Dynamic Programming Solution for LeetCode's Find All Possible Stable Binary Arrays II

Binary Tree Maximum Path Sum Just came across an exciting LeetCode problem that basically asks you to find the maximum path sum in a tree. The maximum sum of a sequence of nodes in a tree, where a node can only appear in the sequence at most once. At first, I thought of a simple DFS traversal for each node, where I find the maximum (the current node value, maximumPathsum(left_subtree), maximumPathSum(RightSubtree), the node value + left_vertical_max_path sum, the node value + right_vertical_max_path sum, the node value + left_vertical_max_path sum + right_vertical_max_path sum). But then I realized I'm going to be recomputing the cost more and more as I traverse down the tree. So I switched to a bottom-up recursion that allows me to find the maximum subtree of each node, starting at the base cases, and bubble up the maximum path sum that starts at the node so that the parent node can reuse that value rather than recomputing. Pretty Interesting Dynamic Programming 😁 #leetCodeIsFun #DynamicProgrammingIsCool

🚀 Day 526 of #750DaysOfCode 🚀 Today I solved LeetCode 3129 – Find All Possible Stable Binary Arrays I. 🔹 Problem Summary We are given three integers: zero, one, and limit. We need to count the number of binary arrays that: • Contain exactly zero number of 0s • Contain exactly one number of 1s • Do not allow more than limit consecutive identical elements In other words, every subarray longer than limit must contain both 0 and 1, preventing long runs of the same digit. 🔹 Approach I solved this using Dynamic Programming. Idea: Track how many zeros and ones are used. Maintain the last placed digit (0 or 1). Ensure the count of consecutive digits never exceeds the limit. Use DP states to count valid configurations and apply modulo (10^9 + 7) for large results. 🔹 Key Concepts Practiced Dynamic Programming State transitions Handling constraints with limit on consecutive elements Modular arithmetic 💡 Problems like this strengthen DP intuition and constraint handling, which are very common in coding interviews. Consistency continues… 🔥 #leetcode #dsa #dynamicprogramming #codingchallenge #softwareengineering #programming #developers #learninginpublic #techjourney #750daysofcode

Built a C program to classify user input 💻 Takes a character using scanf. Checks if input is an alphabet, digit, or special character. Used ASCII value comparison for logic building. Handled both uppercase and lowercase alphabets. Applied if-else statements effectively. Improved understanding of C fundamentals. Practiced clean and structured coding. Strengthening logic step by step 🚀 Consistency is the key to mastering programming 🔥 #CProgramming #CodingJourney #LearnToCode #ProgrammingBasics #StudentDeveloper #LogicBuilding #TechSkills #VSCode #CodingLife #100DaysOfCode

🚀 Day 79 of My Coding Challenge Today I solved the Super Reduced String problem. The challenge was to repeatedly remove adjacent matching characters from a string until no such pairs remain. If the final string becomes empty, we return "Empty String". 💡 Key Idea: I used a stack-based approach to efficiently remove adjacent duplicates in O(n) time complexity. 📌 Example: Input: aaabccddd Output: abd Steps: aaabccddd → abccddd → abddd → abd 🧠 What I practiced today: Stack-based string processing Efficient character comparison Problem-solving with linear time complexity Consistency is the key — every day a little progress toward becoming a better developer. 💻🔥 #Day79 #CodingChallenge #LeetCode #Programming #ProblemSolving #DataStructures #100DaysOfCode #DeveloperJourney

📚 New article just published on SYUTHD! 🔖 Clean Architecture in .NET 10: Mastering C# 14 Discriminated Unions for Type-Safe Error Handling 🏷️ Category: C# Programming 📖 Full article → https://lnkd.in/g6DJeM36 👉 Follow our page for more tech tutorials: https://lnkd.in/gsJDptPM 💬 Telegram: https://t.me/nisethtechno 👍 Facebook: https://lnkd.in/gsKv3Dyn #CProgramming #Tech #Tutorial #Programming #TechBlog #2026

