DAY 14 Mastering Array-Based Challenges

Hello Everyone!

I am Somuya Khandelwal, and I’m excited to share my progress from Day 4 of Week 3 in my competitive programming journey. Today, I tackled Array-based problems, which are among the most common and essential topics in competitive programming. These challenges required a solid understanding of array manipulation, optimization techniques, and edge case handling.

What I Worked On Today

1. Rotate Array (Medium Difficulty)

   • Rotate an array to the right by k steps.
   • Approach:
     • Used a three-step reversal technique:
     • Reverse the entire array.
     • Reverse the first k elements.
     • Reverse the remaining elements.
   • What I Learned:
     • The reversal technique is an efficient way to solve rotation problems in O(n) time and O(1) space.
     • Properly handling k > n by taking k % n ensures correctness for all inputs.

2. Best Time to Buy and Sell Stock II (Medium Difficulty)

   • Find the maximum profit by buying and selling stocks multiple times, ensuring you buy before you sell.
   • Approach:
     • Used a greedy strategy to sum up all positive differences between consecutive days.
     • Skipped days where the stock price decreased.
   • What I Learned:
     • Greedy algorithms are effective for problems where local optimizations lead to a global solution.
     • Understanding the problem constraints is crucial for identifying the simplest solution.

What I Learned Today

1. Efficient Array Manipulations:

   • Problems like Rotate Array highlighted the importance of space-efficient techniques like in-place reversal.

2. Greedy Algorithms for Optimization:

   • The Stock Buy and Sell problem demonstrated how greedy strategies can solve optimization problems quickly and effectively.

3. Handling Edge Cases:

   • Problems involving cyclic rotations (e.g., Rotate Array) require careful consideration of edge cases like k > n or arrays of size 1.

4. Simplifying Complex Problems:

   • Breaking down problems into simpler subproblems or steps, as seen in Rotate Array, makes implementation and debugging much easier.

Reflections and Challenges

The Rotate Array problem was particularly interesting because it required balancing efficiency with clarity. Initially, I attempted a brute-force solution but quickly realized the importance of optimizing both time and space complexity. The Stock Buy and Sell problem was relatively straightforward but reinforced the importance of understanding problem constraints and applying the simplest possible solution.

Looking Ahead

On Monday, I’ll wrap up the week with more Array-based problems, including H-Index and Gas Station. These tasks will test my understanding of array traversal, sorting, and optimization techniques.

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