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Solved today’s LeetCode Daily and it made me pause 👇 “XOR After Range Multiplication Queries I” At first glance, it looks like: Segment Tree? Lazy Propagation? Some heavy optimization? 🤯 But the reality? Sometimes… brute force wins. --- Given constraints were small. And that completely changes the game. So instead of overengineering: ✔️ Just simulate each query ✔️ Jump with k steps ✔️ Apply multiplication (mod 1e9+7) ✔️ Take final XOR And that’s it. --- The interesting part 👇 As developers, we are trained to think: “Optimize first” But problems like this remind us: 👉 Understand constraints before choosing approach Because honestly, A simple O(n * q) solution can beat an overcomplicated design any day. --- What I learned today: • Not every problem needs advanced DS • Constraints are part of the problem statement for a reason • Simplicity is underrated --- Consistency check ✅ One more problem done. --- Curious 👇 Comment your approach. #LeetCode #DSA #Programming #Coding #Developers #ProblemSolving #Rust

🧠 One small mistake can break your entire logic. Today I learned this while solving a grid problem 👇 💻 LeetCode #1559 — Detect Cycles in 2D Grid At first glance, it looks like a simple DFS problem… But there’s a catch ⚠️ 🔍 Common mistake developers make: 👉 “If I visit an already visited cell → cycle exists” Sounds correct… but it’s NOT ❌ 🚀 My Approach (DFS + Parent Tracking): Traverse the grid using DFS Move in 4 directions (up, down, left, right) Only move to cells with the same character 👉 While moving, I track the parent cell 💡 Key Logic: If I reach a cell that is: Already visited AND not the parent 👉 Then a cycle exists ✅ ⚙️ Why parent check is important? Because going back to the previous cell is normal 👉 It should NOT be treated as a cycle 🧠 Takeaway: In DSA, logic rarely fails… 👉 Edge cases do 🔥 The difference between wrong and correct solution is often just one condition Have you ever fixed your solution by changing just 1 line? 😄 #LeetCode #DSA #Algorithms #Programming #Debugging #ProblemSolving #Developers #CodingJourney

💻In this new Ansys Innovation Space blog, we’ll take a closer look at one of the key improvements in Scade One 2026 R1: the Swan code generator. This tool converts Swan models into efficient, portable C code, and with the latest release, it’s now even better at optimizing performance of the generated code. Read more at: https://bit.ly/4c5MUeC #programmer #programming #modelbaseddedign

🚀 Leveling up my DSA skills: Mastering the Sliding Window! I recently tackled the "Longest Substring Without Repeating Characters" problem on LeetCode using C++. This was a great exercise in optimizing time complexity and understanding how to manage dynamic windows within a string. 💡 The Approach To solve this efficiently, I used the Sliding Window technique combined with an unordered_map: Expansion: The high pointer expands the window by adding characters to the frequency map. Contraction: If the number of unique characters in the map is less than the window size ($f.size() < k$), it means we have a duplicate. The low pointer then slides forward, removing characters until the window is valid again. Efficiency: This approach ensures we traverse the string in $O(n)$ time, which is much better than a brute-force $O(n^2)$ search. #LeetCode #CodingJourney #CPP #DataStructures #Algorithms #SoftwareEngineering #ProblemSolving #SlidingWindow #Programming

Understanding the path to the solution. I recently solved LeetCode 62: Unique Paths. While the problem seems simple at first glance, it’s a perfect example of how Dynamic Programming can optimize a solution from exponential time to linear time. The core idea: The number of ways to reach any cell is simply the sum of ways to reach the cell above it and the cell to its left. Seeing that "Accepted" screen with a 0ms runtime is always a great feeling! #SoftwareEngineering #DynamicProgramming #Coding #LeetCodeDaily

Binary tree right side view Approach: - Keep a level variable - If level == result.size(), add current node (first node of that level) - Traverse right first, then left Time: O(n) Space: O(h) (worst: O(n), best: O(log n)) #Algorithms #DSA #LeetCode #coding #Programming

Minimum Distance Between Three Equal Elements Thought process 🤔 Brute force: Run 3 loops, pick every (i, j, k), check if elements are equal, and calculate the absolute difference of indices. Keep updating the minimum. Simple approach, but yeah… O(n³) is too slow when input size grows 😅 How to optimize:: We only care about indices where values are the same, so instead of checking every triplet, let’s store them.. Use a map For each elem, store all its indices Then check only valid triplets from those indices, compute distances for valid groups and track the mini. O(n) time 💡 #leetcode #potd #programming #dsa #developer #softwareengineer #datastructures #algorithms 

Furthest point from origin Thought process: We’re given a string with 'L', 'R', and '_'. 'L' → move left 'R' → move right '_' → can be either left or right 🤔 So the key idea is: the final distance mainly depends on how we use '_'. To maximize distance, we should move all '_' in the direction that already has more moves (left or right). This way, the gap increases as much as possible. So, the ans becomes: abs(lCnt - rCnt) + underscore_cnt #programming #problemSolving #coding #developers #softwareengineering #DSA #algorithms

🚀 Testing your C fundamentals! Can you predict the output of this nested loop? for(int i = 1; i <= 3; i++) { for(int j = 1; j <= 2; j++) { printf("%d%d ", i, j); } } Drop your answer in the comments 👇 #CProgramming #EmbeddedSystems #CodingChallenge #Loops #LearningInPublic

Day 91 on LeetCode —Final Prices With a Special Discount 🛒💸✅ Today’s problem focused on array traversal and discount simulation logic. not apply stack because my array logic works equally fine 🔹 Approach Used in My Solution • Traverse each item in the prices array • Search on the right side for the first smaller or equal value • Apply that value as a discount • Store updated answers directly in the result array Simple, clean, and easy to understand. ⚡ Complexity: • Time Complexity: O(n²) • Space Complexity: O(n) 💡 Key Takeaways: • Sometimes a direct array traversal approach explains the logic more clearly • Focused on building the solution step-by-step instead of forcing optimization immediately • Even brute force approaches strengthen understanding of problem flow and conditions 🔥 Consistency and clarity in logic matter just as much as optimization. #LeetCode #DSA #Algorithms #DataStructures #Arrays #ProblemSolving #Coding #Programming #Cpp #STL #SoftwareEngineering #ComputerScience #CodingPractice #DeveloperLife #TechJourney #CodingDaily #Consistency #100DaysOfCode #BuildInPublic #AlgorithmPractice #CodingSkills #Developers #TechCommunity #SoftwareDeveloper #EngineeringJourney