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Links 1 through 10 of 11 by Atif Aziz tagged fp

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James Roper explains and builds iteratees and enumeratees from ground-up.

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“Research published a few years back indicated that dispatching through a vtable incurred astonishing overheads, as high as 50% of total execution time. Alternative dispatch techniques based on runtime tests, such as a linear sequence of if statements checking for the various concrete class types, or a sequence of nested if statements forming a binary search, were often more efficient on a variety of hardware.”

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“We consider the design of a circuit description library for a pure functional language where circuits are defined as functions and connected together by writing applicative expressions. Just like the return value of any other function in a functional program, the output of a circuit can be bound to a variable and referred to many times. Usually it is the programmer’s intention that such references represent sharing of a circuit’s output, implying a fanout structure. However, in a pure functional language, references are transparent and the circuit description library can only view finite graph-shaped circuit structures as infinitely expanded regular trees. To overcome this problem, we introduce expressible sharing, a technique in which the programmer expresses the fork-points present in a circuit in the same way that they express other circuit components like and-gates and or-gates.”

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Peteris Krumins takes a look at what functors mean to ML, Haskell, C++ and Prolog.

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“Saying that LINQ is a monad isn't quite right, because the LINQ syntax can be used for encoding other types of computations too. In this article, [Tomas demonstrates] how to use it for writing code using idioms. Idioms are weaker than monads - in the object oriented terms, this means that the "monad interface" inherits from "idiom interface". As a result, some computation types can implement the "idiom interface", but cannot be written as monads. [Tomas looks ]at ZipList, which is one example of such computation type.”

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“With the spreading popularity of languages like F# and Haskell, many people are encountering the concept of an algebraic data type for the first time. When that term is produced without explanation, it almost invariably becomes a source of confusion. In what sense are data types algebraic? Is there a one-to-one correspondence between the structures of high-school algebra and the data types of Haskell? Could I create a polynomial data type? Do I have to remember the quadratic formula? Are the term-transformations of (say) differential calculus meaningful in the context of algebraic data types? Isn’t this all just a bunch of general abstract nonsense? We’ll investigate these questions, and perhaps demystify this important concept of functional languages.” Also broaches the idea behind the Zipper data structure.

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Y fixed-point combinator explained through a serious of generalization of anonymous recursion in C#.

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One of the hardest things about learning Haskell is you can't understand Haskell without understanding monads, and you can't understand most of the monad examples without understanding Haskell. Hence, for better or worse, here's Maybe in Python and JavaScript.

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This post demonstrates how to get recursion into own lambda expressions in C#. It is meant to be more fun than practical, especially because readability is sacrificed.

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