Space Complexity – Part 2

The video tutorial discusses space complexity in coding, focusing on how different data structures affect space usage. Initially, a list is used to store results, leading to higher space complexity. The tutorial then explores optimizing space by using a single variable, which reduces space complexity to O(1). The instructor compares these approaches, highlighting the benefits of minimizing space usage. The video concludes with a summary of the key points discussed.

What is the space complexity when using a list to store results for each element?

• O(1)

• O(n)

• O(n^2)

• O(log n)

In the optimized approach, how is the space complexity reduced?

• By using multiple variables

• By storing results in a single variable

• By increasing the number of iterations

• By using a more complex data structure

What happens to the stored result in each iteration in the optimized approach?

• It is appended to a list

• It is stored in a stack

• It is overwritten

• It is stored in a new variable

Why does using a list for each element result in higher space complexity?

• Because it requires additional space for each element

• Because it uses a complex algorithm

• Because it reduces the number of iterations

• Because it uses a single variable

What is the main advantage of the optimized approach discussed?

• It increases time complexity

• It requires more iterations

• It reduces space complexity

• It uses more memory