ML for the Working Programmer

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Críticas: "Paulson is a leader in the field of computer-aided proof, and that field inspires the book's best examples, including a tautology checker, a parser, and a pretty good printer. There is a fascinating collection of search algorithms, which illustrate with good effect how ML can mimic 'lazy' evaluation. These examples culminate in a wonderful final chapter that presents a theorem prover, of just the kind ML was created to support....Paulson writes with vigour and with humour. The book is spiced with jokes and polemics....He minces few words, and as a result he occasionally overstates his case. But better to speak forcefully than to say nothing at all." Philip Wadler, Times Higher Education Supplement ."..a readable guide to functional programming, which will take the reader through all the features of Standard ML, including exceptions, the module system, and imperative reference types...." Simon Thompson, Computing Reviews ."..the first available book that presents ML to a general audience. The author succeeds in explaining the features of ML in digestible chunks. Numerous examples are presented for illustration. Parts of the book, I think, go beyond the interests of a majority of working programmers, but programmers who continue their education (formally or otherwise) will find some interesting material to broaden their knowledge....Overall, I found this book to be informative and useful." Reginald Meeson, ACM SIGPLAN "If you are an experienced programmer who wants to learn Standard ML, then this is the text for you. The book succeeds on two levels: as an introduction both to the strengths of functional programming in general, and to the intricacies of Standard ML in particular. It is filled with well-crafted programs that reveal the tricks of the functional programmer's trade. There is a readable explanation of the sophisticated modules system, and danger signs warn you of the few remaining infelicities in the language.....There is a fascinating collection of search algorithms, which illustrate with good effect how ML can mimic 'lazy' evaluation. These examples culminate in a wonderful final chapter that presents a theorem prover, of just the kind ML was created to support....Paulson writes with vigour and with humor. The book is spiced with jokes and polemics." Philip Wadler, Times Higher Education Supplement