MD Zeeshan

MD ZeeshanJun 13, 2026

The visual definition of "Brute Force vs. Optimal" If you ever wonder why Data Structures and Algorithms matter, just look at this submission history. Getting an "Accepted" status is great, but it's rarely the finish line. Here is the breakdown of the journey: 🔴 The Struggle: Runtime Errors & Wrong Answers. (We've all been there). 🟡 Brute Force (1676 ms | 508.1 MB): The "just make it work" phase. It checks every possibility. It’s resource-heavy, but it gets the green text. 🟢 Optimal (16 ms | 17.6 MB): The "make it fast" phase. By dropping redundant calculations, optimizing space, and picking the right data structure, the runtime dropped by 99%! The takeaway: Brute force solves the problem. Better approaches refine the logic. Optimal solutions scale. Never settle for the first "Accepted". Keep pushing the code! 💻💡 #LeetCode #CPP #DataStructures #Algorithms #ProblemSolving #SoftwareDevelopment #CodingJourney

MD ZeeshanJul 15, 2026

Cleared Round 1 of Flipkart GRiD 8.0 Thrilled to share that I've passed the initial screening and am moving on to the next round of evaluation! The next step is the Coding Assessment, and I want to make sure I am fully prepared for the challenge. To my seniors and connections who have cracked Flipkart GRiD or standard Flipkart OAs before: What is your #1 piece of advice for this round? Which DSA topics or patterns should I absolutely focus on over the next few days? I would love to hear your tips and strategies in the comments! 👇 #FlipkartGRiD #DSA #CodingAssessment #TechCareers #ProblemSolving

MD ZeeshanJun 26, 2026

Ever get so comfortable with a tool that you use it where you shouldn't? 😅 When I first learned about std::vector in C++, it became my go-to. For the last 3 months, I used it for everything—even for constant-size hashing (like a fixed size of 26 for the alphabet). My logic was: "It’s just 26 elements, how much of a difference could a dynamic array actually make?" Today, I got my answer. While optimized a sliding window problem on LeetCode, I swapped out my usual vector<int> hash(26, 0); for a simple static array: int hash[26] = {0};. The logic stayed exactly the same. But the performance? 🚀 Runtime dropped from 3ms (Beating 68%) to a flat 0ms (Beating 100.00%)! 📉 Memory overhead completely vanished, beating 99.41%. Here is the quick breakdown of why this happens: Stack vs. Heap: A static array lives entirely on the Stack. A vector keeps its metadata on the stack but allocates its actual data on the Heap. Pointer Indirection: To read a vector, the CPU has to look at the stack pointer, resolve the address, and jump to the heap. A static array is right there on the stack—zero jumps. Allocation Cost: Vectors carry runtime overhead to request and manage heap memory. Static arrays just move the stack pointer instantly. Lesson learned: Vectors are amazing when size is unpredictable. But if your size is fixed (like an alphabet or ASCII table), a raw static array wins every single time. Lesson learned the hard (but satisfying) way! 💻🔥 #cpp #datastructures #leetcode #programming #coding #optimization #problemsolving #developer