Day 17 of #100DaysOfCode Today I worked on Binary Search (LeetCode 704) — a classic and powerful algorithm every developer should master. What I learned: How binary search reduces time complexity to O(log n) Importance of working on sorted arrays How to efficiently divide the search space using start, end, and mid Writing clean and optimal Java code for real interview scenarios Key takeaway: Instead of checking every element (O(n)), binary search helps us eliminate half of the data in each step — making it super fast and efficient. Problems like these remind me that understanding the logic is more important than just coding the solution. Consistency is the goal, improvement is the result. #Day17 #100DaysOfCode #Java #DataStructures #Algorithms #BinarySearch #CodingJourney #LeetCode
Mastering Binary Search with Java and LeetCode
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Day 96 - LeetCode Journey Solved LeetCode 901: Online Stock Span in Java ✅ This problem is all about recognizing the pattern and using the right data structure. Instead of checking previous prices one by one, I used a Monotonic Stack to efficiently calculate spans. Every element is pushed and popped at most once → super optimized 🔥 Key idea: Keep removing smaller or equal previous prices and accumulate their spans. Key takeaways: • Monotonic Stack concept (very important) • Avoiding nested loops using stack optimization • Efficient span calculation • Thinking in patterns, not brute force ✅ All test cases passed ⚡ O(n) time and O(n) space This is one of those problems that truly levels up your stack game 💯 #LeetCode #DSA #Java #Stack #MonotonicStack #ProblemSolving #CodingJourney #InterviewPrep #Consistency #100DaysOfCode
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𝐃𝐚𝐲 𝟕𝟕 – 𝐃𝐒𝐀 𝐉𝐨𝐮𝐫𝐧𝐞𝐲 | 𝐀𝐫𝐫𝐚𝐲𝐬 🚀 Today’s problem focused on finding all elements that appear more than n/3 times in an array. 𝐏𝐫𝐨𝐛𝐥𝐞𝐦 𝐒𝐨𝐥𝐯𝐞𝐝 • Majority Element II 𝐀𝐩𝐩𝐫𝐨𝐚𝐜𝐡 – 𝐇𝐚𝐬𝐡𝐌𝐚𝐩 • Counted frequency of each element using a map • Calculated threshold = n / 3 • Collected elements whose frequency exceeded the threshold 𝐊𝐞𝐲 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠𝐬 • At most 2 elements can appear more than n/3 times • HashMap is straightforward for frequency counting • Understanding constraints helps reduce possibilities • This problem has an optimized Boyer-Moore Voting (extended) solution 𝐂𝐨𝐦𝐩𝐥𝐞𝐱𝐢𝐭𝐲 • Time: O(n) • Space: O(n) 𝐓𝐚𝐤𝐞𝐚𝐰𝐚𝐲 Constraints often reveal hidden patterns — understanding them leads to better optimizations. 77 days consistent 🚀 On to Day 78. 🔗 Problem Link: https://lnkd.in/dDwdWYJs #DSA #Arrays #HashMap #LeetCode #Java #ProblemSolving #DailyCoding #LearningInPublic #SoftwareDeveloper
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🚀 Day 52 of #100DaysOfLeetCode Solved: Daily Temperatures (Monotonic Stack) Today’s focus was on understanding how to optimize from a brute-force O(n²) approach to an efficient O(n) solution using a stack. Key takeaways: Learned how to identify “next greater element” patterns Understood how monotonic stacks help avoid redundant work Practiced writing clean and optimized code Consistency is starting to pay off. Onto the next one. #DSA #Java #CodingJourney #LeetCode #ProblemSolving
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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 6 of #DSAwithEdSlash – Consistency > Motivation Today’s problem: Two Sum 🔢 A classic, but a powerful reminder that optimization matters. 💡 Started with brute force → O(n²) ⚡ Optimized using HashMap → O(n) Key takeaway: 👉 Think in terms of space-time tradeoff 👉 Always look for patterns like complement searching It’s not just about solving the problem — it’s about solving it better. Small steps every day = Big progress over time. #DSAwithEdSlash #100DaysOfCode #LeetCode #ProblemSolving #Java #CodingJourney #Consistency
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🚀 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
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🚀100 Days of Code Day-26 LeetCode Practice – Remove Duplicates from Sorted Array Solved a classic problem using the Two Pointer Technique 💡 📌 Problem: Given a sorted array, remove duplicates in-place and return the number of unique elements. 🔍 Key Idea: Since the array is sorted, duplicates are adjacent. Using two pointers helps efficiently overwrite duplicates without extra space. ⚡ Complexity: Time → O(n) Space → O(1) 💻 Clean and optimized approach makes this problem a great example of in-place array manipulation! #LeetCode #Java #DataStructures #CodingPractice #ProblemSolving #100DaysOfCode
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#Day76 of my second #100DaysOfCode Binary search continues to surprise me with how many variations it has. DSA • Solved Find Peak Element (LeetCode 162) – Brute: check every element → O(n) – Optimal: binary search based on slope comparison → O(log n) • Key idea: if the next element is greater, move right; else move left — a peak is guaranteed • Didn’t need to check all elements, just follow the increasing/decreasing trend Interesting how this doesn’t require a fully sorted array, yet binary search still works. #DSA #BinarySearch #LeetCode #Algorithms #Java #100DaysOfCode #WomenWhoCode #BuildInPublic #LearningInPublic
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🚀 Day 8 of #100DaysOfCode Solved: Maximum Product of Two Elements in an Array 💻 Today’s problem was all about optimizing logic and thinking smart instead of brute force. Instead of checking every pair, I focused on finding the two largest elements efficiently and used them to compute the result in a single pass 🔥 ✅ Time Complexity: O(n) ✅ Space Complexity: O(1) Small problems like these really sharpen problem-solving skills and reinforce the importance of clean, efficient code. Consistency is key — showing up every day, learning something new, and getting 1% better 💯 #DSA #Java #CodingJourney #LeetCode #ProblemSolving #Consistency #Day8#DSAwithEdSlash
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🚀 Day 47 of #100DaysOfCode Solved: Roman to Integer Today’s problem focused on understanding how to convert Roman numerals into integers using logical rules and efficient traversal. 💡 Key Learnings: Used greedy approach with character comparison Applied subtraction logic when smaller value comes before a larger one Improved string handling and conditional thinking ⚡ Performance: Runtime: 3 ms Beat: ~78% of submissions 🧠 Takeaway: Simple rules + correct observation = optimized solution 💯 Consistency is slowly turning into confidence 🔥 #CodingChallenge #LeetCode #Java #ProblemSolving #100DaysOfCode #PlacementPreparation
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