UMBC CMSC202, Computer Science II, Spring 1998, Sections 0101, 0102, 0103, 0104 and Honors

Thursday February 12, 1998

Assigned Reading:

• A Book on C: 8.15
• Programming Abstractions in C: 7.5-7.6

Handouts (available on-line): Project 2

Topics Covered:

• Announcements:
  • Section 0104 is open and meets on Wednesday 10:00 - 10:50 in ACIV Room 151.
  • Note that the TAs office hours have been posted.
  • The Help Center is open.
  • Reminder that cheating will not be tolerated in this course.
  • Review for Exam 1 will take place during recitation, not lecture.
  • Admonition that learning how to read technical documentation (e.g., the man pages) is an integral part of learning how to program.

• Merge Sort can be implemented without using recursion. However, the iterative program is much more complicated than the recursive version. Somewhat surprisingly, we also discover that this iterative implementation of the Merge Sort is a bit slower than the recursive version (sample runs). Hence, using recursion results in cleaner code and sometimes faster code as well.

• Quicksort is another divide-and-conquer algorithm for the sorting problem. One difference between Quicksort and Merge Sort is that the partition() function is used to divide the array into two parts such that all the numbers in the first half are smaller than the numbers in the second half. This eliminates the need for the merge() function used in merge sort. Testing the Quicksort function shows that the running times are a bit faster than Merge Sort (sample runs).

• Graphing the running times of Merge Sort versus Quicksort reveals that the running times are approximately proportional to n log n, where n is the number of items to be sorted.

• We can tweak the Quicksort and Merge Sort programs for somewhat better performance. We tweaked Merge Sort by calling insertion sort for arrays with fewer than 20 numbers instead of recursively calling Merge Sort. For small arrays, insertion sort can be faster than Merge Sort. The sample runs show approximately 15% improvement in the running times compared to the previous version of Merge Sort.

• Similarly, we tweaked Quicksort to achieve a slight improvement in the running times compared to the previous running times.

• We discussed Project 2.