Course number 67650 – Spring 2011

Experimental Approaches in Computer Science

This course is complementary to Topics in Performance Evaluation. This course is more about measurements, including examples of discovering unknown facts about workloads or the Internet, and generally the use of experimental procedures. The other course places more emphasis on the methodologies of simulation and analysis, and presents several case studies of performance evaluation. The plan is to give these two courses in alternate years.

Course Details:

Class location: Shprintzak 213, Tuesday 16–18
Teacher: Prof. Dror Feitelson
Questions: send email to feit@cs
Exercises: submit exercises and get grades and comments using the Moodle system



And look at the (tentative) week-by-week plan of the course.


The grade in the course will be determined by your work throughout the course (“avoda shotefet”). There will be 12 weekly exercises, worth 7.5 points each. The exercises are designed to be reasonably short and simple (at least once you get the hang of it). They are typically due 6 days after the topic is discussed in class, so that we can talk about the results the following week. Please do the exercises in pairs, and use this to discuss what you are doing, gain a better understanding, and achieve better results.

If you have a good reason for not doing one or more of the exercises (e.g. you have milu'im for the whole period) you will be excused, and the grade will be calculated based on the others (but if your partner has milu'im, only he gets excused!). There will be no final exam, but there will be a short quiz in the last class worth 10 points. The material for the quiz is all the lectures and exercises. Thus you should come to the lectures and really take part in all the exercises (don't alternate with your partner!)

The default grade for a “very good” exercise is 95. A grade of 100 is reserved for whoever does something special extra, or shows some special insights. Note that 100 is not automatic for doing extra work — it has to be interesting and meaningful.


For more information on various topics, see the collection of experimental computer science links.

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