Java Solution for Intersection of Two Arrays Problem

Day 82 of #100DaysOfLeetCode 💻✅ Solved #11. Container With Most Water problem in Java. Approach: • Used Two Pointer technique • Calculated area using min height and width • Moved pointer with smaller height inward • Tracked maximum area throughout Performance: ✓ Runtime: 5 ms (Beats 83.17% submissions) ✓ Memory: 77.35 MB (Beats 53.65% submissions) Key Learning: ✓ Mastered Two Pointer optimization technique ✓ Learned efficient area calculation strategy ✓ Improved decision-making for pointer movement Learning one problem every single day 🚀 #Java #LeetCode #DSA #TwoPointers #Arrays #ProblemSolving #CodingJourney #100DaysOfCode

Day 68 of #100DaysOfLeetCode 💻✅ Solved #977. Squares of a Sorted Array problem in Java. Approach: • Traversed the array and squared each element • Used Arrays.sort() to sort the squared values • Returned the sorted array as the result Performance: ✓ Runtime: 10 ms (Beats 37.38% submissions) ✓ Memory: 47.98 MB (Beats 18.78% submissions) Key Learning: ✓ Practiced array transformation and sorting ✓ Learned how squaring affects order in sorted arrays ✓ Understood the importance of optimizing from O(n log n) to O(n) using two pointers Learning one problem every single day 🚀 #Java #LeetCode #DSA #Arrays #Sorting #ProblemSolving #CodingJourney #100DaysOfCode

Day 90 of #100DaysOfLeetCode 💻✅ Solved #42. Trapping Rain Water problem in Java. Approach: • Used Two Pointer technique • Maintained leftMax and rightMax boundaries • Calculated trapped water based on smaller side • Accumulated water while traversing Performance: ✓ Runtime: 0 ms (Beats 100.00% submissions) 🚀 ✓ Memory: 47.70 MB (Beats 72.36% submissions) Key Learning: ✓ Mastered Two Pointer approach for complex problems ✓ Learned optimal water trapping strategy ✓ Improved understanding of boundary-based calculations Learning one problem every single day 🚀 #Java #LeetCode #DSA #TwoPointers #Arrays #ProblemSolving #CodingJourney #100DaysOfCode

🚀 Day 23 of #75DaysOfCode Solved: Equal Row and Column Pairs 🔹 Problem: Given an n x n matrix, count the number of pairs (ri, cj) such that row ri and column cj are exactly the same. 🔹 Approach: • Stored all rows in a HashMap with their frequency • Converted each column into a comparable string format • Matched columns with stored rows to count equal pairs 🔹 Key Learning: Using StringBuilder instead of String concatenation significantly improves performance due to immutability of Strings in Java. 🔹 Time Complexity: O(n²) 🔹 Takeaway: Smart use of HashMap + efficient string handling can simplify and optimize matrix-based problems. #Day22 #75DaysOfCode #Java #DSA #LeetCode #CodingJourney #ProblemSolving

Day 88 of #100DaysOfLeetCode 💻✅ Solved #56. Merge Intervals problem in Java. Approach: • Sorted intervals based on start time • Compared current interval with last merged interval • Merged overlapping intervals • Added non-overlapping intervals directly Performance: ✓ Runtime: 8 ms (Beats 91.28% submissions) 🚀 ✓ Memory: 49.16 MB (Beats 43.60% submissions) Key Learning: ✓ Learned interval merging technique ✓ Strengthened sorting + traversal logic ✓ Improved handling of overlapping ranges Learning one problem every single day 🚀 #Java #LeetCode #DSA #Arrays #Sorting #ProblemSolving #CodingJourney #100DaysOfCode

Day 77 of #100DaysOfLeetCode 💻✅ Solved #153. Find Minimum in Rotated Sorted Array problem in Java. Approach: • Used Binary Search to find minimum element • Compared mid with right to decide direction • Reduced search space until pointers converged Performance: ✓ Runtime: 0 ms (Beats 100.00% submissions) 🚀 ✓ Memory: 43.62 MB (Beats 78.18% submissions) Key Learning: ✓ Strengthened Binary Search on rotated arrays ✓ Learned how to identify unsorted portion efficiently ✓ Improved optimization over linear search Learning one problem every single day 🚀 #Java #LeetCode #DSA #BinarySearch #Arrays #ProblemSolving #CodingJourney #100DaysOfCode

Day 78 of #100DaysOfLeetCode 💻✅ Solved #299. Bulls and Cows problem in Java. Approach: • Used a frequency array to track digits • Counted bulls when characters matched directly • Used count array to efficiently track cows • Updated counts to handle unmatched digits Performance: ✓ Runtime: 3 ms (Beats 95.59% submissions) 🚀 ✓ Memory: 43.64 MB (Beats 52.40% submissions) Key Learning: ✓ Learned efficient use of frequency arrays ✓ Improved handling of strings with counting logic ✓ Strengthened understanding of bulls vs cows logic Learning one problem every single day 🚀 #Java #LeetCode #DSA #Strings #Arrays #ProblemSolving #CodingJourney #100DaysOfCode

Day 74 of #100DaysOfLeetCode 💻✅ Solved #162. Find Peak Element problem in Java. Approach: • Used Binary Search technique to efficiently find the peak element • Set two pointers, left at start and right at end of the array • Calculated mid index using safe mid formula • Compared nums[mid] with nums[mid + 1] to determine direction • If mid element is smaller, moved search space to right half • Otherwise, moved search space to left half including mid • Continued until left and right pointers converged • Final position (left == right) represents the peak index Performance: ✓ Runtime: 0 ms (Beats 100.00% submissions) 🚀 ✓ Memory: 44.32 MB (Beats 25.49% submissions) Key Learning: ✓ Strengthened understanding of Binary Search on unsorted arrays ✓ Learned how to apply divide-and-conquer beyond traditional searching ✓ Improved intuition for peak finding using neighbor comparison ✓ Practiced optimizing search space instead of linear scanning Learning one problem every single day 🚀 #Java #LeetCode #DSA #BinarySearch #Arrays #ProblemSolving #CodingJourney #100DaysOfCode

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

🚀 Day 48 of My #LeetCode Journey Today’s problem: 2615. Sum of Distances 💡 Key Idea: Instead of calculating distances between equal elements using brute force (O(n²)), I used: HashMap to group indices of same values Prefix Sum to efficiently compute distances This reduced the complexity to O(n) 🔥 🧠 What I Learned: How prefix sums can optimize distance calculations Efficient handling of repeated elements Writing clean and optimized code using Java ⚡ Approach: Store indices of each number Use prefix sums to calculate left & right distances Combine both to get final answer 📈 Time Complexity: O(n) 📦 Space Complexity: O(n) Consistency is key. Small progress every day leads to big results 💪 #Day48 #Java #FullStackDeveloper #CodingJourney #100DaysOfCode #DSA #LeetCode