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Do you think How to Design Programs (TtDP) is a good alternative to SICP? It seems gentler, but if one were to go the HtDP route, what would come after? SICP or

Do you think How to Design Programs (TtDP) is a good alternative to SICP? It seems gentler, but if one were to go the HtDP route, what would come after? SICP or something else? http://www.htdp.org/ http://www.htdp.org/

furo 8y ago
I can't say for sure, but the TYSCS says "For those who find SICP too challenging, we recommend How to Design Programs."
dan-robertson 8y ago
Well I don’t really know anything about it but it seems ok. The programming environment is easier to set up than in SICP which removes a barrier to entry. I’m not really convinced that scheme is the be all and end all of teaching languages. It has some nice qualities and some that can make programming more difficult. For example I think the kind of interaction is good but often in that interaction one is essentially repeatedly refactoring a small part of the program and TNT’s language does not offer much to ensure that these refactoring are correct for any definition of correct. I think a ML style language could be good for teaching too although often the errors that are produced can be quite unhelpful. The book seems like it covers some nice introductory things (like splitting up programs into small functions) and some harder things to get to grips with like quoting. But I haven’t had a very thorough look. The thing I really like about SICP is the idea of building up a model of how programs are interpreted and evaluated. The book produces plausible models for evaluation and demonstrates how one can test between the two and where they are wrong. I like this for two reasons: 1. It really feels like science, coming up with ideas, testing them, seeing when you are wrong. This feels especially useful when one considers mordern systems built out of so many individually large things that it is hard to keep track of things perfectly. It is useful in real life to build up models for what’s going on and think about how you might test them and where you might be wrong. I like that the book reminds you that computer systems may be tested in the same scientific way that the real world might. 2. (Because these evaluation models are implemented in code) it makes the process of compilation and evaluation seem much more understandable and less like magic. One can have an ok understanding of machine code and how a machine roughly works without ever having to write any. On the other hand maybe these reasons are wushu-washy and no one really needs such concepts for computer science.

furo 8y ago

I can't say for sure, but the TYSCS says "For those who find SICP too challenging, we recommend How to Design Programs."

dan-robertson 8y ago

Well I don’t really know anything about it but it seems ok. The programming environment is easier to set up than in SICP which removes a barrier to entry. I’m not really convinced that scheme is the be all and end all of teaching languages. It has some nice qualities and some that can make programming more difficult. For example I think the kind of interaction is good but often in that interaction one is essentially repeatedly refactoring a small part of the program and TNT’s language does not offer much to ensure that these refactoring are correct for any definition of correct. I think a ML style language could be good for teaching too although often the errors that are produced can be quite unhelpful. The book seems like it covers some nice introductory things (like splitting up programs into small functions) and some harder things to get to grips with like quoting. But I haven’t had a very thorough look. The thing I really like about SICP is the idea of building up a model of how programs are interpreted and evaluated. The book produces plausible models for evaluation and demonstrates how one can test between the two and where they are wrong. I like this for two reasons: 1. It really feels like science, coming up with ideas, testing them, seeing when you are wrong. This feels especially useful when one considers mordern systems built out of so many individually large things that it is hard to keep track of things perfectly. It is useful in real life to build up models for what’s going on and think about how you might test them and where you might be wrong. I like that the book reminds you that computer systems may be tested in the same scientific way that the real world might. 2. (Because these evaluation models are implemented in code) it makes the process of compilation and evaluation seem much more understandable and less like magic. One can have an ok understanding of machine code and how a machine roughly works without ever having to write any. On the other hand maybe these reasons are wushu-washy and no one really needs such concepts for computer science.