Binary Search for Equal Areas of Axis-Aligned Squares

Solved the Ugly Number problem using a simple and efficient approach 💡 🔹 Approach: An ugly number is a number whose prime factors are only 2, 3, and 5. So instead of checking all factors, I used a reduction method: If the number is ≤ 0 → not ugly. Keep dividing the number by 2, 3, and 5 as long as it is divisible. If after removing all these factors the number becomes 1, then it is an ugly number. If something else remains, it means another prime factor exists → not ugly. This approach works because ugly numbers are made only by multiplying 2, 3, and 5. Removing these factors should eventually reduce the number to 1. 🔹 Why this approach? Avoids factorization of all numbers. Directly removes allowed prime factors. Simple, clean, and optimal logic. 🔹 Time Complexity: O(log n) Each division reduces the number significantly. 🔹 Space Complexity: O(1) No extra space used, only variable updates. #Java #Coding #ProblemSolving #DSA #LeetCode #Programming #LogicBuilding #DataStructures #Algorithms #JavaDeveloper #CodingJourney #LearnToCode #TechSkills #ComputerScience #CodeDaily #DeveloperLife #PlacementPreparation #CodingPractice #SoftwareEngineering

Day 472 of my #500DaysOfCode challenge 🚀 ✅ LeetCode 3453: Separate Squares I (Medium) 📌 Problem Summary: We are given multiple squares on a 2D plane, each defined by bottom-left coordinate (x, y) and side length (l). The task is to find the minimum y-coordinate of a horizontal line such that: ✅ Total area above the line = Total area below the line ⚠️ Important note: Squares may overlap, and overlapping area should be counted multiple times (each square contributes independently). 💡 Key Insight: For any horizontal line y = mid, each square contributes to the area below based on how much of its height lies below the line: If the line is below the square → contributes 0 If the line is above the square → contributes full area l² If the line cuts the square → contributes l * (mid - y) Since the area below increases monotonically as the line moves upward, we can apply: ✅ Binary Search on the y-coordinate 🎯 Goal: Find smallest y where areaBelow(y) ≥ totalArea / 2. ⚡ Complexity: ✅ Time: O(n log range) (binary search iterations × n squares) ✅ Space: O(1) This was a great problem to reinforce how binary search can be used beyond arrays, especially when the function is monotonic 📈. #leetcode #dsa #java #binarysearch #programming #problemsolving #500daysofcode #consistency #learning

📌 Understanding the Core Components of C++ STL This diagram clearly shows how the Standard Template Library (STL) is built on three powerful pillars: 🔹 Containers – Store and organize data efficiently Examples: vector, list, map, stack, queue 🔹 Algorithms – Perform operations on data Sorting, searching, and manipulating data with optimized logic 🔹 Iterators – Bridge between containers and algorithms They help in navigating and traversing data smoothly 💡 When these three components work together, STL allows us to write cleaner, faster, and more efficient C++ code. #Cplusplus #STL #DSA #DataStructures #Programming #CodingLife #DeveloperJourney #ComputerScience #LearningInPublic #StudentsOfLinkedIn

Continued with Arrays today and worked on reversing an array in place. This problem made it clear that arrays aren’t just about reading values — they’re about modifying data carefully. int[] arr = {4, 7, 1, 9, 3}; int left = 0; int right = arr.length - 1; while (left < right) {   int temp = arr[left];   arr[left] = arr[right];   arr[right] = temp;   left++;   right--; } for (int x : arr) {   System.out.print(x + " "); // Output : 3 9 1 7 4 } What this problem highlighted for me: - two-pointer logic is very common with arrays - in-place operations need careful index handling - swapping looks simple but is easy to mess up - many problems build on this same pattern This felt like an important foundation before moving into rotations. Continuing with Arrays & ArrayLists today. #Java #DSA #Arrays #LearningInPublic #ProblemSolving #Coding #Programming #DeveloperJourney #JavaDeveloper

