ML for the Working ProgrammerCambridge University Press, 1996 M06 28 The new edition of this successful and established textbook retains its two original intentions of explaining how to program in the ML language, and teaching the fundamentals of functional programming. The major change is the early and prominent coverage of modules, which are extensively used throughout. In addition, the first chapter has been totally rewritten to make the book more accessible to those without experience of programming languages. The main features of new Standard Library for the revised version of ML are described and many new examples are given, while references have also been updated. Dr Paulson has extensive practical experience of ML and has stressed its use as a tool for software engineering; the book contains many useful pieces of code, which are freely available (via the Internet) from the author. He shows how to use lists, trees, higher-order functions and infinite data structures. Many illustrative and practical examples are included.. Efficient functional implementations of arrays, queues, priority queues, etc. are described. Larger examples include a general top-down parser, a lambda-calculus reducer and a theorem prover. The combination of careful explanation and practical advice will ensure that this textbook continues to be the preferred text for many courses on ML. |
Dentro del libro
Resultados 1-5 de 87
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... result in injury to a person or loss of property. If you dousethe programs or procedures in such a manner, itisat your own risk.Theauthor and publisher disclaim all liabilityfordirect, incidental or consequential damages resulting ...
... result in injury to a person or loss of property. If you dousethe programs or procedures in such a manner, itisat your own risk.Theauthor and publisher disclaim all liabilityfordirect, incidental or consequential damages resulting ...
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... result of evaluating it, which is why subexpressions can be evaluated independently of eachother. The meaning ofan expressioncanbe extremely simple, likethe number3.The meaning of a command is a state transformation or something equally ...
... result of evaluating it, which is why subexpressions can be evaluated independently of eachother. The meaning ofan expressioncanbe extremely simple, likethe number3.The meaning of a command is a state transformation or something equally ...
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... result: tactics were higherorder functions. Tacticals providedcontrol structures for combining simple tactics into complex ones. Theresulting tactics could be combined toform stillmore complex tactics, which in asingle step could ...
... result: tactics were higherorder functions. Tacticals providedcontrol structures for combining simple tactics into complex ones. Theresulting tactics could be combined toform stillmore complex tactics, which in asingle step could ...
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... resulting environment provides ample support for the most demanding projects. 1.9. ML. and. the. working. programmer. Software ... result could be expensive or disastrous.What would we think ofasailing enthusiast who wears his lifejacket when ...
... resulting environment provides ample support for the most demanding projects. 1.9. ML. and. the. working. programmer. Software ... result could be expensive or disastrous.What would we think ofasailing enthusiast who wears his lifejacket when ...
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... result. Interaction is fun;itgives immediate feedback; it lets you develop programs in easily managed pieces. We can enter an expression followed by a semicolon ... ... and MLresponds Here we see some conventionsthat willbe followed ...
... result. Interaction is fun;itgives immediate feedback; it lets you develop programs in easily managed pieces. We can enter an expression followed by a semicolon ... ... and MLresponds Here we see some conventionsthat willbe followed ...
Contenido
Summary of main points 4 Trees and Concrete Data | |
Functions and InfiniteData Chapter outline Functions asvalues 5 1 Anonymous functionswith | |
Summary of main points 3 Lists | |
Summary of main points 7 Abstract Types andFunctors Chapter outline | |
Imperative Programming in ML | |
Summary of main points 10 A Tactical Theorem Prover | |
Términos y frases comunes
abstract type algorithm applied argument arithmetic binary search trees binary tree callbyvalue canbe characters components compute constructors contains curried function data structures datatype datatype declaration defined depthfirst search dictionary efficient elements empty error example exception Exercise expression flexible arrays foldl foldr formula functional programming functor handler heap higherorder functions imperative programming implement infix infix operator input insert integers iterative label lazy evaluation logic lookup match mathematical mathematical induction matrix merge sort ML’s modules multisets natural numbers node normal form notation numbers ofthe output pairs parameter parser parsing pattern patternmatching polymorphic polynomials predicate priority queues proof proposition prove quantifier real numbers recursive call recursive functions references replaces representation represented result returns rule Section sequence sequent calculus signature solutions sort specifies standard library Standard ML string structural induction subgoal subtrees syntax tactics takes term terminate theorem update vector wellfounded