Program Complexity Analysis MCQ Test 4

1. What is the primary goal of analyzing algorithmic complexity?

2. In the context of algorithmic analysis, what is 'average-case time complexity'?

3. How does 'A* search algorithm' differ from 'Dijkstra's algorithm'?

4. What does 'Dijkstra's algorithm' primarily focus on?

5. How does 'linearithmic time complexity' differ from 'linear time complexity'?

6. What is the primary goal of code optimization in program complexity analysis?

7. Why is 'algorithmic efficiency' a crucial aspect of program complexity analysis?

8. In algorithm analysis, what does 'linear time complexity' signify?

9. What does 'NP-hard' imply about a computational problem?

10. Why is 'average-case complexity' important in algorithmic analysis?

11. What does 'best-case scenario analysis' focus on in algorithmic complexity?

12. What is the significance of 'Amortized Analysis' in algorithmic complexity?

13. When is 'Merge Sort' considered advantageous over 'Quick Sort'?

14. Why is 'exponential time complexity' a concern in algorithm analysis?

15. How does the 'Traveling Salesman Problem' contribute to algorithmic complexity discussions?

16. Why is code optimization important in program complexity analysis?

17. What is the Big O notation used for in program complexity analysis?

18. Why is 'average-case analysis' essential in algorithmic complexity?

19. What characterizes an algorithm with 'exponential growth' in program complexity analysis?

20. What does 'constant time complexity' imply in algorithm analysis?