Turner, D. In: Jouannaud, J. FPCA LNCS, vol. Barendregt, H.
In: de Bakker, J. PARLE Hughes, J. Hinze, R. In: Reps, T.
Why Functional Programming Matters For Me – Welcome
Modular design brings with it great productivity improvements:. It is also the goal for which functional programmers must strive — smaller and simpler and more general modules, glued together with the new glues we shall describe. Higher-order functions enable simple functions to be glued together to make more complex ones. The example given in the paper is foldr , which captures a common computation pattern over lists, such that we can write for example:.
These examples should be enough to convince the reader that a little modularization can go a long way.
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By modularizing a simple function sum as a combination of a higher-order function and some simple arguments, we have arrived at a part foldr that can be used to write many other functions on lists with no more programming effort. All this can be achieved because functional languages allow functions that are indivisible in conventional programming languages to be expressed as a combinations of parts — a general higher-order function and some particular specializing functions. Once defined, such higher-order functions allow many operations to be programmed very easily.
Whenever a new datatype is defined, higher-order functions should be written for processing it.
This makes manipulating the datatype easy, and it also localizes knowledge about the details of its representation. Lazy evaluation requires a little more thinking to see why Hughes classes it as a modularization mechanism: lazy evaluation makes it practical to modularize a program as a generator that constructs a large number of possible answers, and a selector that chooses the appropriate one. Without lazy evaluation this would not always be practical or even possible, in the case of infinite generators.
We have described lazy evaluation in the context of functional languages, but surely so useful a feature should be added to non-functional languages — or should it?
Tell us what you think
Can lazy evaluation and side-effects coexist? Something to think about for those languages that like to blend functional and non-functional constructs…. Such global interdependence would defeat the very modularity that — in functional languages — lazy evaluation is designed to enhance.
There follows in the paper a series of examples demonstrating the power of lazy evaluation and higher-order functions: Newton-Raphson square roots; numerical differentiation and integration; and an alpha-beta heuristic for evaluating game trees. How should we structure complex and large software programs? How can we ensure they are modular and easy to maintain and reason about? Functional programming provides higher order functions and lazy evaluation. How can these features be used to write programs with these nice properties? This paper shows how FP can be not only efficient, productive and formal, but also very beautiful.
With an easy-to-understand style, John uses two examples in this paper to show how complex programs can be written in a VERY elegant and maintainable way.
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I hope to go together with you through these examples, and share the excitement I had when I first read this landmark paper. Sc in Computer Science back in Brazil, and during this period loved low-level tinkering with electronics, operating systems and networking some of this tinkering still persists as lunch chats and hobbies. Also during his bachelor, in , he heard for the first time of this thing called "Haskell" and started to write lots of class projects in it.
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Now he is doing Ph. D research also in Utrecht, on the formal description and verification of digital circuits.