Strategic polymorphism requires just two combinators!

In previous work, we introduced the notion of functional strategies: first-class generic functions that can traverse terms of any type while mixing uniform and type-specific behaviour. Functional strategies transpose the notion of term rewriting strategies (with coverage of traversal) to the functional programming paradigm. Meanwhile, a number of Haskell-based models and combinator suites were proposed to support generic programming with functional strategies. In the present paper, we provide a compact and matured reconstruction of functional strategies. We capture strategic polymorphism by just two primitive combinators. This is done without commitment to a specific functional language. We analyse the design space for implementational models of functional strategies. For completeness, we also provide an operational reference model for implementing functional strategies (in Haskell). We demonstrate the generality of our approach by reconstructing representative fragments of the Strafunski library for functional strategies.Comment: A preliminary version of this paper was presented at IFL 2002, and included in the informal preproceedings of the worksho

Matching objects without language extension

Pattern matching is a powerful programming concept which has proven its merits in declarative programming. The absence of pattern-matching in object-oriented programming languages is felt especially when tackling source code processing problems. But existing proposals for pattern matching in such languages rely on language extension, which makes their adoption overly intrusive. We propose an approach to support pattern matching in mainstream object-oriented languages without language extension. In this approach, a pattern is a first-class entity, which can be created, be passed as argument, and receive method invocations, just like any other object. We demonstrate how our approach can be used in conjunction with existing parser generators to perform pattern matching on various kinds of abstract syntax representation. We elaborate our approach to include concrete syntax patterns, and mixing of patterns and visitors for the construction of sophisticated syntax tree traversals.Thanks to Rob van der Leek of the Software Improvement Group for valuable feedback regarding this paper and the MatchO library. The author is recipient of a research grant from the Fundacao para a Ciencia e a Tecnologia, under grant number SFRH/BPD/11609/2002

Object-oriented Tree Traversal with JJForester

AbstractWe want to use the advanced language processing technology available in the asf+sdf Meta-Environment in combination with general purpose programming languages. In particular, we want to combine the syntax definition formalism sdf and the associated components that support generalized LR parsing, with the object-oriented language Java. To this end, we implemented JJForester, a tool that generates class structures from sdf grammar definitions. The generated class structures implement a number of design patterns to facilitate construction and traversal of parse trees represented by object structures. In a detailed case study, we demonstrate how program analyses and transformations can be constructed with JJForester

Transformation of structure-shy programs : applied to XPath queries and strategic functions

Various programming languages allow the construction of structure-shy programs. Such programs are defined generically for many different datatypes and only specify specific behavior for a few relevant subtypes. Typical examples are XML query languages that allow selection of subdocuments without exhaustively specifying intermediate element tags. Other examples are languages and libraries for polytypic or strategic functional programming and for adaptive object-oriented programming. In this paper, we present an algebraic approach to transformation of declarative structure-shy programs, in particular for strategic functions and XML queries. We formulate a rich set of algebraic laws, not just for transformation of structure-shy programs, but also for their conversion into structure-sensitive programs and vice versa. We show how subsets of these laws can be used to construct effective rewrite systems for specialization, generalization, and optimization of structure-shy programs. We present a type-safe encoding of these rewrite systems in Haskell which itself uses strategic functional programming techniques.(undefined

Strong types for relational databases: functional pearl

Haskell's type system with multi-parameter constructor classes and functional dependencies allows static (compile-time) computations to be expressed by logic programming on the level of types. This emergent capability has been exploited for instance to model arbitrary-length tuples (heterogeneous lists), extensible records, functions with variable length argument lists, and (homogenous) lists of statically fixed length (vectors).We explain how type-level programming can be exploited to define a strongly-typed model of relational databases and operations on them. In particular, we present a strongly typed embedding of a significant subset of SQL in Haskell. In this model, meta-data is represented by type-level entities that guard the semantic correctness of database operations at compile time.Apart from the standard relational database operations, such as selection and join, we model functional dependencies (among table attributes), normal forms, and operations for database transformation. We show how functional dependency information can be represented at the type level, and can be transported through operations. This means that type inference statically computes functional dependencies on the result from those on the arguments.Our model shows that Haskell can be used to design and prototype typed languages for designing, programming, and transforming relational databasesFundação para a Ciência e a Tecnologia (FCT) - POSI/ICHS/44304/2002; SFRH/BPD/11609/2002

XT: a bundle of program transformation tools : system description

{sc xt bundles existing and newly developed program transformation libraries and tools into an open framework that supports component-based development of program transformations. We discuss the roles of {sc xt's constituents in the development process of program transformation tools, as well as some experiences with building program transformation systems with {sc xt. <pr

Strategic polymorphism requires just two combinators!

In previous work, we introduced the notion of functional strategies: first-class generic functions that can traverse terms of any type while mixing uniform and type-specific behaviour. Functional strategies transpose the notion of term rewriting strategies (with coverage of traversal) to the functional programming paradigm. Meanwhile, a number of Haskell-based models and combinator suites were proposed to support generic programming with functional strategies. In the present paper, we provide a compact and matured reconstruction of functional strategies. We capture strategic polymorphism by just two primitive combinators. This is done without commitment to a specific functional language. We analyse the design space for implementational models of functional strategies. For completeness, we also provide an operational reference model for implementing functional strategies (in Haskell). We demonstrate the generality of our approach by reconstructing representative fragments of the Strafunski library for functional strategies