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Solving Leetcode Interviews in Seconds with AI: Minimum Size Subarray Sum

Updated
2 min read

Introduction

In this blog post, we will explore how to solve the LeetCode problem "209" using AI. LeetCode is a popular platform for preparing for coding interviews, and with the help of AI tools like Chatmagic, we can generate solutions quickly and efficiently - helping you pass the interviews and get the job offer without having to study for months.

Problem Statement

Given an array of positive integers nums and a positive integer target, return the minimal length of a subarray whose sum is greater than or equal to target. If there is no such subarray, return 0 instead. Example 1: Input: target = 7, nums = [2,3,1,2,4,3] Output: 2 Explanation: The subarray [4,3] has the minimal length under the problem constraint. Example 2: Input: target = 4, nums = [1,4,4] Output: 1 Example 3: Input: target = 11, nums = [1,1,1,1,1,1,1,1] Output: 0 Constraints: 1 <= target <= 109 1 <= nums.length <= 105 1 <= nums[i] <= 104 Follow up: If you have figured out the O(n) solution, try coding another solution of which the time complexity is O(n log(n)).

Explanation

Here's a breakdown of the approach, followed by the code:

  • Sliding Window: Utilize a sliding window technique to efficiently explore subarrays. Expand the window (increment right) until the window sum is greater than or equal to the target.
  • Minimize Length: Once the sum meets the target, contract the window (increment left) while maintaining the target condition, keeping track of the minimal window length.
  • Handle No Solution: If no suitable subarray is found, return 0.

  • Runtime Complexity: O(n) - each element is visited at most twice. Storage Complexity: O(1) - constant extra space.

Code

    def minSubArrayLen(target: int, nums: list[int]) -> int:
    """
    Finds the minimal length of a subarray whose sum is greater than or equal to target.

    Args:
        target: The target sum.
        nums: The array of positive integers.

    Returns:
        The minimal length of a subarray whose sum is greater than or equal to target, or 0 if no such subarray exists.
    """
    left = 0
    window_sum = 0
    min_len = float('inf')

    for right in range(len(nums)):
        window_sum += nums[right]

        while window_sum >= target:
            min_len = min(min_len, right - left + 1)
            window_sum -= nums[left]
            left += 1

    if min_len == float('inf'):
        return 0
    else:
        return min_len

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