Completed

[shantanujoshi25]

Completed

[super30admin]

Your solution is well-implemented and correct. Here are some points for improvement:

1. Time Complexity Comment: The comment for time complexity is not accurate. The worst-case time complexity is actually exponential. A better way to describe it might be O(k * 2^t), where k is the average length of combinations, but it's complex. You could say it's exponential in the target value.

2. Space Complexity Comment: The space complexity is O(t) for the recursion stack, but note that the output storage (the result list) requires additional space, which is O(n * number_of_combinations). So the overall space complexity is higher. However, the recursion stack space is O(t), which is correct.

3. Sorting and Early Break: Sorting the candidates and breaking early when the candidate exceeds the target is an excellent optimization. This reduces unnecessary recursion.

4. Code Readability: The code is clean and easy to understand. Using a for-loop with index tracking is a standard approach for combination problems. The use of path.copy() ensures that we store a snapshot of the current path, which is correct.

5. Efficiency: The solution is efficient. However, note that the reference solution uses a different approach (choose/not choose) which might be less efficient in terms of space because it creates new lists at each step. Your approach uses backtracking with a single list that is modified in place, which is more space-efficient.

6. Minor Suggestion: Consider adding a docstring to the helper function to explain its parameters, as it improves readability.

Overall, great job! The solution is optimal and follows best practices.