Optimized Longest Increasing Subsequence in Java with Binary Search

Starting with the most fundamental concept: What is an Algorithm? An algorithm is simply a step-by-step process to solve a problem. From sorting data to solving complex problems, algorithms are the backbone of software development. In this short video, I’ve explained: - What is an algorithm - Real-life analogy - Key characteristics - A simple Java example If you're preparing for coding interviews or starting DSA, this is where you begin. For a structured roadmap, practice questions, and complete DSA in Java learning: https://lnkd.in/gMYTHTWN #DSA #Java #Programming #Coding #SoftwareDevelopment #InterviewPreparation

Have you noticed that the same code can behave differently depending on the input? This is where Best Case, Average Case, and Worst Case Analysis becomes important. In this short video, I explained: - Best case (fastest execution) - Worst case (maximum time) - Average case (typical scenario) - Why worst-case analysis is commonly used Understanding this concept helps you build efficient and reliable algorithms, especially for real-world systems and coding interviews. 👉 Explore structured DSA in Java roadmap + practice: www.quipoin.com #DSA #Java #Programming #Coding #SoftwareEngineering #InterviewPreparation #Algorithms

Day 14 of Java + DSA Journey 🚀 Today’s topic: Bit Manipulation Basics ⚡ At first, bits look scary 😵💫 But once you understand them, it feels like unlocking a developer superpower 🧠⚡ Let’s break it down in the simplest practical way 👇 💡 What is Bit Manipulation? It means working directly with binary bits (0s and 1s) Since computers understand everything in binary, this helps us solve problems faster and smarter. 👉 Example: 5 = 101 3 = 011 Using bit operators: & → AND | → OR ^ → XOR ~ → NOT << → Left Shift >> → Right Shift ⚡ Most Important Bit Tricks 🟢 Check EVEN / ODD n & 1 0 → Even 1 → Odd 🟡 Check if power of 2 n & (n - 1) If result = 0 → power of 2 ✅ 🔵 Remove last set bit n & (n - 1) 🟠 Get last set bit n & (-n) 🔴 Count set bits efficiently n = n & (n - 1) 🔥 Why Bit Manipulation Matters It helps in: ✔ Optimized coding ✔ Competitive programming ✔ DSA interviews ✔ XOR / subset problems ✔ Fast math operations 🧠 Real DSA Uses Find unique number using XOR Generate subsets using bitmasking Check flags / permissions Solve DP + state problems Fast exponentiation ⚡ Shifts = Fast Math n << 1 // multiply by 2 n >> 1 // divide by 2 🎯 Final Thought Bit Manipulation teaches you how computers actually think at the lowest level 💻⚡ Once this clicks, many “hard” DSA problems suddenly become easy 🚀 Small topic, massive interview value 🔥 #BitManipulation #DSA #Java #CodingJourney #Algorithms #ProblemSolving #Programming #SoftwareEngineering #CodingInterview #CompetitiveProgramming #EngineeringStudent #PlacementPreparation #LearnToCode #CodeDaily #TechSkills #FutureEngineer #DeveloperJourney #JavaDeveloper #CodingPractice #ComputerScience

🚀 Day 11 of Java with DSA Journey — This one blew my mind 🤯 📌 Problem: Power of Three (LeetCode 326) Yesterday, I used bit manipulation for Power of Two. Today? 👉 That approach completely fails. So I had to think differently… 💡 Breakthrough Idea Instead of loops or recursion… I used math + number theory to solve it in O(1) time. 👉 1162261467 % n == 0 Yes, one line. 🧠 Key Learnings 🔹 Bitwise isn’t universal Works great for base-2, but not for base-3 🔹 Prime Numbers Matter Since 3 is prime, its powers divide each other perfectly 🔹 Max Value Trick Largest power of 3 in 32-bit int = 3^19 = 1162261467 ⚡ Complexity ⏱ Time: O(1) 📦 Space: O(1) 🔥 Pro Tips (Interview Level) 💡 Tip 1: Know Your Data Type Limits Many O(1) tricks depend on constraints like 32-bit integer limits 💡 Tip 2: Prime Numbers Unlock Shortcuts If a number is prime, its powers have clean divisibility properties 💡 Tip 3: Always Question the Default Approach Most people write: while (n % 3 == 0) n /= 3; 💡 Tip 4: This is a Pattern Power of 2 → bitwise Power of 3 → math Power of 4 → hybrid 💡 Tip 5: Edge Cases First Always check n <= 0 🔥 Real Insight This problem forced me to shift my thinking: ❌ Rely on one technique ✅ Adapt based on the problem Consistency compounds 📈 #DSA #LeetCode #Java #CodingJourney #ProblemSolving #NumberTheory #InterviewPrep #Day11 #BitManipulation #CleanCode #Array #Optimization #MCA #lnct #100DaysOfCode #SoftwareEngineering #Algorithms #InPlaceAlgorithms #TechLearning #JavaDeveloper

