Tips for Engineers to Enhance Problem-Solving Skills

I’ve reviewed close to 2000+ code review requests in my career. At this point, it’s as natural to me as having a cup of coffee. However, from a senior engineer to now an engineering manager, I’ve learned a lot in between. If I had to learn to review code all over again, this would be the checklist I follow (inspired from my experience) 1. Ask clarifying questions:      - What are the exact constraints or edge cases I should consider?      - Are there any specific inputs or outputs to watch for?      - What assumptions can I make about the data?      - Should I optimize for time or space complexity?  2. Start simple:      - What is the most straightforward way to approach this?      - Can I explain my initial idea in one sentence?      - Is this solution valid for the most common cases?      - What would I improve after getting a basic version working?  3. Think out loud:      - Why am I taking this approach over another?      - What trade-offs am I considering as I proceed?      - Does my reasoning make sense to someone unfamiliar with the problem?      - Am I explaining my thought process clearly and concisely?  4. Break the problem into smaller parts:      - Can I split the problem into logical steps?      - What sub-problems need solving first?      - Are any of these steps reusable for other parts of the solution?      - How can I test each step independently?  5. Use test cases:      - What edge cases should I test?      - Is there a test case that might break my solution?      - Have I checked against the sample inputs provided?      - Can I write a test to validate the most complex scenario?  6. Handle mistakes gracefully:      - What’s the root cause of this mistake?      - How can I fix it without disrupting the rest of my code?      - Can I explain what went wrong to the interviewer?      - Did I learn something I can apply to the rest of the problem?  7. Stick to what you know:      - Which language am I most confident using?      - What’s the fastest way I can implement the solution with my current skills?      - Are there any features of this language that simplify the problem?      - Can I use familiar libraries or tools to save time?  8. Write clean, readable code:      - Is my code easy to read and understand?      - Did I name variables and functions meaningfully?      - Does the structure reflect the logic of the solution?      - Am I following best practices for indentation and formatting?  9. Ask for hints when needed:      - What part of the problem am I struggling to understand?      - Can the interviewer provide clarification or a nudge?      - Am I overthinking this?      - Does the interviewer expect a specific approach?  10. Stay calm under pressure:      - What’s the first logical step I can take to move forward?      - Have I taken a moment to reset my thoughts?      - Am I focusing on the problem, not the time ticking away?      - How can I reframe the problem to make it simpler?  

I spent 2+ years grinding Leetcode and learning DSA & problem-solving as a CSE student at BITS Pilani. If I had to start again from 0, this is exactly how I’d do it to get hired as a Software Engineer in 2025:  1️⃣ 𝗺𝗮𝘀𝘁𝗲𝗿 𝗰𝗼𝗿𝗲 𝗮𝗹𝗴𝗼𝗿𝗶𝘁𝗵𝗺𝘀 𝗯𝗲𝗳𝗼𝗿𝗲 𝗮𝗻𝘆𝘁𝗵𝗶𝗻𝗴 𝗲𝗹𝘀𝗲 ○ Before touching random Leetcode problems, I’d master core algorithms like: Binary Search, DFS, BFS, Sliding Window, Two Pointers, Recursion, Backtracking, and Dynamic Programming. ○ The goal isn’t just to “understand” these but to be able to implement them from scratch without hesitation. ○ I’d write each algorithm at least 5-10 times from memory until it becomes second nature.  2️⃣ 𝗳𝗼𝗰𝘂𝘀 𝗼𝗻 𝗽𝗿𝗼𝗯𝗹𝗲𝗺 𝗽𝗮𝘁𝘁𝗲𝗿𝗻𝘀, 𝗻𝗼𝘁 𝗷𝘂𝘀𝘁 𝘀𝗼𝗹𝘃𝗶𝗻𝗴 𝗽𝗿𝗼𝗯𝗹𝗲𝗺𝘀 ○The biggest mistake people make is solving hundreds of random problems without recognizing patterns. ○ 90% of interview problems fall into ~20 coding patterns. ○ Instead of solving 1000+ questions, I’d focus on understanding:    ►How problems within a pattern are similar.    ►What small variations make them different.    ►Which techniques help optimize them.  3️⃣ 𝗿𝗲𝗽𝗲𝗮𝘁 𝗽𝗿𝗼𝗯𝗹𝗲𝗺𝘀 𝗶𝗻𝘀𝘁𝗲𝗮𝗱 𝗼𝗳 𝗷𝘂𝘀𝘁 𝗺𝗼𝘃𝗶𝗻𝗴 𝗼𝗻 ○ Just because I solved a problem once doesn’t mean I’ll remember it. ○ I’d follow this reinforcement schedule for problems I struggled with: Solve it today, solve it again in 1 week and finally solve it again in 1 month. ○This is how I’d make sure I actually retain what I learn.  4️⃣ 𝘀𝘁𝘂𝗱𝘆 𝘀𝗼𝗹𝘂𝘁𝗶𝗼𝗻𝘀 𝘁𝗵𝗲 𝗿𝗶𝗴𝗵𝘁 𝘄𝗮𝘆 ○ When I can’t solve a problem, I’d first struggle with it for at least 30 minutes before looking at the solution. ○ Then, I’d:   ► Write out the solution from memory after understanding. ► Explain why it works in simple words ► (if I can’t explain it, I don’t truly understand it).   ► Look at alternative solutions to compare trade-offs.  5️⃣ 𝗯𝘂𝗶𝗹𝗱 𝗮 𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲𝗱 𝗽𝗿𝗼𝗯𝗹𝗲𝗺 𝗹𝗶𝘀𝘁 (𝗻𝗼𝘁 𝗷𝘂𝘀𝘁 𝗿𝗮𝗻𝗱𝗼𝗺 𝗴𝗿𝗶𝗻𝗱𝗶𝗻𝗴) ○ Instead of jumping between random problems, I’d follow a structured roadmap like:  ► First 50-60 easy problems → Get comfortable with implementation.   ► Next 80-100 medium problems → Focus on pattern recognition & optimization.   ► Last 30-40 hard problems → Only after mastering the fundamentals.  ○ 150-200 well-selected problems are enough to crack most interviews.  6️⃣ 𝘀𝘁𝗮𝗿𝘁 𝗺𝗼𝗰𝗸 𝗶𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄𝘀 𝗲𝗮𝗿𝗹𝘆 (𝗲𝘃𝗲𝗻 𝘄𝗵𝗲𝗻 𝗜 𝗳𝗲𝗹𝘁 𝘂𝗻𝗽𝗿𝗲𝗽𝗮𝗿𝗲𝗱)   ○ Simulating real interviews early helps with time pressure & communication skills.  ○ I’d start setting strict 30-45 min timers on problems to simulate interview conditions.  ○ I’d practice explaining my thought process out loud, since half of the interview is about communication.  (Bonus tip in the comments) ↓

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