Completed DP-1 exercises

[LakshmiPriya90-tech]

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[super30admin]

Coin Change (Exercise_1.py)

Excellent work! Your solution demonstrates a strong understanding of dynamic programming. Here are some specific strengths:

1. Optimal Approach: You chose the bottom-up DP approach, which is the standard optimal solution for this problem. This is much more efficient than the naive recursive approach shown in the reference solution.

2. Clean Sentinel Value: Using amount + 1 as the sentinel for unreachable states is a clever and clean technique. It's more readable than using float('inf') and avoids potential issues with integer overflow in other languages.

3. Good Documentation: Your comments clearly explain the approach, complexity, and any challenges faced. This is excellent practice for collaborative coding.

4. Correct Edge Case Handling: You correctly handle amount = 0 (returns 0) and impossible combinations (returns -1).

Potential minor improvements:

• The variable name current_amount could be shortened to just i for conciseness, though the current name is more descriptive.
• You could add a brief comment explaining why amount + 1 is used as the sentinel value (since it's guaranteed to be larger than any valid answer).

Overall, this is a high-quality solution that correctly and efficiently solves the problem.

VERDICT: PASS

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House Robber (Exercise_2.py)

This is an outstanding solution! Your iterative DP approach with O(1) space is the optimal way to solve this problem. A few highlights:

Strengths:

• Excellent recognition that only the previous two states are needed — this is a key insight that many students miss
• Clean variable naming makes the logic very easy to follow
• The comments explaining your design decisions (especially the "why only two variables" part) show strong analytical thinking
• Your solution is strictly better than the reference solution in both time and space complexity

Minor suggestions for further improvement:

• Consider adding a brief edge case comment (e.g., "Constraints guarantee nums.length >= 1, so no empty array handling needed")
• For very large inputs, you could potentially use bit manipulation tricks, but for this problem O(n) is optimal
• You could explore the same pattern in other "previous two states" problems (e.g., Fibonacci, Climbing Stairs) to reinforce this technique

Comparison to reference: Your solution is strictly superior — the reference uses naive recursion without memoization, resulting in O(2^n) time. Your iterative approach with O(1) space is the textbook optimal solution.

VERDICT: PASS