Mastering Binary Search Techniques for Efficient Problem Solving

“Why does this traversal not need a stack?” 🧠 Morris Traversal (Inorder) A way to traverse a binary tree using O(1) space. No recursion. No stack. Just smart use of pointers. ⚡ How it works: → If left is NULL → visit, go right → If left exists → find inorder predecessor → Create a temporary link (predecessor → current) → Move left → On return → remove link, visit, go right 💡 Core idea: We don’t use extra space… we reuse NULL pointers as a return path. 🎯 Conclusion: • Same traversal • Zero extra space • Deeper understanding of trees Took me a few dry runs to really get it. Did this concept click for you instantly or after struggle? 👀 #DataStructures #Algorithms #BinaryTree #CodingInterview #SoftwareEngineering  #LearnInPublic #ProblemSolving #DeveloperJourney #TechLearning #CodingJourney  #DSA #CodeNewbie #Programming #ComputerScience #Coding

Been spending the last few days tinkering with mini LLM prototypes. My first instinct was to explore a GNU Radio Companion (GRC) flowgraph setup to think in terms of dataflow pipelines, drawing from my SDR background. It helped reinforce a modular view of processing, but it quickly became clear that it isn’t well suited for LLM prototyping. (experimented and logged) I’ve since moved the work into standard Python notebooks, which gives a much cleaner path for iterating on tokenization, embeddings, and basic model structure. Still early days, but it’s been valuable for connecting theory with something I can actually run locally. Next steps are to better structure my learning notes, then eventually move into dataset handling and basic evaluation. DM to share your thoughts. #LLM #Learning

Growth in DSA is not just about solving problems, but about learning powerful techniques that simplify them. Day 37/100 — Data Structures & Algorithms Journey Today I’m starting a new topic — Sliding Window Technique. After working on problems like Two Pointers and Trapping Rain Water, I realized how important it is to learn patterns that help optimize solutions. Sliding Window is one such powerful technique that can turn complex nested loops into efficient linear solutions. Today’s Focus: Understanding how sliding windows work Learning when to expand and when to shrink the window Identifying problems where this pattern can be applied Building intuition before jumping into coding Why this matters? Because many array and string problems can be solved efficiently using this technique. Key Takeaways (Starting Phase): Learning patterns helps reduce problem complexity Sliding Window is useful for subarray and substring problems Understanding the concept is the first step to mastering it Strong basics lead to faster problem-solving Excited to dive deeper into this pattern and apply it to real problems 🚀 #Day37 #DSA #LeetCode #ProblemSolving #SoftwareEngineering #CodingJourney #100DaysOfCode #TechLearning #DeveloperJourney #Programming #Python #InterviewPreparation #CodingSkills #ComputerScience #FutureEngineer #TechCareers #SoftwareDeveloper #LearnInPublic #Consistency

Explain about a Depth-First Search (DFS)? Depth-First Search (DFS) is a graph traversal algorithm that explores as deep as possible along each branch before backtracking, utilizing a stack (or recursion) to keep track of nodes. It starts at a designated root node, marks nodes as visited to avoid cycles, and recursively visits unvisited neighbors. #DepthFirstSearch #DFS #DataStructures #Algorithms #GraphTheory #TreeTraversal #Coding #Programming #ComputerScience #Developer #SoftwareEngineering #LearnToCode #CodingInterview #ProblemSolving #AlgorithmDesign #DSA

I’ve unfortunately had to start learning Dart recently, and honestly, the "TheAlgorithms" repo saved me. Whenever I have to pick up a new language, I usually just go there. They update so frequently that I can always find exactly what I need to see how the logic translates. It’s basically been my shortcut for getting comfortable with Dart syntax without having to dig through endless documentation. If you’re diving into a new language and want to see real implementations, definitely check them out: https://lnkd.in/gdcMChzz #coding #dart #programming #learning #opensource

Recover the Tree ?? by providing water! Approach (Recover BST) Do inorder traversal (BST should be sorted) Track previous node If order breaks (prev > current), it’s a violation First violation: first = prev middle = current Second violation (if exists): last = current Time Complexity: O(n) → you traverse all nodes once using inorder Space Complexity: O(h) → recursion stack (h = height of tree) Worst case (skewed tree): O(n) Best case (balanced tree): O(log n) #LeetCode #DSA #DataStructures #Algorithms #Coding #Programming #binarysearchtree

