Java String Manipulation Basics

📅 Day 10 – Strings in Java 📚 Topic: String Manipulation (Hashing) Today I solved the problem of checking whether two strings are anagrams using an efficient frequency-count approach. This helped me understand how hashing can be used to compare character distributions instead of sorting. ✔ Key Learnings: • Applied hashing using a frequency array • Improved understanding of character frequency comparison • Learned how to optimize from sorting (O(n log n)) to linear time (O(n)) Building problem-solving skills step by step and focusing on writing efficient code 🚀 #DSA #Strings #Java #ProblemSolving #LearningJourney

Day 89 of #100DaysOfLeetCode 💻✅ Solved #15. 3Sum problem in Java. Approach: • Sorted the array first • Fixed one element and used Two Pointers for the rest • Skipped duplicates to avoid repeated triplets • Adjusted pointers based on sum comparison Performance: ✓ Runtime: 30 ms (Beats 87.77% submissions) ✓ Memory: 59.02 MB (Beats 77.30% submissions) Key Learning: ✓ Mastered Two Pointer technique with sorting ✓ Learned handling duplicates efficiently ✓ Improved problem-solving for combination-based problems Learning one problem every single day 🚀 #Java #LeetCode #DSA #TwoPointers #Arrays #Sorting #ProblemSolving #CodingJourney #100DaysOfCode

🚀 I thought I knew Java Arrays… until I actually revised them properly. Most beginners memorize syntax like: int[] arr = new int[5]; But interviews don’t test syntax. They test understanding. Here’s what actually matters: • Why array index starts from 0 • How memory is allocated internally • Why arrays are fixed size • Why O(1) access time makes arrays powerful • When to use Array vs ArrayList If your array basics are weak, Data Structures will feel difficult. Today I revised: ✔ Declaration & Initialization ✔ 2D and Jagged Arrays ✔ Traversal methods ✔ Arrays utility methods Strong fundamentals > Fancy topics. Are your array basics really strong? #Java #DSA #Programming #JavaDeveloper #CodingJourney

Day 65 of #100DaysOfLeetCode 💻✅ Solved “Majority Frequency Group” problem in Java. Approach: • Created a frequency array of size 26 for all characters • Counted occurrences of each character in the string • For each unique frequency, counted how many characters share that frequency • Selected the frequency with the highest group size • In case of tie, chose the higher frequency • Built the result string with characters having the selected frequency Performance: ✓ Runtime: 5 ms (Beats 57.84% submissions) ✓ Memory: 44.51 MB (Beats 72.88% submissions) Key Learning: ✓ Practiced frequency grouping techniques ✓ Learned how to handle tie-breaking conditions ✓ Strengthened logic building with nested loops and conditions Learning one problem every single day 🚀 #Java #LeetCode #DSA #Strings #Hashing #ProblemSolving #CodingJourney #100DaysOfCode

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

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 76 of #100DaysOfLeetCode 💻✅ Solved #33. Search in Rotated Sorted Array problem in Java. Approach: • Applied Binary Search on rotated array • Checked which half is sorted at each step • Reduced search space based on target position Performance: ✓ Runtime: 0 ms (Beats 100.00% submissions) 🚀 ✓ Memory: 43.80 MB (Beats 70.96% submissions) Key Learning: ✓ Mastered searching in rotated sorted arrays ✓ Improved Binary Search decision-making ✓ Learned efficient handling of edge cases Learning one problem every single day 🚀 #Java #LeetCode #DSA #BinarySearch #Arrays #ProblemSolving #CodingJourney #100DaysOfCode

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 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 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