞 𝐂𝐨𝐧𝐜𝐞𝐩𝐭𝐬, 𝐍𝐨𝐭 𝐉𝐮𝐬𝐭 𝐭𝐡𝐞 𝐒𝐨𝐥𝐮𝐭𝐢𝐨𝐧𝐬: While it's tempting to memorize solutions, the interviewers are more interested in how you think and approach a problem. So, focus on the underlying techniques, patterns, and algorithms. Once you deeply understand a concept, you'll be able to apply it to a variety of questions. 👉𝐒𝐩𝐚𝐜𝐞𝐝 𝐑𝐞𝐩𝐞𝐭𝐢𝐭𝐢𝐨𝐧: Instead of reviewing all questions every day, use the spaced repetition technique. For example: 1. Review a question you've solved today. 2. Review it again in two days. 3. If you solve it successfully, review it again in a week. 4. If you still solve it successfully, review it again in two weeks. This technique will help you remember the approach over the long term. 👉𝐃𝐢𝐬𝐜𝐮𝐬𝐬 𝐰𝐢𝐭𝐡 𝐏𝐞𝐞𝐫𝐬: Talking through your solution, or even your confusion, with someone else can be very beneficial. This could be in online forums, study groups, or with friends preparing for similar interviews. Explaining your thought process to someone else can help solidify your understanding. 👉𝐂𝐚𝐭𝐞𝐠𝐨𝐫𝐢𝐳𝐞 𝐏𝐫𝐨𝐛𝐥𝐞𝐦𝐬: Many problems can be grouped together into certain categories like sliding window. Once you've solved a few problems in a category, try to summarize the general approach that apply to that category. This way, when faced with a new problem, you can try to fit it into a known category and apply the corresponding techniques. 👉𝐌𝐨𝐜𝐤 𝐈𝐧𝐭𝐞𝐫𝐯𝐢𝐞𝐰𝐬: Consider mock interviews with friends or using platforms that offer this service (check https://lnkd.in/gwrarnyD). This not only helps with problem-solving but also gets you comfortable with explaining your thought process. 👉𝐕𝐚𝐫𝐢𝐚𝐭𝐢𝐨𝐧 𝐢𝐬 𝐊𝐞𝐲: Instead of solving similar problems repeatedly in a short span, try a mix. For instance, after two-pointer problems, move on to recursion, then sliding window, and then come back to two-pointers. This cyclic variation helps cement your learning better. 👉𝐔𝐧𝐝𝐞𝐫𝐬𝐭𝐚𝐧𝐝 𝐌𝐢𝐬𝐭𝐚𝐤𝐞𝐬: Whenever you can't solve a problem, instead of just reading the solution, ask yourself why you couldn't solve it. Is there a pattern or concept you're consistently missing? By recognizing your weak spots, you can focus on improving in those areas. #codinginterview #datastructures

10 pieces of advice that helped me get good at solving problems and cracking coding interviews, I wish someone had told me when I was 20 and grinding at BITS Pilani.... 1. How do I pick which problems to solve? - Start with easy problems in each topic (arrays, strings, etc.) - Use curated lists like “Top 150 Interview Questions” - Don’t waste time on random, obscure problems - Repeat the basics till they’re muscle memory 2. What to do when you’re stuck on a problem for hours? - Spend 30–60 minutes thinking hard - If still stuck, check hints or partial solutions, not full code - Try writing the solution from scratch after reading it - Make a note to revisit after a week 3. How to avoid feeling overwhelmed by 3000+ LeetCode problems? - Ignore the total count - Focus on a shortlist of 250–300 core problems - One topic at a time, one pattern at a time - Track your progress on a sheet 4. What’s the best way to learn a new data structure or algorithm? - Watch a trusted YouTube video (not 10!) - Implement it from scratch - Solve 3–5 related easy/medium problems - Teach it to a friend or write a summary note 5. How do I actually retain what I learn? - Make a habit of revisiting solved problems - Explain your solution out loud or to someone else - Maintain a notebook with your ‘aha’ moments - Practice old topics every 2 weeks 6. How to get faster at solving problems? - Set a timer: 15 mins for easy, 30 for medium, 1 hour for hard - Focus on pattern recognition, not brute force - Analyze time/space complexity for every problem - Practice under interview conditions (mock tests, contests) 7. What language should I use? - Stick to what you’re comfortable with (Python/Java/C++) - Learn built-in libraries for arrays, maps, queues, etc. - Don’t switch languages unless you’re stuck 8. How do I stop memorizing solutions and actually understand them? - Re-write solutions from memory after learning - Break down why each step works - Relate the approach to real-world problems - Never copy-paste, always type it out 9. How do I tackle hard problems or topics? - Break into smaller subproblems - Use pen & paper to draw out tricky inputs - Start with a brute-force solution, then optimize - Look for similar solved patterns 10. How to not lose motivation when it gets tough? - Celebrate small wins (accepted solution, a new pattern cracked) - Take breaks and walk away when you’re frustrated - Join a group or community for accountability - Remember: Growth compounds, it gets easier with time

