Robot Returns to Origin: LeetCode 657

🚀 Solved LeetCode 2463 – Minimum Total Distance Traveled Today I worked on a challenging Hard-level Dynamic Programming problem that combines Greedy + Sorting + DP with Memoization — a great exercise for strengthening problem-solving skills. 🔍 Problem Insight: We are given positions of robots and factories (with limited capacity). The goal is to assign each robot to a factory such that the total distance traveled is minimized, while respecting capacity constraints. 💡 Key Learnings: Sorting plays a crucial role in optimizing assignments Greedy intuition helps in pairing closest robots with factories Dynamic Programming is essential to explore all valid assignments efficiently Memoization avoids recomputation and improves performance ⚙️ Approach Used: Sort robots and factories based on position Use DP to decide whether to skip or use a factory Try assigning multiple robots (within capacity) and track minimum cost 📈 Complexity: Efficient solution using DP reduces exponential possibilities to manageable computation. 🔥 Takeaway: This problem is a perfect example of how combining multiple concepts leads to an optimal solution. It really helped me improve my thinking around state transitions and optimization strategies. #LeetCode #DataStructures #Algorithms #DynamicProgramming #CodingJourney #ProblemSolving #Java #CompetitiveProgramming

Day 88 on LeetCode Add Two Numbers 🔗➕💡 A classic linked list problem focusing on digit-wise addition with carry handling. 🔹 Approach Used in My Solution • Traverse both linked lists simultaneously • Maintain a carry variable for overflow • Add corresponding node values + carry • Create new nodes for result using a dummy head • Continue until both lists and carry are fully processed ⚡ Complexity: • Time Complexity: O(max(n, m)) • Space Complexity: O(max(n, m)) 💡 Key Takeaways: • Dummy node simplifies linked list construction • Carry handling is the core concept in this problem • Reinforces simulation of real-world arithmetic using linked lists 🔥 Another step forward in strengthening pointer-based problem solving. #LeetCode #DSA #Algorithms #DataStructures #LinkedList #AddTwoNumbers #CarryLogic #ProblemSolving #Coding #Programming #Cpp #STL #SoftwareEngineering #ComputerScience #CodingPractice #DeveloperLife #TechJourney #CodingDaily #Consistency #100DaysOfCode #BuildInPublic #AlgorithmPractice #CodingSkills #Developers #TechCommunity #SoftwareDeveloper #EngineeringJourney

I used to write a lot of "if let" when dealing with "Option" in Rust. It works. It’s clear. No problem with it. But after a while, it started to feel a bit... repetitive. Then I came across a small pattern that changed how I write this kind of code: Instead of this: let mut items = vec![1, 2, 3]; if let Some(x) = maybe_value { items.push(x); } I started doing this: let mut items = vec![1, 2, 3]; items.extend(maybe_value); At first, it feels almost too simple. But that’s kind of the point. No branching. No extra lines. Just: “if there’s something, add it.” And it scales really nicely: items.extend(maybe_value); items.extend(other_optional); items.extend(optional_vec); This small shift helped me think differently about "Option<T>" — not as a special case, but as a tiny collection (zero or one element). Since then, my code feels a bit more uniform… and honestly, easier to read. Nothing groundbreaking here. Just one of those small improvements that quietly make your code better over time. #Rust #CleanCode #SoftwareEngineering #RustLang #Programming #CodeQuality #DevTips #BackendDevelopment

🚀 Day 29 of 100 Days LeetCode Challenge Problem: Check if Strings Can be Made Equal With Operations I Day 29 is a short but pattern + constraint observation problem 🔥 💡 Key Insight: We can only swap characters where: 👉 j - i = 2 For a string of length 4, possible swaps: Index 0 ↔ 2 Index 1 ↔ 3 👉 That means: Positions (0,2) form one group Positions (1,3) form another group 🔍 Core Approach: 1️⃣ Group Characters Extract characters from: Even indices → [0, 2] Odd indices → [1, 3] 2️⃣ Compare Groups Sort both groups for s1 and s2 If both corresponding groups match → ✅ true Else → ❌ false 💡 Why This Works: You can rearrange freely within each group But cannot mix between groups 🔥 What I Learned Today: Limited operations define independent groups Think in terms of index grouping Small problems still test logical clarity 📈 Challenge Progress: Day 29/100 ✅ One day to 30! LeetCode, Strings, Swapping, Greedy, Pattern Recognition, Arrays, DSA Practice, Coding Challenge, Problem Solving #100DaysOfCode #LeetCode #DSA #CodingChallenge #Strings #ProblemSolving #TechJourney #ProgrammerLife #SoftwareDeveloper #CodingLife #LearnToCode #Developers #Consistency #GrowthMindset #InterviewPrep

🔥 Day 76 of #100DaysOfCode Solved Climbing Stairs (LeetCode 70) today — a classic Dynamic Programming problem 🚀 At first, it looks simple… but the real learning is in identifying the pattern behind it. 💡 Key Insight: Each step depends on the previous two steps. That’s when it clicked — this is basically a Fibonacci pattern in disguise. Instead of using recursion (which is slow), I used an optimized iterative approach to achieve: ⚡ O(n) time complexity ⚡ O(1) space complexity 📈 Result: ✅ 100% runtime ✅ 90%+ memory efficiency This problem taught me: 👉 Always look for patterns before jumping into coding 👉 Optimization matters as much as correctness Small problems → Big concepts #Day76 #LeetCode #DynamicProgramming #CodingJourney #ProblemSolving #LearnInPublic

