Completed Graph-1. Requesting Review

[AnirudhS30]

No description provided.

[super30admin]

Let me evaluate each file separately.

For problem_1.py (Find Judge):

1. Correctness: The solution correctly implements the standard approach for finding the town judge by tracking in-degree and out-degree. It handles the edge case when n=1 appropriately.
2. Time Complexity: O(E + N) where E is the number of trust relationships and N is the number of people. This is optimal.
3. Space Complexity: O(N) for storing in-degree and out-degree arrays, which is optimal.
4. Code Quality: The code is clean, well-structured, and easy to understand. Variable names are appropriate.
5. Efficiency: The solution is already efficient. No obvious optimizations needed.

For problem_2.py (Maze Path):

1. Correctness: The BFS approach seems correct for finding a path in a maze, but there's a typo in the parameter name 'destiantion' which should be 'destination'. The logic appears sound otherwise.
2. Time Complexity: O(M*N) in worst case where M and N are maze dimensions, as each cell might be visited once. This is standard for BFS.
3. Space Complexity: O(M*N) in worst case for the queue, which is standard for BFS.
4. Code Quality:
   • The typo in parameter name should be fixed
   • Variable names could be more descriptive (e.g., 'Dir' could be 'directions')
   • The while loop condition could be written more clearly as 'while q:'
   • The maze modification (setting to 2) might not be desirable if the maze needs to be reused
5. Efficiency: The solution is generally efficient, but could consider:
   • Early termination if source == destination
   • Using a visited set instead of modifying the maze

Overall, both solutions are correct and efficient, but problem_2.py has some code quality issues that should be addressed.