LeetCode Challenge: Minimum Absolute Difference in Array

#leetcodePotd — Cracked with 100% Runtime Performance Just wrapped up “Find Smallest Letter Greater Than Target” on LeetCode, and this one is a clean example of how Binary Search dominates even “easy” problems when used strategically. At first glance, it looks like a basic character comparison task. In reality? It’s a search-space optimization problem disguised as a string question. 🧠 Problem Snapshot We’re given: A sorted array of characters A target character Goal: 👉 Return the smallest letter greater than the target 👉 If none exists, wrap around to the first character This wrap-around twist is where most brute-force approaches fumble. 💡 Key Insight Because the array is sorted, we don’t scan — we binary search the answer space. We’re not just finding a match. We’re searching for the first element strictly greater than target. That’s a lower bound variant problem. ⚙️ Strategy Breakdown ApproachTimeSpaceVerdictBrute Force ScanO(n)O(1)Acceptable, but not eliteBinary SearchO(log n)O(1)Scalable & optimal Binary search reduces operations dramatically — that’s why runtime hits 0 ms. 🧩 Core Logic (High-Level) Use binary search to narrow the window Track smallest positive difference from target Move left when a valid candidate appears If no greater char found → return first element (wrap) This ensures we always land on the minimal valid successor. 📈 Performance Metrics ✅ Runtime: 0 ms (100th percentile) ✅ Memory: Top-tier efficiency ✅ Test Cases Passed: 167/167 Precision > brute force hustle. 🎯 Takeaway Even “easy” problems test your understanding of: Boundary conditions Lower bound search Wrap-around logic Efficient comparison strategy Master these patterns and your medium/hard problems start looking easy. #LeetCode #DSA #DataStructures #Algorithms #BinarySearch #CodingInterview #TechCareers #SoftwareEngineering #ProblemSolving #Java #ProgrammingLife #CodeNewbie #DeveloperLife #CompetitiveProgramming #100DaysOfCode #CodingJourney #TechSkills #CareerGrowth #InterviewPrep #BigTech #FAANGPrep #LearnToCode #TechCommunity #WomenWhoCode #AIEngineer #FutureEngineer #ComputerScience #CSStudents #TechLeaders #BuildInPublic

𝗗𝗮𝘆 𝟮𝟵/𝟭𝟬𝟬 | 𝗟𝗲𝗻𝗴𝘁𝗵 𝗼𝗳 𝗟𝗮𝘀𝘁 𝗪𝗼𝗿𝗱 Day 29 ✅ — One day away from a full month. Sometimes simple is powerful. 𝗧𝗼𝗱𝗮𝘆'𝘀 𝗣𝗿𝗼𝗯𝗹𝗲𝗺: ✅ 𝗣𝗿𝗼𝗯𝗹𝗲𝗺 #𝟱𝟴: Length of Last Word (Easy) 𝗪𝗵𝗮𝘁 𝗖𝗹𝗶𝗰𝗸𝗲𝗱: Find the length of the last word in a string. Sounds simple, but edge cases make it interesting: Trailing spaces: "Hello World " Leading spaces: " Hello" Multiple spaces between words The efficient approach? 𝗧𝗿𝗮𝘃𝗲𝗿𝘀𝗲 𝗳𝗿𝗼𝗺 𝘁𝗵𝗲 𝗲𝗻𝗱. Skip trailing spaces, count characters until you hit another space. 𝗠𝘆 𝗔𝗽𝗽𝗿𝗼𝗮𝗰𝗵: 👉 Start from the end of the string 👉 Skip all trailing spaces 👉 Count characters until next space 👉 Return count Time complexity: O(n), Space complexity: O(1) One pass. No split(). No extra space. 𝗠𝘆 𝗥𝗲𝗮𝗹𝗶𝘇𝗮𝘁𝗶𝗼𝗻: Easy problems teach you to handle edge cases cleanly. String manipulation might seem basic, but it's tested in every coding interview. The difference between junior and senior developers? Handling edge cases without being told. 29 days in, and I'm paying attention to the details that matter. 𝗖𝗼𝗱𝗲: https://lnkd.in/gBXpSzgy 𝟮𝟵 𝗱𝗮𝘆𝘀. 𝗧𝗼𝗺𝗼𝗿𝗿𝗼𝘄 𝗺𝗮𝗿𝗸𝘀 𝗼𝗻𝗲 𝗳𝘂𝗹𝗹 𝗺𝗼𝗻𝘁𝗵. Almost there. Consistency compounds. 𝗗𝗮𝘆 𝟮𝟵/𝟭𝟬𝟬 ✅ | 𝟳𝟭 𝗺𝗼𝗿𝗲 𝘁𝗼 𝗴𝗼! #100DaysOfCode #LeetCode #StringManipulation #EdgeCases #CodingInterview #Java #Algorithms #SoftwareEngineer #ProblemSolving #CleanCode #TechnicalInterview #Programming #DataStructures #TimeComplexity #TechCareers

