Akbarhusain Ambaliyasana’s Post

Solved the Maximum Consecutive Ones problem using a simple linear scan. The approach keeps track of the current streak of ones and updates the maximum whenever the streak increases, resetting the count when a zero appears. This ensures an efficient single-pass solution without extra memory. Time Complexity: O(n) Space Complexity: O(1) Practicing such linear traversal and pattern recognition improves problem-solving ability and helps in writing clean, optimized, and interview-ready code. #Java #DSA #ProblemSolving #Coding #SoftwareEngineering #LeetCode #Developers

Solved the Two Sum problem using a HashMap for an efficient one-pass solution. Instead of checking every pair, the approach stores previously seen numbers and checks in constant time whether the required complement exists. This reduces unnecessary comparisons and ensures an optimized solution. Time Complexity: O(n) Space Complexity: O(n) Understanding hashing and complement-based logic is fundamental for solving array problems efficiently and building strong interview-ready problem-solving skills. #Java #DSA #ProblemSolving #Coding #SoftwareEngineering #LeetCode #Developers

Solved the Sort Colors problem using the three-pointer approach (Dutch National Flag algorithm). The solution sorts an array containing only 0s, 1s, and 2s in a single pass without using any extra space. By maintaining three pointers — low, mid, and high — the algorithm places 0s at the beginning, 1s in the middle, and 2s at the end through controlled swaps. Time Complexity: O(n) Space Complexity: O(1) Understanding pointer-based in-place algorithms is important for mastering array manipulation and writing clean, optimized, interview-ready code. #Java #DSA #ProblemSolving #Coding #SoftwareEngineering #LeetCode #Developers

Solved the Majority Element problem using the Boyer–Moore Voting Algorithm. This approach efficiently finds the element that appears more than n/2 times by maintaining a candidate and a counter. Instead of using extra space like HashMap, the algorithm works by canceling out different elements and keeping track of the potential majority element in a single pass. Time Complexity: O(n) Space Complexity: O(1) Understanding such optimal algorithms strengthens problem-solving skills and helps in writing clean, memory-efficient, and interview-ready code. #Java #DSA #ProblemSolving #Coding #SoftwareEngineering #LeetCode #Developers

🟢Important Methods of Vector Here are commonly used methods in Vector: add(E e) addElement(E e) get(int index) set(int index, E element) remove(int index) size() capacity() firstElement() lastElement() elements() Example: Vector<Integer> nums = new Vector<>(); nums.add(10); nums.add(20); System.out.println(nums.firstElement()); #Java #VectorMethods #JavaCollections #Coding #CoreJava #BackendCoding #DevelopersLife #TechSkills #ProgrammingTips #JavaLearning #SoftwareDev #backenddevelopment #day50ofJavaandSpringboot

🚀 Day 133 of #1000DaysOfCode LeetCode Daily Challenge — Day 57 57 consecutive days. Consistency is no longer effort — it’s routine. Today’s challenge focused on binary simulation and carry propagation — optimizing the number of steps required to reduce a binary string under defined operations. ⚡ Runtime: 0 ms — Beat 100% Key takeaways: • Strengthened understanding of binary arithmetic simulation • Improved carry handling logic during reverse traversal • Practiced writing efficient linear-time solutions • Continued refining clean and minimal Java implementation ✔️ Accepted solution 🔁 57-Day Coding Streak The biggest change after 50+ days? Problems feel structured. Patterns feel familiar. Execution feels faster. Onward to 60 days. 🚀 #LeetCode #Consistency #Algorithms #DataStructures #Java #BitManipulation #ProblemSolving #100Percentile #SoftwareEngineering #CodingJourney

Solved the Subarray Sum Equals K problem using the Prefix Sum and HashMap approach. Instead of checking all possible subarrays, the solution tracks cumulative sums and uses a map to count how many times a required prefix sum has appeared before. By storing frequencies of prefix sums, the algorithm efficiently calculates the number of subarrays whose sum equals the target value in a single pass. Time Complexity: O(n) Space Complexity: O(n) Understanding prefix sums and hashing patterns is essential for solving advanced array problems efficiently and building strong problem-solving foundations. #Java #DSA #ProblemSolving #Coding #SoftwareEngineering #LeetCode #Developers

Day 17/30: Connecting the Dots 🧬 One of the coolest things about Day 17 is realizing that "new" problems aren't actually new—they are just familiar patterns in different clothes. The Day 17 Insight: Coding is less about memorizing solutions and more about building a library of Reusable Patterns. Once you see the structure, the syntax follows naturally. #PatternRecognition #SoftwareEngineering #Java #DSA #ProblemSolving #LeetCodeChallenge #CareerGrowth

#PostLog130 🚀  𝗣𝗿𝗼𝗯𝗹𝗲𝗺 𝗦𝗼𝗹𝘃𝗲𝗱: 𝗠𝗮𝘅𝗶𝗺𝘂𝗺 𝗣𝗿𝗼𝗱𝘂𝗰𝘁 𝗦𝘂𝗯𝗮𝗿𝗿𝗮𝘆 (𝗟𝗲𝗲𝘁𝗖𝗼𝗱𝗲 𝟭𝟱𝟮) Solved Maximum Product Subarray, a classic problem that teaches an important lesson beyond coding: 🔹 Negative numbers can completely change the game. 🔹 Thinking only in one direction isn’t always enough. 🔹 Sometimes the best solution comes from viewing the problem from both ends. 💡 Key takeaway: Instead of relying only on a forward pass, using a left-to-right and right-to-left traversal helps handle negatives and zeros efficiently — resulting in an optimized O(n) solution. #LeetCode #DSA #Algorithms #Java #ProblemSolving #CodingJourney #SoftwareEngineering #LearningInPublic

Most developers learn polymorphism as a definition. But in real systems, it’s what enables flexible architectures, plug-and-play components, and scalable design. In today’s post, I break down Polymorphism in a simple, practical way: • What it really means in software design • Why runtime polymorphism matters most • Real-world examples like payment systems • How it connects to system design patterns If you’re preparing for interviews or trying to move from coding to designing systems, this concept is a must-know. Save this post for revision, and follow the series as we move from OOP fundamentals to system design thinking. #OOP #SoftwareEngineering #SystemDesign #Programming #CleanCode #CodingInterview #DeveloperJourney #TechLearning #BackendDevelopment #DotNet #Java #FullStackDeveloper