𝗜𝗻 𝗝𝗮𝘃𝗮, 𝗬𝗼𝘂𝗿 𝗠𝗲𝘁𝗵𝗼𝗱 𝗦𝗶𝘇𝗲 𝗦𝗮𝘆𝘀 𝗮 𝗟𝗼𝘁 𝗔𝗯𝗼𝘂𝘁 𝗬𝗼𝘂𝗿 𝗗𝗲𝘀𝗶𝗴𝗻 𝗟𝗼𝗻𝗴 𝗺𝗲𝘁𝗵𝗼𝗱𝘀 𝗼𝗳𝘁𝗲𝗻 𝘀𝘁𝗮𝗿𝘁 𝘀𝗺𝗮𝗹𝗹. Just one more condition. One more validation. One more call. And suddenly, a 10-line method becomes 100+ lines. The problem is not length alone. 𝗜𝘁’𝘀 𝘄𝗵𝗮𝘁 𝗹𝗼𝗻𝗴 𝗺𝗲𝘁𝗵𝗼𝗱𝘀 𝗵𝗶𝗱𝗲: • mixed responsibilities • unclear flow • hard-to-test logic • hidden side effects 𝗜𝗻 𝗴𝗼𝗼𝗱 𝗝𝗮𝘃𝗮 𝗰𝗼𝗱𝗲, 𝗺𝗲𝘁𝗵𝗼𝗱𝘀 𝘂𝘀𝘂𝗮𝗹𝗹𝘆: ✔ do one thing ✔ have a clear name ✔ are easy to scan ✔ are easy to test Short methods are not about style. They are about clarity and control. When a method grows too much, it’s often a signal — not a success. What’s the longest method you’ve seen in a real project? #Java #CleanCode #SoftwareEngineering #BackendDevelopment #JavaDeveloper
Java Method Length and Code Clarity
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Day 42 of consistency 💻🔥 Solved Add Two Numbers using linked lists — a classic problem that really tests understanding of pointers, carry handling, and edge cases. Key takeaways: Handling carry efficiently is crucial Dummy nodes make list problems much cleaner Iterative approach keeps space optimal Not the fastest runtime yet, but improvement is a process — optimizing step by step. Consistency > Perfection. #Day42 #LeetCode #DSA #Java #CodingJourney #ProblemSolving #100DaysOfCode
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🚀 Day 16 of #100DaysOfCode Today’s problem: Minimum Absolute Difference 📊 🔍 Problem Understanding: Given an array of distinct integers, find all pairs with the minimum absolute difference. 🧠 Approach: First, I sorted the array Then compared adjacent elements (since minimum difference will always be between neighbors in sorted order) Tracked the minimum difference and stored all valid pairs 👉 Key Insight: Sorting reduces unnecessary comparisons and simplifies the problem ⚙️ Concepts Used: Sorting (Arrays.sort) Greedy observation (check only neighbors) List handling for storing pairs 📊 Complexity: ⏱️ Time Complexity: O(N log N) (due to sorting) 💾 Space Complexity: O(N) (for storing result pairs) 📚 Key Learnings: Learned how sorting simplifies problems Understood how to reduce complexity from brute force O(N²) → O(N log N) Improved thinking in terms of patterns and optimization 💯 Result: ✔️ Accepted (All test cases passed) ✔️ Runtime: 1 ms (100%) 🔥 ✔️ Clean and efficient solution Sometimes the best optimization is just sorting + observation 💡 Let’s keep building consistency 🚀 #Day16 #100DaysOfCode #Java #DSA #LeetCode #ProblemSolving #Sorting
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I thought the validation was solid… until real users started clicking faster than expected. Recently, while working on a form flow, everything looked fine during testing. - Inputs were validated. - Responses were clean. - Flow worked as expected. Then a real scenario exposed an edge case: Some users clicked the submit button twice during slow network moments. Result? Duplicate records were created. That reminded me that validation isn’t only about checking fields. It’s also about handling user behavior, timing, retries, and unexpected usage patterns. I improved the flow with request locking / idempotent handling and better button state management. Much more reliable after that. Sometimes users don’t break systems intentionally, they just use them in real ways we didn’t simulate. Build for expected inputs. Test for real behavior. #Java #BackendDevelopment #Validation #SystemDesign #SpringBoot #LearningInPublic
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🚀 Day 7 – Exception Handling: More Than Just try-catch Today I focused on how exception handling should be used in real applications—not just syntax. try { int result = 10 / 0; } catch (Exception e) { System.out.println("Error occurred"); } This works… but is it the right approach? 🤔 👉 Catching generic "Exception" is usually a bad practice 💡 Better approach: ✔ Catch specific exceptions (like "ArithmeticException") ✔ Helps in debugging and handling issues more precisely ⚠️ Another insight: Avoid using exceptions for normal flow control Example: if (value != null) { value.process(); } 👉 is better than relying on exceptions 💡 Key takeaway: - Exceptions are for unexpected scenarios, not regular logic - Proper handling improves readability, debugging, and reliability Small changes here can make a big difference in production code. #Java #BackendDevelopment #ExceptionHandling #CleanCode #LearningInPublic
