Solving Leetcode Interviews in Seconds with AI: Longest Strictly Increasing or Strictly Decreasing Subarray
Introduction
In this blog post, we will explore how to solve the LeetCode problem "3105" 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
You are given an array of integers nums. Return the length of the longest subarray of nums which is either strictly increasing or strictly decreasing. Example 1: Input: nums = [1,4,3,3,2] Output: 2 Explanation: The strictly increasing subarrays of nums are [1], [2], [3], [3], [4], and [1,4]. The strictly decreasing subarrays of nums are [1], [2], [3], [3], [4], [3,2], and [4,3]. Hence, we return 2. Example 2: Input: nums = [3,3,3,3] Output: 1 Explanation: The strictly increasing subarrays of nums are [3], [3], [3], and [3]. The strictly decreasing subarrays of nums are [3], [3], [3], and [3]. Hence, we return 1. Example 3: Input: nums = [3,2,1] Output: 3 Explanation: The strictly increasing subarrays of nums are [3], [2], and [1]. The strictly decreasing subarrays of nums are [3], [2], [1], [3,2], [2,1], and [3,2,1]. Hence, we return 3. Constraints: 1 <= nums.length <= 50 1 <= nums[i] <= 50
Explanation
Here's the breakdown of the solution:
- Iterate and Track: Iterate through the
numsarray, maintaining two counters: one for the length of the current strictly increasing subarray and one for the length of the current strictly decreasing subarray. - Update Counters: At each element, check if it extends the current increasing or decreasing subarray. If it does, increment the respective counter. If not, reset the counter to 1.
Maximize Length: Keep track of the maximum length seen so far and update it whenever a longer increasing or decreasing subarray is found.
Runtime Complexity: O(n), where n is the length of the input array. Storage Complexity: O(1).
Code
def longest_subarray(nums):
"""
Finds the length of the longest subarray of nums which is either strictly increasing or strictly decreasing.
"""
if not nums:
return 0
max_len = 1
increasing_len = 1
decreasing_len = 1
for i in range(1, len(nums)):
if nums[i] > nums[i - 1]:
increasing_len += 1
decreasing_len = 1 # Reset decreasing length
elif nums[i] < nums[i - 1]:
decreasing_len += 1
increasing_len = 1 # Reset increasing length
else:
increasing_len = 1
decreasing_len = 1
max_len = max(max_len, increasing_len, decreasing_len)
return max_len