A pattern for almost compositional functions

Bringert, Björn; Ranta, Aarne

doi:10.1145/1159803.1159834

Cited by 13 publications

(22 citation statements)

References 12 publications

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“…These are well-documented and have the best-maintained implementations of the traversal-centric approaches. Other similar approaches include Smash (Kiselyov, 2006), Alloy (Brown & Sampson, 2009), Compos (Bringert &Ranta, 2008), andMultiplate (O'Connor, 2011). We already mentioned Alloy for its emphasis on selective traversal.…”

Section: Approaches To Strategic and Generic Programmingmentioning

confidence: 99%

The Kansas University rewrite engine

Sculthorpe¹,

Frisby²,

Gill³

2014

J. Funct. Prog.

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When writing transformation systems, a significant amount of engineering effort goes into setting up the infrastructure needed to direct individual transformations to specific targets in the data being transformed. Strategic programming languages provide general-purpose infrastructure for this task, which the author of a transformation system can use for any algebraic data structure.The Kansas University Rewrite Engine (KURE) is a typed strategic programming language, implemented as a Haskell-embedded domain-specific language. KURE is designed to support typed transformations over typed data, and the main challenge is how to make such transformations compatible with generic traversal strategies that should operate over any type.Strategic programming in a typed setting has much in common with datatype-generic programming. Compared to other approaches to datatype-generic programming, the distinguishing feature of KURE's solution is that the user can configure the behaviour of traversals based on the location of each datum in the tree, beyond their behaviour being determined by the type of each datum.This article describes KURE's approach to assigning types to generic traversals, and the implementation of that approach. We also compare KURE, its design choices, and their consequences, with other approaches to strategic and datatype-generic programming.

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Section: Approaches To Strategic and Generic Programmingmentioning

confidence: 99%

The Kansas University rewrite engine

Sculthorpe¹,

Frisby²,

Gill³

2014

J. Funct. Prog.

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“…Thus the overall system written in Haskell provides linearization and parsing via the GF grammar, and abstract syntax trees can be manipulated as Haskell data objects. In particular, the technique of almost compositional functions [23] is available, which makes it easy for Haskell programmers to implement conversions such as the ones in Section 5.3. The same technique is available for Java as well, and provides the easy way for Java programmers to use GF for building natural language interfaces to Java programs.…”

Section: Beyond the Baseline Translations: Easy Improvementsmentioning

confidence: 99%

Translating between Language and Logic: What Is Easy and What Is Difficult

Ranta

2011

Lecture Notes in Computer Science

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Abstract. Natural language interfaces make formal systems accessible in informal language. They have a potential to make systems like theorem provers more widely used by students, mathematicians, and engineers who are not experts in logic. This paper shows that simple but still useful interfaces are easy to build with available technology. They are moreover easy to adapt to different formalisms and natural languages. The language can be made reasonably nice and stylistically varied. However, a fully general translation between logic and natural language also poses difficult, even unsolvable problems. This paper investigates what can be realistically expected and what problems are hard.

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“…Note that this is a well-known way to implement generic functions, derived from how generic functions are implemented in PolyP. Now, using fmap, we define the compos operator of Bringert and Ranta (2006), which applies a function to the immediate subtrees of a value. A pattern functor abstracts precisely over those subtrees, so we use Regular to define compos generically:…”

Section: Generic Mapmentioning

confidence: 99%

“…Libraries that provide generic traversal combinators, such as Strafunski (Lämmel and Visser 2002), Scrap Your Boilerplate (Lämmel and Peyton Jones 2003), Uniplate (Mitchell and Runciman 2007), a pattern for almost compositional functions (Bringert and Ranta 2006), and probably more, can be used to define rewrite rules in the form of functions. This has the disadvantages we describe in Section 2, the most important of which is that it is impossible to document, test, and analyse rewrite rules.…”

Section: Related Workmentioning

confidence: 99%

A lightweight approach to datatype-generic rewriting

Noort

Rodriguez

Holdermans

et al. 2008

Proceedings of the ACM SIGPLAN Workshop on Generic Programming

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Previous implementations of generic rewriting libraries have a number of limitations: they require the user to either adapt the datatype on which rewriting is applied, or the rewriting rules are specified as functions, which makes it hard or impossible to document, test, and analyse them. We describe a library that demonstrates how to overcome these limitations by defining rules in terms of datatypes, and show how to use a type-indexed datatype to automatically extend a datatype for syntax trees with a case for metavariables. We then show how rewrite rules can be implemented without any knowledge of how the datatype is extended with metavariables. We use Haskell, extended with associated type synonyms, to implement both type-indexed datatypes and generic functions. We analyse the performance of our library and compare it with other approaches to generic rewriting.

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A pattern for almost compositional functions

Cited by 13 publications

References 12 publications

The Kansas University rewrite engine

The Kansas University rewrite engine

Translating between Language and Logic: What Is Easy and What Is Difficult

A lightweight approach to datatype-generic rewriting

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