Solved Maximum Subarray problem with Kadane's Algorithm in C++

🚀 LeetCode Daily Challenge – Day 4 (November 2025) 🧩 Problem: 3318. Find X-Sum of All K-Long Subarrays I 📚 Topic: Arrays | Sliding Window | HashMap | Prefix Sum 🔍 Approach: Used a sliding window of size k to compute the X-sum for each subarray. Maintained frequency counts of elements within the window and dynamically updated the sum as elements entered and left the window. This approach efficiently avoids recalculating sums from scratch for every subarray. ✅ Time Complexity: O(n) ✅ Space Complexity: O(k) 💡 Key Takeaway: Sliding window problems reinforce how optimizing repetitive computations can drastically improve performance — small logic, big impact! ⚡ #LeetCode #LeetcodeDailyChallenge #Coding #DSA #SlidingWindow #Array #HashMap #Day4 #Programming #Engineering

In this program, I used a while loop to print numbers from 1 to 5 and calculate their total sum at the same time. 🔁 It’s a great example of how loops can perform multiple tasks — displaying numbers and performing calculations in one go! 🚀 ✨ Concepts Used: ➡️ Variable initialization (c = 1, sum = 0) ➡️ While loop condition (c <= 5) ➡️ Increment operators (c = c + 1, sum = sum + 1) ➡️ Output using printf() This simple logic builds the foundation for more complex algorithms in programming! 💪 #CProgramming #WhileLoop #CodingPractice #LearnToCode #ProgrammingBasics #CodeJourney #ProblemSolving 💻

💥THE ULTIMATE BRAINF#CK💥 Did you know there are Turing-complete programming languages with just 2 instructions? SUBLEQ (Subtract and Branch if Less than or Equal to Zero) ▫️SUBLEQ a, b, c → mem[b] = mem[a] - mem[b]; JUMP IF mem[b] ≤ 0 ▫️SUBLEQ a, -1 → HALT With one array of integers, you can simulate any computation (even DOOM). INC + JEZ (Increment & Jump if Zero) ▫️INC r → r = r + 1 ▫️JEZ r, target → if r == 0, jump to target With just 2 registers and unbounded values, these are Minsky machines.

Question1: Used top-down dynamic programming with memoization to minimize recalculations for overlapping subproblems. For each segment, maintained the running maximum and total sum to compute wasted space efficiently. Explored all possible partition points recursively to find the minimum total wasted space with at most k resizings. Question2: Sorted the prices to make it easier to apply a greedy check for minimum tastiness gaps. Used binary search on the tastiness value to find the maximum possible minimum difference between chosen candies. Implemented a greedy okay function to verify if a given tastiness can be achieved by selecting k candies. Question3: Sorted events by start time to process them in chronological order. Used a min-heap to track the best value from non-overlapping previous events. Combined the best previous event value with the current event to maximize the total value. #sde #softwaredevelopment

🚀 Algorithm Challenge #15 🧠 Problem Title: Calculate the area of a rectangle based on user input for its length and width. ✅ Language Used: C++ 💡 What it covers: Working with user inputs Performing arithmetic operations (multiplication) Using variables and basic math formulas Understanding how to apply logic from geometry in programming 📂 GitHub Repo: 🔗 https://lnkd.in/dGe3ZbxK 📝 Short Description: In this challenge, I wrote a simple C++ program that asks the user to enter the length and width of a rectangle, then calculates and displays the area. It’s one of the foundational examples that combines mathematical formulas with programming logic — a great step toward building more practical problem-solving skills. 💬 Feedback Welcome! I’d love to hear your thoughts or suggestions for expanding this example — maybe by adding perimeter calculation or input validation next time 👀 🔁 Stay tuned for Challenge #16 coming soon! #Cpp #Programming #CodingChallenge #Algorithms #ProblemSolving  #MathInProgramming #Geometry #LearnToCode #CodeNewbie #SoftwareDevelopment #BuildInPublic #CppProgramming #TechLearning #LogicalThinking  #100DaysOfCode #LinkedInLearning

#NationSkill Day 99| Problem Solving Challenge Today’s task: Get Minimum Squares Platform: #GeeksforGeeks | Concepts Used: Dynamic Programming (DP) Problem: Find the minimum number of perfect squares that sum up to a given integer n. Approach: Bottom-Up DP — calculating the minimum count for each value up to n by checking all perfect squares less than it. Example: Input: 6 → Output: 3 Explanation → 1*1 + 1*1 + 2*2 = 6 Time Complexity: O(n * √n)

Even if a problem can be solved using dynamic programming, it's not always the best solution possible, and sometimes a simple DFS/BFS approach might produce a better solution with less code. Thus, it's essential to understand how to calculate the complexity of graph traversal algorithms, even for non-standard graphs. The post: https://lnkd.in/dATG59j3 The problem: https://lnkd.in/d5TahY47 #LeetCode #DSATips #DSA #ThinkDSA #ProblemSolving

#Day_110/160 – GFG Problem Solving Challenge Problem: Longest String Chain Topic: Dynamic Programming + Sorting Today I worked on a problem where we need to determine the longest possible chain of words such that each word can be formed by adding exactly one character to the previous word without disturbing the character order. Key Idea: Sort the words based on length. For each word, generate all possible predecessor words by removing one character. Use a hash map to store the longest chain ending at each word. Update the maximum chain length dynamically. Takeaway: This problem reinforced how dynamic programming can be applied effectively on strings. Instead of comparing every pair of words, generating possible predecessors provides a much more efficient solution and fits well within constraints. On to Day 111. #GFG #ProblemSolving #CodingChallenge #DynamicProgramming #C++