"Day 5 of #100DaysOfCode: Finding Missing Number in Array"

🚀 Day 8 of #75DaysofDSAChallenge Today’s learning session covered two classic and highly important LeetCode problems that sharpen both algorithmic thinking and mathematical intuition. 📌 1. Best Time to Buy and Sell Stock This problem teaches the art of identifying the maximum profit with a single buy–sell transaction. Key takeaways: Track the minimum price seen so far Continuously compute profit with the current price Maintain the maximum profit Efficient one-pass solution: O(n) This problem strengthens the ability to optimize solutions with strategic tracking. 📌 2. Pow(x, n) – Fast Exponentiation A foundational math + algorithm problem. Key learnings: Using Binary Exponentiation brings down complexity from O(n) → O(log n) Handles negative powers, large exponents, and precision issues Beautiful use of divide-and-conquer Fast exponentiation is used everywhere — competitive coding, cryptography, modular arithmetic, and real-world systems. 🔥 Wrapping Up Day 8 gave a strong boost in both optimization and mathematical problem-solving skills. Onwards to stronger logic and consistent progress! 💪✨ #75DaysChallenge #LeetCode #DSA #ProgrammingJourney #problemSolving #CodingLife

Day 5 of #30DaysOfCode Solving "Loud and Rich" - A Graph Theory Challenge Just tackled an interesting problem that combines graph traversal with dynamic programming! The Problem: Given people with different wealth levels and quietness scores, find the quietest person among those who are equally or more wealthy than each individual. Key Insights: ✓ Model wealth relationships as a directed graph ✓ Use DFS/BFS with memoization to traverse richer individuals ✓ Track the quietest person at each level The Approach: 1. Build an adjacency list where edges point from richer to poorer individuals 2. For each person, traverse all people who are richer (or equal) 3. Use memoization to avoid redundant calculations 4. Return the person with minimum quiet value in each subtree Time Complexity: O(n + e) where e is the number of wealth relationships Space Complexity: O(n) for the memoization cache This problem beautifully demonstrates how graph algorithms can model real-world hierarchical relationships! What's your favorite approach to solving graph traversal problems with optimization constraints? #DSA #GraphTheory #ProblemSolving #SoftwareEngineering #Algorithms #TechChallenges #30DaysOfCode #educative Educative

🚀 Day 67 | Math & Dynamic Programming Insights Today’s challenge was all about maximizing product through intelligent partitioning — a perfect mix of mathematical intuition and dynamic programming. 🧩 Problem Solved: 343. Integer Break • Approach: Used dynamic programming to compute the maximum product by breaking n into smaller integers, or derived the math-based insight that splitting into 3s gives the optimal product. • Insight: Not every optimization needs brute force — sometimes, number patterns reveal the most efficient path. ✨ Key Takeaway: Mathematics and programming go hand in hand — understanding the underlying formula often leads to cleaner and faster solutions. 📚 Topics: Math · Dynamic Programming · Optimization 💻 Platform: LeetCode #DSA #LeetCode #ProblemSolving #DailyCoding #DynamicProgramming #Math #Consistency

🌟 Day 10 of #100DaysOfCoding Today’s challenge was the “Missing Number” problem — a neat exercise in mathematical reasoning and array manipulation. The task: Given an array containing n distinct numbers taken from 0 to n, find the one number that’s missing. Instead of using extra space or sorting, I applied a simple mathematical approach — leveraging the formula for the sum of the first n natural numbers. By comparing the expected sum to the actual sum of elements, the missing number reveals itself instantly! 💡 Key takeaway: Sometimes, the most elegant solutions come from combining math with programming logic. #100DaysOfCode #Day10 #CodingChallenge #ProblemSolving #Algorithms #DataStructures #LearnInPublic #CPP #KeepCoding #CodeNewbie

🗓 Day 9 / 100 – #100DaysOfLeetCode 📌 Problem 2654: Minimum Number of Operations to Make All Array Elements Equal to 1 The goal was to determine the minimum number of operations required to make every element in the array equal to 1, where in one operation, you can replace any element with the GCD of two chosen elements. 🧠 My Approach: Checked if there was already a 1 in the array — since each existing 1 helps reduce operations directly. If not, iterated through the array to find a subarray whose GCD = 1. Once found, calculated how many steps are required to propagate this 1 throughout the entire array. Applied GCD (Greatest Common Divisor) properties to minimize redundant operations. ⏱ Time Complexity: O(n²) 💾 Space Complexity: O(1) 💡 Key Learning: This problem beautifully connects number theory with array transformations. Understanding how the GCD operation interacts across array elements can dramatically reduce the number of steps — turning a brute-force idea into an efficient solution. Every problem solved is one more step toward thinking more analytically and coding more efficiently 🚀 #100DaysOfLeetCode #LeetCodeChallenge #Python #ProblemSolving #MathInCoding #GCD #NumberTheory #Algorithms #DataStructures #DSA #CodingJourney #CompetitiveProgramming #SoftwareEngineering #LearningInPublic #CodeEveryday #DeveloperJourney #TechStudent #LogicBuilding #CodingCommunity #CareerGrowth #Optimization #KeepLearning

