Solved Ones and Zeroes with DP on LeetCode

🚀 LeetCode POTD — 474. Ones and Zeroes 🎯 Difficulty: Medium | Topics: Dynamic Programming, 0/1 Knapsack 🔗 Solution Link: https://lnkd.in/gscqurzi Today’s #LeetCode Problem of the Day was a classic 0/1 Knapsack variation — and a great reminder of how dynamic programming helps balance multiple constraints efficiently. The task was to find the largest subset of binary strings that can be formed with at most m zeros and n ones. 🧠 My Approach: For each string, count the number of 0s and 1s. Use a 2D DP array (dp[m+1][n+1]), where dp[i][j] represents the maximum subset size possible using i zeros and j ones. Traverse in reverse (to avoid recomputation) and update using: dp[i][j] = max(dp[i][j], dp[i - zeros][j - ones] + 1); The final answer is dp[m][n]. 📈 Complexity: Time: O(len(strs) × m × n) Space: O(m × n) 💡 Takeaway: Dynamic Programming is all about breaking problems into smaller overlapping subproblems — once you see that, even “complex” constraints start falling into place logically. #LeetCode #ProblemOfTheDay #DynamicProgramming #Knapsack #DSA #CodingChallenge #ProblemSolving #C++ #SoftwareEngineering #CodingJourney #100DaysOfCode #LearningInPublic #TechCommunity

🚀 LeetCode Daily Challenge — 3726. Remove Zeros in Decimal Representation (Easy) Ever thought how a simple number like 1020030 can turn into 123? 🤔 That’s the power of string manipulation in programming — short, clean, and efficient! 💡 🧩 Problem Summary: You’re given a positive integer n. Your task: Remove all zeros from its decimal representation. Example: Input: n = 1020030  Output: 123 ✅ Hint: Convert the number to a string → remove all '0' → convert back to integer. That’s it — one-liner solution for clean data transformation. 🔥 💻 I’ve explained this problem with step-by-step approaches and code on my website 👉 algopush.com Check it out for brute force to optimized explanations! #LeetCode #LeetCodeChallenge #Coding #ProblemSolving #DSA #Programming #100DaysOfCode #CodeSeCareer #TechLearning #Developers #algopush #LeetCodeDaily #StringManipulation #LearnToCode #erdelhiboy #leetcodeeasy

🚀 Day 2 Topic: Inheritance & Polymorphism in C# 🧬 Inheritance Inheritance allows one class (child/derived class) to reuse, extend, or modify the behaviour of another class (parent/base class). 👉 It helps in code reusability, cleaner architecture, and building relationships between classes. 1️⃣ Single Inheritance A class inherits from one base class. Most common in C#. 2️⃣ Multi-level Inheritance A class inherits from a class that already inherited from another class. 3️⃣ Hierarchical Inheritance Multiple classes inherit from the same base class. 4️⃣ Multiple Inheritance (Not supported for classes) C# does not support multiple inheritance using classes (to avoid ambiguity) 5️⃣ Hybrid Inheritance A combination of multiple inheritance types, enabled using interfaces. 🎭 Polymorphism Polymorphism allows the same method to behave differently based on the object that is calling it. Two types: 1️⃣ Compile-time Polymorphism (Method Overloading) 2️⃣ Runtime Polymorphism (Method Overriding using virtual & override) ✔️ Method Overloading Based on number of parameters Based on type of parameters Based on order of parameters ✔️ Method Overriding Base class has virtual method Derived class uses override Demonstrates runtime polymorphism using base-class reference holding derived object ❓ Tricky Interview Question 👉 If method overloading happens at compile time and method overriding happens at runtime, how does the compiler decide which method to call when both seem valid? 👉 Why does C# not allow method overriding without the virtual keyword, but allows method hiding using the new keyword? 👉 Can we overload and override the same method name in one class hierarchy? If yes, how does C# decide which one to call? #DotNet #CSharp #DotNetDeveloper #DotNetCommunity #CodingChallenge #30DaysOfCode #LearnToCode #Programming

