Bulls and Cows Problem Solution with Frequency Arrays

Some problems are not about moving elements, but about understanding structure. Day 22/100 — Data Structures & Algorithms Journey Today’s Problem: Rotate List This problem helped me understand how linked lists behave when we manipulate their structure efficiently. Approach: Instead of rotating the list step by step (which is inefficient), I first calculated the length of the list. Then, I connected the tail to the head to form a circular linked list. By finding the correct breaking point using k % length, I was able to determine the new head and tail of the rotated list. At each step: Convert list into a circular structure Find the new tail position Break the circle to form the rotated list Key Takeaways: Understanding structure is more important than brute force Modulo operation helps avoid unnecessary rotations Linked list problems often become easier when visualized as cycles Efficient thinking leads to cleaner and faster solutions This problem strengthened my understanding of linked list manipulation and optimization techniques. #DSA #LeetCode #LinkedList #ProblemSolving #SoftwareEngineering #CodingJourney #100DaysOfCode #TechLearning #DeveloperJourney #Programming #Python #InterviewPreparation #CodingSkills #ComputerScience #FutureEngineer #TechCareers #SoftwareDeveloper #LearnInPublic #OpenToWork

Consistency in DSA beats intensity every single time. Day 39/100 — Data Structures & Algorithms Journey Today I solved Best Time to Buy and Sell Stock, and it gave me a strong introduction to the Sliding Window / Greedy approach. Instead of checking all possible buy-sell pairs, I learned how to track the minimum price and calculate profit efficiently in a single pass. Today’s Focus: Understanding how to track minimum values dynamically Applying a one-pass optimized approach Avoiding brute force (O(n²)) solutions Strengthening problem-solving intuition Why this matters? Because recognizing patterns like this helps reduce complexity and improves performance. Key Takeaways: Optimal solutions often come from simple observations Tracking values efficiently can solve problems faster Sliding Window / Greedy thinking reduces unnecessary work Clarity in approach leads to clean code Learning to simplify problems step by step 🚀 #Day39 #DSA #LeetCode #ProblemSolving #SoftwareEngineering #CodingJourney #100DaysOfCode #TechLearning #DeveloperJourney #Programming #Python #InterviewPreparation #CodingSkills #ComputerScience #FutureEngineer #TechCareers #SoftwareDeveloper #LearnInPublic #Consistency

Growth in DSA is not just about solving problems, but about choosing the right approach efficiently. Day 34/100 — Data Structures & Algorithms Journey Today’s problem was Container With Most Water, and it strengthened my understanding of the Two Pointer pattern. At first glance, this problem looks like it requires checking all possible pairs, but that would be inefficient. The real learning was understanding how to reduce complexity using a smarter approach. Today’s Focus: Applying Two Pointer technique effectively Understanding why moving the smaller height pointer works Avoiding brute force solutions Optimizing time complexity from O(n²) to O(n) Why this matters? Because identifying the right pattern can drastically improve performance and make solutions scalable. Key Takeaways: Not all problems need brute force — optimization is key Two Pointer technique can solve problems efficiently in linear time Understanding the logic behind pointer movement is crucial Pattern recognition leads to faster problem-solving This problem helped me see how a simple idea can lead to a highly optimized solution. Learning to think smarter, not harder 🚀 #Day34 #DSA #LeetCode #ProblemSolving #SoftwareEngineering #CodingJourney #100DaysOfCode #TechLearning #DeveloperJourney #Programming #Python #InterviewPreparation #CodingSkills #ComputerScience #FutureEngineer #TechCareers #SoftwareDeveloper #LearnInPublic #Consistency

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

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Some problems are not about searching everywhere, but about searching smartly. Day 26/100 — Data Structures & Algorithms Journey Today’s Problem: Two Sum II (Input Array is Sorted) This problem helped me understand how sorting can simplify searching and improve efficiency. Approach: Since the array is already sorted, I used the Two Pointer technique instead of brute force. I placed one pointer at the beginning and another at the end of the array. By adjusting pointers based on the sum: If the sum is too small → move left pointer If the sum is too large → move right pointer If equal → solution found This approach avoids unnecessary checks and works efficiently in a single pass. Key Takeaways: Sorted data can unlock optimized solutions Two Pointer technique reduces complexity significantly Thinking smart is better than brute force Efficient algorithms improve performance and clarity This problem strengthened my understanding of pointer techniques and optimization strategies. #DSA #LeetCode #TwoPointers #ProblemSolving #SoftwareEngineering #CodingJourney #100DaysOfCode #TechLearning #DeveloperJourney #Programming #Python #InterviewPreparation #CodingSkills #ComputerScience #FutureEngineer #TechCareers #SoftwareDeveloper #LearnInPublic #OpenToWork

Growth in DSA is not just about understanding problems, but about applying that understanding to solve them. Day 36/100 — Data Structures & Algorithms Journey After spending time learning the intuition behind Trapping Rain Water, today I focused on actually solving it. This problem pushed me to combine visualization with logic and apply an optimized approach. Instead of brute force, I used the Two Pointer technique to efficiently calculate the trapped water. Today’s Focus: Applying Two Pointer approach to a complex problem Using left max and right max concepts effectively Translating understanding into working code Improving problem-solving confidence Why this matters? Because solving a problem after deeply understanding it builds real confidence and clarity. Key Takeaways: Understanding + Implementation = Mastery Optimized thinking reduces time and space complexity Complex problems become manageable with the right approach Consistency in practice leads to improvement From learning → to understanding → to solving 🚀 #Day36 #DSA #LeetCode #ProblemSolving #SoftwareEngineering #CodingJourney #100DaysOfCode #TechLearning #DeveloperJourney #Programming #Python #InterviewPreparation #CodingSkills #ComputerScience #FutureEngineer #TechCareers #SoftwareDeveloper #LearnInPublic #Consistency

Handling Time Data: Logic over Strings. Today I worked on a common challenge: comparing time values like '7:15' and '10:30' stored in a list.The Problem: Standard string comparison can be unreliable (e.g., '7:15' vs '10:30'), and using float numbers leads to mathematical inaccuracies.The Solution: I converted all time entries into a single unit — Total Minutes from the start of the day (hours * 60 + minutes).This transformation turns time-strings into simple integers, creating a robust and scalable logic for sorting and filtering. A solid foundation is everything, whether it's infrastructure or code. 🛡️🦾#Python #Coding #ProblemSolving #SoftwareEngineering #Backend #Summerson

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

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