Longest Common Prefix Solution with Iterative Reduction

Some problems are not about choosing one path, but about validating all possible paths. Day 20/100 — Data Structures & Algorithms Journey Today’s Problem: Interleaving String This problem challenged me to think in terms of combining two inputs to form a third one while maintaining order. Approach: I used Dynamic Programming to track whether a substring of s3 can be formed using substrings of s1 and s2. At each step, I checked whether the current character in s3 could come from s1 or s2, and built the solution progressively. Key Takeaways: Dynamic Programming helps manage multiple choices efficiently Thinking in terms of states simplifies complex problems Validating combinations is a key problem-solving skill This problem strengthened my understanding of DP and string manipulation. #DSA #LeetCode #DynamicProgramming #ProblemSolving #SoftwareEngineering #CodingJourney #100DaysOfCode #TechLearning #DeveloperJourney #Programming #Python #InterviewPreparation #CodingSkills #ComputerScience #JobReady #FutureEngineer #TechCareers #SoftwareDeveloper #LearnInPublic #OpenToWork

Some problems are not about removing elements, but about removing them wisely. Day 25/100 — Data Structures & Algorithms Journey Today’s Problem: Remove K Digits This problem helped me understand how greedy decisions can lead to an optimal solution. Approach: Instead of trying all possible combinations, I used a stack-based greedy approach. While traversing the number, I removed digits that were larger than the current digit to make the number as small as possible. If there were still digits left to remove, I removed them from the end. Finally, I handled leading zeros to get the correct result. At each step: - Remove larger digits from stack - Add current digit - Handle remaining removals - Remove leading zeros Key Takeaways: Greedy algorithms help make optimal local decisions Stack is useful for maintaining order Small changes can significantly impact the final result Thinking step-by-step avoids unnecessary complexity This problem strengthened my understanding of greedy strategies and stack usage. #DSA #LeetCode #Greedy #Stack #ProblemSolving #SoftwareEngineering #CodingJourney #100DaysOfCode #TechLearning #DeveloperJourney #Programming #Python #InterviewPreparation #CodingSkills #ComputerScience #FutureEngineer #TechCareers #SoftwareDeveloper #LearnInPublic #OpenToWork

Sometimes progress is not about solving new problems, but about revisiting what we’ve learned. Day 28/100 — Data Structures & Algorithms Journey (Revision Day) Today, I focused on revising key problems and concepts from the past few days to strengthen my understanding. Topics Revised: - Dynamic Programming (Interleaving String) - Bit Manipulation (Single Number II) - Linked List (Rotate List) - String Matching (Bulls and Cows) - Greedy + Stack (Remove K Digits) - Two Pointer Technique (Two Sum II) - Concurrency (Print Zero Even Odd) What I focused on: - Understanding the intuition behind each solution - Revisiting optimized approaches - Practicing dry runs without looking at code - Strengthening problem-solving patterns Key Takeaways: Revision helps convert knowledge into long-term memory Recognizing patterns is more important than memorizing solutions Confidence grows when concepts are revisited Consistency is the real key to improvement This revision helped me connect multiple concepts and improve my problem-solving clarity. #DSA #LeetCode #Revision #ProblemSolving #SoftwareEngineering #CodingJourney #100DaysOfCode #TechLearning #DeveloperJourney #Programming #Python #InterviewPreparation #CodingSkills #ComputerScience #FutureEngineer #TechCareers #SoftwareDeveloper #LearnInPublic #OpenToWork

Sometimes, solving a problem is about managing a window efficiently. Day 17/100 — Data Structures & Algorithms Journey Today’s Problem: Longest Substring Without Repeating Characters Approach: I used the sliding window technique to maintain a substring without duplicate characters. As I expanded the window, I checked for duplicates. If a duplicate was found, I shrank the window from the left until all characters were unique again. This allowed me to efficiently track the maximum length of a valid substring. Key Takeaways: - Sliding window helps optimize substring problems - Managing duplicates efficiently is crucial - Expanding and shrinking dynamically improves performance This problem strengthened my understanding of window-based algorithms. #DSA #LeetCode #SlidingWindow #ProblemSolving #SoftwareEngineering #CodingJourney #100DaysOfCode #TechLearning #DeveloperJourney #Programming #Python #InterviewPreparation #CodingSkills #ComputerScience #JobReady #FutureEngineer #TechCareers #SoftwareDeveloper #LearnInPublic #OpenToWork

Leveling up my problem-solving skills with consistent practice 💻🔥 Compiled my LeetCode solutions in Python covering Linked Lists, Trees, Graphs, Arrays, and more. This collection reflects my learning journey, coding consistency, and understanding of data structures & algorithms. Check it out and keep grinding 🚀 #Consistency #CodingJourney #LeetCode #DSA #PythonProgramming #Coding #Programming #DataStructures #Algorithms #ProblemSolving #TechSkills #SoftwareDeveloper #CodingPractice #InterviewPrep #100DaysOfCode #DevelopersLife #TechJourney #PlacementPreparation

