LeetCode Execution Time Calculation Bug Identified

𝑷𝒐𝒕𝒆𝒏𝒕𝒊𝒂𝒍 𝑩𝒖𝒈 𝑰𝒅𝒆𝒏𝒕𝒊𝒇𝒊𝒆𝒅 𝒊𝒏 𝑳𝒆𝒆𝒕𝑪𝒐𝒅𝒆 𝑬𝒙𝒆𝒄𝒖𝒕𝒊𝒐𝒏 𝑻𝒊𝒎𝒆 𝑪𝒂𝒍𝒄𝒖𝒍𝒂𝒕𝒊𝒐𝒏  I recently noticed an issue with how LeetCode calculates and displays code execution time. By adding a simple static block with a shutdown hook, it is possible to alter the displayed runtime of a submitted solution. This indicates that the execution time can be influenced outside the actual algorithm logic, which should ideally not be possible. Below is the code snippet that demonstrates this behavior: static { Runtime.getRuntime().addShutdownHook(new Thread(() -> { try (FileWriter writer = new FileWriter("display_runtime.txt")) { writer.write("0"); } catch (IOException e) { e.printStackTrace(); } })); } This suggests a bug on LeetCode’s end, where execution time tracking may be relying on artifacts that can be manipulated during JVM shutdown. Sharing this for awareness and hoping the LeetCode team can look into it to ensure fair and accurate performance measurement for all submissions. #LeetCode #Java #JVM #CompetitiveProgramming #SoftwareEngineering #Performance #Debugging LeetCode

🚀 Day 5/30 – Understanding Stack-Based Validation Today I worked on validating balanced parentheses in a string — a classic problem that tests understanding of stacks and order of operations. The challenge was to ensure that every opening bracket has a corresponding closing bracket in the correct order. Instead of relying on pattern matching, I implemented a stack-based approach, which naturally fits this type of problem. 💡 Approach Traverse the string character by character Push opening brackets onto the stack When encountering a closing bracket, check whether it matches the most recent opening bracket If at any point the structure breaks, return false This approach ensures: O(n) time complexity O(n) space complexity (in worst case) 📊 Result ✅ Accepted (All test cases passed) ⚡ Efficient runtime performance 📚 Key Takeaway This problem reinforced an important concept: Stacks are extremely powerful when dealing with nested structures, syntax validation, and expression parsing. Small problems like this build strong fundamentals for larger system-level logic. Day 5 complete. Consistency continues. #Day5 #30DaysOfCode #LeetCode #Java #Stacks #Algorithms #DataStructures #ProblemSolving #SoftwareEngineering #CodingJourney #Consistency

LeetCode Grinding 🚀 Today was focused on strengthening Two Pointers mastery and improving problem-solving speed through practice. 🔹 DSA & LeetCode Practice Solved multiple problems by applying the Two Pointers pattern: LeetCode 11 — Container With Most Water Learned how pointer movement helps maximize area efficiently LeetCode 125 — Valid Palindrome Applied two pointers for string validation after preprocessing LeetCode 2824 — Count Pairs Whose Sum is Less than Target Understood how sorted arrays + two pointers help count pairs efficiently LeetCode 26 — Remove Duplicates from Sorted Array Strengthened in-place array manipulation using pointer technique 📌 Key takeaway: The Two Pointers pattern is powerful for: Sorted arrays Pair problems String validation Space-optimized solutions The more I practice patterns, the faster I recognize where to apply them. #DailyGrind #DSA #LeetCode #TwoPointers #ProblemSolving #Java #Consistency #LearningInPublic #InterviewPrep

🚀 Day 20 of #100DaysOfCode Solved 54. Spiral Matrix on LeetCode 🌀 🧠 Key insight: Spiral traversal is all about maintaining boundaries. By shrinking the top, bottom, left, and right limits after each pass, we can cover every element exactly once. ⚙️ Approach: 🔹Maintain four pointers: top, down, left, right 🔹Traverse: 🔹Left → Right (top row) 🔹Top → Bottom (right column) 🔹Right → Left (bottom row) 🔹Bottom → Top (left column) 🔹Update boundaries after each traversal ⏱️ Time Complexity: O(m × n) 📦 Space Complexity: O(1) (excluding output list) #100DaysOfCode #LeetCode #DSA #Matrix #Java #ProblemSolving #LearningInPublic #CodingJourney

