Day 63/100 Completed ✅ 🚀 Solved LeetCode – Find Minimum in Rotated Sorted Array (Java) ⚡ Applied an efficient Binary Search approach to locate the minimum element in a rotated sorted array. Instead of scanning linearly, reduced the search space by comparing mid with the right boundary to identify the unsorted portion. 🧠 Key Learnings: 1. Understanding rotated sorted array patterns 2. Identifying the pivot (minimum element) using binary search 3. Optimizing search to O(log n) time complexity 4. Strengthening decision-making on search boundaries 💯 This problem improved my confidence in handling tricky variations of binary search — a must-know pattern for coding interviews. 🔗 Profile: https://lnkd.in/gaJmKdrA #LeetCode #100DaysOfCode #Java #DSA #BinarySearch #CodingPractice #ProblemSolving #TechJourney
Java Binary Search: Rotated Sorted Array Minimum
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🚀 Day 84/100 – 𝐒𝐞𝐚𝐫𝐜𝐡 𝐢𝐧 𝐑𝐨𝐭𝐚𝐭𝐞𝐝 𝐒𝐨𝐫𝐭𝐞𝐝 𝐀𝐫𝐫𝐚𝐲 𝐈𝐈 🔍 𝐊𝐞𝐲 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠: Binary search works great on sorted arrays, but duplicates introduce ambiguity — making it harder to decide which half is sorted. 💡 𝐂𝐨𝐫𝐞 𝐈𝐝𝐞𝐚: Use modified binary search Identify the sorted half Handle duplicates by shrinking the search space ⚡ 𝐀𝐩𝐩𝐫𝐨𝐚𝐜𝐡: Find 𝐦𝐢𝐝 If 𝐭𝐚𝐫𝐠𝐞𝐭 𝐟𝐨𝐮𝐧𝐝 → 𝐫𝐞𝐭𝐮𝐫𝐧 𝐭𝐫𝐮𝐞 𝐇𝐚𝐧𝐝𝐥𝐞 𝐝𝐮𝐩𝐥𝐢𝐜𝐚𝐭𝐞𝐬 (𝐥𝐨𝐰++) Check which half is sorted Narrow down search accordingly #Day84 #100DaysOfCode #Java #DSA #LeetCode #BinarySearch #CodingJourney
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🚀 Day 35 of my #100DaysOfCode Journey Today, I solved the LeetCode problem: Valid Anagram Problem Insight: Given two strings, check if one is an anagram of the other. Approach: • First, check if the strings have the same length; if not, return false • Convert both strings to character arrays • Sort both arrays • Compare the sorted arrays — if equal, the strings are anagrams Time Complexity: • O(n log n) — due to sorting the arrays Space Complexity: • O(n) — for the character arrays Key Learnings: • Sorting is a simple and effective way to compare character compositions • Edge cases like different lengths should be handled first • Breaking the problem into small steps makes it easy to reason about Takeaway: Sometimes, sorting can reduce a seemingly complex problem into a simple comparison. #DSA #Java #LeetCode #100DaysOfCode #CodingJourney #ProblemSolving #Strings
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✅ LeetCode Top Interview 150 – Day 87 Today I solved Find Minimum in Rotated Sorted Array Key Idea : Use Binary Search to find the pivot (minimum element) efficiently. In a rotated sorted array, one half is always sorted. Compare middle element with the rightmost element: If nums[mid] > nums[right] → Minimum lies in right half Else → Minimum lies in left half (including mid) This helps reduce the search space in half each time #DSA #Java #Leetcode #Day87
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✅ LeetCode — Remove Duplicates from Sorted Array | Solved in Java! Another problem down, one step closer to the goal. 💪 🔍 Problem: Remove duplicates from a sorted array in-place. 💡 My Approach: Used a HashSet to filter unique elements, then wrote them back into the array and sorted the result — clean, readable, and efficient. 📊 Results: • Runtime: 8 ms (beats 3.87%) • Memory: 46.56 MB (beats 87.88% 🏆) 🚀 Key takeaway: Sometimes the simplest solution is the clearest one. Understanding the problem deeply matters more than clever tricks. Consistency is everything. One problem at a time, one day at a time. If you're also grinding LeetCode or preparing for interviews, let's connect and grow together! 🤝 #LeetCode #Java #DSA #DataStructures #Algorithms #CodingInterview #ProblemSolving #SoftwareEngineering #100DaysOfCode #CompetitiveProgramming #TechCareers
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✅ LeetCode Top Interview 150 – Day 93 Today I solved Lowest Common Ancestor of a Binary Tree Key Idea : Use DFS recursion to traverse the tree If current node is null, p, or q → return it Search in left and right subtrees If both sides return non-null → current node is LCA Else return the non-null side This approach efficiently finds the lowest common ancestor in one traversal #DSA #Java #Leetcode #Day93
