Mastering Java with LeetCode: Highest Altitude Problem Solution

🚀 Mastering Java Through LeetCode 🧠 Day 22 of My DSA Journey Today I solved an interesting matrix-based problem that improved my understanding of arrays and comparison logic. 📌 LeetCode Problem Solved Today: 2352 – Equal Row and Column Pairs Problem Statement: Given an n x n matrix, find how many pairs (row, column) are exactly the same. A pair is valid only if both contain the same elements in the same order. 🧠 Key Idea: Compare each row with every column Check element-by-element equality Count all matching pairs 🔍 Example: Input: [[3,2,1], [1,7,6], [2,7,7]] Output: 1 Matching Pair: Row 2 = Column 1 → [2,7,7] ⚙️ Approach: Traverse all rows Build each column dynamically Compare row[i][k] with column[k][j] If all elements match → increment count ⏱️ Time Complexity: O(n³) (Optimized solution using HashMap possible in O(n²)) What I Learned: Matrix traversal techniques Row vs Column comparison logic Importance of nested loops in grid problems 🔥 Consistency is the key! Every day one problem closer to my goal of becoming a Software Engineer #LeetCode #DSA #Java #CodingJourney #100DaysOfCode #SoftwareEngineer #ProblemSolving #Learning #Tech

🚀 Mastering Java Through LeetCode 🧠 Day 33 Not all nodes are “Good”… but finding them made me better at Trees 📌 LeetCode Problem Solved: Q.1448 – Count Good Nodes in Binary Tree 💭 Problem Summary: A node is called “Good” if no node on the path from root to it has a greater value. 🎯 Approach: ✔ Used DFS (Depth First Search) ✔ Tracked the maximum value seen so far in the path ✔ If current node ≥ maxSoFar → count it as a Good Node ✔ Updated max and continued recursion 🧠 Key Insight: Instead of storing the full path, just carry maxSoFar — simple yet powerful optimization! 💡 Complexity: ⏱ Time: O(N) 📦 Space: O(H) 🔥 What I Learned: How to maintain state during recursion Clean way to solve tree problems using DFS Thinking in terms of path-based conditions Consistency builds confidence 💪 Day 33 done… Let’s keep going 🚀 #Java #LeetCode #DataStructures #Algorithms #CodingJourney #100DaysOfCode #DSA #Tech #Learning

🚀 Mastering Java Through LeetCode 🧠 Day 32 Today I solved an Easy-level Tree problem that strengthened my understanding of Recursion + Depth Calculation — a fundamental concept for tree-based problems 📌 LeetCode Problem Solved: Q.104. Maximum Depth of Binary Tree 💭 Problem Summary: Given a binary tree, the task is to find the maximum depth — i.e., the number of nodes along the longest path from root to leaf. 🧠 Approach (Optimal): Instead of iterating level by level, I used a clean recursive approach: ✔️ If node is null → return 0 ✔️ Recursively calculate left subtree depth ✔️ Recursively calculate right subtree depth ✔️ Return 1 + max(left, right) ⚡ Key Learning: Recursion makes tree problems much simpler when you think in terms of “what should each function return for a node?” Complexity: Time: O(n) Space: O(h) Takeaway: Tree problems become easier once you master recursion and start recognizing patterns. Consistency is the key — showing up every day #Day32 #LeetCode #Java #DSA #CodingJourney #Recursion #BinaryTree #100DaysOfCode #SoftwareEngineering

🚀 Mastering Java Through LeetCode 🧠 Day 21 of My DSA Journey 📌 Problem Solved: Q.1657 – Determine if Two Strings Are Close 💡 Problem Insight: At first glance, this problem looks like a simple string comparison… But it actually tests your understanding of patterns, hashing, and transformations. We are allowed to: ✔ Swap characters (change order) ✔ Transform characters (swap frequencies) 🧠 Key Learning: Two strings are "close" if: ✅ They have the same set of characters ✅ Their frequency distribution matches (order doesn’t matter) 👉 That means: Order is irrelevant Only character presence + frequency pattern matters 🔍 Approach I Used: 1️⃣ Checked if lengths are equal 2️⃣ Counted frequency using arrays 3️⃣ Verified both strings have same unique characters 4️⃣ Sorted frequency arrays and compared ⚡ Example: word1 = "cabbba" word2 = "abbccc" ✔ Same characters → {a, b, c} ✔ Frequencies match after sorting → [1,2,3] 👉 Result: true Tech Stack: Java Concepts Covered: Hashing | Arrays | Frequency Count Takeaway: This problem taught me how to: Think beyond direct comparison Focus on data patterns instead of structure Consistency + Practice = Growth #LeetCode #DSA #Java #CodingJourney #100DaysOfCode #ProblemSolving #Developers #SoftwareEngineer #Learning #Growth #CDAC #PlacementPreparation #Tech

🚀 DSA in Java – Day 89 ✅ Today, I solved the Minimum Distance to the Target Element problem on LeetCode 💻 🔍 Problem Insight: Given an array, a target element, and a starting index — we need to find the minimum distance between the start index and any occurrence of the target. 🧠 Approach I Used: Traversed the array using a loop Checked where the element equals the target Calculated distance using Math.abs(i - start) Updated the minimum distance using Math.min() ⚡ Key Learning: Sometimes the simplest linear traversal (O(n)) gives the most optimal solution. No need to overcomplicate! 💡 Code Concept: Use a variable to track minimum distance Update it whenever a closer target is found 💬 What I Learned Today: Consistency is more important than complexity. Even simple problems strengthen your fundamentals! 🔥 Day 89 Progress: Strengthened problem-solving skills Improved understanding of distance-based logic Practiced writing clean and optimized Java code 📈 Still learning, still growing… one problem at a time! #LeetCode #DSAinJava #ProblemSolving #Java #CodingJourney #Consistency #SoftwareDeveloper 🚀

