Sliding Window on Arrays in DSA Python - Practice Problems & Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

Output of sliding window maximum sum

What is the output of the following code that finds the maximum sum of any subarray of size 3 using sliding window?

DSA Python

arr = [2, 1, 5, 1, 3, 2]
window_size = 3
max_sum = 0
window_sum = sum(arr[:window_size])
max_sum = window_sum
for i in range(window_size, len(arr)):
    window_sum += arr[i] - arr[i - window_size]
    if window_sum > max_sum:
        max_sum = window_sum
print(max_sum)

A 9

B 8

C 7

D 6

💡 Hint

Think about how the window slides and updates the sum by adding the new element and removing the old one.

The sliding window sums are: 2+1+5=8, then 1+5+1=7, then 5+1+3=9, then 1+3+2=6. The maximum is 9.

❓ Predict Output

intermediate

Output of minimum average subarray

What is the output of this code that finds the minimum average of any subarray of size 4?

DSA Python

arr = [4, 2, 2, 5, 1, 5, 8]
window_size = 4
window_sum = sum(arr[:window_size])
min_sum = window_sum
for i in range(window_size, len(arr)):
    window_sum += arr[i] - arr[i - window_size]
    if window_sum < min_sum:
        min_sum = window_sum
min_avg = min_sum / window_size
print(min_avg)

A 3.25

B 2.5

C 3.0

D 4.0

💡 Hint

Calculate sums of each 4-element window and find the smallest sum, then divide by 4.

The sums of windows are: 4+2+2+5=13, 2+2+5+1=10, 2+5+1+5=13, 5+1+5+8=19. The minimum sum is 10, so average is 10/4=2.5.

🔧 Debug

advanced

Identify the error in sliding window code

What error does this code raise when trying to find the maximum sum of subarrays of size 3?

DSA Python

arr = [1, 2, 3, 4, 5]
window_size = 3
max_sum = 0
window_sum = sum(arr[:window_size])
for i in range(window_size, len(arr)):
    window_sum += arr[i] - arr[i - window_size]
    if window_sum > max_sum:
        max_sum = window_sum
print(max_sum)

A No error, output is 12

B IndexError: list index out of range

C NameError: name 'max_sum' is not defined

D TypeError: unsupported operand type(s)

💡 Hint

Check if all variables are defined and indices are valid.

All variables are defined and indices are valid. The code runs without error and outputs 12, which is the sum of last 3 elements (3+4+5).

🚀 Application

advanced

Find the count of subarrays with sum equal to k

Given an array and a number k, which option correctly counts the number of continuous subarrays whose sum equals k using sliding window?

DSA Python

arr = [1, 1, 1, 2, 3]
k = 3
count = 0
start = 0
current_sum = 0
for end in range(len(arr)):
    current_sum += arr[end]
    while current_sum > k and start <= end:
        current_sum -= arr[start]
        start += 1
    if current_sum == k:
        count += 1
print(count)

A 2

B 1

C 4

D 3

💡 Hint

Think about how the window shrinks when sum exceeds k and counts when sum equals k.

The subarrays with sum 3 are: [1,1,1], [1,2], [3]. So count is 3.

🧠 Conceptual

expert

Why sliding window fails for negative numbers in subarray sum problem?

Why does the sliding window technique fail to find the count of subarrays with sum equal to k if the array contains negative numbers?

A Because sliding window cannot handle arrays longer than 100 elements

B Because negative numbers cause index errors in sliding window

C Because sliding window assumes all numbers are positive to shrink window correctly

D Because sliding window requires sorted arrays

💡 Hint

Think about how the window shrinks when sum exceeds k and how negative numbers affect this logic.

Sliding window works by shrinking the window when sum exceeds k, assuming adding more elements increases sum. Negative numbers can decrease sum, breaking this logic.