Reversing Integers with LeetCode Challenge

🔢 Day 69 of #100DaysOfCode 🔢 🔹 Problem: Maximum Count of Positive and Negative Integers – LeetCode ✨ Approach: A simple yet powerful one-pass solution! Iterated through the array, counting positives and negatives separately — and returned whichever count was greater. Clean, direct, and efficient. ⚡ 📊 Complexity Analysis: Time Complexity: O(n) — single traversal of the array Space Complexity: O(1) — no extra data structures used ✅ Runtime: 1 ms (Beats 12.27%) ✅ Memory: 46.89 MB 🔑 Key Insight: Sometimes, simplicity wins — clarity in logic often outperforms complex tricks. Counting right leads to coding right! 💡 #LeetCode #100DaysOfCode #ProblemSolving #DSA #Array #AlgorithmDesign #LogicBuilding #CodeJourney #ProgrammingChallenge #CodingDaily #Efficiency

🚀 Day 37 of #100DaysOfCode Challenge 🚀 🧠 Problem: 🧩 LeetCode 282 — Expression Add Operators (Hard) This problem was all about exploring backtracking with arithmetic logic. We’re given a string of digits and need to insert +, -, or * between them to reach a target value. ⚙️ Approach Used backtracking to: -Pick every possible substring as the next number. -Try adding each operator before it (+, -, *). -Track three things: -current value → total so far -previous operand → to handle multiplication correctly -expression → the string we’re building -Also skipped invalid paths like numbers with leading zeros. 📘 Learning -Understood how to evaluate expressions on the fly without using eval(). -Learned to manage operator precedence (* before +/-) using recursion and previous operand adjustment. -Realized that some problems can’t be optimized further — they test how well you can prune and organize recursion. #100DaysOfCode #DSA #CodingChallenge #StriversSheet #ProblemSolving #TakeUForward  #Recursion #CodingInterview #ProgrammingTips #LeetCode  #Backtracking 

💡 Day 78 of #100DaysOfCode 💡 🔹 Problem: Find Closest Number to Zero – LeetCode ✨ Approach: Traversed through the array while keeping track of the number closest to zero using absolute difference comparison. Handled ties by preferring the positive number — because even in code, positivity wins 😉 📊 Complexity Analysis: ⏱ Time Complexity: O(n) — single pass through the array 💾 Space Complexity: O(1) — no extra space used ✅ Runtime: 3 ms (Beats 44.80%) ✅ Memory: 46.87 MB 🔑 Key Insight: Even the smallest differences matter — especially when you’re finding what’s closest to zero! ⚡ #LeetCode #100DaysOfCode #DSA #ProblemSolving #CodingChallenge #JavaProgramming #AlgorithmDesign #CodeJourney #StayPositive

🌟 Day 71 of #100DaysOfCode 🌟 💡 Problem: Matrix Diagonal Sum – LeetCode ✨ Approach: Traversed both primary and secondary diagonals in a single loop — adding elements smartly while avoiding double-counting the center in odd-sized matrices. Simple logic, elegant optimization! ⚡ 📊 Complexity Analysis: Time Complexity: O(n) — single traversal through the matrix rows Space Complexity: O(1) — constant auxiliary space ✅ Runtime: 0 ms (Beats 100%🔥) ✅ Memory: 46.26 MB 🔑 Key Insight: In coding, clarity wins. The shortest paths often come from the clearest logic. 🎯 #LeetCode #100DaysOfCode #ProblemSolving #DSA #AlgorithmDesign #ProgrammingChallenge #CodeJourney #LogicBuilding #Efficiency #DeveloperGrowth #CodingDaily