🚀 Day 10 of 100 Days LeetCode Challenge Problem: Find All Possible Stable Binary Arrays II Today’s problem is an extension of Day 9—but with optimized Dynamic Programming ⚡ 💡 Key Insight: Same constraints: Fixed number of 0s and 1s No more than limit consecutive identical elements 👉 Which means: We must carefully control streak length And efficiently count all valid combinations 🔍 Approach (Optimized DP): Use DP + Prefix Sum Optimization State includes: Count of 0s used Count of 1s used Ending with 0 or 1 💡 Optimization: Instead of recalculating ranges repeatedly, use prefix sums This reduces time complexity significantly 👉 Apply modulo (10⁹ + 7) for large answers 🔥 What I Learned Today: Same problem can have multiple levels of optimization Prefix sum is powerful in reducing DP transitions Moving from brute → DP → optimized DP is real growth 📈 📈 Challenge Progress: Day 10/100 ✅ Double digits achieved! LeetCode, Dynamic Programming, Prefix Sum, Optimization, Combinatorics, Binary Arrays, DSA Practice, Coding Challenge, Problem Solving #100DaysOfCode #LeetCode #DSA #CodingChallenge #DynamicProgramming #PrefixSum #Optimization #ProblemSolving #TechJourney #ProgrammerLife #SoftwareDeveloper #CodingLife #LearnToCode #Developers #Consistency #GrowthMindset #InterviewPrep

🚀 LeetCode POTD — 233. Number of Digit One Solved | Hard | Digit DP | Dynamic Programming 🔗 Solution Link: https://lnkd.in/gyKCsE-8 💡 Approach To solve this efficiently, I used Digit DP to count the occurrences of '1' across all numbers up to $n$ without iterating through every single number. Key Logic: State Definition: dp[idx][tight][one_count] represents the number of ways to form a valid number starting from idx, given the tight constraint and the number of 1s already placed. Tight Constraint: Ensures the number we are building doesn't exceed $n$. Transitions: For each position, iterate through digits $0$ to last_digit. If the current digit is $1$, increment the one_count for the next state. Base Case: When idx == digit.size(), return the total one_count accumulated for that specific number. Steps: Convert the integer $n$ to a string for easy digit-by-digit processing. Initialize a DP table with $-1$ for memoization. Recursively explore all possible digit combinations while tracking the frequency of digit $1$. 📈 Complexity Time: $O(\text{Number of Digits} \times 2 \times \text{Number of Digits} \times 10) \approx O(\log_{10} n)$ Space: $O(\text{Number of Digits} \times 2 \times \text{Number of Digits})$ #LeetCode #ProblemOfTheDay #DigitDP #DynamicProgramming #HardProblem #DSA #CodingJourney #ProblemSolving

Think you’re good at C programming? 💻⚡ Let’s test your logic in 15 seconds… Look carefully at the code 👀 int a = 10; printf("%d", a++ + ++a); This line confuses even experienced programmers because of how increment operators and evaluation order work in C. So what will be the output? 🤯 A) 21 B) 22 C) 23 D) Undefined Behaviour ⏳ You have 15 seconds to solve it. Comment your answer below ⬇️ (A / B / C / D) Let’s see who actually understands C increment operators. Tag a friend who thinks they’re a C expert 😏 Share this reel with your coding friends and challenge them. Follow for more Daily Coding Logic Challenges 🚀 #cprogramming #codingchallenge #codequiz #programminglogic #learnc codercommunity codingquestions

LLMs still confuse me a lot for software development. How possibly you can specify something with less information than you’d do with code? It is possible that we haven’t figured out the most concise programming language yet, but it’s definitely not natural language.

Day 20 of Programming – Rearranging Programs Today I practiced array rearrangement problems, which are very useful for improving logic building and problem-solving skills. Rearranging elements in an array helps in understanding index manipulation, swapping techniques, and efficient iteration. 🔹 What I learned today: ✅ Rearranging elements based on conditions ✅ Using loops and swapping techniques ✅ Improving array manipulation skills ✅ Writing optimized solutions 🔹 Practice Problems I Worked On: • Rearrange array in ascending and descending order • Rearrange array so positive and negative numbers alternate • Move all zeros to the end of the array • Rearrange elements so that even numbers come before odd numbers • Reverse an array using swapping technique #Programming #Java #Arrays #ProblemSolving #CodingJourney #Developer #LearningToCode