Top 20 Sliding Window Interview Questions and Answers (2026)

1. Introduction to Sliding Window

Sliding window optimizes contiguous subarray and substring problems. Below are 20 essential questions with full implementations in C++, Java, Python, and JavaScript.

2. Core Sliding Window Questions

Q1. Maximum Sum Subarray of Size K

cpp
int maxSumSubarray(vector<int>& nums, int k) {
    int windowSum = 0;
    for (int i = 0; i < k; i++) windowSum += nums[i];
    int maxSum = windowSum;
    for (int i = k; i < nums.size(); i++) {
        windowSum += nums[i] - nums[i - k];
        maxSum = max(maxSum, windowSum);
    }
    return maxSum;
}

java
public int maxSumSubarray(int[] nums, int k) {
    int windowSum = 0;
    for (int i = 0; i < k; i++) windowSum += nums[i];
    int maxSum = windowSum;
    for (int i = k; i < nums.length; i++) {
        windowSum += nums[i] - nums[i - k];
        maxSum = Math.max(maxSum, windowSum);
    }
    return maxSum;
}

python
def maxSumSubarray(nums: list, k: int) -> int:
    window_sum = sum(nums[:k])
    max_sum = window_sum
    for i in range(k, len(nums)):
        window_sum += nums[i] - nums[i - k]
        max_sum = max(max_sum, window_sum)
    return max_sum

javascript
function maxSumSubarray(nums, k) {
    let windowSum = 0;
    for (let i = 0; i < k; i++) windowSum += nums[i];
    let maxSum = windowSum;
    for (let i = k; i < nums.length; i++) {
        windowSum += nums[i] - nums[i - k];
        maxSum = Math.max(maxSum, windowSum);
    }
    return maxSum;
}

Time Complexity: O(n) | Space Complexity: O(1)

3. Summary Table

Practice all sliding window problems on DSAMaster's practice platform.