In software engineering, code that you have wrote will evolve. No matter it's written by #ai or by you. Because: ✅Requirements change a lot ✅Optimization comes ✅Bugs occurs, and fixes happens ✅Code base grows There are many more things that will evolve and you have to make changes in the code. Keep coding!! #dotnet #dotnetdevelopers #softwareengineering #coding

𝗗𝗮𝘆 𝟮𝟳/𝟭𝟬𝟬 | 𝗗𝗲𝗰𝗼𝗱𝗲 𝗦𝘁𝗿𝗶𝗻𝗴 Day 27 ✅ — When recursion makes everything elegant. 𝗧𝗼𝗱𝗮𝘆'𝘀 𝗣𝗿𝗼𝗯𝗹𝗲𝗺: ✅ 𝗣𝗿𝗼𝗯𝗹𝗲𝗺 #𝟯𝟵𝟰: Decode String (Medium) 𝗪𝗵𝗮𝘁 𝗖𝗹𝗶𝗰𝗸𝗲𝗱: Decode strings like "3[a2[c]]" → "accaccacc". Numbers indicate repetition, brackets show nested patterns. My first thought? Stack. But then I realized: nested brackets = 𝗿𝗲𝗰𝘂𝗿𝘀𝗶𝗼𝗻 territory. Each time I hit '[', recursively decode what's inside. When I hit ']', return to the outer level. The recursion naturally handles the nesting. 𝗠𝘆 𝗔𝗽𝗽𝗿𝗼𝗮𝗰𝗵: 👉 Build number from consecutive digits 👉 When '[' appears, recursively decode inner string 👉 Repeat the decoded string by the number 👉 When ']' appears, return result to caller 👉 Regular characters get appended directly Time: O(maxK × n) where maxK is max repeat count, Space: O(n) for recursion stack 𝗠𝘆 𝗥𝗲𝗮𝗹𝗶𝘇𝗮𝘁𝗶𝗼𝗻: Recursion isn't just for trees and graphs—it's for any problem with 𝗻𝗲𝘀𝘁𝗲𝗱 𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲𝘀. The key: recognize when a subproblem looks exactly like the main problem. That's your recursion signal. 27 days in, and I'm getting more comfortable with recursive thinking. 𝗖𝗼𝗱𝗲: https://lnkd.in/gFfUH6bk 𝟮𝟳 𝗱𝗮𝘆𝘀 𝘀𝘁𝗿𝗮𝗶𝗴𝗵𝘁. 𝗔𝗹𝗺𝗼𝘀𝘁 𝗮 𝗺𝗼𝗻𝘁𝗵. Every problem teaches a pattern. Every pattern becomes a tool. 𝗗𝗮𝘆 𝟮𝟳/𝟭𝟬𝟬 ✅ | 𝟳𝟯 𝗺𝗼𝗿𝗲 𝘁𝗼 𝗴𝗼! #100DaysOfCode #LeetCode #Recursion #StringManipulation #DataStructures #CodingInterview #TechnicalInterview #SoftwareEngineer #FAANG #ProblemSolving #Algorithms #Java #Programming #ComputerScience #DeveloperJourney #LearnInPublic #SoftwareDevelopment #CodingSkills #TechJobs #CareerGrowth

🚀 #Day98 of my #100DaysCodingChallenge Today, I solved an interesting simulation + observation based problem related to circular traversal — Most Visited Sector in a Circular Track. This problem looks tricky at first, but once you observe the pattern, the solution becomes clean and elegant. 🔹 Problem: Most Visited Sector in a Circular Track Problem Statement: - You are given: (i) An integer n representing the number of sectors on a circular track (labeled 1 to n) (ii) An array rounds where each element represents the sector visited in order during a marathon Your task is to return all sectors that were visited the maximum number of times, in ascending order. ✅ Approach: The key insight here is: 👉 The most visited sectors are always those between the starting sector and the ending sector of the marathon path. Why? (a) Every round starts from rounds[i] and ends at rounds[i+1] (b) All intermediate sectors get covered uniformly (c) Only the path from the first sector to the last sector determines the maximum visits Steps: (1) Identify start = rounds[0] (2) Identify end = rounds[last] (3) If start ≤ end → sectors are simply [start … end] (4) If start > end → wrap around the circular track: [start … n] and [1 … end] (5) Finally, sort the result (as required by the problem) ⏳ Time Complexity: O(n) At most, we traverse all sectors once. 📦 Space Complexity: O(n) To store the result list. 💡 Key Takeaways ✔ Recognizing patterns avoids unnecessary simulation ✔ Circular problems often reduce to range analysis ✔ Sorting may still be required even after correct traversal ✔ Clean logic beats brute-force counting ✔ Frequently asked problem to test observation skills This problem was a great reminder that thinking before coding can dramatically simplify the solution. Grateful to Abhishek Kumar Sir and K R Mangalam University for their continuous support and guidance 🙌 #100DaysOfCode #Day98 #Java #DSA #Arrays #Simulation #ProblemSolving #InterviewPreparation #CodingChallenge #LeetCode #KRMangalamUniversity