🚀 Day 34 – TUF A to Z DSA Journey Today’s focus was on a fundamental Recursion problem — ✨ Print All Subsequences (Power Set) This problem beautifully demonstrates how recursion explores all possible combinations of choices — either include an element or skip it. Understanding this pattern is key to solving many backtracking problems ahead. 🔁 📊 Current Progress: 127 / 455 questions solved Every line of recursive code teaches one thing — the power of breaking big problems into smaller, logical steps. 💪 #DSA #Coding #Recursion #ProblemSolving #StriversSheet #TUF #100DaysOfCode #Consistency #LogicBuilding #Backtracking #LeetCode #LeecoAI #CodeEveryday #Motivation

⚙️ Day 72 of #100DaysOfCode ⚙️ 💡 Problem: GCD of Odd and Even Sums – LeetCode ✨ Approach: Calculated the sum of the first n odd and even numbers separately, then determined their GCD through iterative checking. A neat blend of arithmetic patterns and number theory logic! 🔢 📊 Complexity Analysis: Time Complexity: O(n)** — summing and iterating up to the limit Space Complexity: O(1)** — constant auxiliary space ✅ Runtime: 575 ms ✅ Memory: 42.79 MB 🔑 Key Insight: Even the simplest mathematical patterns can reveal deep logic — coding is where math meets creativity! ✨ #LeetCode #100DaysOfCode #ProblemSolving #DSA #NumberTheory #LogicBuilding #AlgorithmDesign #ProgrammingChallenge #Efficiency #CodeJourney #DeveloperGrowth #CodingDaily

🚀 LeetCode POTD — 1513. Number of Substrings With Only 1s 🎯 Difficulty: Medium | Topics: Counting, Math, Sliding Window 🔗 Solution Link: https://lnkd.in/gw_b_eXH Today’s #LeetCode Problem of the Day was a straightforward counting problem — all about finding how many substrings contain only '1' in a binary string. My approach was simple yet efficient: Traverse the string and count consecutive sequences of 1s. For any streak of length n, the number of valid substrings is: n⋅(n+1)2\frac{n \cdot (n + 1)}{2}2n⋅(n+1) After collecting a streak, jump the index forward by count - 1 (since all those characters are already processed). This keeps the solution clean and avoids unnecessary nested checks. 📈 Complexity: Time: O(n) Space: O(1) 💡 Takeaway: Problems like this remind us how far simple math can take you — a clean formula can replace dozens of lines of brute-force logic. #LeetCode #ProblemOfTheDay #Math #StringProcessing #Counting #DSA #CodingChallenge #SoftwareEngineering #CodingJourney #100DaysOfCode #LearningInPublic #TechCommunity

Day 5/75 – #75DaysofDSAChallenge Today’s learning revolved around one of the most fundamental yet powerful problems — Maximum Subarray Sum using Brute Force Approach and Kadane’s Algorithm. It’s fascinating how different approaches can transform the same problem’s efficiency! 📚 Topics Covered: Maximum Subarray Sum Brute Force Approach (O(n²)) Kadane’s Algorithm (O(n)) ✅ Solved LeetCode #53 – Maximum Subarray, which reinforced how dynamic programming simplifies complex logic into elegant solutions. Consistency and curiosity are the real keys to mastering problem-solving. 🔥 #75DaysOfDSA #Day5 #CodingChallenge #ProblemSolving #LeetCode #KadaneAlgorithm #SoftwareEngineering #LearningJourney

🎯 #Day10 of #30DaysOfDSA Challenge 🚀 Today I explored how to Evaluate a Postfix Expression using Stack in C 💻 Stack plays a key role in solving expression problems using the LIFO (Last In, First Out) principle 🧠 🧩 Concept Recap: 👉 In Postfix (Reverse Polish Notation), operators come after operands. 👉 Stack helps store operands and perform operations efficiently. 💡 Example: Expression: 231*+9- Steps: 3 × 1 = 3 2 + 3 = 5 5 − 9 = −4 ✅ ⚙️ Language: C Programming 📚 Topic: Stack Implementation 🚀 Concept Used: Expression Evaluation Code 🖇️ : https://lnkd.in/eJQigf7m 💬 Every day, I’m learning something new and getting closer to mastering Data Structures & Algorithms 💪 #Day10 #30DaysOfDSA #CProgramming #DSA #Stack #PostfixExpression #ReversePolishNotation #CodingChallenge #LearnToCode #ProgrammersLife #CodeNewbie #StudentDeveloper #EngineeringStudent #TechLearner #CodingCommunity #100DaysOfCode #ProgrammersOfIndia #TechEnthusiast #CodeEveryday #DSAwithC #ProgrammersJourney #ProblemSolving #ComputerScience #DataStructures #Algorithm #CDeveloper #TechSkills #LearnCoding #FutureEngineer #SoftwareDeveloper #CodeLife 👨💻🔥