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𝐃𝐚𝐲 𝟓𝟒 – 𝐃𝐒𝐀 𝐉𝐨𝐮𝐫𝐧𝐞𝐲 | 𝐀𝐫𝐫𝐚𝐲𝐬 🚀 Today’s problem focused on finding the minimum element in a rotated sorted array using binary search. 𝐏𝐫𝐨𝐛𝐥𝐞𝐦 𝐒𝐨𝐥𝐯𝐞𝐝 • Find Minimum in Rotated Sorted Array 𝐀𝐩𝐩𝐫𝐨𝐚𝐜𝐡 • Used binary search to reduce the search space • Compared the middle element with the rightmost element Logic: • If nums[mid] > nums[right] → minimum lies in the right half • Else → minimum lies in the left half (including mid) • Continued until left meets right 𝐊𝐞𝐲 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠𝐬 • Rotated arrays require a modified binary search • Comparing with boundary elements helps identify the sorted half • Binary search is not only for exact matches • Reducing the search space is the core idea 𝐂𝐨𝐦𝐩𝐥𝐞𝐱𝐢𝐭𝐲 • Time: O(log n) • Space: O(1) 𝐓𝐚𝐤𝐞𝐚𝐰𝐚𝐲 Binary search is about asking the right question — not just finding the middle. 54 days consistent 🚀 On to Day 55. #DSA #Arrays #BinarySearch #LeetCode #Java #ProblemSolving #DailyCoding #LearningInPublic #SoftwareDeveloper
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🚀 #100DaysOfCode | Day 47 🔍 Solved: Find Minimum in Rotated Sorted Array Today I explored another interesting variation of Binary Search. Instead of searching for a target, the goal was to find the minimum element in a rotated sorted array. 💡 Key Insight: By comparing the middle element with the last element, we can determine which half contains the minimum value. Approach: ✔ Used Binary Search to achieve O(log n) time complexity ✔ Compared mid with end to identify the unsorted portion ✔ Narrowed down the search space efficiently What I Learned: This problem helped me understand how binary search can be applied beyond simple searching—especially in rotated and partially sorted arrays. #Java #DSA #LeetCode #BinarySearch #CodingJourney #ProblemSolving #TechSkills
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𝐃𝐚𝐲 𝟕𝟔 – 𝐃𝐒𝐀 𝐉𝐨𝐮𝐫𝐧𝐞𝐲 | 𝐀𝐫𝐫𝐚𝐲𝐬 🚀 Today’s problem focused on summarizing continuous ranges in a sorted array. 𝐏𝐫𝐨𝐛𝐥𝐞𝐦 𝐒𝐨𝐥𝐯𝐞𝐝 • Summary Ranges 𝐀𝐩𝐩𝐫𝐨𝐚𝐜𝐡 – 𝐓𝐰𝐨 𝐏𝐨𝐢𝐧𝐭𝐞𝐫𝐬 • Iterated through the array • Marked the start of a range • Expanded while elements are consecutive Logic: • If only one element → add as single number • If multiple → format as "start->end" • Moved pointer to next new range 𝐊𝐞𝐲 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠𝐬 • Two-pointer technique simplifies range problems • Consecutive patterns are common in arrays • Formatting output is part of problem-solving • Simple logic can still be interview-relevant 𝐂𝐨𝐦𝐩𝐥𝐞𝐱𝐢𝐭𝐲 • Time: O(n) • Space: O(1) (excluding output) 𝐓𝐚𝐤𝐞𝐚𝐰𝐚𝐲 Not all problems are complex — some test how clearly you can identify patterns. 76 days consistent 🚀 On to Day 77. 🔗 Problem Link:https://lnkd.in/dXq9tU58 #DSA #Arrays #TwoPointers #LeetCode #Java #ProblemSolving #DailyCoding #LearningInPublic #SoftwareDeveloper
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📘 DSA Journey — Day 33 Today’s focus: Binary Search for next greater element. Problem solved: • Find Smallest Letter Greater Than Target (LeetCode 744) Concepts used: • Binary Search • Upper bound concept • Circular handling Key takeaway: The goal is to find the smallest character strictly greater than a given target in a sorted array. This is a classic upper bound problem: We use binary search to find the first element greater than the target. During search: • If letters[mid] > target, store it as a possible answer and move left • Else move right An important edge case: If no character is greater than the target, we return the first element (circular behavior). Continuing to strengthen binary search patterns and problem-solving consistency. #DSA #Java #LeetCode #CodingJourney
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🚀 Day 55 of #100DaysOfCode Solved 147. Insertion Sort List on LeetCode 🔗 🧠 Key Insight: We apply the classic Insertion Sort, but on a linked list instead of an array. The challenge is handling pointer manipulation efficiently. ⚙️ Approach: 1️⃣ Create a dummy node to act as the start of the sorted list 2️⃣ Traverse the original list node by node 3️⃣ For each node: Find its correct position in the sorted part Insert it there by updating pointers 🔁 This builds a sorted list incrementally ⏱️ Time Complexity: O(n²) 📦 Space Complexity: O(1) #100DaysOfCode #LeetCode #DSA #LinkedList #Sorting #Java #InterviewPrep #CodingJourney
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