I recently had a chance to connect with a Sr. Software Engineer who cracked Google, Meta, Microsoft, and Amazon in the last 10 years of his career. He started at Amazon in 2015 and is now working at Facebook. I asked him one question: How should one start Leetcode in 2025? and got some pointers that I think would benefit everyone.  [1] Stop trying to “cover” Leetcode → The real game is not in “solving 1000 problems.” It’s in identifying patterns behind the questions (sliding window, backtracking, tree traversals, etc.) and understanding when and why to use each. → Each pattern unlocks 10–15 problems. Your goal: See a question and immediately recognize the pattern behind it. [2] Build a rock-solid DSA foundation → Before you even open Leetcode, deeply understand how and why core data structures (arrays, hashmaps, trees, heaps, graphs) work internally. → Don’t just learn how to use them, know their weaknesses, edge cases, and which real-world scenarios they solve best. → For every new topic, write your own implementation (e.g., your own LinkedList, your own Stack, your own Trie) from scratch once, just to internalize the mechanics. [3] Train yourself to break down problems, not just solve them → When you see a new problem, never code immediately. → Spend 5–10 minutes analyzing constraints, drawing diagrams, and “talking out” your approach. → Ask: “What are the edge cases?” “What would brute force look like?” “Can I spot an early optimization?” → In interviews, your ability to explain and reason before coding matters more than racing to a solution. [4] Use problem selection as a learning tool, not a confidence booster → Don’t just grind easy questions to feel “productive.” → Each session, choose a mix: 1 comfort-zone problem to warm up, 2–3 new pattern-based mediums, and 1 “stretch” hard problem, even if you know you’ll struggle. → Log why you struggled and what new pattern or trick you learned (keep a mistake log; review it every week). [5] Build mental maps of tradeoffs and “when to use what” → For every pattern you learn (e.g., sliding window vs. prefix sum, hash set vs. sorting for duplicates), write down:   → What’s the time and space complexity?   → When does this pattern break down?   → When is an alternative more efficient? → Building these comparison instincts is what sets apart those who “grind” Leetcode vs. those who think like strong engineers. Continued In Comments ↓ --- P.S: If you’re currently preparing for DSA, HLD, and LLD. Check out my one-stop resource guide: → https://lnkd.in/eYHSjbys ( 750+ students are already using it) This guide will help you with: - DSA, HLD, and LLD for interviews - good resources that I used personally - lots of problems and case studies for DSA and system design

Most people don’t fail in DSA because it’s hard. They fail because they try to learn everything instead of learning the right patterns. If you’re a fresher preparing for coding interviews, stop collecting questions. Start mastering patterns. Here’s the exact roadmap I recommend 👇 1️⃣ Arrays Core patterns you must know: • Two Pointers • Sliding Window (fixed and variable) • Prefix Sum • Kadane’s Algorithm • Hashing / Frequency Map • Sorting + Greedy • Cyclic Sort • Binary Search 2️⃣ Linked Lists Core patterns: • Fast & Slow Pointer • Dummy Node • Reversal (entire list / k-group) • Merge Lists • Pointer Rewiring 3️⃣ Stack & Queue Core patterns: • Monotonic Stack • Monotonic Queue • Stack for Previous / Next Greater • Sliding Window + Deque 4️⃣ Trees & Graphs Core patterns: • DFS (pre / in / post order) • BFS (level order) • Recursion • Backtracking on Trees • Dijkstra • Topological Sort • Union Find 5️⃣ Advanced Patterns • Binary Search on Answer • Greedy • Dynamic Programming ◦ 0/1 Knapsack ◦ Unbounded Knapsack ◦ DP on Strings • Heap (Top K, Merge K) • Bit Manipulation You don’t need 1000 problems. You need clarity on these patterns. Once you understand the pattern, 10 different questions start looking the same. That’s when preparation becomes smart. If you’re preparing for placements or switching jobs, save this post and follow for more such content ❤️

