ML for the Working Programmer

Rating:
Summary: a good book, but it wasn't compelling for me
Review: I have no doubt this is a well-written book (I read it in its entirety). Unfortunately, the examples weren't compelling to me at all. While the lambda calculus interpreter was interesting, the time spent on the theorem prover was not very interesting (I wonder if it was added as an homage to ML's legacy??).

Overall, I suppose this book is a little dated.

Rating:
Summary: Good introductory book with some advanced chapters
Review: If you want to know something about ML, but learn it through good examples and interesting problems. This is the book! Also has some neat chapters on automated theorem proving, logic and interpreters.

Rating:
Summary: Completely mistitled
Review: This book is not bad; the explanation of all that it does explain is very good. It's just somewhat impractical, especially given the name; the title is a terrible misnomer for a book whose major example projects involve a lambda calculus evaluator and a proof assistant for first-order logic (not exactly the sort of thing "working" programmers usually have to do!). It does have some pretty solid demonstrations of how to implement various useful data structures and algorithms in SML (e.g. trees), but no "real-world" projects.

The problem with this book is typical of the problem facing a lot of introductory material for many of the more academic languages-- they explain the theory behind the language very well and how the features work, but they don't really teach you how to organize programs in the language, stuff like what code to put in what file, when to use modules and functors, etc. If you cut your teeth in imperative OOP like I did, reading this book you might get to understand the features of this language, but without still being clear about how one would go about writing an actual program in it.

Still, this is a book worth owning.