🚀 50 Days of Java – Day 49 🚀 Continuing my #50DaysOfJava journey by solving another interesting Graph problem using DFS 💻📊 📘 What I covered today: • Wrote a Java program to print all paths from source to target in a graph • Used Depth First Search (DFS) to explore different paths • Represented the graph using an Adjacency List • Learned how DFS can help in exploring multiple possible paths between nodes This problem helped me understand how graph traversal can be used to explore and track different routes in a network. Sharing my daily learning and code on GitHub to stay consistent 🚀 🔗 GitHub repo: (https://lnkd.in/ezZkPqxt) Almost at the final day of the challenge 💪 #Java #50DaysOfJava #Day49 #Graphs #DFS #DataStructures #DSA #LearningInPublic #CodingJourney #bca #student #invertis_university
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🚀 Day 92 – #100DaysOfCode Qn. Combination Sum III Today I worked on the Combination Sum III problem using recursion and backtracking in Java. 🔹 Problem Summary: Find all possible combinations of k numbers that add up to n, using numbers 1–9 only once. 🔹 My Approach: Used recursion to explore all possible number combinations. Maintained a running sum and a temporary list. When the sum equals n and the list size equals k, the combination is added to the result. Used a HashSet to avoid duplicate combinations. 🔹 Key Learning: This problem helped me strengthen my understanding of: Backtracking Recursive decision trees Managing state during recursion (adding/removing elements) 📌 Next Goal: Optimize the solution further by avoiding the HashSet and pruning unnecessary recursive calls. #Day92 #LeetCode #DSA #Java #Recursion #Backtracking #CodingJourney
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Day 46 of #100DaysOfLeetCode 💻✅ Solved #374. Guess Number Higher or Lower problem in Java. Approach: • Used Binary Search to efficiently guess the number. • Calculated mid using low + (high - low) / 2 to avoid overflow. • Used the guess(mid) API to check if the number is higher, lower, or correct. • Updated the search range accordingly until the number was found. Performance: ✓ Runtime: 0 ms (Beats 100% submissions) 🚀 ✓ Memory: 41.68 MB (Beats 97.84% submissions) Key Learning: ✓ Practiced implementing binary search on a real problem ✓ Learned how to safely calculate mid to prevent integer overflow ✓ Strengthened problem-solving skills with search algorithms Learning one problem every single day 🚀 #Java #LeetCode #DSA #BinarySearch #ProblemSolving #CodingJourney #100DaysOfCode
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Day 66 of #100DaysOfLeetCode 💻✅ Solved #3427. Sum of Variable Length Subarrays problem in Java. Approach: • Iterated through each index of the array • Determined the starting index using i - nums[i] • Ensured the start index does not go below 0 • Calculated sum of elements from start to current index i • Added each subarray sum to the total Performance: ✓ Runtime: 1 ms (Beats 99.90% submissions) ✓ Memory: 45.22 MB (Beats 56.30% submissions) Key Learning: ✓ Practiced handling variable-length subarrays ✓ Improved understanding of index-based range calculations ✓ Strengthened nested loop logic for array problems Learning one problem every single day 🚀 #Java #LeetCode #DSA #Arrays #PrefixSum #ProblemSolving #CodingJourney #100DaysOfCode
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Day 47 of #100DaysOfLeetCode 💻✅ Solved #101. Symmetric Tree problem in Java. Approach: • Used recursion to compare the left and right subtrees of the root • If both nodes are null, the tree is symmetric at that level • If one node is null and the other is not, the tree is not symmetric • Compared the values of both nodes • Recursively checked left.left with right.right and left.right with right.left to verify mirror structure Performance: ✓ Runtime: 0 ms (Beats 100% submissions) ✓ Memory: 43.62 MB (Beats 48.60% submissions) Key Learning: ✓ Practiced mirror comparison in binary trees ✓ Learned how recursion can verify symmetry between two subtrees ✓ Strengthened understanding of tree traversal and structural comparison Learning one problem every single day 🚀 #Java #LeetCode #DSA #BinaryTrees #ProblemSolving #CodingJourney #100DaysOfCode
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Day 64 of #100DaysOfLeetCode 💻✅ Solved #724. Find Pivot Index problem in Java. Approach: • Calculated the total sum of the array • Maintained a variable left to track left sum • For each index, computed right sum as total - left - nums[i] • Compared left and right sums • If both are equal, returned the index as pivot • Updated left sum by adding current element Performance: ✓ Runtime: 1 ms (Beats 98.68% submissions) 🚀 ✓ Memory: 47.58 MB (Beats 32.00% submissions) Key Learning: ✓ Learned prefix sum technique for efficient calculations ✓ Practiced reducing time complexity from O(n²) to O(n) ✓ Strengthened understanding of array traversal and sum logic Learning one problem every single day 🚀 #Java #LeetCode #DSA #Arrays #PrefixSum #ProblemSolving #CodingJourney #100DaysOfCode