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I didn’t realise the problem at first… everything was working. But something felt slow. While working on a feature, I noticed that for a single action, the system was making multiple API calls in the background. Each call was fast on its own. But together, they were adding up. That’s when it clicked, the issue wasn’t the API speed, it was the number of calls. So instead of calling the API again and again, I combined the data and handled it in a single request. That small change made a clear difference. The response felt quicker, and the flow became much cleaner. It was a simple fix, but a useful reminder: Sometimes performance issues are not about optimization… they’re about reducing unnecessary work. #Java #BackendDevelopment #APIDesign #Performance #FullStackDeveloper #LearningInPublic
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Day 9:- Conditional Statements A Journey with Frontlines EduTech (FLM) and Fayaz S Conditional statements 👉 if- else If -else is a conditional statement used to execute different blocks of code base on a condition. if statement:- -- It excute code only if the condition is true -- if the condition is true.it prints the message -- id false nothing happens Example:- { int age = 18; if(age >=18); System.out.println("he is major"); } If-else :- It executes one block if the condition is true and another block if it is false. Syntax:- if(condition){ System.out.println(block); } else{ // else block } if-else-if:- It is used multiple conditions are checking. Syntax:- if(condition) { // Code } else if(condition 2) { // Code } else { // Code } #Corejava #ConditionalStatements #java #frontlinesmediaedutech
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Solved: Product of Array Except Self 💡 Key Takeaway: Instead of recalculating product for every index, we can use prefix and suffix products to build the result efficiently. 👉 Approach I followed: - First pass → store left (prefix) product - Second pass → multiply with right (suffix) product - No division used 📊 Time Complexity: O(n) 📦 Space Complexity: O(1) 🔍 What made it interesting: Understanding how left and right contributions combine at each index to avoid redundant calculations. Consistency + clarity is slowly building confidence 💪 #DSA #Java #LeetCode #CodingJourney #BackendDeveloper #SoftwareEngineering
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Topic: Avoiding Premature Abstraction Not everything needs to be abstracted from day one. Developers often try to generalize code too early. This leads to: • Unnecessary complexity • Hard-to-read code • Over-engineered solutions A better approach: • Solve the current problem first • Refactor when patterns emerge • Introduce abstraction when it’s actually needed Because abstraction without clarity creates confusion. Good design evolves over time — it’s not forced early. Simple code today is better than complex code for a problem that doesn’t exist yet. When do you decide it’s the right time to abstract? #CleanCode #SoftwareEngineering #BackendDevelopment #Java #SystemDesign
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🚀 Day 52 of #100DaysOfLeetCode Solved: Daily Temperatures (Monotonic Stack) Today’s focus was on understanding how to optimize from a brute-force O(n²) approach to an efficient O(n) solution using a stack. Key takeaways: Learned how to identify “next greater element” patterns Understood how monotonic stacks help avoid redundant work Practiced writing clean and optimized code Consistency is starting to pay off. Onto the next one. #DSA #Java #CodingJourney #LeetCode #ProblemSolving
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🔥 𝗗𝗮𝘆 𝟵𝟬/𝟭𝟬𝟬 — 𝗟𝗲𝗲𝘁𝗖𝗼𝗱𝗲 𝗖𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲 𝟭𝟯𝟰𝟲. 𝗖𝗵𝗲𝗰𝗸 𝗜𝗳 𝗡 𝗮𝗻𝗱 𝗜𝘁𝘀 𝗗𝗼𝘂𝗯𝗹𝗲 𝗘𝘅𝗶𝘀𝘁 | 🟢 𝗘𝗮𝘀𝘆 | 𝗝𝗮𝘃𝗮 90 days in — still finding elegant solutions. 🎯 𝗧𝗵𝗲 𝗽𝗿𝗼𝗯𝗹𝗲𝗺: Check if there exist two indices i ≠ j such that arr[i] == 2 * arr[j]. 𝗔𝗽𝗽𝗿𝗼𝗮𝗰𝗵 — 𝗛𝗮𝘀𝗵𝗦𝗲𝘁 𝗼𝗻𝗲-𝗽𝗮𝘀𝘀: ✅ For each element, check if its double already exists in the set ✅ Also check if half of it exists — but only if it's even (to avoid false integer division) ✅ Add the element to the set and move on 𝗧𝗵𝗲 𝘀𝘂𝗯𝘁𝗹𝗲 𝗲𝗱𝗴𝗲 𝗰𝗮𝘀𝗲: Why guard i%2 == 0 before checking i/2? If i = 3, then i/2 = 1 in integer division — but 3 is not double of 1. The even check ensures we only look for a true half, not a truncated one. 💡 𝗖𝗼𝗺𝗽𝗹𝗲𝘅𝗶𝘁𝘆: ⏱ Time: O(n) — single pass 📦 Space: O(n) — HashSet No sorting. No nested loops. Just one scan with O(1) lookups. The even-check guard is the kind of small detail that separates a correct solution from a buggy one in an interview. 🧠 📂 𝗙𝘂𝗹𝗹 𝘀𝗼𝗹𝘂𝘁𝗶𝗼𝗻 𝗼𝗻 𝗚𝗶𝘁𝗛𝘂𝗯: https://lnkd.in/gYqNTTEZ 10 more days. Double digits left — let's finish this! 🚀 #LeetCode #Day90of100 #100DaysOfCode #Java #DSA #HashSet #Arrays #CodingChallenge #Programming
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Also dont forget about the opposite, many private 1-2 Liner Method to archieve DRY/ atomacy / reusabality. I would prefer a 1000 Line method over it as i can follow from top to bottom.