Day 22 Flashy work gets attention. Dependable work gets promotions. In automation, noise is easy. Big frameworks. Big test counts. Big coverage numbers. But real value hides in small things: One flaky test removed. One pipeline sped up. One failure made crystal clear. “Quantity gets applause. Reliability gets trust.” Nobody celebrates the test that didn’t fail randomly. But everyone feels it. “Fast code feels smart. Stable code feels safe.” The best automation engineers I’ve seen don’t talk much. They ship stable builds. They reduce friction. They make releases boring. And boring releases are elite. Because in the end: Busy looks impressive. Impact looks quiet. #AutomationTesting #QA #SDET #QualityEngineering #Python #TechCareers #EngineeringMindset #BuildInPublic

Many people believe that if they solve hundreds of LeetCode problems, they will automatically get a job. But this is one of the biggest misconceptions in software engineering. LeetCode, Codeforces, and CodeChef are good platforms, but they mostly train you to recognize patterns and write fast solutions. They don’t teach you how a computer actually works. Think of coding like driving a car. If you only know how to press the accelerator and brake, you can drive on an empty road. But if something goes wrong or the road is difficult, you will panic. Understanding computers is like understanding how the engine works. When you write code, data is stored in memory. Some data goes to the stack, some goes to the heap. The CPU doesn’t read your code directly. It reads instructions from memory through cache. This is why arrays are faster than linked lists, and why recursion can cause stack overflow. Interviewers don’t just want correct answers. They ask why a solution is faster, how memory is allocated, and what happens behind the scenes. LeetCode alone doesn’t prepare you for these questions. The right approach is to first understand basics like memory, CPU, stack, heap, and cache. Then learn data structures using this knowledge. After that, practice LeetCode. LeetCode teaches you how to solve problems. Understanding how computers work teaches you how to think. And interviews test how you think. #dsa #softwareengineer #computerscience #tech #leetcode https://lnkd.in/geFNFNeF

Day 13 of 150: Environment Isolation and Script Automation Transitioning today from core language logic to the professional development environment. Managing how and where your code runs is just as important as the code itself. Technical Focus: • Virtual Environments (venv): Mastering environment isolation to manage dependencies and prevent package version conflicts across different projects. • Environment Reproducibility: Understanding why requirements.txt is the backbone of collaborative software engineering. • Script Automation: Developed a Self-Intro Script Generator—a practical application of string manipulation and user-input handling to automate repetitive tasks. • Project Structure: Organizing files to ensure the environment remains separate from the source code. Setting up the right foundation today to build scalable applications tomorrow. 137 days to go. #Python #SoftwareEngineering #BackendDevelopment #150DaysOfCode #DevOps

LeetCode Grinding 🚀 Today was focused on pattern recognition in problem solving and applying it through hands-on practice. 🔹 DSA & LeetCode Practice 1. Solved LeetCode 15 — 3Sum Understood how sorting + two pointers help reduce time complexity Learned how to handle duplicates effectively 2. Solved LeetCode 167 — Two Sum II (Input Array is Sorted) Implemented the two pointers pattern Gained clarity on pointer movement based on sum comparison Overall takeaway: 👉 Strong understanding of how the Two Pointers pattern works and when to apply it in sorted arrays. 🔹 Learning Mindset Focused not just on solving problems, but on understanding the underlying pattern to reuse it in similar questions 📌 Progress happens when concepts start connecting, not just when problems get solved. #DailyGrind #DSA #LeetCode #TwoPointers #ProblemSolving #Java #Consistency #LearningInPublic

Building small tools is often the fastest way to understand how software behaves under constraints. Recently, I’ve been working on CHECK, a CLI-based task management tool developed as a hands-on exploration of structured state handling, persistence, and testable application logic. The project emphasizes fundamentals that tend to emerge as complexity increases: modeling real-world entities as code, validating user input consistently, separating concerns across modules, and ensuring expected behavior through automated tests. CHECK currently supports features such as JSON-based persistence, regex-driven search, and defensive handling of invalid usage scenarios, all intentionally implemented in a simple, inspectable codebase. This project has been a valuable exercise in thinking about software not just as “code that works,” but as a system that remains understandable, testable, and maintainable as it evolves. I’ll continue iterating on it as I deepen my software engineering skill set and explore different design trade-offs. #softwareengineering #softwaredevelopment #python #cli #taskmanagement #todolist #productivitytools #systemsengineering #cleanarchitecture #testing #learningbybuilding