LeetCode Rotate Image Problem 48 Bug Report Discussion Non-In-Place Solutions Accepted

Hey guys! It seems there's a bit of a snag with the Rotate Image problem (Problem 48) on LeetCode, and I wanted to bring it to your attention. The issue revolves around the problem's constraint that the solution should be in-place, meaning we shouldn't be using any extra space by creating new matrices. However, some of us have noticed that solutions which do use extra space are being accepted, which kinda defeats the purpose of the constraint. Let's dive into the specifics and see what's going on.

Problem Overview: Rotate Image (Problem 48)

The problem, titled "Rotate Image", asks us to rotate a given n x n 2D square matrix (representing an image) by 90 degrees clockwise. The catch? We have to do it in-place, meaning we should modify the original matrix directly without using any additional memory (O(1) space complexity). This is a classic matrix manipulation problem that tests our understanding of array indexing and in-place algorithms.

The problem statement clearly states the in-place constraint, which is a crucial part of the challenge. It forces us to think about how to rearrange the elements within the existing matrix structure, making it a more interesting and efficient problem to solve.

The Bug: Non-In-Place Solutions Getting Accepted

So, here's the core of the issue. Several users, including DhruvSarvaiya009, have reported that their solutions, which do not adhere to the in-place constraint (i.e., they use extra space by creating a new matrix), are being accepted by the LeetCode judge. This is a bug because it contradicts the problem statement and makes the constraint meaningless.

DhruvSarvaiya009's report highlights this perfectly. They submitted a C++ solution that creates a new matrix (check) to keep track of visited elements during the rotation process. This clearly violates the in-place requirement. Yet, their solution was accepted without any warnings or errors. This means the test cases aren't properly validating whether the solution is truly in-place.

This is problematic for a few reasons:

1. Misleading Feedback: It gives users the false impression that their code is correct when it's not fully compliant with the problem's constraints.
2. Unfair Evaluation: It creates an uneven playing field because some users might solve the problem using the intended in-place approach, while others might get away with a simpler (but incorrect) solution that uses extra space.
3. Undermining Problem Intent: The in-place constraint is there for a reason – to encourage efficient algorithms and memory usage. By accepting non-in-place solutions, the problem loses its intended challenge and educational value.

Code Example: A Non-In-Place Solution

Let's take a closer look at the code snippet provided by DhruvSarvaiya009:

class Solution {
public:
    void rotate(vector<vector<int>>& matrix) {
        int n = matrix.size()-1;
        vector<vector<int>> check(n+1, vector<int>(n+1, 0));
        int k = 0;
        for(int i = 0;i<=n;i++){
            for(int j = 0;j<=n;j++){
                if(!check[i][j]){
                    swap(matrix[i][j],matrix[i+j+k][n-i]);
                    check[i+j+k][n-i]=1;
                }
            }
            k--;
        }
    }
};

As you can see, the code creates a new 2D vector called check, which acts as an auxiliary matrix to keep track of visited cells. This immediately disqualifies it as an in-place solution. The check matrix is used to avoid revisiting elements during the rotation process, but it comes at the cost of extra space complexity.

Another common approach that violates the in-place constraint is to create a completely new matrix and populate it with the rotated elements. While this approach is conceptually simple, it's not the intended solution for this problem.

Expected Behavior and Solutions

So, what should the LeetCode judge do when it encounters a non-in-place solution for the Rotate Image problem? There are a few possible ways to handle this:

1. Rejection: The most straightforward approach is to simply reject the solution with an error message indicating that it violates the in-place constraint. This is the strictest approach and ensures that users are adhering to the problem's requirements.
2. Warning: Another option is to accept the solution but issue a warning message to the user. This would inform them that their solution works but doesn't meet the in-place requirement. This approach is more lenient but still provides valuable feedback.
3. Note: A third option is to add a note to the problem description or the solution output, explicitly stating that the submitted code uses extra space and might not be the most efficient solution. This provides context without directly rejecting the solution.

Ideally, LeetCode should implement a combination of these approaches. For example, they could reject solutions that allocate a significant amount of extra space (e.g., a new matrix of the same size) while issuing warnings for solutions that use a smaller amount of extra space (e.g., a few extra variables).

Why In-Place Matters

You might be wondering, why is this in-place constraint so important? Well, in many real-world scenarios, memory is a limited resource. When dealing with large images or matrices, using extra memory can be costly or even infeasible. In-place algorithms are crucial for optimizing memory usage and improving performance.

By forcing us to solve the Rotate Image problem in-place, we're encouraged to think creatively about how to manipulate the matrix elements directly without relying on extra space. This leads to more efficient and elegant solutions.

The in-place approach typically involves a series of swaps between elements in the matrix. We can rotate the image layer by layer, swapping elements in a circular fashion. This requires a bit more thought and careful indexing, but it's the key to solving the problem correctly.

Conclusion and Call to Action

The bug in the Rotate Image problem highlights the importance of thorough test cases and accurate constraint validation. It's crucial that LeetCode ensures its problems are properly evaluated to provide meaningful feedback to users and maintain the integrity of the platform.

I encourage anyone who has encountered this issue (or any other bugs on LeetCode) to report it through the appropriate channels. Your feedback helps LeetCode improve its platform and provide a better learning experience for everyone.

In the meantime, let's make sure we're all striving to solve the Rotate Image problem the right way – in-place! Happy coding, guys! This issue needs to be addressed to maintain the integrity of the LeetCode platform and the learning experience it offers. It ensures that the constraint is meaningful and all users are evaluated fairly. By addressing such bugs, LeetCode can continue to be a valuable resource for programmers looking to improve their skills and prepare for technical interviews.

Bug Category: Missing test case (Incorrect/Inefficient Code getting accepted because of missing test cases) Bug Description: The problem statement clearly instructs that the solution must be done in-place, meaning we should not allocate another 2D matrix. However, I submitted a solution that uses an extra matrix, and it was still accepted without any errors or warnings. This contradicts the stated constraints of the problem. Expected behavior: Solutions that violate the "in-place" requirement should be rejected, trigger a warning, or be accompanied by a note that the use of extra space violates the intended constraints.

Can you rephrase the bug report and expected behavior related to the LeetCode Rotate Image problem (48) where non-in-place solutions are being accepted, focusing on clarity and impact?

LeetCode Rotate Image Problem 48 Bug Report Non In-Place Solutions Accepted Discussion