1. In computer science, best, worst, and average cases of a given algorithm express what the resource usage is at least, at most and on average, respectively

2. In real-time computing, the best-case execution time is often of particular concern since it is important to know how much time might be needed in the best case to guarantee that the algorithm will always finish on time.

3. Computer A appears to be running an algorithm that is more efficient. What do we need to do to truly test the algorithms?

4. Computer A, running the linear search program, exhibits a linear growth rate. The program's run-time is _________________________

5. The followning algorithms/groups of statements are examples that have a time complexity of:

6. The best case time complexity for the merge sort is:

7. The best case time complexity for the insertion sort is:

8. Th worst case time complexity for the insertion sort is:

9. Th worst case time complexity for the bubble sort is:

10. If your priority was to ensure the quickest possible 'access by index', you would be most likely to use:

11. The addition feature in an array would be O(n) and in a linked list would be:

12. The worst case space complexity for Merge sort is:

13. The worst case space complexity for Bubble sort is:

14. O(n) access time would mean whether you're accessing from 100 or 100,000 records, the retrieval time will be the same

15. A simple example of O(1) might be return 23; -- whatever the input, this will return in a fixed, finite time

16. A typical example of O(n) would be sorting an input array with a good algorithm (e.g. mergesort).