Completed Array-2

[ashritha0806]

No description provided.

[super30admin]

Disappeared Numbers (Dissapper_number.py)

Strengths:

• The solution is optimal in both time and space complexity.
• The code is clean and well-commented, making it easy to understand.
• The approach is correctly implemented.

Areas for improvement:

• There are no major issues. However, it's worth noting that the solution modifies the input array. While this is acceptable in many contexts (including Leetcode), in some real-world scenarios we might need to preserve the input. But since the problem doesn't require it, this is fine.
• The comment says "Took sometime to reach O(1) space solution." This is normal for this problem, as it requires a non-trivial insight.

Overall, this is an excellent solution.

VERDICT: PASS

---

max and min (Game_of_life.py)

It appears there has been a mix-up in your submission. You submitted a solution for the "Game of Life" problem (LeetCode 289) instead of the "max and min" problem. For the "max and min" problem, you need to find the minimum and maximum values in an array with a constraint on the number of comparisons (less than 2*(N-2)).

Your "Game of Life" solution is well-written and efficient. However, for the "max and min" problem, you should implement a different approach. The reference solution uses a method that processes elements in pairs to reduce the number of comparisons. Here's a brief explanation:

• If the array has an even length, initialize min and max by comparing the first two elements.
• If the array has an odd length, initialize min and max to the first element.
• Then, iterate through the rest of the array in pairs. For each pair, compare them to each other, then compare the smaller with the current min and the larger with the current max. This reduces the number of comparisons to about 3n/2.

Please resubmit a solution for the correct problem. If you need help with the "max and min" problem, let me know.

VERDICT: NEEDS_IMPROVEMENT

---

Life Game

Your solution for the Life Game problem is excellent. It correctly implements the in-place update with O(1) space and O(m*n) time. The use of markers (2 and 3) is appropriate and handles the simultaneous update requirement. Your code is clean and well-commented.

Strengths:

• Correct implementation of the algorithm.
• Efficient in-place modification.
• Good use of comments to explain the approach.

Areas for improvement:

• Consider defining the direction list as a constant (e.g., at the class level or as a tuple) to avoid recreating it for every call to countAlive. This is a minor optimization but can improve performance slightly for larger grids.
• The function name "countAlive" is slightly misleading because it counts both currently alive (1) and about-to-die (3) cells. A more precise name like "count_live_neighbors" might be better.

Note: The first file "Dissapper_number.py" is for a different problem (Find Disappeared Numbers) and should not be included in the same submission for the Life Game problem. Make sure to submit only the relevant code for each problem.

VERDICT: PASS