🚀 Day 74 of #100DaysOfLeetcodeHard — CF (1500) rated: Mortal Kombat Tower (Dynamic Programming) Today’s problem was from Codeforces, and it involved an interesting turn-based DP setup that required carefully tracking alternating player moves and minimizing skip usage. My Submission:https://lnkd.in/gFzAiGYs 🧩 Problem Summary: There are n bosses in a tower — each either easy (0) or hard (1). You and your friend take turns defeating them in order, where each turn allows defeating 1 or 2 bosses. Your friend starts first, but he can only defeat easy bosses — for hard ones, he uses skip points. The goal is to minimize the total number of skip points used. 💡 Key Idea: We can model this using Dynamic Programming with two states: dp[i][turn] → the minimum skips needed starting from boss i, where turn = 0 (friend) or 1 (you). Transitions: If it’s your friend’s turn, add skip cost for hard bosses and choose 1 or 2 bosses to fight. If it’s your turn, just move forward 1 or 2 bosses (no skip cost). 🧠 Approach: 1️⃣ Use recursion with memoization or bottom-up DP. 2️⃣ Alternate between turns while exploring all valid moves (1 or 2 bosses). 3️⃣ Return the minimal skip total after processing all bosses. 📈 Complexity: Time: O(n) per test case Space: O(n) A fun and clean two-state dynamic programming problem — small transitions, elegant optimization! #Codeforces #DynamicProgramming #Algorithms #ProblemSolving #CompetitiveProgramming #100DaysOfCode #LearningEveryday

💡 Functions — The Building Blocks of Clean Code 🧠 In programming, functions are more than just reusable blocks of code — they’re the foundation of structured and efficient software. 💻 A function lets developers break complex problems into smaller, logical parts, making code easier to read, test, and maintain. 🔍 Why functions matter: Encourage code reusability Improve debugging and testing Help maintain modular and clean code Make collaboration in large projects smoother 🚀 Mastering functions is the first big step from writing code to thinking like a developer. #Technology #Programming #Developers #Functions #CleanCode #SoftwareEngineering #Python #Learning

💯 Day 7/100: Dynamic Programming — LeetCode 474 Today’s challenge was a classic optimization puzzle: selecting the largest subset of binary strings under strict limits on the number of 0s and 1s. It’s essentially a two-dimensional knapsack problem, where each string consumes a portion of your limited resources. The key breakthrough was realizing that you need to traverse the DP table in reverse to preserve state dependencies. Each update reflects the best outcome when including a new string, without overwriting previous possibilities. This problem sharpened my understanding of multi-dimensional constraints and reinforced the importance of state reuse in dynamic programming. It’s a great reminder that even medium-difficulty problems can hide deep algorithmic insights. Onward to Day 8 — the grind continues. #100DaysOfCode #LeetCode #DynamicProgramming #TechJourney #ScarCodes #ProblemSolving #CodeChallenge #SoftwareEngineering

𝐇𝐨𝐰 𝐝𝐨 𝐚𝐬𝐬𝐨𝐜𝐢𝐚𝐭𝐞𝐝 𝐭𝐲𝐩𝐞𝐬 𝐬𝐢𝐦𝐩𝐥𝐢𝐟𝐲 𝐠𝐞𝐧𝐞𝐫𝐢𝐜 𝐩𝐫𝐨𝐠𝐫𝐚𝐦𝐦𝐢𝐧𝐠? In generic programming, we often need to define a link between related types. For instance, modeling a repository that produces a certain kind of entity. Associated types make this possible by expressing that relationship directly within a trait or concept. This allows the compiler to enforce consistency without requiring extra template or generic parameters. Without associated types, we’d end up with more verbose and repetitive code that’s harder to read and maintain. 🔹 In C++, associated types are usually modeled using nested type aliases combined with concepts. In the example below, the 𝙍𝙚𝙥𝙤𝙨𝙞𝙩𝙤𝙧𝙮 concept requires any type 𝙏 to define a nested type 𝙀𝙣𝙩𝙞𝙩𝙮 and to provide a 𝙂𝙚𝙩() method returning that 𝙀𝙣𝙩𝙞𝙩𝙮. This expresses a clear compile-time relationship between the repository and its data type. The compiler verifies this contract, ensuring that 𝙋𝙧𝙞𝙣𝙩𝙀𝙣𝙩𝙞𝙩𝙮() can safely call 𝙂𝙚𝙩() and handle the returned type. 🔸 In Rust, associated types are built directly into the language and form part of a trait’s definition. Instead of defining a nested alias, the trait declares an internal type that each implementation specifies. This makes the relationship between the trait and its concrete type explicit, without repeating type parameters or extra syntax. ⚖️ In short, both C++ and Rust can represent relationships between types. Understanding associated types can help create cleaner and more expressive generic abstractions. #CppToRustJourney #ModernCpp #RustLang #GenericProgramming #SoftwareArchitecture

