Data Structures and Its Applications

1.       What does Big O notation describe?

• A) Space complexity

• B) Worst-case time complexity

• C ) Average-case time complexity

• D) Best-case time complexity

2. 2. Which notation describes the lower bound of an algorithm’s running time?

• A) Big O

• B) Omega

• C) Theta

• D) Small o

3.       Which case complexity considers the average inputs?

• A) Best case

• B) Average case

• C) Worst case

• D) All of the above

4. 4.       What does asymptotic analysis focus on?

• A) Real-time performance

• B) Input size trends

• C) Hardware efficiency

• D) Algorithm pseudocode

5. 5.       The time complexity of accessing an element in an array is:

• A) O(1)

• B) O(n)

• C) O(log n)

• D) O(n log n)

6.       Which notation describes the upper bound of an algorithm’s running time?

• A) Big O

• B) Omega

• C) Theta

• D) Small o

7.       If an algorithm takes constant extra space, its space complexity is:

• A) O(1)

• B) O(n)

• C) O(n^2)

• D) O(log n)

8.       What is the time complexity of a nested loop structure with two levels each iterating n times?

• A) O(n)

• B) O(log n)

• C) O(n^2)

• D) O(n log n)

9.       Which notation provides an exact asymptotic behavior?

• A) Big O

• B) Omega

• C) Theta

• D) Little o

10.       An algorithm has a complexity of O(n log n). Which of the following is an example?

• A) Binary Search

• B) Merge Sort

• C) Insertion Sort

• D) Bubble Sort