GEORGE MASON UNIVERSITY
DEPARTMENT OF COMPUTER SCIENCE
CS 700 - RESEARCH METHODOLOGY IN CS
Fall 2018
Prof. Sanjeev Setia
setia at gmu.edu
703-993-4098
Description
Prerequisites: Admission to PhD in
CS or PhD in IT programs. 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. All incoming CS PhD
students are required to take this course in their first year in the
program.
Readings
Textbook:
David Lilja, Measuring Computer Performance: A
Practitioner's Guide, Cambridge University Press,
2005. ISBN: 05216-4670-7.
Other recommended
books:
- Raj Jain, The Art of
Computer Systems Performance Analysis, John Wiley, 1991,
ISBN: 0-471-50336-3. Please download the errata
- Dror Feitelson. Workload
Modeling for Computer Systems Performance Analysis.Cambridge
University Press, 2016. ISBN: 978-1-107-07823-9
- Balachander Krishnamurthy
and Mark Crovella, Internet Measurement:
Infrastructure, Traffic, And Applications, John
Wiley and Sons, Inc., 2006. ISBN: 04700-1461-x
- I. Miller, J. Freund, R.
Johnson, Probability and Statistics for Engineers,
Sixth Edition, Prentice Hall, 2000, ISBN: 0-13-014158-5.
- David M. Levine, Patricia
P. Ramsey, Robert K. Smidt, Applied Statistics for
Engineers and Scientists: Using Microsoft Excel &
MINITAB, Prentice Hall, 2001, ISBN: 0134888014.
- Averill M. Law and W. David
Kelton, Simulation Modeling
and Analysis, McGraw Hill, 2000.
Course Outline
The following topics will be covered (not necessarily in the order
below):
- Overview of Research Process for a PhD student
- Research Integrity
- Reading and Reviewing Research Papers
- Presentation techniques
- Experimental Techniques for CS researchers
- Measurement Tools & Techniques
- Introduction to Simulation & Emulation
- Statistical and Quantitative Methods for CS research
- Summarizing Measured Data
- Characterizing Measured Data
- Introduction to analytical modeling
All CS faculty will be invited to give research overview talks to
the class. The faculty research talks will be scheduled multiple
times a semester (with perhaps all the faculty working in an area
giving talks on the same day).
All incoming PhD students are required to take CS 701 - Research
Experience in CS during their second semester. Students will be
matched with faculty for CS 701 during the course of the semester
in CS 700.
Grading
The grade for the course will be based on the following
components: (i) Homework Assignments (50%) (iii) Mid-term exam
(25%) (iii) Take home final exam (25%).
Important Dates
Mid-term exam: October 26 (tentative)
Office Hours
Office hours will be on Thursday from 3-4 pm in my office (Room
4300, Engineering Building), or by appointment.
Course Material
All handouts and other course material will be available at the
Blackboard page for the class.