[BUG] - <title> Handling Empty Arrays in Median of Two Sorted Arrays Solution

LeetCode Username

SUMITXP10

Problem Number, Title, and Link

Median of Two Sorted Arrays https://leetcode.com/problems/median-of-two-sorted-arrays/

Bug Category

Incorrect or missing "Related Topics"

Bug Description

The bug lies in the incomplete or inaccurate depiction of the " Related Topics " section within the problem statement . This section plays a pivotal role in providing users with essential guidance regarding the underlying concepts and methodologies crucial for tackling the problem effectively .

The absence or misrepresentation of related topics undermines the users' ability to discern the appropriate problem-solving strategies . For instance , omitting key topics such as Array , Binary Search and Divide and Conquer deprives users of valuable insights into the fundamental techniques applicable to the problem .

A comprehensive and accurate " Related Topics " section is vital for furnishing users with the necessary knowledge framework to approach the problem methodically . It serves as a roadmap , guiding users towards understanding the problem's intricacies and formulating efficient solutions .

Therefore , rectifying this bug entails ensuring the inclusion of pertinent topics like Array , Binary Search and Divide and Conquer within the " Related Topics " section . This enhancement will empower users with the requisite understanding and resources to tackle the problem adeptly , fostering a more enriching problem-solving experience .

Language Used for Code

Python/Python3

Code used for Submit/Run operation

from typing import List

class Solution:
    def findMedianSortedArrays(self, nums1: List[int], nums2: List[int]) -> float:
        # Ensure nums1 is the smaller array to improve efficiency
        if len(nums1) > len(nums2):
            nums1, nums2 = nums2, nums1

        x, y = len(nums1), len(nums2)
        low, high = 0, x

        while low <= high:
            partitionX = (low + high) // 2
            partitionY = (x + y + 1) // 2 - partitionX

            # If partitionX is 0, it means nothing is there on left side. Use -inf for maxLeftX
            # If partitionX is length of input then there is nothing on right side. Use +inf for minRightX
            maxLeftX = float('-inf') if partitionX == 0 else nums1[partitionX - 1]
            minRightX = float('inf') if partitionX == x else nums1[partitionX]

            maxLeftY = float('-inf') if partitionY == 0 else nums2[partitionY - 1]
            minRightY = float('inf') if partitionY == y else nums2[partitionY]

            if maxLeftX <= minRightY and maxLeftY <= minRightX:
                # We have partitioned array at correct place
                # Now get max of left elements and min of right elements to get the median in case of even length combined array size
                # or get max of left for odd length combined array size.
                if (x + y) % 2 == 0:
                    return (max(maxLeftX, maxLeftY) + min(minRightX, minRightY)) / 2
                else:
                    return max(maxLeftX, maxLeftY)
            elif maxLeftX > minRightY: # we are too far on right side for partitionX. Go on left side.
                high = partitionX - 1
            else: # we are too far on left side for partitionX. Go on right side.
                low = partitionX + 1

        # If the array sizes are zero or the arrays do not meet the criteria,
        # the problem statement guarantees that it will not happen, so this line will never be reached.
        raise ValueError("Input arrays are not valid for finding median.")

# Example usage:
solution = Solution()
print(solution.findMedianSortedArrays([1,3], [2]))  # Output: 2.00000
print(solution.findMedianSortedArrays([1,2], [3,4]))  # Output: 2.50000

Expected behavior

Expected behavior would entail the problem statement including a comprehensive " Related Topics " section that accurately reflects the core concepts essential for solving the problem . Specifically , this section should highlight key methodologies like Array , Binary Search and Divide and Conquer , providing users with clear guidance on the relevant strategies to employ .

However , upon review , it was observed that the problem statement lacked this critical " Related Topics " section altogether . This omission represents a significant shortfall as it deprives users of crucial insights into the fundamental techniques necessary for addressing the problem effectively . Without this guidance , users may struggle to navigate the problem space , potentially leading to confusion and suboptimal solutions .

In summary , the anticipated behavior would involve the problem statement containing a robust " Related Topics " section , whereas the actual behavior falls short by neglecting to provide this essential guidance , thereby hindering users' problem-solving experience .

Screenshots

The issue is not related to a specific portion of code but rather to the absence of a " Related Topics " section within the problem statement . This section should typically appear alongside the problem description , providing users with guidance on the key concepts and methodologies relevant to solving the problem .

Additional context

The absence of a " Related Topics " section in the problem statement not only impacts users' understanding of the problem but also affects their ability to efficiently navigate the problem-solving process . Providing this section is crucial as it guides users towards relevant techniques and strategies , ensuring a more effective problem-solving experience . Additionally , including " Related Topics " helps users grasp the broader context of the problem and fosters a deeper understanding of the underlying concepts involved . Therefore , rectifying this issue is essential for enhancing the overall usability and clarity of the problem statement .

LeetCode-Feedback / LeetCode-Feedback