🚀 Mastering Java Through LeetCode 🧠 Day 20 of My DSA Journey Today I solved another problem from the LeetCode 75 list to improve my understanding of HashMap and HashSet concepts and strengthen my problem-solving skills. 📌 LeetCode Problem Solved Today: Q.1207 – Unique Number of Occurrences 💡 Problem Statement: Given an integer array arr, return true if the number of occurrences of each value in the array is unique, otherwise return false. 🧩 Example 1: Input: [1,2,2,1,1,3] Output: true 🧩 Example 2: Input: [1,2] Output: false Key Learning: Today I learned how to efficiently solve problems using Hashing techniques: ✔️ Use HashMap to count frequency of each number ✔️ Use HashSet to check if frequencies are unique ✔️ If any frequency repeats → return false 🧠 Approach: 1️⃣ Traverse array and store frequency using getOrDefault() 2️⃣ Traverse map values 3️⃣ Check duplicates using HashSet ⏱️ Complexity: Time Complexity: O(n) Space Complexity: O(n) This problem helped me understand how frequency counting + uniqueness checking works in real interview scenarios. Consistency is the key — solving problems daily to become a better software engineer 💻 #LeetCode #Java #DSA #ProblemSolving #CodingJourney #LearningInPublic #SoftwareDevelopment #Programming #Coding #Tech #Developers #100DaysOfCode #TechCareer #InterviewPreparation #HashMap #HashSet #CodingPractice #PGCP #CDAC #LeetCode75

Day 31 of #50DaysLeetCode Challenge 💻🔥 Today I solved the “Permutations” problem using Java. 🔹 Problem: Given an array of distinct integers, return all possible permutations. 🔹 Reality check: If you don’t understand recursion properly, this problem will expose you. There’s no shortcut here. 🔹 Approach (Backtracking): Fix one element at a time Swap it with every possible choice Recurse for the remaining positions Backtrack (undo the swap) to explore other possibilities 🔹 Key Insight: This isn’t about generating values — it’s about exploring a decision tree. Every level = a position in the array Every branch = a choice 🔹 Time Complexity: O(n!) — and that’s unavoidable 📌 What I learned: Backtracking is not optional for DSA. If you try to avoid it, you’ll get stuck on a whole category of problems. Stop memorizing patterns blindly. Understand why the recursion works. #Day25 #LeetCode #Java #Backtracking #DSA #CodingChallenge #ProblemSolving

🚀 DSA Journey — LeetCode Practice 📌 Problem: Maximum Depth of Binary Tree 💻 Language: Java 🔹 Approach: To solve this problem, I used Breadth-First Search (BFS) with a Queue to perform level-order traversal of the binary tree. • Start by adding the root node to the queue • Traverse the tree level by level • For each level, process all nodes currently in the queue • Add left and right children of each node to the queue • Increment the level count after completing each level 📌 Logic Insight: Each iteration of the outer loop represents one level of the tree, which directly helps in calculating the maximum depth. ⏱ Time Complexity: O(n) 🧩 Space Complexity: O(n) (queue storage in worst case) 💡 Key Learning: This problem helped me understand how level-order traversal (BFS) can be used not just for traversal, but also for solving structural problems like finding tree depth efficiently. It also reinforced the importance of queue-based processing in trees. #DSA #Java #LeetCode #BinaryTree #BFS #Queue #CodingJourney #ProblemSolving #LearningInPublic #TreeTraversal

Day 38 – 44 of my Frontlines EduTech (FLM) AI-Powered Java Full Stack Journey Day 38: Started learning Collections in Java. Focused on ArrayList and how it stores dynamic data. Understood how it is different from arrays. Day 39: Learned about Iterator. Used it to traverse elements in collections. It made looping through data more clean and flexible. Day 40: Explored Set interface. Learned that it stores only unique elements. Good for removing duplicates from data. Day 41: Learned Map in Java. Stores data in key-value pairs. Very useful for real-world applications. Day 42: Covered Enum and Command Line Arguments. Also learned Static and Instance Blocks. Understood when and how they are executed. Day 43: Learned Clone, Comparator, and Comparable. Used for copying objects and sorting data. Important for customizing sorting logic. Day 44: Solved problem on frequency of characters. Used logic with collections to count occurrences. Good practice for improving problem-solving skills. Consistent learning, step by step. Fayaz S 🔗 Github: https://lnkd.in/gV_uis3J #Java #Collections #CodingJourney #100DaysOfCode #LearnJava #FullStack 🚀

🔥 Title Cracked the "Counting Valleys" Problem Using Java 🚀 📄 Description I recently solved the Counting Valleys problem, a popular coding question that tests logic building and problem-solving skills. 🔍 Problem Insight: A valley is a sequence of steps below sea level, starting with a downhill and ending with an uphill. 💡 Approach: Track the altitude level Increase for 'U' and decrease for 'D' Count a valley whenever we return to sea level from below ✨ Key Learning: Understanding how to track state changes (altitude) efficiently can simplify many real-world problems. #Java #DSA #ProblemSolving #Coding #HackerRank