Hello Everyone!
The final day of Week 10 was all about Arrays and Two-Pointer Techniques, with tasks that emphasized simplicity and efficiency. These problems combined traversal, modification, and reorganization, challenging me to think systematically and optimize every step. It was the perfect conclusion to a week of foundational problem-solving.
How the Day Played Out
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String Compression (Medium Difficulty)
- Modify a string in place by compressing consecutive characters, appending their count when greater than one.
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The Strategy:
- Used two pointers:
- One pointer (
write) to track the position for writing compressed characters. - Another pointer (
read) to traverse the string, counting consecutive occurrences. - Updated the string in place by appending the character and its count, ensuring no extra space was used.
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The Fun Part:
- Watching the compressed string build dynamically was like solving a puzzle where every move brought the solution closer.
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Move Zeroes (Easy Difficulty)
- Rearrange an array so all
0s are moved to the end, preserving the order of non-zero elements. -
The Strategy:
- Applied a two-pointer approach:
- One pointer (
nonZeroPos) to track the next position for a non-zero element. - The other pointer (
i) to iterate through the array, swapping non-zero elements into place. - Completed the task in a single pass with constant space.
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The Fun Part:
- Watching the zeros “bubble” to the end while preserving the order felt like organizing a chaotic queue into perfect order.
- Rearrange an array so all
What Made Today Special
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Two Pointers at Work:
- Both problems showcased how two-pointer techniques can optimize traversal and modification tasks efficiently.
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In-Place Simplicity:
- Modifying data directly without extra memory emphasized the value of space-efficient solutions in real-world scenarios.
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Organized Problem-Solving:
- Breaking tasks into logical steps, such as counting, writing, and swapping, made the solutions intuitive and rewarding.
Key Takeaways
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Two Pointers Simplify Reorganization:
- Problems like Move Zeroes demonstrate how to tackle reordering tasks effectively with minimal overhead.
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In-Place Modifications Save Space:
- Tasks like String Compression highlight the importance of using existing data structures for efficient solutions.
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Precision is Key:
- Both problems required careful tracking of indices and conditions to ensure correctness without additional complexity.
Reflections
The String Compression problem tested my ability to combine traversal and in-place updates seamlessly, while Move Zeroes reinforced the importance of efficient data reorganization. Together, they brought Week 10 to a satisfying conclusion, showcasing the power of foundational techniques in solving everyday challenges.
What’s Next?
With Week 10 complete, I’m excited to plan Week 11, focusing on Dynamic Programming, Advanced Graph Problems, and Greedy Algorithms. The upcoming challenges will push my skills further and open new doors for learning.
Thank you for following along! Let’s keep exploring, optimizing, and solving together.
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