Reversing Integers with LeetCode Discipline

🚀 Day 23/60 — LeetCode Discipline Problem Solved: Remove Duplicates from Sorted Array (Revision) Difficulty: Easy Today’s practice focused on revisiting a classic array problem that leverages the two-pointer technique. Since the array is already sorted, duplicates naturally appear next to each other. The idea is to maintain one pointer for the position of the last unique element and another pointer to traverse the array, updating the array in-place whenever a new unique value appears. Problems like this beautifully demonstrate how understanding the structure of the data can simplify the solution significantly. 💡 Focus Areas: • Strengthened two-pointer array technique • Practiced in-place array modification • Reinforced understanding of sorted array properties • Improved clean and efficient iteration logic • Focused on writing simple and readable code ⚡ Performance Highlight: Achieved ~79% runtime efficiency on submission. Consistent practice with classic problems continues to refine core algorithmic patterns and strengthen problem-solving discipline. #LeetCode #60DaysOfCode #100DaysOfCode #DSA #TwoPointers #Arrays #Algorithms #DataStructures #ProblemSolving #CodingJourney #SoftwareEngineering #Programming #Developers #TechCareers #Java

🚀 Day 24/60 — LeetCode Discipline Problem Solved: Symmetric Tree (Revision) Difficulty: Easy Today’s practice focused on revisiting a classic binary tree problem — checking whether a tree is symmetric around its center. The key idea is to treat the left and right subtrees as mirror images and recursively compare their corresponding nodes. By verifying both structure and node values simultaneously, the algorithm determines whether the tree maintains perfect symmetry. Problems like this highlight how recursion naturally fits tree-based structures and helps simplify complex comparisons. 💡 Focus Areas: • Strengthened recursive tree traversal • Practiced mirror comparison of subtrees • Improved understanding of binary tree symmetry • Reinforced recursive problem-solving patterns • Focused on writing clean and structured logic ⚡ Performance Highlight: Achieved 0 ms runtime (100% performance) on submission. Consistent practice across arrays, strings, stacks, bit manipulation, and now tree structures continues to deepen my overall algorithmic intuition. #LeetCode #60DaysOfCode #100DaysOfCode #DSA #BinaryTree #Recursion #Algorithms #DataStructures #ProblemSolving #CodingJourney #SoftwareEngineering #Programming #Developers #TechCareers #Java

🚀 Day 26/60 — LeetCode Discipline Problem Solved: Remove Element (Revision) Difficulty: Easy Today’s practice focused on revisiting a fundamental array problem involving in-place modification. The task was to remove all occurrences of a given value without using extra space, while efficiently maintaining the remaining elements. The solution leverages a simple yet powerful approach of iterating through the array and overwriting unwanted elements. Problems like this reinforce the importance of space optimization and clean in-place operations, which are often crucial in real-world scenarios. 💡 Focus Areas: • Strengthened in-place array manipulation • Practiced efficient element filtering • Reinforced two-pointer style iteration • Improved understanding of space optimization • Focused on writing concise and readable code ⚡ Performance Highlight: Achieved 0 ms runtime (100% performance) on submission. Simple problems, when practiced with discipline, continue to sharpen the core of problem-solving ability. #LeetCode #60DaysOfCode #100DaysOfCode #DSA #Arrays #TwoPointers #Algorithms #DataStructures #ProblemSolving #CodingJourney #SoftwareEngineering #Programming #Developers #TechCareers #Java

Day 38 of My DSA Journey Today I solved LeetCode 152 – Maximum Product Subarray on LeetCode. 📌 Problem Given an integer array nums, find the contiguous subarray that has the largest product, and return that product. Example: Input: [2,3,-2,4] Output: 6 → subarray [2,3] 🧠 Approach – Dynamic Programming (Tracking Max & Min) This problem is tricky because of negative numbers. Key Idea: • At each index, we maintain: maxProduct → maximum product ending at current index minProduct → minimum product ending at current index 👉 Why min? Because a negative number can turn a small (negative) product into a large positive one. Steps I followed: • Initialize maxProduct, minProduct, and ans with the first element • Traverse the array from left to right • If the current number is negative → swap max and min • Update: maxProduct = max(current, current × maxProduct) minProduct = min(current, current × minProduct) • Update the final answer using maxProduct ⏱ Time Complexity: O(n) — Single pass through the array 📦 Space Complexity: O(1) — No extra space used 💡 Key Learnings ✔ Handling negative numbers in product problems ✔ Using dynamic programming with state tracking ✔ Understanding why tracking both max & min is important This is one of those problems that looks simple but tests deep understanding of edge cases 🚀 Consistency continues — leveling up every day 💪 #100DaysOfCode #DSA #DynamicProgramming #Arrays #LeetCode #Java #ProblemSolving #CodingJourney #DeveloperJourney #Programming #SoftwareEngineering

🚀 Day 29/60 — LeetCode Discipline Problem Solved: Longest Common Prefix Difficulty: Easy Today’s problem focused on identifying the longest common starting pattern across multiple strings — a classic exercise in string comparison and iteration. The approach involved checking characters position by position across all strings until a mismatch is found. This reinforces how simple iterative logic can elegantly solve problems involving multiple inputs. It’s a reminder that sometimes, clarity in approach matters more than complexity in code. 💡 Focus Areas: • Strengthened string traversal techniques • Practiced comparing multiple inputs efficiently • Improved understanding of edge cases (empty strings, mismatch handling) • Reinforced early stopping conditions for optimization • Focused on clean and readable logic ⚡ Performance Highlight: Achieved efficient runtime with minimal overhead. Finding common ground across multiple inputs is not just a coding skill — it’s a pattern recognition mindset. #LeetCode #60DaysOfCode #100DaysOfCode #DSA #Strings #Algorithms #ProblemSolving #CodingJourney #SoftwareEngineering #Java #Developers #Consistency #TechGrowth #LearnToCode