Some problems are not about matching values, but about matching them correctly. Day 23/100 — Data Structures & Algorithms Journey Today’s Problem: Bulls and Cows This problem was a great exercise in handling comparisons carefully and avoiding double counting. Approach: I divided the problem into two parts: First, I counted the "bulls" — digits that match in both value and position. Then, for the remaining digits, I used frequency counting to find "cows" — digits that exist but are in the wrong position. By using two arrays to track digit frequencies, I ensured that duplicate values were handled correctly. At each step: Identify exact matches (bulls) Store unmatched digits Count common digits using frequency (cows) Key Takeaways: Separating logic into steps simplifies complex problems Avoiding double counting is crucial in matching problems Frequency arrays are very useful for digit-based problems Clear thinking leads to accurate results This problem improved my understanding of string comparison and counting techniques. #DSA #LeetCode #Strings #ProblemSolving #SoftwareEngineering #CodingJourney #100DaysOfCode #TechLearning #DeveloperJourney #Programming #Python #InterviewPreparation #CodingSkills #ComputerScience #FutureEngineer #TechCareers #SoftwareDeveloper #LearnInPublic #OpenToWork

Some problems are not about finding a solution, but about maintaining the right window. Day 14/100 — Data Structures & Algorithms Journey Today’s Problem: Minimum Window Substring This problem introduced me to one of the most powerful techniques in DSA — the Sliding Window. Approach: I used two pointers to create a dynamic window over the string. The idea was to expand the window until it contains all required characters, and then shrink it to find the smallest valid substring. By maintaining character counts and tracking when all requirements are satisfied, I was able to efficiently identify the minimum window. Key Takeaways: Sliding window helps reduce unnecessary computations Expanding and shrinking dynamically is key to optimization Tracking conditions correctly is crucial for correctness This problem significantly improved my understanding of window-based algorithms. #DSA #LeetCode #SlidingWindow #ProblemSolving #SoftwareEngineering #CodingJourney #100DaysOfCode #TechLearning #DeveloperJourney #Programming #Python #InterviewPreparation #CodingSkills #ComputerScience #JobReady #FutureEngineer #TechCareers #SoftwareDeveloper #LearnInPublic #OpenToWork

🌳 Cracked another tree problem on LeetCode! Problem: Diameter of Binary Tree Concept: Depth-First Search (DFS) + Height Calculation Today I solved a classic problem where the goal is to find the longest path between any two nodes in a binary tree (measured in edges). Key Insight: ->Instead of finding paths directly, compute the height of left and right subtrees for every node. ->The diameter at any node = left height + right height. ->Keep updating the maximum as you traverse! What I learned: ->Think in terms of subproblems (heights) instead of full paths ->Recursion can simplify complex tree problems ->Always clarify whether the problem counts edges or nodes Complexity: ->Time: O(n) ->Space: O(h) Implemented using Python with a clean DFS approach. Every small problem like this strengthens my foundation in Data Structures & Algorithms 💪 #LeetCode #DSA #BinaryTree #Python #CodingJourney #TechLearning #ProblemSolving FACE Prep Campus Geetha Dinesh

Sometimes, organizing the data first makes the solution much simpler. Day 18/100 — Data Structures & Algorithms Journey Today’s Problem: Merge Intervals Approach: I started by sorting the intervals based on their starting values. Then, I iterated through the list and compared each interval with the last merged interval. If there was an overlap, I merged them by updating the end value. Otherwise, I added it as a new interval. Key Takeaways: - Sorting simplifies interval-based problems - Greedy approach helps in making optimal local decisions - Understanding overlap conditions is key This problem helped me understand how combining sorting and greedy logic leads to efficient solutions. #DSA #LeetCode #Intervals #Greedy #ProblemSolving #SoftwareEngineering #CodingJourney #100DaysOfCode #TechLearning #DeveloperJourney #Programming #Python #InterviewPreparation #CodingSkills #ComputerScience #JobReady #FutureEngineer #TechCareers #SoftwareDeveloper #LearnInPublic #OpenToWork

Sometimes, solving a problem efficiently is about choosing the right direction. Day 15/100 — Data Structures & Algorithms Journey Today’s Problem: Merge Sorted Array Approach: The goal was to merge two sorted arrays into one, without using extra space. Instead of merging from the beginning, I used a two-pointer approach starting from the end of both arrays. By comparing elements from the back and placing the larger one at the last available position, I avoided overwriting existing values and achieved an efficient in-place solution. Key Takeaways: Thinking in reverse can simplify in-place problems Two-pointer technique is powerful for sorted data Avoiding extra space improves efficiency Learning to think differently with each problem. #DSA #LeetCode #ProblemSolving #SoftwareEngineering #CodingJourney #100DaysOfCode #TechLearning #DeveloperJourney #Programming #Python #InterviewPreparation #CodingSkills #ComputerScience #JobReady #FutureEngineer #TechCareers #SoftwareDeveloper #LearnInPublic #OpenToWork