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🚀 Day 5 of My DSA Journey (Java) Today’s problem: Subarray Sums Divisible by K 📌 Problem Summary: Given an integer array and a value k, find the number of subarrays whose sum is divisible by k. 💡 Key Learning: The brute-force approach would be too slow, so I explored an optimized solution using: Prefix Sum HashMap for storing remainder frequencies 🔍 Core Insight: If two prefix sums have the same remainder when divided by k, the subarray between them is divisible by k. ⚙️ Approach: Maintain a running sum Compute remainder: (sum % k + k) % k (to handle negatives) Use a HashMap to count frequencies of remainders Add to count when remainder repeats 🧠 What I Improved Today: Better understanding of prefix sum patterns Handling negative modulo cases Writing clean and efficient Java code ✅ Time Complexity: O(n) ✅ Space Complexity: O(k) 📷 I’ve attached my handwritten notes + implementation for better clarity Consistency is key 🔁 — learning something new every day! #DSA #Java #CodingJourney #LeetCode #ProblemSolving #100DaysOfCode
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Day 63 of #100DaysOfLeetCode 💻✅ Solved #2085. Count Common Words With One Occurrence problem in Java. Approach: • Iterated through each word in the first array • Avoided duplicate checks by ensuring each word is processed only once • Counted occurrences of the current word in both arrays • If the word appears exactly once in both arrays, incremented the result • Returned the final count Performance: ✓ Runtime: 88 ms (Beats 7.45% submissions) ✓ Memory: 46.06 MB (Beats 93.07% submissions) Key Learning: ✓ Practiced handling duplicates and frequency counting ✓ Improved understanding of string comparison in arrays ✓ Learned importance of optimizing nested loop solutions Learning one problem every single day 🚀 #Java #LeetCode #DSA #Strings #Arrays #ProblemSolving #CodingJourney #100DaysOfCode
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✨ DSA in Java – Day 83 🚀 Today I solved an interesting problem on Binary Trees: 👉 Sum of Root to Leaf Binary Numbers 🌱 What I Learned: How to traverse a binary tree using DFS (Depth First Search) Building numbers along the path using: ➤ current = current * 2 + node.val Identifying leaf nodes and calculating final values Improving recursion understanding in tree problems 💡 Approach: Start from root with value 0 At each node, update the current number If it's a leaf node → add it to the final sum Traverse left and right recursively 📌 Key Insight: Binary tree problems become easier when you think of them as path-based problems rather than node-based problems. 💻 Consistency is the key! Day by day, step by step, getting stronger in DSA 💪 #DSA #Java #BinaryTree #CodingJourney #LeetCode #100DaysOfCode #WomenInTech #Consistency
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🚀 DSA in Java — Day 79 📌 Problem Solved: Sum Root to Leaf Numbers Today I solved the Sum Root to Leaf Numbers problem on LeetCode using Depth First Search (DFS) and Recursion. In this problem, each root-to-leaf path in a binary tree forms a number. The goal is to calculate the sum of all these numbers. 🔹 Approach Used: Used recursive DFS traversal Maintained a running number while moving from root to leaf At each step, updated the number using current = current * 10 + node.val When a leaf node is reached, added the number to the final sum 🔹 Key Concepts Practiced: ✔ Binary Trees ✔ Depth First Search (DFS) ✔ Recursion ✔ Tree Path Problems This problem improved my understanding of how recursion can be used to build values while traversing tree paths. Consistent practice is helping me become more comfortable with tree-based problems in DSA. #DSA #Java #BinaryTree #Recursion #LeetCode #CodingJourney #WomenInTech #100DaysOfCode
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🚀 Day 23 of my Java DSA Journey Today I worked on Linked List Cycle — LeetCode #141 🔹 Topic: Linked List 🔹 Pattern: Fast & Slow Pointers (Floyd’s Algorithm) 💡 Key Idea: Instead of using extra space like a HashSet, we use two pointers: • Slow pointer moves 1 step • Fast pointer moves 2 steps If a cycle exists, the fast pointer will eventually meet the slow pointer inside the loop. 🧠 Key Learning: The real trick is understanding why they meet — Fast pointer gains one step every move, so in a loop it will always catch up. 📊 Complexity: • Time: O(n) • Space: O(1) Sharing a visual breakdown of the algorithm 👇 Back to building consistency. 🔗 GitHub Solution: https://lnkd.in/gQRv2Qp3 #Java #DSA #LinkedList #LeetCode #ProblemSolving #CodingJourney
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