Add 1 to a Number in Array Form

Day 81 on LeetCode Remove Linked List Elements 🔗🧹✅ Still prioritizing consistency during busy days — and today’s problem was a solid linked list traversal & deletion practice 💯 🔹 Approach Used in My Solution The goal was to remove all nodes with a given value from a linked list. Key idea: • First, handle edge cases where head itself contains the target value • Move head forward until it points to a valid node • Then traverse the list using two pointers:   – prev → last valid node   – temp → current node • If temp->val == val → skip the node by linking prev->next • Otherwise → move both pointers forward This ensures all matching nodes are removed efficiently. ⚡ Complexity: • Time Complexity: O(n) • Space Complexity: O(1) 💡 Key Takeaways: • Practiced pointer manipulation in linked lists • Learned how to safely handle deletions, especially at head • Reinforced importance of edge case handling 🔥 Small consistent steps → strong fundamentals. #LeetCode #DSA #Algorithms #DataStructures #LinkedList #Pointers #ProblemSolving #Coding #Programming #Cpp #STL #SoftwareEngineering #ComputerScience #CodingPractice #DeveloperLife #TechJourney #CodingDaily #Consistency #100DaysOfCode #BuildInPublic #AlgorithmPractice #CodingSkills #Developers #TechCommunity #SoftwareDeveloper #EngineeringJourney

🚀 Day 561 of #750DaysOfCode 🚀 📌 Problem: Minimum Distance to the Target Element Today’s problem was simple yet a great reminder of how powerful basic iteration can be when applied correctly. 🔍 The task was to find the minimum distance between a given start index and any index i such that nums[i] == target. 💡 Key Insight: Instead of overthinking, just iterate through the array and track the minimum value of |i - start| whenever the target is found. Clean, efficient, and effective. 🧠 What I Learned: Sometimes brute force with clarity is the best solution Always look for opportunities to minimize operations with simple logic Writing clean and readable code matters as much as solving the problem ⚡ Approach: Traverse the array Check for target Update minimum distance ⏱️ Complexity: Time: O(n) Space: O(1) 💻 Consistency is key. Small steps every day build strong problem-solving skills over time. #leetcode #dsa #programming #java #coding #developers #softwareengineering #100daysofcode #codingjourney #tech #learning #growth

Daily Dose of Surviving in a Programming Contest - sometimes the real optimisation isn’t in the process, it’s in redefining what you track. In competitive programming contests especially on CodeForces, linear combination equations across multiple variables can quickly explode in complexity. But instead of tracking full values, a smarter approach is to manage remainders using modulo—shrinking the problem into something far more controllable. This matters in contests because time isn’t just about coding—it’s about how efficiently you think. This technique is itself called as Frobenius technique or problem. Here’s the thinking flow: • Problem Reading → Identify it as a linear combination / sum constraint problem • Pattern Recognition → Full values aren’t required, only divisibility or remainder matters • Constraints Analysis → Direct DP or brute force grows too large • Approach Selection → Track states using remainders modulo k • Implementation → Transition between states using (current + value) % k • Debugging → Handle cycles, duplicate states, and unreachable remainders What most people miss is this: • They try to compute exact values • When the problem only cares about equivalence classes (remainders) That shift reduces both time complexity and cognitive load under pressure. This maps directly to real systems: • Hashing, partitioning, load balancing → all rely on grouping by equivalence Efficient systems don’t track everything—they track what matters. If you’re plateauing in CP, it’s rarely about syntax—it’s about abstraction. Where I learned this trick? Try solving this question - https://lnkd.in/gpnmPQN4 Are you solving the exact problem—or the minimal version required to get the answer? Let's discuss in comments below. Follow Vishu Kalier for more such Competitive Programming insights. #CompetitiveProgramming #DSA #Algorithms #Modulo #ProblemSolving #Optimization #Coding #SystemDesign #dailydose #cfbr #datastructures #java #math #codeforces #eternal #zomato #VIT

