L2 Big O Notation Quiz

What does Big O Notation describe?

• The amount of space required by an algorithm

• The efficiency of hardware components

• The number of inputs an algorithm accepts

• The worst-case scenario for an algorithm’s time complexity

What is the time complexity of binary search?

• O(n)

• O(log n)

• O(n^2)

• O(1)

Which of the following Big O notations represents the fastest time complexity?

• O(n^2)

• O(n)

• O(log n)

• O(n log n)

In Big O Notation, what does O(1) represent?

• Constant time

• Linear time

• Quadratic time

• Exponential time

What is the time complexity of a nested loop where the inner loop runs n times and the outer loop also runs n times?

• O(n)

• O(log n)

• O(n log n)

• O(n^2)

Which of the following operations on a sorted array has a time complexity of O(n)?

• Binary search

• Inserting an element at the end

• Inserting an element at a specific index

• Accessing an element by index

What is the time complexity of accessing an element in a hash table (average case)?

• O(n)

• O(log n)

• O(1)

• O(n^2)

Which time complexity grows the fastest as the input size increases?

• O(n)

• O(log n)

• O(n^2)

• O(1)

If an algorithm's time complexity is O(n!), what type of algorithm is this?

• Constant

• Linear

• Exponential

• Factorial

Which Big O notation represents linear time complexity?

• O(log n)

• O(n^2)

• O(1)

• O(n)