Understanding Dynamic Programming with Aditya Verma

On Day 295 of my #300daysofcode challenge, I'm sharing my solution to LeetCode Problem 981, "Time Based Key-Value Store." This problem requires designing a specialized data store for version control. My video provides a clear walkthrough of the optimal design: using a HashMap to quickly find the key and then applying Binary Search on the timestamps to retrieve the correct historical value. This is a valuable skill for advanced data structure implementation and system design interviews. #DataStructures #Algorithms #LeetCode #CodingInterview #Programming #SystemDesign #300daysofcode

🚀 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 34 of #100DaysOfLeetCode Today’s Challenge: 83. Remove Duplicates from Sorted List 🔹 Problem: Given the head of a sorted linked list, delete all duplicates such that each element appears only once. Return the linked list sorted as well. Key Insight: Because the list is already sorted, duplicates will always be adjacent—this allows us to remove them in a single pass using pointer manipulation. 🔍 Approach: Traverse the list using a pointer. Compare current node with the next node. If values are equal → skip the next node by linking to the next of next. Otherwise → move forward. 🕒 Time Complexity: O(n) 📦 Space Complexity: O(1) ✨ Key Takeaway: This problem reinforces the importance of pointer manipulation and understanding how memory references work in linked lists. A simple check can eliminate duplicates efficiently without using extra space. Link:[https://lnkd.in/gsjVxHXM] #100DaysOfLeetCode #Day34 #LeetCode #ProblemSolving #DSA #Algorithms #LinkedList #CodingChallenge #CodeNewbie #InterviewPreparation #SoftwareEngineering #Programming #CodingCommunity #TechCareers #CareerGrowth #ArjunInfoSolution

🔍Concepts in 60 Seconds: Ep-5 Ever noticed how one word can mean different things depending on the situation? That’s exactly what Polymorphism is in Object-Oriented Programming (OOP)! The term “Polymorphism” literally means “many forms”, it allows the same function or method to behave differently based on the object that’s calling it. ⁉️ Why it’s important: -Makes code flexible and dynamic -Supports reusability and extensibility -Allows us to use one interface for different underlying data types 💡 Types of Polymorphism: 1. Compile-time Polymorphism (Static Binding): Achieved using method overloading — same method name, different parameters. 2. Run-time Polymorphism (Dynamic Binding): Achieved using method overriding — child class redefines a method of the parent class. ⚙️ In simple terms: Polymorphism is like a single command that knows how to behave differently depending on who’s using it. 🧠 Next Wednesday: Let’s simplify complexity with Abstraction — showing only what’s necessary and hiding the chaos behind clean design. 🕶️ #ConceptsIn60Seconds #OOP #Polymorphism #DynamicBinding #MethodOverloading #MethodOverriding #CodeReusability #ProgrammingConcepts #ObjectOrientedProgramming #TechLearning #WednesdayWisdom #LearnWithNatlie #CodeBetter #OOPS  #StudentLearning #CSFundamentals #TechWednesdays #CSEConcepts #OOPSeries #CodingConcepts #ProgrammingBasics

🚀 Today I practiced one of the most important Linked List problems — Sorting a Linked List efficiently. Instead of converting the list into an array (which increases extra memory usage), I implemented Merge Sort directly on the linked list. 🔍 Why Merge Sort for Linked List? Linked lists don’t have random indexing. Merge Sort works naturally by rearranging pointers. No need of extra space for arrays. 🎯 Result: Time Complexity: O(n log n) Space Complexity: O(log n) due to recursion Stable & Clean Solution 💡 What I learned: Using slow–fast pointer technique to find the middle of the list. Splitting the linked list into two halves efficiently. Merging two sorted linked lists without extra memory. Writing cleaner, structured logic improves readability a LOT. Everyday small progress really compounds. Trying to solve at least one challenge daily 💪 #ConsistencyWins #leetcode #dsa #linkedlist #algorithms #programming #cpp  #softwareengineering #codingjourney #learningeveryday #100daysofcode

💯 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

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 

💻 Day 33 of #100DaysOfLeetCode 🔗 Today’s Challenge: Intersection of Two Linked Lists 🔹 Problem: Find the node at which two singly linked lists intersect. If the two linked lists do not intersect, return null. This is a classic problem to test understanding of linked list structure, pointer manipulation, and memory reference. 🔍 Naive Approach: Use nested loops to compare each node in list A with each node in list B. Time Complexity: O(m × n) Not efficient and not recommended for large lists. 🚀 Optimized Two-Pointer Approach: Use two pointers that traverse both lists. When one pointer reaches the end, redirect it to the head of the other list. If they intersect, the pointers will meet at the intersection node. If not, both will reach null simultaneously. 🕒 Time Complexity: O(m + n) 📦 Space Complexity: O(1) Link:[https://lnkd.in/gyTB4GqG] #100DaysOfLeetCode #Day33 #LeetCode #ProblemSolving #Algorithms #DSA #LinkedList #CodingChallenge #CodeNewbie #InterviewPreparation #SoftwareEngineering #Programming #CodingCommunity #TechCareers #CareerGrowth #ArjunInfoSolution

🚀 Day 5 – LeetCode Problem Solving Journey 💻 Today’s problem was “Remove Element”, an easy-level array problem that focuses on in-place modification — a key concept for memory-efficient programming. Problem Statement: Given an array nums and a value val, remove all occurrences of val in-place and return the number of elements that are not equal to val. The relative order of elements may be changed. Example 1: Input: nums = [3,2,2,3], val = 3 Output: 2, nums = [2,2,_,_] Example 2: Input: nums = [0,1,2,2,3,0,4,2], val = 2 Output: 5, nums = [0,1,4,0,3,_,_,_] 🧠 Concept Used: Two-pointer technique In-place replacement of valid elements Time Complexity: O(n) Space Complexity: O(1) Every problem builds consistency, clarity, and confidence — one step closer to mastering DSA. 💪 #LeetCode #Day5 #ProblemSolving #CodingJourney #100DaysOfCode #Python #DSA #Programming #DevelopersCommunity #SoftwareEngineering #TechLearning #CareerGrowth #ipec #ipec30

🟩 Day 56 of Leetcode 150 days challenge – Add Two Numbers (LeetCode #2) #LeetCode150 #Day56 #AddTwoNumbers #LinkedList #DataStructures #Algorithms #ProblemSolving #LeetCode #CodingChallenge #CPP #Programming #150DaysOfCode #LearnDSA #SDEPrep #CodingJourney 🔹 Problem: Given two non-empty linked lists representing two non-negative integers. The digits are stored in reverse order, and each node contains a single digit. Add the two numbers and return the sum as a linked list. Example: Input: (2 -> 4 -> 3) + (5 -> 6 -> 4) Output: 7 -> 0 -> 8 Explanation: 342 + 465 = 807 🧠 Approach: We perform the addition just like we do on paper: Initialize a carry as 0. Traverse both lists simultaneously. Add the digits from both lists + carry. Store the last digit in a new node. Update carry = sum / 10. Continue until both lists are done and carry is 0. 🕒 Time Complexity: O(max(M, N)) 💾 Space Complexity: O(max(M, N)) 🏁 Key Takeaway: Linked list addition is a classic problem that strengthens your understanding of pointer manipulation, carry handling, and edge cases like unequal list lengths. 💡