90% of software engineering is debugging. The other 10% is writing bugs. #SoftwareEngineering #Debugging #CodingLife #Developers #Programmers #TechLife #BuildInPublic #LearnToCode #DevCommunity #EngineeringLife #AI #AIForDevelopers #Productivity #ProblemSolving #CodeNewbie

#Day358 of #1001DaysOfCode 📘 LeetCode Daily Challenge Problem: Robot Return to Origin (LeetCode 657) 💡 Approach: Simulated the robot’s movement on a 2D plane by tracking vertical and horizontal positions. Each move updates the position, and if the robot returns to (0,0), it means all movements are balanced. ⏱ Time Complexity: O(n) 🧠 Space Complexity: O(1) Consistency is key — one problem every day 🚀 #DSA #Java #LeetCode #ProblemSolving #Coding

🚀 Day 3 of 180 — Spiral Matrix III ✅ Yesterday I tried this problem. Today I solved it. Let's get into it. LeetCode 885 — Spiral Matrix III You start from a given cell (rStart, cStart) on a rows × cols grid and spiral outward. The goal is to collect all valid cells in the order you visit them. The catch — the spiral goes beyond the grid boundaries. You keep moving but only collect a cell if it actually exists inside the grid. My thought process: I used a direction array to handle movement cleanly: dir = 0 → East ( 0, +1) dir = 1 → South (+1, 0) dir = 2 → West ( 0, -1) dir = 3 → North (-1, 0) The most important pattern to notice in a spiral — step count increases after every 2 turns. East → 1 step South → 1 step West → 2 steps North → 2 steps East → 3 steps ... and so on So whenever direction is East or West, I increment the step count. At every cell — check if it's inside the grid. If yes, collect it. If no, just keep moving. The spiral never stops, we just skip invalid cells. Start → add (rStart, cStart) directly while(collected < rows * cols): if dir == East or West → step++ move 'step' times in current direction → inside grid? collect it turn clockwise → dir = (dir+1) % 4 One thing this problem taught me — sometimes the movement pattern is more important than the boundary logic. Once I saw the step pattern clearly, everything else followed. Day 3 done. 177 to go. 🔥 #180DaysDSA #Day3 #LeetCode #SpiralMatrix #Java #DSA #Arrays #Matrix #DSAJourney #CodingJourney #Programming #DataStructures #Algorithms #ProblemSolving #BuildInPublic #CodeNewbie #LearnToCode #100DaysOfCode #SoftwareDevelopment #Developer #StudentDeveloper #TechCommunity #LinkedInTech #CompetitiveProgramming

🚀 Day 560 of #750DaysOfCode 🚀 🔍 LeetCode 1320: Minimum Distance to Type a Word Using Two Fingers Today’s problem was a Hard-level DP challenge that really tested optimization and state management 🧠⚡ 💡 Problem Insight: We are typing a word using two fingers on a grid keyboard, and we need to minimize the total movement distance. 👉 Key twist: Both fingers can start anywhere (no initial cost!) At each step, we choose which finger to move ✨ Approach I Used (3D Dynamic Programming): ✔ State: dp[i][j][k] → Minimum cost after typing i characters Finger 1 at letter j Finger 2 at letter k ✔ Transition: Move Finger 1 → cost = distance(j → current char) Move Finger 2 → cost = distance(k → current char) ✔ Take minimum of both choices at every step 💻 Key Optimization: Represent characters as indices (0–25) Use grid math: row = index / 6 col = index % 6 🧠 Learning: This problem is a classic example of: 👉 State compression + decision making at each step 👉 Choosing the optimal path among multiple moving agents ⚡ Complexity: Time: O(n × 26 × 26) Space: O(n × 26 × 26) 💬 Takeaway: When multiple agents (like fingers, robots, etc.) are involved, think in terms of DP states representing positions of each agent. #LeetCode #DSA #DynamicProgramming #Java #CodingJourney #ProblemSolving #Tech #Developers #100DaysOfCode

Day 81 on LeetCode Remove Linked List Elements 🔗🧹✅ Still prioritizing consistency during busy days — and today’s problem was a solid linked list traversal & deletion practice 💯 🔹 Approach Used in My Solution The goal was to remove all nodes with a given value from a linked list. Key idea: • First, handle edge cases where head itself contains the target value • Move head forward until it points to a valid node • Then traverse the list using two pointers:   – prev → last valid node   – temp → current node • If temp->val == val → skip the node by linking prev->next • Otherwise → move both pointers forward This ensures all matching nodes are removed efficiently. ⚡ Complexity: • Time Complexity: O(n) • Space Complexity: O(1) 💡 Key Takeaways: • Practiced pointer manipulation in linked lists • Learned how to safely handle deletions, especially at head • Reinforced importance of edge case handling 🔥 Small consistent steps → strong fundamentals. #LeetCode #DSA #Algorithms #DataStructures #LinkedList #Pointers #ProblemSolving #Coding #Programming #Cpp #STL #SoftwareEngineering #ComputerScience #CodingPractice #DeveloperLife #TechJourney #CodingDaily #Consistency #100DaysOfCode #BuildInPublic #AlgorithmPractice #CodingSkills #Developers #TechCommunity #SoftwareDeveloper #EngineeringJourney