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module1-print - Module 1 Overview and background Whats it...

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Module 1 Overview and background What’s it all about? CS 360: Introduction to the Theory of Computing Daniel G. Brown, modified by Margareta Ackerman, University of Waterloo 1.1 1 Welcome Topics of Module 1 Administrivia Overview of the course Mathematical background 1.2 2 Administrivia Staff Instructor Margareta (Rita) Ackerman, mackerma@uwaterloo.ca Office hour: Thursdays 4-5, DC 2515 TAs Jalaj Upadhyay, jkupadhy@cs.uwaterloo.ca Office hours: Fridays 11-12, DC 3324 Soumojit Sarkar, s9sarkar@uwaterloo.ca Office hours: Wednesdays 12-1, DC2302C We’re here to help. 1.3 Administrivia Course information (assignments, lecture notes, schedules, etc.) all on course web page. www.student.cs.uwaterloo.ca/ cs360 Grading for the course: 5 assignments: 25% (5% each) midterms: 25 % final exam: 50% 1.4 Dates and times Midterms A midterm on October 20 during class time, in MC 4045. Homeworks Due at 4 PM on Fridays. Final exam In December. I’ll tell you when once I know. 1.5 1
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Overview of course What is this course about? Theory of computing What does it mean to compute? What kinds of machines compute? How much more can computers do as we give them new powers? Who cares? 1.6 Who cares? We’ll keep coming back to that. Here are a few reasons: Philosophical: Good to have a sense of what computation means Mathematical: Mathematical rigor underlying computer science Engineering: Many practical problems are about engineering with small resources. How does this limit us? Scientific: Some advances will not change the power of computers; others would be enormous. Let’s pursue the important ones. 1.7 How we’ll study theory A focus on mathematical rigor. Example: you’ve already seen a lot of the first few weeks of the course, but without detail. Prove almost everything we do Lots of proof techniques and approaches Functions, sets, sets of sets, etc. 1.8 Course myths This course has several: It’s too easy You’ve seen regular expressions in 241. A lot of it sounds reasonable. Easy to convince yourself you understand them, even if you don’t! This is dangerous! It’s too hard Some complicated topics in the course come back after you think you’re done with them Later part of the course is harder than the beginning 1.9 Other myths It’s irrelevant Problems are like puzzles, not like what happens at your co-op jobs Where’s the connection between a finite automaton and your desktop? We’re ignoring all the complexity of computation! But these are myths. 1.10 Only myths Myths are not always true. The advantage of our approach: Focus on important core of a problem, not implementation details Abstraction lets you get at the essence of computing, not than wiring details And, many 360 ideas are used directly in important applications. They come up in bioinformatics, parsing, data compression, and in other areas.
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module1-print - Module 1 Overview and background Whats it...

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