I cracked Microsoft coming from a Tier-3 college, and I can tell you one thing for sure: Mehnat karne se sab hota hai. 🚀 The path to cracking Microsoft or any top-tier product company isn't about luck. It’s about building a solid foundation and having the discipline to see it through. As someone who has navigated this path, I can tell you that the mantra is simple: Mehnat krne se hi sab hota hai. Here is the roadmap to get you there: 🚀 Language Mastery Pick one language—Java or C++—and own it. Don't just learn syntax; understand how it interacts with memory and how its core libraries are built. Microsoft looks for engineers who know exactly what happens under the hood of their code. 🧠 Pattern Recognition Stop counting the number of problems you’ve solved. Start identifying patterns. Whether it’s Sliding Window, Two Pointers, or Backtracking, mastering the pattern allows you to solve dozens of similar problems effortlessly. Focus on about 150-200 high-quality medium problems. 🌳 Data Structure Depth Pay extra attention to Trees, Graphs, and Linked Lists. These are the bread and butter of Microsoft interviews. You should be able to visualize and implement recursion and traversals like BFS and DFS without hesitation. 🏗️ System Design Thinking An engineer’s job is to build systems, not just solve puzzles. Learn Low-Level Design (LLD) to write clean, maintainable code using SOLID principles. Dive into High-Level Design (HLD) to understand how to scale applications for millions of users using load balancers and databases. 💻 Real-World Projects Coming from a Tier-3 background, your projects are your proof of work. Build something functional and complex—like a GenAI tool or a distributed service. Showing you can build and deploy real software is the best way to prove your caliber. The distance between a Tier-3 college and a dream company like Microsoft is exactly the amount of effort you are willing to put in. Mehnat krne se ho jata hai, but it has to be the right kind of effort. ✨ Stop grinding Leetcode blindly. Start mastering the 15 core patterns that define 90% of interview questions. ✨ Stop building tutorial projects. Start building real solutions that showcase your architectural thinking. ✨ Stop worrying about your college name. Start focusing on the logic in your code. In the world of software architecture, the compiler doesn't check your degree—it checks your logic. Stay consistent, stay curious, and keep building. Your background is just the starting point, not the finish line. 🏁 #Microsoft #SoftwareEngineer #DSA #Leetcode #CareerGrowth #Tier3ToFAANG #SystemDesign #CodingMotivation #TechCareer #Consistency

Not able to recognize patterns even after solving hundreds of Leetcode problems? With this pattern recognition cheatsheet you will be able to solve more than 80% of the problems: ➡️Array / String Inputs 1. Is the array sorted? - Yes → Think: Binary Search, Two Pointers, or Prefix Sums. - No → Move to structural/intent-based decisions. 2. What's the intent of the problem? - Optimization (Max/Min, count of ways, min cost) - Interdependent choices? → Use Dynamic Programming (Top-Down or Bottom-Up). - Independent decisions? → Consider a Greedy approach (with proof of correctness). - Feasibility / Existence Check - Use Backtracking, DFS with pruning, or Binary Search on Answer. - Does it involve String Manipulation? - Prefix/Suffix logic? → Trie, Rolling Hash, or Z-Algorithm. - Sequential manipulation? → Stack, Monotonic Stack, or Deque. - Frequent lookups / duplicates / uniqueness - Use Hash Maps, Hash Sets, or Counting Arrays. - Sliding window behavior - Use Two Pointers, Deque, or Counting Hash Map. - Frequent Min/Max retrieval - Use Heap, Monotonic Queue, or Segment Tree (for range queries). ➡️ Graph Inputs 1. Pathfinding / Traversals Shortest path / fewest steps → BFS (Unweighted), Dijkstra (Weighted). Exhaustive exploration / component discovery → DFS, Union-Find. 2. Cycle Detection / Topological Order Use DFS with visited tracking, Kahn’s Algorithm, or Disjoint Sets. 3. Optimization on graphs Minimum Spanning Tree? → Kruskal, Prim. Connectivity? → Tarjan's Algorithm, Bridge Finding, etc. ➡️ Tree Inputs (Typically Binary Trees) 1. Traversals / Depth Calculations Level-order traversal / Lowest Common Ancestor → Use BFS / DFS with depth tracking. Recursive divide-and-conquer logic → Postorder traversal is your friend. 2. Balancing / Ordering Constraints Use BST properties, AVL / Red-Black trees, or Segment Trees if mutable. ➡️ Linked List Inputs 1. Cycle detection → Fast/Slow Pointers 2. Structural changes Reversal? → Track prev, curr, next pointers. Head/edge cases? → Use a dummy node strategy. Follow me Suresh G. for more content around System Design and Interview Prep