Day 16 – LeetCode 1004 | Sliding Window Done Right (O(n) Solution) Day 16 of solving problems consistently. Solved LeetCode 1004 – Max Consecutive Ones III. Problem: Given a binary array, you can flip at most k zeros. Return the maximum number of consecutive 1s possible. Brute force checks every subarray → O(n²) → wasteful. A better approach is Sliding Window + Two Pointers → O(n). Core logic: • Expand window with right pointer • Count zeros • If zeros exceed k → move left pointer • Track max window length This problem is a good reminder that: Constraints usually hint the optimal technique. If you see “subarray + max/min + linear time” → think Sliding Window first. Consistency builds skill. 16 days. No breaks. Code + explanation in the video 👇 #LeetCode #DSA #Algorithms #SlidingWindow #TwoPointers #Java #ProblemSolving #CodingInterview #SoftwareDeveloper #100DaysOfCode #TechJourney

Day 17 – LeetCode 1004 | Sliding Window Done Right (O(n) Solution) Day 17 of solving problems consistently. Solved LeetCode 1004 – Max Consecutive Ones III. Problem: Given a binary array, you can flip at most k zeros. Return the maximum number of consecutive 1s possible. Brute force checks every subarray → O(n²) → wasteful. A better approach is Sliding Window + Two Pointers → O(n). Core logic: • Expand window with right pointer • Count zeros • If zeros exceed k → move left pointer • Track max window length This problem is a good reminder that: Constraints usually hint the optimal technique. If you see “subarray + max/min + linear time” → think Sliding Window first. Consistency builds skill. 17 days. No breaks. Code + explanation in the video 👇 #LeetCode #DSA #Algorithms #SlidingWindow #TwoPointers #Java #ProblemSolving #CodingInterview #SoftwareDeveloper #100DaysOfCode #TechJourney

🚀 Day 5 – LeetCode Practice Today, I solved the Reverse Nodes in k-Group problem on LeetCode: 🎯 Difficulty: Hard 💻 Language Used: Java 💡 Approach: • Given a linked list and an integer k, the task was to reverse every group of k nodes. • I used pointer manipulation and a dummy node to handle group reversals cleanly. • Moved through the list in blocks of k, reversing each sub-group by re-wiring next pointers. • Ensured that if the final group had fewer than k nodes, it was kept as-is. • This approach ensured in-place reversal without extra space. ⏱ Complexity: • Time Complexity: O(n) • Space Complexity: O(1) 📚 Key Takeaway: This problem deepened my understanding of in-place linked list manipulation, group operations, and edge-case handling when list length isn’t a multiple of k. Solving pattern-rich, hard problems like this consistently improves my algorithmic thinking and implementation precision. 💪 #LeetCode #Java #DSA #LinkedList #ProblemSolving #Algorithms #CodingPractice #100DaysOfCode #SoftwareDeveloper

🚀 Day 7 of #100DaysOfCode Solved Search a 2D Matrix on LeetCode using an optimized matrix traversal approach 🔎 🧠 Key insight: Since rows and columns are sorted, starting from the top-right corner helps eliminate either a row or a column in each step. ⚙️ Approach: 🔹Start at top-right element 🔹If value < target → move down 🔹If value > target → move left 🔹Repeat until target is found or bounds are crossed ⏱️ Time Complexity: O(m + n) 📦 Space Complexity: O(1) #100DaysOfCode #LeetCode #DSA #Matrix #Java #ProblemSolving #LearningInPublic #CodingJourney

Continued the matrix LeetCode practice with 48. Rotate Image. Unlike transpose, this problem required rotating the matrix in-place, which means no extra matrix could be used. That constraint made the logic more interesting. Approach used: - first performed a transpose across the main diagonal - then reversed each row to complete the 90° clockwise rotation - kept the focus on clear index manipulation instead of complex tricks Result : Accepted Runtime : 0 ms Clean in-place transformation without extra space Key learning from this problem: - many matrix rotations are just transpose + reverse in disguise - in-place operations demand careful index handling - understanding the pattern is more valuable than memorizing code This felt like a natural step forward from transpose toward more complex traversal and matrix logic. #LeetCode #DSA #Matrices #Java #ProblemSolving #CodingJourney #LearningInPublic #JavaDeveloper

Started the matrix LeetCode practice today with 867. Transpose Matrix. This problem was straightforward in logic, but important for strengthening the row–column index relationship that keeps showing up in matrix questions. Approach used: - created a new matrix with swapped dimensions - mapped transpose[j][i] = matrix[i][j] using nested loops - focused on correctness and clarity rather than clever tricks Result : Accepted Runtime : 0 ms Beats: 100% (runtime) Main takeaway from this problem: - transpose is one of the most fundamental matrix transformations - many harder matrix problems secretly rely on this same idea - clean indexing matters more than complicated logic Good first step before moving to rotation and spiral traversal problems. #LeetCode #DSA #Matrices #Java #ProblemSolving #CodingJourney #LearningInPublic #JavaDeveloper