Day 36 of My DSA Journey Today I solved LeetCode 150 – Evaluate Reverse Polish Notation (RPN) on LeetCode. 📌 Problem Evaluate the value of an arithmetic expression in Reverse Polish Notation. Valid operators are: +, -, *, / Each operand may be an integer. Example: Input: ["2","1","+","3","*"] Output: 9 Explanation: (2 + 1) * 3 = 9 🧠 Approach – Stack This problem is a perfect application of the Stack data structure. Steps I followed: • Traverse the tokens array. • If the element is a number → push it onto the stack. • If it is an operator: Pop the top two elements (a and b) Perform the operation (a operator b) Push the result back into the stack • At the end, the stack contains the final result. ⏱ Time Complexity: O(n) — We process each token once 📦 Space Complexity: O(n) — Stack to store operands 💡 Key Learnings ✔ Understanding Reverse Polish Notation (Postfix Expression) ✔ Applying stack for expression evaluation ✔ Handling operator precedence implicitly using stack This problem connects DSA with compiler/interpreter concepts, which makes it even more interesting 🚀 Consistency continues — improving every day 💪 #100DaysOfCode #DSA #Stack #LeetCode #Java #ProblemSolving #CodingJourney #DeveloperJourney #Programming #SoftwareEngineering

🚀 Day 25/60 — LeetCode Discipline Problem Solved: Search Insert Position (Revision) Difficulty: Easy Today’s practice focused on revisiting one of the most fundamental algorithms in computer science — Binary Search. The task was to efficiently determine the position of a target element in a sorted array, or identify the correct index where it should be inserted while maintaining order. This problem reinforces how dividing the search space in half at each step leads to highly efficient solutions with logarithmic time complexity. 💡 Focus Areas: • Strengthened binary search fundamentals • Practiced boundary condition handling • Improved mid-index calculation logic • Reinforced logarithmic-time problem solving • Focused on writing clean and precise code ⚡ Performance Highlight: Achieved 0 ms runtime (100% performance) on submission. Revisiting foundational algorithms like binary search continues to sharpen problem-solving precision and efficiency. #LeetCode #60DaysOfCode #100DaysOfCode #DSA #BinarySearch #Algorithms #DataStructures #ProblemSolving #CodingJourney #SoftwareEngineering #Programming #Developers #TechCareers #Java

🚀 Day 535 of #750DaysOfCode 🚀 ✅ Solved: Count Submatrices with Top-Left Element and Sum ≤ k (LeetCode 3070) Today’s problem was a great example of using 2D Prefix Sum to optimize matrix queries. Instead of checking every possible submatrix, we can observe that the question only allows submatrices that include the top-left element (0,0). This means every valid submatrix is just a prefix rectangle, so we can compute the sum efficiently using prefix sums. 💡 Key Learning: Used 2D Prefix Sum technique Reduced brute force complexity to O(m × n) Learned how to handle matrix range sum problems efficiently 📌 Approach: Build prefix sum for each cell Check if sum from (0,0) to (i,j) ≤ k Count valid submatrices This problem improved my understanding of: ✔️ Prefix Sum ✔️ Matrix DP patterns ✔️ Optimization from brute force to efficient solution Consistency continues 🔥 On to Day 536 tomorrow. #leetcode #java #datastructures #algorithms #codingchallenge #prefixsum #matrix #programming #softwareengineering #750daysofcode

🚀 Day 30/60 — LeetCode Discipline Problem Solved: 3Sum Closest Difficulty: Medium Today’s problem pushed beyond exact answers and focused on finding the closest possible sum to a given target — a subtle yet powerful variation of the classic 3Sum problem. By sorting the array and using a two-pointer approach, the solution efficiently explores combinations while continuously updating the closest result. This problem highlights how small modifications in logic can significantly change the nature of a problem — from exact matching to optimal approximation. 💡 Focus Areas: • Strengthened two-pointer technique • Practiced working with sorted arrays • Improved handling of optimization conditions • Learned to track and update closest values dynamically • Reinforced problem-solving under constraints ⚡ Performance Highlight: Achieved efficient runtime with optimized traversal. Not every problem asks for perfection — sometimes, the goal is to get as close as possible. #LeetCode #60DaysOfCode #100DaysOfCode #DSA #TwoPointers #Algorithms #ProblemSolving #CodingJourney #SoftwareEngineering #Java #Developers #Consistency #TechGrowth #LearnToCode

🚀 Day 8 of 30 Days Coding Challenge Today I solved a problem on LeetCode: Minimum Distance Between Three Equal Elements. 🔍 Approach: Initially implemented a brute-force solution using three nested loops (O(n³)). It worked for smaller constraints but highlighted the importance of optimizing. 💡 Key Learning: Instead of checking all possible triplets, grouping indices of identical elements and analyzing consecutive occurrences leads to a much more efficient solution. ⚡ Optimization Insight: Reduced time complexity from O(n³) → O(n) Leveraged HashMap to store indices and process only relevant combinations. 📈 Takeaway: This problem reinforced an important concept: 👉 When dealing with repeated elements, think in terms of grouping and patterns rather than brute force. Consistency is key — learning something new every day and improving step by step. #Day8 #30DaysOfCode #CodingChallenge #LeetCode #Java #DataStructures #Algorithms #ProblemSolving #CodingJourney #SoftwareDevelopment #LearnToCode #TechGrowth