🚀 Day 29 of 100 Days LeetCode Challenge Problem: Check if Strings Can be Made Equal With Operations I Day 29 is a short but pattern + constraint observation problem 🔥 💡 Key Insight: We can only swap characters where: 👉 j - i = 2 For a string of length 4, possible swaps: Index 0 ↔ 2 Index 1 ↔ 3 👉 That means: Positions (0,2) form one group Positions (1,3) form another group 🔍 Core Approach: 1️⃣ Group Characters Extract characters from: Even indices → [0, 2] Odd indices → [1, 3] 2️⃣ Compare Groups Sort both groups for s1 and s2 If both corresponding groups match → ✅ true Else → ❌ false 💡 Why This Works: You can rearrange freely within each group But cannot mix between groups 🔥 What I Learned Today: Limited operations define independent groups Think in terms of index grouping Small problems still test logical clarity 📈 Challenge Progress: Day 29/100 ✅ One day to 30! LeetCode, Strings, Swapping, Greedy, Pattern Recognition, Arrays, DSA Practice, Coding Challenge, Problem Solving #100DaysOfCode #LeetCode #DSA #CodingChallenge #Strings #ProblemSolving #TechJourney #ProgrammerLife #SoftwareDeveloper #CodingLife #LearnToCode #Developers #Consistency #GrowthMindset #InterviewPrep

Day 69 on LeetCode Search in Rotated Array (Brute Force Insight) 🔍✅ Today’s problem initially felt tricky, but turned out to be one of the simplest when approached directly. 🔹 Approach Used in My Solution Instead of overcomplicating with rotation logic, I used a straightforward linear search. Key idea: • Traverse the array from start to end • Compare each element with the target • Return the index once found, otherwise -1 Sometimes, the simplest approach is the most reliable. 🔹 Initial Thought Process (Overthinking Phase 😅) • Considered rotating the array and then searching • Thought about adjusting indices using formulas like:   (index - rotation + n) % n • But realized that all of this is unnecessary for basic search ⚡ Complexity: • Time Complexity: O(n) • Space Complexity: O(1) 💡 Key Takeaways: • Not every problem needs an optimized approach — clarity > complexity • Avoid overengineering when a simple solution works perfectly • Always validate if a direct approach solves the problem efficiently enough 🔥 Great reminder: Sometimes the “easy way” is the smart way. #LeetCode #DSA #Algorithms #DataStructures #Arrays #LinearSearch #ProblemSolving #Coding #Programming #Cpp #STL #SoftwareEngineering #ComputerScience #CodingPractice #DeveloperLife #TechJourney #CodingDaily #100DaysOfCode #BuildInPublic #AlgorithmPractice #CodingSkills #Developers #TechCommunity #SoftwareDeveloper #EngineeringJourney

When I first learned programming as a kid, switch statements genuinely confused me. I was taught that after every case, you should add a break. switch(status) { case "success": console.log("Payment successful"); break; case "failed": console.log("Payment failed"); break; } But I remember constantly wondering: “If the whole point of a switch statement is to execute the matching case… then why do I need another keyword to stop it?” Why wasn’t that already the default behavior? Why could execution continue into the next case at all? At the time, it honestly felt like bad design. Almost buggy. And when I forgot a break once and watched multiple cases execute, it only made the confusion worse. Later I understood something important: case labels are not isolated blocks. They’re more like entry points inside one continuous execution flow. A switch statement jumps to the matching label and keeps executing forward until something explicitly stops it. That “something” is break. And suddenly the design started making sense. What initially felt unnecessary was actually intentional control over execution flow. In fact, this pattern exists in a lot of real systems and open-source codebases where multiple states intentionally share logic through fall-through. For example, parsers, compilers, and even low-level runtimes often group multiple token types or instruction states together: switch(tokenType) { case "NUMBER": case "STRING": case "BOOLEAN": parseLiteral(); break; } Different entry points. Shared execution path. Even in large production systems, this prevents duplicated logic and keeps state handling predictable. The older I get in software engineering, the more I realize this happens everywhere. A lot of things in programming feel wrong initially because our intuition assumes invisible boundaries that the machine never promised in the first place. The machine only follows flow. Not expectations. Funny how some of my earliest frustrations with programming eventually became lessons in how execution actually works underneath the abstraction. #Programming #SoftwareEngineering #JavaScript #Coding #ComputerScience #ProgrammingLanguages #SoftwareDevelopment #Developer #Tech #CleanCode #BackendDevelopment #SystemsProgramming #Developers #Engineering #Debugging #TechThoughts

