DAY 8 Exploring the Power of Hashmaps

Hello Everyone!

I am Somuya Khandelwal, back with updates from Day 3 of Week 2 of my competitive programming journey. Today, I shifted focus to Hashmaps, one of the most versatile data structures in problem-solving. Hashmaps simplify the process of storing and retrieving data efficiently, making them essential for a wide variety of problems.

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What I Worked On Today

1. Group Anagrams (Medium Difficulty)

   • Group strings that are anagrams of each other into separate lists.
   • Approach:
     • Used a hashmap with sorted strings as keys and grouped words with the same key.
   • What I Learned:
     • Sorting or frequency counting can be effective ways to generate unique keys for grouping.
     • Hashmaps make grouping problems intuitive and efficient.

2. Happy Number (Easy Difficulty)

   • Determine if a number eventually reaches 1 by replacing it repeatedly with the sum of the squares of its digits.
   • Approach:
     • Used a hashmap to detect cycles in the iterative process.
     • If a number repeats, it’s not a happy number; otherwise, it converges to 1.
   • What I Learned:
     • Hashmaps can be used effectively for cycle detection in iterative processes.
     • Problems with repeated computations often require memoization or cycle detection techniques.

3. Contains Duplicate II (Medium Difficulty)

   • Check if a number in the array is repeated within a given range k.
   • Approach:
     • Used a sliding window technique with a hashmap to track indices of recently seen numbers.
   • What I Learned:
     • Combining sliding windows with hashmaps is a powerful approach for range-based problems.
     • Efficient data storage and retrieval are crucial for handling large input arrays.

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What I Learned Today

1. Hashmaps for Grouping and Counting:

   • Problems like Group Anagrams and Happy Number demonstrated the versatility of hashmaps in organizing data for efficient retrieval and processing.

2. Cycle Detection Using Hashmaps:

   • Hashmaps can track visited states, making them ideal for detecting cycles in iterative problems.

3. Sliding Window with Hashmaps:

   • The combination of a sliding window and hashmaps optimizes range-based searches while maintaining clarity in implementation.

4. Handling Edge Cases:

   • For problems like Contains Duplicate II, considering small input sizes and edge conditions (e.g., k being larger than the array) ensures robust solutions.

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Reflections and Challenges

The Group Anagrams problem was a delightful challenge, as it pushed me to think about how to generate unique keys for grouping efficiently. The Happy Number problem required patience to debug cycle detection, but the concept of using hashmaps for tracking states felt incredibly useful.

Overall, today’s problems reinforced how hashmaps are indispensable for efficient problem-solving, especially in scenarios involving quick lookups and grouping.

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Looking Ahead

Tomorrow, I’ll be working on Binary Tree problems, including Path Sum, Sum Root to Leaf Numbers, and Binary Tree Maximum Path Sum. These tasks will require a solid understanding of tree traversal and recursion.

Thank you for following along on my journey! Stay tuned for more insights and updates as I continue to learn and grow in competitive programming.