Day 65 on LeetCode Sort Characters By Frequency 🔤📊✅ Today’s problem focused on combining hash maps with custom sorting. 🔹 Approach Used in My Solution The goal was to sort characters in a string based on their frequency in descending order. Key idea in the solution: • Use a hash map to count frequency of each character • Store (character, frequency) pairs in a vector • Apply custom sorting based on frequency (descending order) • Build the result string by repeating characters according to their frequency This approach efficiently organizes characters by importance (frequency). ⚡ Complexity: • Time Complexity: O(n log n) (due to sorting) • Space Complexity: O(n) 💡 Key Takeaways: • Practiced frequency counting using hash maps • Learned how to apply custom comparators in sorting • Reinforced building results based on frequency-driven logic #LeetCode #DSA #Algorithms #DataStructures #HashMap #Sorting #Strings #ProblemSolving #Coding #Programming #Cpp #STL #SoftwareEngineering #ComputerScience #CodingPractice #DeveloperLife #TechJourney #CodingDaily #100DaysOfCode #BuildInPublic #AlgorithmPractice #CodingSkills #Developers #TechCommunity #SoftwareDeveloper #EngineeringJourney

Solved a great DP problem today: Count Binary Strings Without Consecutive 1’s. Given a length n, the task is to count all distinct binary strings such that no two 1s are adjacent. Example: n = 3 → 000, 001, 010, 100, 101 → 5 n = 2 → 00, 01, 10 → 3 The key insight: 1. Strings ending with 0 can be formed by appending 0 to all valid strings of previous length. 2. Strings ending with 1 can only be formed by appending 1 to strings that previously ended with 0. This leads to a simple DP relation: 1. zero[i] = zero[i-1] + one[i-1] 2. one[i] = zero[i-1] So the pattern follows a Fibonacci-style sequence, and the problem can be solved in: O(n) time and O(1) space I enjoy how problems like this look simple at first, but the right state definition makes them very elegant. #DataStructures #Algorithms #DynamicProgramming #Coding #ProblemSolving #Cpp #Programming #SoftwareDevelopment

✅ Day 99 of 100 Days LeetCode Challenge Problem: 🔹 #999 – Available Captures for Rook 🔗 https://lnkd.in/gAw_XpbJ Learning Journey: 🔹 Today’s problem focused on simulating rook movement on a chessboard. 🔹 First, I located the position of the rook 'R' on the board. 🔹 Then, I explored all four directions: up, down, left, and right. 🔹 In each direction, I moved step-by-step until: • I hit a bishop 'B' → stop (blocked) • I found a pawn 'p' → increment count and stop • Or reached the board boundary 🔹 Summed all valid captures and returned the result. Concepts Used: 🔹 Matrix Traversal 🔹 Simulation 🔹 Direction Vectors 🔹 Boundary Checking Key Insight: 🔹 The rook’s movement is linear in 4 directions, and each direction is independent. 🔹 Early stopping (on bishop or pawn) is critical for correctness and efficiency. Complexity: 🔹 Time: O(1) (fixed 8×8 board, constant work) 🔹 Space: O(1) #LeetCode #Algorithms #DataStructures #100DaysOfCode #Python #CodingJourney #ProblemSolving #LearningInPublic

Every great idea has a "lightbulb" moment. For CodeMatrix, it wasn't in a boardroom—it was in a college seminar hall. I asked 150+ students if they were "job-ready," and almost every hand went up. But when I presented a real-world logic problem—no Google, no ChatGPT, just pure thinking—the room went silent. That silence was the spark. We realized that learning to code isn't just about memorizing syntax; it’s about mastering logic. That’s why we built CodeMatrix: a skill intelligence platform designed to measure how you actually think and solve problems. #CodeMatrix #SkillIntelligence #EdTech #CodingLife #LogicBuilding #JobReady #Programming #DataScience #Python #MERNStack #TechInnovation #SoftwareDevelopment #InterviewPrep