Three years ago, I was deep in interview prep for roles at Amazon, Google and Meta. And Leetcode almost broke me. I remember staring at problems for hours, wondering if I'd ever get it. I tried solving everything randomly, Arrays, Graphs, DP — hoping something would click. But solving 3500+ questions felt impossible. Then I realised something that changed everything: It’s not about solving thousands of problems. It’s about learning the patterns behind them. Once I focused on the core data structure and algorithm (DSA) patterns, everything started to make sense. Here are 25 DSA coding patterns that cover most interview questions: 1. Two Pointers 2. Fast & Slow Pointers 3. Sliding Window 4. Prefix Sum 5. Monotonic Stack / Queue 6. Merge Intervals 7. Sorting-Based Patterns 8. Divide & Conquer 9. Binary Search (and Variants) 10. Overlapping Intervals 11. Greedy Algorithms 12. Linked List Techniques (Dummy Node, In-place Reversal) 13. Top-K Elements (Heap / QuickSelect) 14. Kth Largest/Smallest Elements 15. Hashmaps & Frequency Counting 16. Dynamic Programming (1D, 2D, Knapsack, Range DP) 17. Backtracking & Recursive Search 18. Graph Traversals (BFS, DFS) 19. Topological Sort 20. Binary Tree Traversals (Preorder, Inorder, Postorder, Level Order) 21. Path Sum & Root-to-Leaf Techniques 22. Matrix Traversal 23. Expression Evaluation (Stacks & Queues) 24. Design Problems (LRU Cache, Twitter, Rate Limiter, etc.) 25. Trie / Prefix Tree Once you understand these patterns, you’ll start recognising them everywhere — from Leetcode to real-world systems. You don’t need to solve thousands of questions to land great offers. You just need to master these patterns and practice them deliberately. If you’re starting today: → Learn the core data structures first: Arrays, Linked Lists, Stacks, Queues, Hashmaps, Heaps, Trees, Graphs, Tries, and Matrices. → Check out Taro (YC S22) 75 questions by Alex and Rahul. Curated beautifully around these patterns. → Give NeetCode a go — Navdeep did a cracking job explaining the patterns above. This is how you go from frustration to confidence. And from endless grinding to real results. #softwareengineering #leetcode

6 things about learning DSA & problem solving I know now after spending 13+ years as a Software engineer, I wish I knew in my 20s:  [1] Problem-solving isn’t memorization. It’s pattern recognition. - You don’t need to invent solutions from scratch. - The best developers quickly recognize patterns by connecting new problems to old ones. - Tip: Train your mind to spot familiar structures in new questions.  [2] Develop Your "Fast Brain" - Our brain has two modes: Fast (intuitive) and Slow (analytical). - Your fast brain quickly points you in the right direction (e.g., "This feels like a binary search!"). - Tip: Solve varied problems repeatedly so your intuition instantly kicks in during interviews.  [3] Verify Solutions With Your "Slow Brain" - Your fast brain isn't always right. - Use your analytical brain to logically verify solutions step-by-step. - Tip: Always pause and double-check your intuition—don’t rush.  [3] Build Your Personal "Pattern Library" - Problems aren’t random, they follow common patterns. - Examples: Sliding Window, Two-Pointers, Backtracking. - Tip: After each problem, note down the core components and approach, building your own mental library.  [4] Just Solving Problems Isn’t Enough - Simply solving problems without analyzing them won’t build intuition. - Tip: Break problems down, identify core components, and deeply understand why certain solutions work.  [5] Intuition Comes from Deliberate Practice - Memorizing solutions won't help in new situations. - Repeated, intentional practice of problems, especially challenging ones, trains your intuition to "see" solutions quickly. - Tip: Practice intentionally, focusing on identifying patterns rather than just solving fast.  [6] Accept That Mastery Takes Time - You won’t build intuition overnight. Be patient. - Regular, thoughtful practice compounds, your skill improves gradually. - Tip: Trust the process and keep practicing consistently. If you feel stuck right now, remember:   Every great engineer you admire once struggled with the basics too. Keep practicing, keep growing, you'll get there. – P.S: If you're preparing for a SWE role, do check out my guide on behavioral interviews. If you want to break into big tech, startups, or MAANG companies, you must ace the behavioral round. This guide will help you do it → https://lnkd.in/drnsTNhU (230+ engineers are already using this!)

