![\"Foundations](\"https:\/\/i0.wp.com\/farm1.static.flickr.com\/22\/97150393_42a89de26c_m.jpg?resize=240%2C157\" "\\"Langdon")
<\/a>\nSome deluded people believe that textbook orders for Fall Semester were due a month ago, but I’m never, ever close to on-time on these things, and am just now getting to it in a serious way. I’m teaching three courses in the fall:<\/p>\n
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- Models of Computing Systems<\/li>\n
- Fuzzy logic and fuzzy sets<\/li>\n
- Refactoring<\/li>\n<\/ul>\n
I’ve taught Refactoring several times and have a pretty good handle on that. Fuzzy Logic I’ve taught once before and am pretty comfortable with. The Systems course, however, is one I’ve never taught before and am still struggling with on a number of levels, including the textbook.<\/p>\n
Any suggestions and ideas on any of these would most certainly be appreciated. I’ll say a little more about each course below the fold for those who want all the gory details.<\/p>\n
<\/p>\n
Models of Computing Systems<\/strong> This is one of our three core courses (the others being Algorithms and Computability, and Software Design and Development), is a 5 credit course (4 hours of lecture and a 2 hour lab each week), and is intended to expose students to computing systems using a layer model that includes as major topics<\/p>\n
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- Assembly language and a quickie overview of basic architecture<\/li>\n
- Operating systems basics, with an emphasis on processes, process management, and threading\/concurrancey<\/li>\n
- Computer networks<\/li>\n
- System administration, including the installation, configuration, and management of common tools like web servers<\/li>\n<\/ul>\n
I’m planning to use x86 assembly for the first item, and the sysadmin work will happen on Linux boxes. I’m planning (still in a vague way at the moment) to try to use computer security issues to motivate\/illustrate a number of key concepts in this course. Things like file system and disk structure can be pretty abstract, for example, but I’m thinking that doing a lab where we see how those decisions lead to lots of “erased” data being recoverable might make it seem more “real” and significant.<\/p>\n
I realize that no book is going to cover all these things, and on-line resources plus lecture can provide the necessary background for several of these. This course has typically using a “standard” OS book like Silberschatz, et al<\/a>, but this is large and expensive and really only addresses one of the four topics. If anyone knows of a good book that would touch meaningfully on more than one of these areas, though, that would be really helpful.<\/p>\n
Fuzzy logic<\/strong> This is a 2 credit elective course, and should provide a reasonable background in the theoretical definitions and concepts in fuzzy logic, as well as giving the students a chance to apply those ideas. (My current plan is to write robot race car drivers using fuzzy notions of concepts like fast, slow, near, and straight.)<\/p>\n
I’m probably more interested in solid coverage of the theoretical material than the applications side. The students will benefit from a good introduction and reference on the mathematical material, and I can probably handle the motivation and application side in class pretty well.<\/p>\n
When I last taught this (Spring, 2006) I used An Introduction to Fuzzy Logic for Practical Applications<\/em> by Kazuo Tanaka, translated by T. Niimura<\/a>. That book actually worked quite decently. There were some predictable translation issues, but nothing that we couldn’t manage.<\/p>\n
Refactoring<\/strong> This is also a 2 credit elective course. I’ve taught this course several times, and I’m likely to again use a combination of Fowler’s Refactoring<\/em><\/a> and Kerievsky’s Refactoring to Patterns<\/em><\/a>. Fowler is the “standard” in the field; the first five chapters of his book are absolutely classic material on the realities of software development and should be read by pretty much anyone who aspires to write good software. Kerievsky’s book builds on Fowler and does a really nice job of demystifying design patterns, converting them from magical insights codified by geniuses into things you could discover on your own through careful refactoring. When I last taught it I think I had Kerievsky as the required text and Fowler as the optional book. Given that together they still add up to less than $100, I’m tempted to require them both. We have lots of copies of Fowler in the lab, though, so I might just require Kerievsky again. Ideas\/thoughts on this would definitely be appreciated.<\/p>\n
One of the problems we’ve run into in this course in the past has been attempting refactorings on code with limited automated testing. Without good tests you lose your courage to refactor mercilessly, or you have false courage and end up breaking things without realizing it until (sometimes much) later. With only 2 credits to work with, however, you don’t want to spend two weeks writing unit tests for a system before you can start refactoring it, especially when you don’t really understand what the units are and what they’re supposed to be doing. This time I’m planning to use BDD tools like Cucumber, RSpec, and JBehave this time to more cheaply write high level acceptance\/functional tests that exercise the key parts of the system in meaningful ways without getting bogged down in a bunch of poorly understood unit tests. We’ll see how that goes.<\/p>\n