Oddly, graphics processing is very functional, yet procedural languages are used to teach it. In a nutshell, matrices operate on matrices operate … . In between some of the stages, drawing takes place; the rightmost argument is the beginning of the scene. Years ago, I gave up learning OpenGL because it was so tedious. Now that I am enlightened by FP, I understand and enjoy graphics programming so much more that I wrote an API just for the fun of it.
(via PLT)
This is a good article that might make you think twice about making performance optimizations in your code. My take is that the author is implying that you only have so much time to work on the code so you should focus on areas where the users will actually appreciate your efforts. That makes sense.
Costanza asked Sussman why MIT had switched away from Scheme for their introductory programming course, 6.001. This was a gem. He said that the reason that happened was because engineering in 1980 was not what it was in the mid-90s or in 2000. In 1980, good programmers spent a lot of time thinking, and then produced spare code that they thought should work. Code ran close to the metal, even Scheme — it was understandable all the way down. Like a resistor, where you could read the bands and know the power rating and the tolerance and the resistance and V=IR and that’s all there was to know. 6.001 had been conceived to teach engineers how to take small parts that they understood entirely and use simple techniques to compose them into larger things that do what you want.
But programming now isn’t so much like that, said Sussman. Nowadays you muck around with incomprehensible or nonexistent man pages for software you don’t know who wrote. You have to do basic science on your libraries to see how they work, trying out different inputs and seeing how the code reacts. This is a fundamentally different job, and it needed a different course.
So the good thing about the new 6.001 was that it was robot-centered — you had to program a little robot to move around. And robots are not like resistors, behaving according to ideal functions. Wheels slip, the environment changes, etc — you have to build in robustness to the system, in a different way than the one SICP discusses.
And why Python, then? Well, said Sussman, it probably just had a library already implemented for the robotics interface, that was all.
(via wingolog)
The release notes here for PLT Scheme 4.1.5 mention support for literate programming. Not being familiar with the term; I read more about it on Wikipedia here.
I have wanted in-code documentation generation tools to serve this purpose; but I have never succeeded with them. It had always felt like I was battling the intent of the tool. Even Eiffel’s notion of different views on code-as-documentation never quite fit for me. This approach is fascinating; it allows for you to tell a story about the code as you write the code. Having posted to the PLT list asking about it here; two folks replied with details on this style and Scheme.
PLT Scheme recently added literate programming support; documented here. One example of its application is in Chat Noir here; and the source code for it may be viewed here (Thanks Robby).
A tool for literate programming in Scheme called is schemeweb located here (Thanks Phil).
Here is a seemingly nice presentation by Guy Steele. I haven’t watched it yet but the original poster vouched for it.
(via comp.lang.scheme)
A few weeks on a PBS television show hosted by Alan Alda the scientists being interviewed were talking about the “Contentment of Content”. They said the the research shows that most humans learn the bulk of their knowledge (in particular their approach for all sorts of problem solving) younger in life and never learn any new approaches later on because it would just show them how much they don’t know. In other words; it would require the act of learning and that takes work. They go on to explain that in fact, this approach not only happens at the macro level in life but also in the macro level for particular areas of expertise. For sake of discussion, I would focus on programming.
The idea is that once you learn how; you are very, very unlikely to learn “new ways of doing it”, and why would you? It makes you feel bad since it makes you look like you don’t know what you are doing. It is also very, very unpopular to admit that you don’t know everything (I wonder if it has always been this way?). This is unfortunate because most of us really never learned how to program well and in fact seems to be the complete antithesis of the behavior and approaches that are likely to have made you successful as a programmer in the first place.
Here is a good post about language design philosophy and implementation details of inner classes in Java. The focus is more on the latter; and the article is still interesting.
If you have already got a lot of PDFs then you probably have a personal approach to managing all of the content. For example, I keep everything sorted by topic in a directory structure. Here are two ways that seem to provide a better approach (both are interesting): Papers and Digital Editions.
(via Pascal)
This presentation is brilliant and inspiring. Maybe the ideas aren’t new; but the way that Hamming put it all together really “spoke” to me.
It might seem like a long read; but isn’t personal success worth your time?
For now I am not going to highlight the key points; that is an exercise much better left to the reader.
(via Reddit)
Here I asked “What is a good multi-paradigm book on programming?”.
Michael answered:
“Concepts, Techniques, and Models of Computer Programming” by Peter Van Roy and Seif Haridi
http://www.info.ucl.ac.be/~pvr/book.html
