Java Array Concepts: Concatenation, Slicing, and Multidimensional Arrays

Day 82 – Univalued Binary Tree Solved a problem to determine whether all nodes in a binary tree have the same value using depth-first traversal. Key Learnings: Applied DFS recursion to traverse all nodes in the tree Compared each node’s value with the root value for validation #DSA #Java #BinaryTree #DFS #Recursion #ProblemSolving #CodingPractice

🚀 Day 38/50 – #50DaysOfCode Today, I learned about ArrayList operations — concatenation, slicing, converting between arrays and ArrayLists, and the comparison between Array and ArrayList. Understanding these differences helps in choosing the right data structure effectively. ☕💻 #Day38 #JavaFullStack #Java #CCBP #NxtWave #LearningJourney #Consistency

Day 78 - Binary Tree Level Order Traversal Implemented level-by-level traversal of a binary tree using a queue (BFS). Approach: • Use a queue to process nodes • Traverse level by level • Track size of each level • Store values accordingly Time Complexity: O(n) Space Complexity: O(n) #Day78 #LeetCode #BinaryTree #DSA #Java #CodingJourney #ProblemSolving

Day 84 - Binary Tree Right Side View Computed the visible nodes when viewing a binary tree from the right side. Approach: • Use level order traversal (BFS) • Process nodes level by level • Add the last node of each level to the result Key Idea: The rightmost node at each level is the visible one Time Complexity: O(n) Space Complexity: O(n) #Day84 #LeetCode #BinaryTree #BFS #DSA #Java #CodingJourney

🚀 Day 60 of #100DaysOfCode Solved 100. Same Tree on LeetCode 🔗 🧠 Key Insight: Two trees are the same if: 👉 Their structure is identical 👉 Corresponding nodes have equal values ⚙️ Approach (Recursive DFS): 1️⃣ If both nodes are null → ✅ return true 2️⃣ If one is null and other is not → ❌ return false 3️⃣ If values are different → ❌ return false 4️⃣ Recursively check: 🔹 Left subtree → isSame(p.left, q.left) 🔹 Right subtree → isSame(p.right, q.right) 5️⃣ Return: 👉 leftCheck && rightCheck ⏱️ Time Complexity: O(n) 📦 Space Complexity: O(h) (recursive stack) #100DaysOfCode #LeetCode #DSA #BinaryTree #Recursion #DFS #Java #InterviewPrep #CodingJourney

🚀 Day 70 of #100DaysOfCode Solved 107. Binary Tree Level Order Traversal II on LeetCode 🔗 🧠 Key Insight: This is just level order traversal (BFS) but: 👉 Return levels from bottom to top instead of top to bottom ⚙️ Approach (DFS with Level Tracking): 1️⃣ Start traversal with level = 0 2️⃣ For each node: 🔹 If level not present → insert new list at front 🔹 Add value at correct position: 👉 res.get(res.size() - 1 - level) 3️⃣ Recurse: 🔹 Left → level + 1 🔹 Right → level + 1 ⏱️ Time Complexity: O(n) 📦 Space Complexity: O(n) #100DaysOfCode #LeetCode #DSA #BinaryTree #BFS #DFS #Java #InterviewPrep #CodingJourney

Still writing instanceof + casts + nested conditionals? That’s legacy Java. With Java25, pattern matching simplifies type checks, switch logic, and data extraction. Learn how with Mihaela Gheorghe-Roman: https://lnkd.in/d6PuSZdH #CleanCode #PatternMatching #JDK25 OpenJDK #Java #Java25

🚀 Day 40 of #100DaysOfDSA (Java) Today was focused on practicing Graph concepts. I attended a live session with my mentor where I: 🔹 Solved graph-based problems using BFS & DFS 🔹 Practiced traversal and path-related questions 🔹 Improved my understanding of graph problem-solving strategies Key takeaway: Graphs require strong conceptual clarity, and solving problems with guidance helps in building the right approach. Practicing BFS and DFS is helping me understand how to explore nodes efficiently and solve connectivity problems. Day 40 ✅ Focused on practice, consistency, and improving problem-solving skills. #DSA #Java #Graphs #BFS #DFS #ProblemSolving #100DaysOfCode #DeveloperJourney #LearningInPublic #Consistency

Most Java performance issues don’t show up in code reviews They show up in object lifetimes. Two pieces of code can look identical: same logic same complexity same output But behave completely differently in production. Why? Because of how long objects live. Example patterns: creating objects inside tight loops → short-lived → frequent GC holding references longer than needed → objects move to old gen caching “just in case” → memory pressure builds silently Nothing looks wrong in the code. But at runtime: GC frequency increases pause times grow latency becomes unpredictable And the worst part? 👉 It doesn’t fail immediately. 👉 It degrades slowly. This is why some systems: pass load tests work fine initially then become unstable weeks later Takeaway: In Java, performance isn’t just about what you do. It’s about how long your data stays alive while doing it. #Java #JVM #Performance #Backend #SoftwareEngineering

Day 66 — LeetCode Progress (Java) Problem: Find the Difference of Two Arrays Required: Given two integer arrays, return: Elements present in nums1 but not in nums2 Elements present in nums2 but not in nums1 Idea: Use sets to remove duplicates and quickly check membership. Approach: Convert both arrays into sets Iterate over nums1 set: Add elements not present in nums2 set to result1 Iterate over nums2 set: Add elements not present in nums1 set to result2 Return both lists Time Complexity: O(n + m) Space Complexity: O(n + m) #LeetCode #DSA #Java #HashSet #Arrays #ProblemSolving #CodingJourney