dp1

[spencerkrebs]

No description provided.

[super30admin]

The Coin Change (coin-change.py)

Strengths:

• You have explored multiple approaches to the problem, which shows a good understanding of different techniques.
• Your 2D DP solution is correct and follows the standard pattern.
• You have included comments to explain your thought process.

Areas for Improvement:

1. For the 1D DP solution:

   • Initialize the dp array with dp[0]=0 and the rest to inf (or a large number). Then, for each coin, iterate from the coin value to the amount (not from 0 to amount) to update dp[j] = min(dp[j], 1+dp[j-coin]).
   • The current 1D code initializes dp[col] to inf for col>=1 after setting dp[0]=0, which is redundant because you can initialize the entire array to inf except dp[0]=0 at the start.

2. For the recursive solution with memoization:

   • The memoization table should be passed to the helper function or stored as a class variable. Also, you need to define memo properly and use it to store and retrieve results.
   • There is a typo: memo[i][amount] = res should be memo[i][amount] = re (or better, use a consistent variable name).

3. General:

   • It's better to submit only one solution that is correct and efficient. The 1D DP solution is preferred for its space efficiency.
   • Ensure that you test your code with the provided examples to verify correctness.

Here is a corrected version of the 1D DP solution:

class Solution:
    def coinChange(self, coins: List[int], amount: int) -> int:
        dp = [float('inf')] * (amount + 1)
        dp[0] = 0
        for coin in coins:
            for j in range(coin, amount + 1):
                dp[j] = min(dp[j], 1 + dp[j - coin])
        return dp[amount] if dp[amount] != float('inf') else -1

VERDICT: NEEDS_IMPROVEMENT

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House Robber (house-robber.py)

Strengths:

• The student recognizes that greedy won't work and considers exhaustive search (recursion) and dynamic programming.
• The student understands the concept of "choose or not choose" for each house.
• The student is thinking about optimization (memoization and pointers).

Areas for Improvement:

• Syntax and Completeness: The code has several syntax errors (e.g., missing colons, incorrect indentation, undefined variables). The helper function is not properly defined or called.
• Edge Cases: The DP solution does not handle cases where the list length is 0 or 1. For example, if nums is empty, dp[0] would cause an index error.
• Memoization: If using recursion, memoization should be implemented to avoid repeated calculations. The student mentions memo[i] but doesn't initialize or use it correctly.
• DP Implementation: The DP solution should be carefully implemented. The recurrence relation is correct: dp[i] = max(dp[i-1], nums[i] + dp[i-2]). However, the dp array needs to be initialized properly. Also, for n=1, dp[1] would be out of bounds.
• Code Structure: The student should write complete, runnable code. It's better to focus on one approach and implement it correctly.

Suggestions:

• For the DP approach, initialize dp as a list of zeros with length n. Then set dp[0] = nums[0] and if n>1, dp[1] = max(nums[0], nums[1]). Then iterate from i=2 to n-1.
• Alternatively, use two variables to store the previous two states to reduce space complexity to O(1).
• Test the solution with edge cases (empty list, list with one element).

VERDICT: NEEDS_IMPROVEMENT