In programming, particularly in object-oriented programming, a mixin is a class that provides methods and properties to other classes, without being their direct parent class in a traditional inheritance hierarchy. Mixins are designed to be "mixed in" with other classes, adding specific functionalities or behaviors to them. In Go, while there isn't a direct language feature explicitly called "mixins" , the concept can be effectively implemented using struct embedding and interfaces. This approach allows for the reuse of fields and methods across different structs, mimicking the behavior of mixins. How do we do that ? Struct Embedding: You can embed a struct (the "mixin" struct) within another struct. This makes the fields and methods of the embedded struct directly accessible as if they were part of the outer struct. The mixin pattern (implemented via struct embedding) in Go is primarily used for code reuse of common functionalities across otherwise unrelated structs and for managing cross-cutting concerns. #golang #backendDevelopment #mixins #learnfun #goLangTips

Every great programmer knows that coding isn’t just about syntax - it’s about logic, problem-solving, and efficiency. These 5 essential algorithms will help you think smarter, code faster, and build a strong foundation for any programming challenge.👨🏽💻👍🏼 #programmingbasics #codingskills #learntocode #algorithms #techeducation #problemsolving #programmingtips #logicbuilding #codingwithSCOPE #scopesumago 

What if adding and subtracting numbers could lead to the same target? ➕➖ Let’s decode how. Hey everyone! Day 319 of my 365-day coding journey brought me face-to-face with one of the most interesting dynamic programming problems — LeetCode 494: Target Sum. This problem is a fantastic blend of recursion, logic, and optimization through DP. Let’s dive in. ⚡ 🛠️ The Problem You’re given an integer array nums and a target value.   By assigning either a “+” or “−” sign before each number, the goal is to count how many different expressions can evaluate to the given target. Example: nums = [1, 1, 1, 1, 1], target = 3 → Output = 5   (There are 5 ways to assign symbols to reach 3.) 🎯 The Approach I solved this using two approaches — starting from the basics and optimizing it further. Solution 1: Recursion (Brute Force) I used a recursive function that tries adding and subtracting each element to explore all possible combinations. This clearly demonstrates the problem’s structure but leads to exponential time complexity (O(2^N)). Solution 2: 1D Dynamic Programming To optimize, I transformed the problem into a subset-sum variation. By using a 1D DP array, I tracked how many ways we can achieve each possible sum. This reduced the complexity to O(N * Sum), making it scalable for larger inputs. 🧠 Key Takeaways 💡 Many DP problems start with recursion — identifying overlapping subproblems helps in building optimized solutions.   🧩 Transforming a problem (like Target Sum → Subset Sum) can often reveal a cleaner, more efficient path.   ⚙️ 1D DP arrays save space without compromising clarity or performance.  💬 Challenge for You! How do you usually transition from recursion to dynamic programming? What’s your mental model for identifying patterns like this? 📺 Watch My Full Walkthrough I explain both the recursive and optimized DP solutions step-by-step in my latest video: https://lnkd.in/gE9Ma7uA 🔥 Join the Conversation If you’re exploring dynamic programming or solving LeetCode challenges daily, let’s connect and grow together! 🚀 #CodingJourney #DSA #DynamicProgramming #LeetCode #ProblemSolving #TargetSum #Recursion #Algorithms #CodeNewbies #DeveloperLife #Programming #LearningEveryDay #365DaysOfCode