Sliding Window Algorithms | Dataford Interview Questions

Describe how you would solve a problem using a sliding window approach.

Implement longest_subarray(nums, target) for a list of non-negative integers. Return the maximum length of a contiguous subarray whose sum is at most target, or 0 if no non-empty subarray qualifies.

Examples: nums = [2, 1, 5, 1, 3, 2], target = 7 returns 3; nums = [3, 1, 1, 1, 3], target = 5 returns 3 because no qualifying window has length four. Use a single pass with O(1) auxiliary space.

Constraints

0 <= nums.length <= 1000
0 <= nums[i] <= 10^6
0 <= target <= 10^9
The subarray must be contiguous

Function Signature

def longest_subarray(nums, target):

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Problem

Describe how you would solve a problem using a sliding window approach.

Constraints

0 <= nums.length <= 1000
0 <= nums[i] <= 10^6
0 <= target <= 10^9
The subarray must be contiguous

Function Signature

def longest_subarray(nums, target):

Your question is Sliding Window Algorithms. Start with the requirements in the Question tab.

Run and submit as often as you like. When you're ready, talk me through your approach or go straight to the code.