🚀 Day 18 of my 120 Days of LeetCode Challenge 📘 Problem 18: 4Sum Difficulty: Medium 🧩 Problem Statement: Given an integer array nums of length n, return all unique quadruplets [nums[a], nums[b], nums[c], nums[d]] such that: 0 <= a, b, c, d < n a, b, c, and d are distinct nums[a] + nums[b] + nums[c] + nums[d] == target You may return the answer in any order. Example: Input: nums = [1, 0, -1, 0, -2, 2], target = 0 Output: [[-2, -1, 1, 2], [-2, 0, 0, 2], [-1, 0, 0, 1]] 💡 Approach Used: To solve this problem efficiently, I used a combination of sorting and the two-pointer technique (an optimized version of the 3Sum approach): Sort the array to handle duplicates and simplify traversal. Fix two numbers using two nested loops. For the remaining two numbers, apply the two-pointer approach (left and right) to find pairs that make up the target sum. Skip duplicates for all four numbers to ensure only unique quadruplets are added to the result. Use long long to avoid integer overflow when numbers are large. This structured and optimized method ensures that all valid quadruplets are found without redundancy. ⏱️ Time Complexity: O(n³) → Sorting takes O(n log n), and the nested loops with two-pointers make it cubic overall. 💾 Space Complexity: O(1) (excluding the result storage) since only pointers and a few variables are used. ✨ Key Takeaway: This problem builds upon the logic of 3Sum and extends it to a higher combination level, helping improve understanding of multi-pointer techniques and nested search optimizations. #LeetCode #Day18 #4Sum #C++ #ProblemSolving #CodingChallenge #100DaysOfCode #DSA #TwoPointer #Sorting #Programming

#digitaltechnology #code #logic #objectorientedprogramming #oop #reallife #ides #assembler #compiler #interpreters #action #calling #systems #stewardship #purpose Code is not just logic... it’s a dynamic fusion of logic, language, and design. While logic forms the backbone, enabling a program to make decisions and follow structured steps, coding also demands fluency in syntax, creativity in problem-solving, and clarity in communication. Developers must not only think algorithmically but also write readable, maintainable code that interacts with users, systems, and other developers. They navigate tools, frameworks, and evolving requirements, often balancing efficiency with elegance. In essence, coding is as much about crafting thoughtful, adaptable solutions as it is about executing logical instructions.

I recently tackled LeetCode 2654 – Minimum Number of Operations to Make All Array Elements Equal to 1. Most solutions simulate every operation. The approach that worked for me came from stepping back and thinking mathematically: 1️⃣ If there’s already a 1 in the array, it can be spread to all other elements efficiently. 2️⃣ If no 1 exists, find the shortest subarray whose GCD is 1 – creating a 1 from that subarray is the minimal first step. 3️⃣ Once a 1 exists, the rest follows in a straightforward way. It’s a reminder that sometimes understanding the structure of a problem beats brute-force coding. And here’s a little validation: ✅ Runtime: 1ms, beats 100% of submissions ✅ Memory: 56.1MB, beats 100% of submissions For anyone doing coding challenges or preparing for interviews, focus on insights like these – they often save more time than writing extra lines of code. #ProblemSolving #Algorithms #CodingMindset #LeetCode #SoftwareEngineering

🧩 Day 64 of #100DaysOfCode 🧩 🔹 Problem: Remove All Adjacent Duplicates in String – LeetCode ✨ Approach: Used a stack-based approach to efficiently remove adjacent duplicates. For each character, if it matches the stack’s top element, pop it — otherwise, push it. A simple yet powerful way to process strings in O(n) time while maintaining clean logic. ⚡ 📊 Complexity Analysis: Time Complexity: O(n) — each character is processed once Space Complexity: O(n) — for the stack and output string ✅ Runtime: 23 ms (Beats 54.52%) ✅ Memory: 45.26 MB (Beats 85.43%) 🔑 Key Insight: Sometimes, solving problems isn’t about brute force — it’s about using the right data structure to make every step count. 💡 #LeetCode #100DaysOfCode #ProblemSolving #DSA #Stack #StringManipulation #CleanCode #CodingChallenge #AlgorithmDesign #LogicBuilding #CodeJourney #Programming

🎯 Day 83 of #100DaysOfCode 🔹 Problem: Count the Digits That Divide a Number – LeetCode ✨ Approach: A simple yet elegant digit-based problem! I extracted each digit of the number using modulo and division, then checked whether the digit cleanly divides the original number. Every valid digit increases the count — a perfect use-case for number breakdown and modular arithmetic. 🔢⚡ 📊 Complexity Analysis: ⏱ Time Complexity: O(d) — where d is the number of digits 💾 Space Complexity: O(1) — no extra data structures used ✅ Runtime: 0 ms (Beats 100% 🚀) ✅ Memory: 42.29 MB 🔑 Key Insight: Even basic problems sharpen precision — breaking numbers digit-by-digit reinforces strong logical thinking and clean coding habits. Sometimes the simplest loops teach the most. ✨ #LeetCode #100DaysOfCode #DSA #NumberTheory #ModularArithmetic #CleanCode #EfficientCoding #LogicBuilding #TechJourney #ProgrammingChallenge #CodingDaily