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Unformatted text preview: CSE 503: Program Analysis Winter 2010 Syllabus Course website: http://www.cs.washington.edu/503/ Class meetings: MW 10:30-11:50, room MGH 238 Lecturer: Michael Ernst http://www.cs.washington.edu/homes/mernst/ Office hours: by appointment. While there are no set office hours, I welcome discussions with students. Please don’t be shy about contacting me if you wish to meet! TA: Todd Schiller http://www.cs.washington.edu/homes/tws/ Office hours: TBA 1 Structure of the course In many years CSE 503 is a broad course that covers all aspects of software development. This year’s offering is more narrow but deeper, and can be repeated by people who have already taken CSE 503 in the past. For a list of specific topics that may be covered, see the course webpage. 2 Grades Grades will be assigned based on the project (80%), class participation (20%), and instructor discretion. As this is a graduate class, the class is likely to be A-centered, but students are not guaranteed a grade of A. 3 Papers CSE 503 is a graduate paper-reading seminar. Each class session will begin with a brief discussion and presentation of material, after (or during) which the floor will be open to rebuttals, discussion of related work, criticism, brainstorming about follow-on research, etc. At this level in your career, you should no longer be a passive listener to lectures but an active participant in the discussion. To help you prepare, you will write a one-paragraph commentary on each paper, and submit it at least 24 hours before the class meets to discuss the paper. You will post your commentary to the course webpage for viewing by the instructor and by other students. The commentary should reflect your understanding and analysis of the issues raised by the paper, and should also help direct (both your and others’) preparation for in-class discussion. You may write the commentary in whatever style you prefer that meets the goals listed above. One good format for the commentary is to critique the paper, listing the following three points: its biggest contribution (and, briefly, why that result was not already obvious), its biggest mistake (in motivation, methodology, algorithm, data analysis, conclusions, or some other area), and the biggest question that it raises (or the most interesting and important follow- on work that it suggests). Another acceptable format is to summarize the paper, describing its thesis, approach, and conclusions, and stating why it is significant. The commentary should also list questions that you have about the paper, such as about technical points or connections to related work. It’s OK if you read the paper and there are issues you do not understand. Please ask questions about those issues — both in your summary and in class — and we will all gain by the discussion. It’s best to explain why something makes no sense to you. For example, don’t just say, “I didn’t understand section 2”, but state where there is a logical fallacy or a conclusion that does not follow. The lecturer will use these questions to help shape the lectures....
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