Description: Topics include approaches for evaluating, writing, and presenting scholarly papers, research integrity issues, and quantitative models and methods in experimental computer science. Techniques for the use of analytic and simulation models, design of experiments, hypothesis testing, and statistical analysis of data are presented. Students apply these techniques to a project, write a report, and make a presentation to the class.
All PhD CS students with start term Spring'25 or Fall'25 must take this course during Fall'25.
Prerequisites: Admission to PhD in Computer Science or PhD in Information Technology programs.
Meeting Time and Location: Wednesday 4:30 - 7:10 PM, Art and Design Building Room L008.
Required reading: David Lilja, Measuring Computer Performance: A Practitioner's Guide, Cambridge University Press, 2000.Instructor Office Hours: Wednesday 2:00 - 3:00 PM and by appointment. (ENGR 5308)
Graduate Teaching Assistant (GTA):
Amit Paudyal (apaudya@gmu.edu)
GTA Office Hours: TBA.
Grading: Grading components will be as follows.
| A+ | 95% |
| A | 90% |
| A- | 85% |
| B+ | 80% |
| B | 75% |
| C | 50% |
| F | 0% |
Completed homeworks and assignments must be submitted on Canvas, unless otherwise stated. If a student makes multiple submissions, only the last submission will be graded. It is critical that the students double check the files they are submitting, as submitting a wrong, corrupt, or empty file is very likely to result in a score of 0 for that assignment. Students are responsible for keeping back-ups of their work while they are working on an assignment. The students are required to take measures to protect the confidentiality of their class work on shared computers.
The students, if they feel that their work is not accurately graded, must initiate contact with the grader within seven days that follows the availability of the grade on Canvas. Grade contesting beyond this time window will not be allowed.
Academic Standards Code (Honor Code): All students must abide by the GMU Academic Standards Code and CS Department's Honor Code and Academic Integrity Policies during the semester. We reserve the right to use automated tools such as MOSS to detect plagiarism. The violations of Honor Code will be reported to GMU Academic Office without any exception. The university procedures for adjudicating such violations, including types of sanctions and GMU Sanctions Matrix can be found at the following link. All students must be familiar with the Academic Standards code, as well as Common Policies Affecting all Courses at George Mason University.
AI tools: The use of assistive technology or artificial-intelligence-based tools is not allowed in any assignment/project/assessment.
Use of electronic devices During the lectures, students can use tablet or laptop computers only for note-taking purposes. Smartphones should be silenced and put away during the lectures.
Class Home Page: Throughout the term, the course material (announcements, slides, handouts, etc.) will be available on the GMU Canvas system. Important announcements will be also sent by e-mail to the students' GMU e-mail addresses through Canvas announcements. Students must make sure to turn on the immediate notification (by e-mail) feature on Canvas in order to receive instructor announcements in a timely manner.
Disability Statement: If you have a learning or physical difference that may affect your academic work, you will need to furnish appropriate documentation to GMU Disability Resource Center (DRC). If you qualify for accommodation, the DRC staff will give you a form detailing appropriate accommodations for your instructor. If you have such a condition, you must contact the instructor during the first week of the term about the issue.