We describe a design pattern for writing programs that traverse data structures built from rich mutually-recursive data types. Such programs often have a great deal of "boilerplate" code that simply walks the structure, hiding a small amount of "real" code that constitutes the reason for the traversal. Our technique allows most...

Abstract. Strafunski is a Haskell-centred software bundle for implementing language processing components — most notably program analyses and transformations. Typical application areas include program optimisation, refactoring, software metrics, software re- and reverse engineering. Strafunski started out as generic programming library complemented by generative tool support to address the concern of generic traversal over typed representations of parse trees in a scalable manner. Meanwhile, Strafunski also encompasses means of integrating external components such as parsers, pretty printers, and graph visualisation tools. In a selection of case studies, we demonstrate that typed functional programming in Haskell, augmented with Strafunski’s support for generic traversal and external components, is very appropriate for the development of practical language processors. In particular, we discuss using Haskell for Cobol reverse engineering, Java code metrics, and Haskell re-engineering.

Strategic programming is a generic programming idiom for processing compound data such as terms or object structures. At the heart of the approach is the separation of two concerns: basic dataprocessing computations vs. traversal schemes. Actual traversals are composed by passing the former as arguments to the latter. Traversal schemes can be defined by the strategic programmer using a combinator style that relies on primitives for layered traversal. In this paper, we take a look at strategic programming from an aspect-oriented programming perspective. Throughout the paper, we compare strategic programming with adaptive programming, which is a well-established aspectual approach to the traversal of object structures. We start from the observation that aspect-oriented programming terms, e.g., crosscutting, join point, and advice can be instantiated for aspectual traversal approaches.

A typed model of strategic term rewriting is developed. The key innovation is that generic. The calculus traversal is covered. To this end, we define a typed rewriting calculus S ′ γ employs a many-sorted type system extended by designated generic strategy types γ. We consider two generic strategy types, namely the types of type-preserving and type-unifying strategies. S ′ γ offers traversal combinators to construct traversals or schemes thereof from many-sorted and generic strategies. The traversal combinators model different forms of one-step traversal, that is, they process the immediate subterms of a given term without anticipating any scheme of recursion into terms. To inhabit generic types, we need to add a fundamental combinator to lift a many-sorted strategy s to a generic type γ. This step is called strategy extension. The semantics of the corresponding combinator states that s is only applied if the type of the term at hand fits, otherwise the extended strategy fails. This approach dictates that the semantics of strategy application must be type-dependent to a certain extent. Typed strategic term rewriting with coverage of generic term traversal is a simple but expressive model of generic programming. It has applications in program

Abstract. The goal of domain-specific languages (DSLs) is to increase the productivity of software engineers by abstracting from low-level boilerplate code. Introduction of DSLs in the software development process requires a smooth workflow for the production of DSLs themselves. This requires technology for designing and implementing DSLs, but also a methodology for using that technology. That is, a collection of guidelines, design patterns, and reusable DSL components that show developers how

Datatype-generic programming is defining functions that depend on the structure, or “shape”, of datatypes. It has been around for more than 10 years, and a lot of progress has been made, in particular in the lazy functional programming language Haskell. There are more than 10 proposals for generic programming libraries or language extensions for Haskell. To compare and characterize the many generic programming libraries in a typed functional language, we introduce a set of criteria and develop a generic programming benchmark: a set of characteristic examples testing various facets of datatype-generic programming. We have implemented the benchmark for nine existing Haskell generic programming libraries and present the evaluation of the libraries. The comparison is useful for reaching a common standard for generic programming, but also for a programmer who has to choose a particular approach for datatype-generic programming.

Abstract. The last decade has seen a number of approaches to datatype-generic programming: PolyP, Functorial ML, ‘Scrap Your Boilerplate’, Generic Haskell, ‘Generics for the Masses’, etc. The approaches vary in sophistication and target audience: some propose full-blown programming languages, some suggest libraries, some can be seen as categorical programming methods. In these lecture notes we compare the various approaches to datatype-generic programming in Haskell. We introduce each approach by means of example, and we evaluate it along different dimensions (expressivity, ease of use, etc). 1

We describe the design of a rule-based language for expressing changes to Haskell programs in a systematic and reliable way. The update language essentially offers update commands for all constructs of the object language (a subset of Haskell). The update language can be translated into a core calculus consisting of a small set of basic updates and update combinators. The key construct of the core calculus is a scope update mechanism that allows (and enforces) update specifications for the definition of a symbol together with all of its uses. The type of an update program is given by the possible type changes it can cause for an object programs. We have developed a typechange inference system to automatically infer type changes for updates. Updates for which a type change can be successfully inferred and that satisfy an additional structural condition can be shown to preserve type correctness of object programs. In this paper we define the Haskell Update Language HULA and give a translation into the core update calculus. We illustrate HULA and its translation into the core calculus by several examples.

Abstract. Strategic programming is generic programming with the use of strategies. A strategy is a generic data-processing action which can traverse into heterogeneous data structures while mixing uniform and type-specific behaviour. With strategic programming, one gains full control over the application of basic actions, most notably full traversal control. Using a combinator style, traversal schemes can be defined, and actual traversals are obtained by passing the problem-specific ingredients as parameters to suitable schemes. The prime application domain for strategic programming is program transformation and analysis. In this paper, we provide a language-independent definition that generalises over existing incarnations of this idiom in term rewriting, functional programming, and object-oriented programming.

Abstract. A two-level data transformation consists of a type-level transformation of a data format coupled with value-level transformations of data instances corresponding to that format. Examples of two-level data transformations include XML schema evolution coupled with document migration, and data mappings used for interoperability and persistence. We provide a formal treatment of two-level data transformations that is typesafe in the sense that the well-formedness of the value-level transformations with respect to the type-level transformation is guarded by a strong type system. We rely on various techniques for generic functional programming to implement the formalization in Haskell. The formalization addresses various two-level transformation scenarios, covering fully automated as well as user-driven transformations, and allowing transformations that are information-preserving or not. In each case, two-level transformations are disciplined by one-step transformation rules and type-level transformations induce value-level transformations. We demonstrate an example hierarchicalrelational mapping and subsequent migration of relational data induced by hierarchical format evolution. Keywords: Two-level transformation, Program calculation, Refinement calculus, Strategic term rewriting, Generalized abstract datatypes, Generic programming,