Hello Everyone!
I’m Somuya Khandelwal, back with updates from Day 1 of Week 4 in my competitive programming journey. Today, I worked on Array-based problems, which are always an exciting category. These problems demand a combination of logical thinking, efficient implementation, and a creative approach. Each challenge today pushed me to explore different ways of utilizing arrays alongside other data structures, reinforcing some key concepts.
What I Worked On Today
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Insert Delete Get Random O(1) (Medium Difficulty)
- Task: Design a data structure that supports
insert
,delete
, andgetRandom
operations in constant time. -
Approach:
- Combined a hashmap for fast lookups and an array for efficient random access.
- Maintained the index of each element in the hashmap, ensuring quick deletion by swapping the target element with the last one in the array before removing it.
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What I Learned:
- Combining multiple data structures effectively can solve problems that seem complex at first.
- Managing indices carefully is crucial for maintaining constant time operations during insertions and deletions.
- Task: Design a data structure that supports
-
Integer to Roman (Medium Difficulty)
- Task: Convert a given integer into its Roman numeral representation.
-
Approach:
- Used a greedy algorithm by repeatedly matching the largest Roman numeral values to the given integer.
- Iterated over a predefined list of numeral-value pairs in descending order to subtract values and build the Roman numeral string.
-
What I Learned:
- Greedy algorithms work well for problems with fixed mappings or repetitive patterns, like Roman numeral conversions.
- Iterating over sorted numeral-value pairs simplifies the logic and ensures the solution is straightforward and efficient.
-
Zig Zag Conversion (Medium Difficulty)
- Task: Transform a string into a zig-zag pattern across a given number of rows, then read it row by row.
-
Approach:
- Simulated the zig-zag traversal using a list of strings to represent rows.
- Traversed the string while maintaining a pointer to the current row and toggling the direction (downward or upward) as needed.
-
What I Learned:
- Simulating patterns with auxiliary data structures, like row arrays, simplifies the implementation of complex traversal problems.
- Carefully tracking state variables, like the current direction and row index, is key to solving pattern-based problems accurately.
What I Learned Today
-
Leveraging Multiple Data Structures:
- The Insert Delete Get Random O(1) problem showed how combining arrays and hashmaps can optimize performance for seemingly conflicting operations.
-
Greedy Problem Solving:
- Problems with fixed mappings or repetitive rules, like Integer to Roman, are well-suited to greedy strategies for simplicity and efficiency.
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Simulating Complex Patterns:
- For Zig Zag Conversion, using a clear representation of intermediate states (in this case, rows) makes solving pattern-based problems easier.
-
Attention to Edge Cases:
- Handling edge cases like empty strings in Zig Zag Conversion or large numbers in Integer to Roman ensures that solutions are robust and reliable.
Reflections and Challenges
The Insert Delete Get Random O(1) problem was the most challenging of the day. It took time to figure out how to manage the indices during deletions while maintaining constant time complexity. Debugging this part was tricky but rewarding once I saw the solution working efficiently. The Zig Zag Conversion problem was less complicated but still fun to implement, especially as the visual nature of the zig-zag pattern made the process intuitive and satisfying.
Looking Ahead
Tomorrow, I’ll switch gears to focus on Math-based problems, including challenges like Palindrome Number, Plus One, and Factorial Trailing Zeros. These problems will test my ability to combine mathematical reasoning with coding efficiency.
Thank you for following my journey! I’m excited to continue learning and growing in the fascinating world of competitive programming. Stay tuned for more updates!
Best regards,
Somuya
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