- Memorizing solutions to 500 questions - Jumping straight into the IDE - Guessing the data structure - Trying to write perfect code from line one Here is what always works (The "Pattern Trigger" Strategy): 1. The 10-Minute Read + Match Do not start coding. Spend the first 10 minutes clarifying constraints and matching keywords to patterns. - Sorted input? → Binary Search. - Subarray or substring? → Sliding Window. - Pairs or triplets? → Two Pointers. - Frequency or grouping? → Hashmap. - Grid or connections? → Graph. - Repeated choices? → Dynamic Programming. - Next greater or histogram? → Monotonic Stack. 2. The 20-Minute "Safe Point" (Question 1) Write a simple approach first. Apply the identified pattern. Dry run on sample input immediately. Goal: Lock one correct solution. 3. The 10-Minute "Speed Mode" (Question 2) Do not chase perfection. Go with your first strong instinct. Goal: Reuse known patterns and try small constraints fast. 4. The 5-Minute Communication Close Explain time complexity. Explain space complexity. Goal: State why you chose this pattern and mention one alternative. What would you add? You do not win interviews by memorizing solutions. You win by recognizing patterns under pressure. Save this mapping for your next prep session. ♻️ Repost to help an engineer pass their interview. ➕ Follow me for more system design and engineering tips.

From leaving TCS in Jan 2025… to landing an SDE-1 (L59) offer from Microsoft India in April 2025… This is the story of one of my mentees. (He’s asked me not to tag him, but I’m sharing his full DSA + LeetCode strategy because his approach fixed what most candidates get wrong.) Most students struggle with DSA, not because their logic is weak… but because their approach is broken.  ✅ Step 1: Choose Your Language Based on Speed  Don’t waste time debating Java vs C++ vs Python.  Pick what you’re fastest at when stressed.  Tip: If you’re solving string-heavy questions, Python will save time.  ✅ Step 2: Learn Pattern-Wise This was the biggest game-changer. Instead of solving problems randomly, he studied DSA patterns. → Sliding Window → Two Pointers → Hashing → Recursion + DP → Backtracking → Binary Search on Answers → Monotonic Stack / Queue Every new question became easier to recognize, not just solve. 👉 Here’s my pattern-based learning guide he followed: https://bit.ly/3SmlAzr More on learning DSA pattern-wise here: https://lnkd.in/dkW_CkH5  ✅ Step 3: Get Solid on Time + Space You’re expected to:  Estimate time/space complexity fast  Start with brute force, then optimize  Know tradeoffs (code clarity vs performance) 📌 Before interviews, revise:  Time/space of all core data structures  Big-O notations (keep a printed cheat sheet)  ✅ Step 4: Master the Fundamentals First Don’t rush to DP or Graphs if your basics aren’t solid. He spent his first 4 weeks on: — Arrays — LinkedLists — HashMaps — Stack/Queue operations — Custom implementations like LRU Cache, HashMap 📌 These showed up in his interviews at Microsoft.  ✅ Step 5: Use a Clear, Ordered Roadmap His DSA roadmap looked like this: 1. Arrays, LinkedLists, HashMaps 2. Searching + Sorting 3. Trees (Pre, In, Post order) 4. Graphs, Heaps, Backtracking 5. Recursion 6. DP, Tries, Union-Find He didn’t jump between 10s of DSA sheets out there  ✅ Step 6: Practice With Depth — 10 problems done deeply >> 50 done shallowly — Always ask: “What pattern does this question follow?” Examples:  Max sum of subarray? → Sliding Window  Repeated sub-problems? → Try Recursion → then DP  Multiple paths? → Backtracking  ✅ Step 7: Interview Like a Problem Solver — Start with brute force — Explain your thinking out loud — Clarify the question before writing code — Know your edge cases (nulls, empty inputs, one element) Your goal isn’t to become a LeetCode machine. It’s to become the person who knows how to think, debug, and deliver when it matters. And that’s what this offer from Microsoft proved.