# Solving Leetcode Interviews in Seconds with AI: Longest Continuous Increasing Subsequence


	# 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](https://www.chatmagic.app), 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
	```python
	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
	```