I spent 30 minutes overthinking a problem that had a 2-minute solution. Problem: Construct Uniform Parity Array I At first, it feels like a construction + constraints problem. You start thinking about cases, patterns, edge conditions… But then I stepped back and looked at the operations: nums2[i] = nums1[i] nums2[i] = nums1[i] - nums1[j] (j ≠ i) Now ask a better question: 👉 What happens to parity under these operations? Same value => parity unchanged Difference of two numbers => can be even or odd depending on choice That’s the key. You can control parity freely. Just to make the entire array all even or all odd And that’s always possible. So the answer would be always TRUE . #FirstPrinciples #ProblemSolving #CodingJourney #LeetCode #DSA #Algorithms #SoftwareEngineering #Developers #CodeNewbie #LearnToCode #ProgrammingLife #TechThinking #LogicalThinking #BuildInPublic #DeveloperMindset #CleanThinking #CodingLife #TechCareers #GrowthMindset #ThinkDifferent

Day 89 on LeetCode Valid Parentheses 🧠🧱✅ A fundamental problem that builds strong intuition for stack-based thinking. 🔹 Approach Used in My Solution • Traverse the string character by character • Push all opening brackets onto the stack • For every closing bracket:   – Check if stack is empty → invalid   – Compare with top element   – If mismatch → return false • At the end → stack should be empty for a valid string ⚡ Complexity: • Time Complexity: O(n) • Space Complexity: O(n) 💡 Key Takeaways: • Stack is perfect for handling nested structures • Order and matching are crucial in such problems • Always check for empty stack before accessing top 🔥 Simple problem, but a powerful pattern used in many advanced scenarios. #LeetCode #DSA #Algorithms #DataStructures #Stack #ValidParentheses #ProblemSolving #Coding #Programming #Cpp #STL #SoftwareEngineering #ComputerScience #CodingPractice #DeveloperLife #TechJourney #CodingDaily #Consistency #100DaysOfCode #BuildInPublic #AlgorithmPractice #CodingSkills #Developers #TechCommunity #SoftwareDeveloper #EngineeringJourney

- SOLID Principles – Super Simple Explanation (Beginner Friendly) If you're new to coding, think of SOLID as simple rules to keep your code clean and easy to manage 👇 🔹 S – Single Responsibility 👉 One class = one job Example: Keep login logic separate from UI 🔹 O – Open/Closed 👉 Add new features without changing old code Example: Add a new payment type using a new class 🔹 L – Liskov Substitution 👉 Child class should work perfectly in place of parent 🔹 I – Interface Segregation 👉 Don’t force unnecessary methods Example: Use small, focused interfaces 🔹 D – Dependency Inversion 👉 Depend on abstraction, not direct implementation 💡 Real tip: While coding, just ask: “Can I extend this without breaking it?” Start with Single Responsibility — it’s the easiest and most powerful 💯 #SOLID #CleanCode #BeginnerFriendly #Coding

Day 77 on LeetCode Find Smallest Letter Greater Than Target 🔤🔍✅ Continuing the streak with a clean Binary Search application — keeping things simple and consistent during mids 💯 🔹 Approach Used in My Solution The goal was to find the smallest character strictly greater than the target in a sorted array, with wrap-around behavior. Key idea: • Apply binary search on the sorted array • Whenever letters[mid] > target, store it as a potential answer • Move left to find an even smaller valid character • If no such character exists, return letters[0] (wrap-around case) This ensures we always get the next greatest letter efficiently. ⚡ Complexity: • Time Complexity: O(log n) • Space Complexity: O(1) 💡 Key Takeaways: • Practiced binary search for “next greater element” problems • Learned how to handle wrap-around edge cases • Reinforced writing clean and optimized search logic 🔥 Small wins every day consistency is the real progress. #LeetCode #DSA #Algorithms #DataStructures #BinarySearch #Arrays #ProblemSolving #Coding #Programming #Cpp #STL #SoftwareEngineering #ComputerScience #CodingPractice #DeveloperLife #TechJourney #CodingDaily #Consistency #100DaysOfCode #BuildInPublic #AlgorithmPractice #CodingSkills #Developers #TechCommunity #SoftwareDeveloper #EngineeringJourney