When we drive, we don’t care about the engine and wires. We only use steering, brake, and accelerator. -Same in programming: Abstraction hides complex details and shows only what we need. That makes code simple, clean, and easy to maintain.  With Abstraction: ✔ Easy to use ✔ Clean and readable code ✔ Faster development ✔ Less bugs ✔ Easy maintenance ❌ Without Abstraction: ⚠ Code becomes messy ⚠ Hard to understand ⚠ Hard to fix and update ⚠ More chances of errors 📌 Lesson: Always hide complexity from users and expose only what they need. That’s how real-world software becomes scalable and maintainable. #Abstraction #OOP #Java #Programming #Coding #SoftwareDevelopment

Just published a clear, beginner-friendly breakdown on Medium: Concurrency vs Parallelism vs Multithreading vs Multiprocessing – explained in plain English (no metaphors, no fluff). This article covers: - What each term actually means - The key differences (goals vs tools) - When to use which one - A simple comparison table If you've ever wondered why threads don't always speed up your Python code or when to reach for multiprocessing instead, this one's for you. Read it here: https://lnkd.in/gvMjEZ3s #Programming #Python #Concurrency #Parallelism #Multithreading #Multiprocessing #SoftwareEngineering

Array Balance with a Two-Pointer Approach in TypeScript 👉 Day 84 / Day 93👈 33 🔥 - Sort the array - Use two pointer check either balenced or not - nums[j] > nums[i] * k - if this true skip one level - maxLen = Math.max(maxLen, (j - i + 1)) check this maxLen; - Return arrLength - maxLen Input: nums = [2,1,5], k = 2 Output: 1 #TypeScript #CodingChallenge #Algorithms #DataStructures #ProblemSolving #LeetCode #Programming #Tech

✅ Day 37 of 100 Days LeetCode Challenge Problem: 🔹 #322 – Coin Change 🔗 https://lnkd.in/gtfVrvhV Learning Journey: 🔹 Today’s problem focused on finding the minimum number of coins needed to make up a given amount. 🔹 I used Dynamic Programming with a bottom-up approach, building solutions for smaller amounts first. 🔹 A DP array tracks the minimum coins required for each value from 0 up to the target amount. 🔹 For every amount, I iterated through all coin denominations to compute the optimal solution. Concepts Used: 🔹 Dynamic Programming 🔹 Bottom-Up DP 🔹 Optimization Problems 🔹 State Transition Key Insight: 🔹 Breaking problems into smaller subproblems makes optimization manageable. 🔹 Initializing with infinity helps represent unreachable states clearly. 🔹 Iterative DP ensures efficient computation and avoids repeated work. #LeetCode #DataStructures #Algorithms #CodingInterview #SoftwareEngineering #SoftwareDeveloper #ProblemSolving #Programming #ComputerScience #TechCareers #100DaysOfCode #DailyCoding #Consistency #LearningInPublic #Python #BackendDevelopment #InterviewPreparation #TechCommunity

Continued with Arrays today and worked on finding the maximum element in an array. This problem looks basic, but it quietly teaches how careful you need to be with initialization and comparisons. int[] arr = {4, 7, 1, 9, 3}; int max = arr[0]; for (int i = 1; i < arr.length; i++) {   if (arr[i] > max) {     max = arr[i];   } } System.out.println(max); // Output : 9 What this problem highlighted for me: - arrays need a sensible starting reference - comparisons depend on correct initialization - one wrong starting value can break the logic - this pattern shows up in many other problems Simple logic, but it sets the base for more complex array questions. Continuing with Arrays & ArrayLists today. #Java #DSA #Arrays #LearningInPublic #ProblemSolving #Coding #Programming #DeveloperJourney #JavaDeveloper

📐 Jagged Arrays. A jagged array means: ✅ Different rows can have different number of columns ✅ int[][] arr = new int[rows][]; → only rows fixed ✅ each row can have different columns ✅ arr[i].length will be different for different rows GitHub Link: https://lnkd.in/g6JtkYCA 🔖Frontlines EduTech (FLM) #Java #Arrays #DeepCopy #ShallowCopy #2DArray #JavaProgramming #Coding #DSA #ProgrammingBasics #LearnJava #CodeSnippet