Day 7 of Java with DSA Journey 🚀 📌 Topic: Missing Number (LeetCode 268) Quote: "Sometimes the best way to solve a coding problem is to put down the keyboard and pick up a calculator." ✨ What I learned today: 🔹 Mathematical Optimization: Instead of brute force, I used a simple formula to compute the expected sum. {Sum} = \frac{n(n+1)}{2} 🔹 Core Idea: Expected Sum − Actual Sum = Missing Number 🔹 Alternative Approach: Used XOR technique where duplicates cancel out → leaving the missing value. 🔹 Efficiency: ✔️ Time Complexity: O(n) ✔️ Space Complexity: O(1) 🧠 Problem Solved: ✔️ Missing Number 💡 Key Insight: We often jump to HashSet or Sorting, but this problem taught me to pause and think mathematically first. A simple formula reduced space complexity from O(n) → O(1) 🚀 ⚡ Interview Tip (Important!): Be careful of integer overflow in Java: n * (n + 1) can exceed int limit Use long OR switch to XOR method for safety Consistency is the real key 🔑 #DSA #LeetCode #Java #Mathematics #CodingJourney #ProblemSolving #Day7 #Algorithms #Optimization #Array #MCA #lnct #100DaysOfCode #Algorithms #SoftwareEngineering #InPlaceAlgorithms #TechLearning #JavaDeveloper

Day 6 of Java with DSA Journey 🚀 📌 Topic: Max Consecutive Ones (LeetCode 485) 💭 Quote: "Progress is about maintaining momentum—just like a streak of consecutive ones." ✨ What I learned today: 🔹 State Tracking: Learned how to maintain a current streak vs a maximum streak — a key concept for sequence-based problems. 🔹 The Power of Resetting: Understanding when to reset the counter (on encountering 0) is crucial to solving streak problems correctly. 🔹 Simple Yet Powerful Logic: No complex data structures needed — just a clean linear scan with strong logic. 🔹 Performance: ✔️ Time Complexity: O(n) (Single pass) ✔️ Space Complexity: O(1) (Only variables used) 🧠 Problem Solved: ✔️ Max Consecutive Ones 💡 Key Insight: This problem is a foundation for the Sliding Window pattern. Instead of managing two pointers, we track a running window of 1s that resets when a 0 appears. ⚡ Interview Insight – Using Math.max(): Instead of writing: if (current > max) max = current; Using: max = Math.max(max, current); makes the code cleaner and more professional — a small detail that reflects strong coding practices. 📈 Growth Reflection: With each problem, I’m focusing on: 🔹 Explaining logic clearly and step-by-step (important for interviews) 🔹 Thinking in patterns (like Sliding Window & State Tracking) 🔹 Writing clean and optimized code like a software engineer Consistency is the real key 🔑 #DSA #LeetCode #Java #CodingJourney #SlidingWindow #ProblemSolving #Day6 #SoftwareEngineer #Algorithms #Array #MCA #lnct #100DaysOfCode #Algorithms #SoftwareEngineering #InPlaceAlgorithms #TechLearning #JavaDeveloper

🚀 Operators in Java — and this is where coding actually starts feeling real 👇 Instead of just theory, I tried solving small problems using operators. 💡 Example 1: Even or Odd int num = 7; System.out.println(num % 2 == 0 ? "Even" : "Odd"); 💡 Example 2: Find largest number int a = 10, b = 5; int max = (a > b) ? a : b; System.out.println("Max: " + max); 💡 Example 3: Using increment int count = 1; count++; System.out.println(count); // 2 👉 What I learned today: Arithmetic → for calculations Relational → for comparisons Logical → for combining conditions Unary → for quick updates (++/--) Ternary → for writing clean if-else Understanding operators made me realize how logic is built step by step in programming. #Java #CodingJourney #LearnJava #FullStackDeveloper

Optimizing problems is what separates good developers from great ones. In this short video, I explained the Prefix Sum Technique, which helps answer range sum queries efficiently. - Precompute cumulative sums in O(n) - Answer queries in O(1) - Widely used in subarray and matrix problems This simple idea can drastically improve performance in real-world scenarios. Explore structured DSA in Java roadmap + practice: www.quipoin.com #DSA #Java #Programming #Coding #Algorithms #SoftwareEngineering #InterviewPreparation

💻 Practicing Binary to Decimal Conversion using Java Today I worked on converting a binary number into its decimal equivalent using logic and iteration. 🔍 Key Learnings: Understanding how binary digits map to powers of 2 Strengthening loop and mathematical logic Improving problem-solving skills step by step Instead of just memorizing, I focused on understanding the logic deeply and practicing with different inputs. 📌 Example: Binary: 1010 → Decimal: 10 Consistency + Practice = Progress 🚀 #Java #DSA #CodingJourney #Programming #100DaysOfCode #LearnToCode #ProblemSolving #DeveloperJourney #CodingPractice #TechSkills

🚀 Day 7/100 – DSA Journey Today’s focus was on implementing a classic and important problem in number theory — Armstrong Numbers — using Java. 🔍 What I built: A program to find all Armstrong numbers within a given range (100 to 2000). 💡 Approach Breakdown: Iterated through each number in the range Counted the number of digits Extracted each digit and computed its power using Math.pow() Summed the results and compared with the original number Printed the number if it satisfies the Armstrong condition ⚙️ Key Concepts Used: Loops (while, for) Mathematical logic (digit extraction, power calculation) Function design for reusability Clean iteration over a range 📌 Output Observed: 153, 370, 371, 407, 1634 📈 Learning Insight: This problem strengthened my understanding of number manipulation and algorithmic thinking, which are fundamental in DSA and frequently asked in interviews. 🔥 Consistency is the key — building problem-solving skills step by step! #Day7 #100DaysOfCode #DSA #Java #ProblemSolving #CodingJourney #SoftwareDevelopment #LearnInPublic 🙌 Tagging: 10000 Coders Pathulothu Navinder