Time & Space Complexity Quiz

8 questions10 minPass: 60%+10 XP on first pass

Can you find the Big-O of real code? 8 questions on loops, logarithms, recursion and space.

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Question 1

What is the time complexity of this code?

for i in range(n):
    for j in range(n):
        print(i, j)

O(n)O(2n)O(n²)O(n log n)

Question 2

What is the time complexity of this code?

for i in range(n):
    print(i)
for j in range(n):
    print(j)

O(n)O(n²)O(2ⁿ)O(log n)

Question 3
What is the time complexity of this loop?
```
i = n
while i > 1:
    i = i // 2
```
O(n)O(log n)O(√n)O(1)
Question 4
Simplify the complexity 3n² + 5n + 100.
O(3n²)O(n²)O(n² + n)O(n)
Question 5
An array has n ≤ 100,000 elements. Which solution is likely too slow for a typical 1-second limit?
O(n²)O(n log n)O(n)O(log n)
Question 6Select all that apply
Which operations are O(1) on average? (select all that apply)
Reading arr[i] from an arrayChecking if a key exists in a hash mapChecking x in my_list for a Python listSorting an array

Question 7

What is the extra space complexity of this recursive function?

def count_down(n):
    if n == 0:
        return
    count_down(n - 1)

O(1)O(n)O(log n)O(n²)

Question 8
You loop over array a (length n) and, inside it, over array b (length m). What is the time complexity?