Introduction

In this blog post, we will explore how to solve the LeetCode problem "674" 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 unsorted array of integers nums, return the length of the longest continuous increasing subsequence (i.e. subarray). The subsequence must be strictly increasing. A continuous increasing subsequence is defined by two indices l and r (l < r) such that it is [nums[l], nums[l + 1], ..., nums[r - 1], nums[r]] and for each l <= i < r, nums[i] < nums[i + 1]. Example 1: Input: nums = [1,3,5,4,7] Output: 3 Explanation: The longest continuous increasing subsequence is [1,3,5] with length 3. Even though [1,3,5,7] is an increasing subsequence, it is not continuous as elements 5 and 7 are separated by element 4. Example 2: Input: nums = [2,2,2,2,2] Output: 1 Explanation: The longest continuous increasing subsequence is [2] with length 1. Note that it must be strictly increasing. Constraints: 1 <= nums.length <= 104 -109 <= nums[i] <= 109

Explanation

• Sliding Window: Use a sliding window approach to iterate through the array, expanding the window as long as the current element is greater than the previous element.
  • Track Maximum Length: Keep track of the maximum length encountered so far.
  • Reset Window: If the current element is not greater than the previous element, reset the window to start from the current element.

• Time Complexity: O(n), where n is the length of the input array. Space Complexity: O(1).

Code

    def findLengthOfLCIS(nums):
    """
    Finds the length of the longest continuous increasing subsequence.

    Args:
        nums: A list of integers.

    Returns:
        The length of the longest continuous increasing subsequence.
    """

    if not nums:
        return 0

    max_length = 1
    current_length = 1

    for i in range(1, len(nums)):
        if nums[i] > nums[i - 1]:
            current_length += 1
            max_length = max(max_length, current_length)
        else:
            current_length = 1

    return max_length