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Stratego: A Language for Program Transformation Based on Rewriting Strategies System Description of Stratego 0.5

  • Eelco Visser
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2051)

Abstract

Program transformation is used in many areas of software engineering. Examples include compilation, optimization, synthesis, refactoring, migration, normalization and improvement [15]. Rewrite rules are a natural formalism for expressing single program transformations. However, using a standard strategy for normalizing a program with a set of rewrite rules is not adequate for implementing program transformation systems. It may be necessary to apply a rule only in some phase of a transformation, to apply rules in some order, or to apply a rule only to part of a program. These restrictions may be necessary to avoid non-termination or to choose a specific path in a non-con uent rewrite system.

Stratego is a language for the specification of program transformation systems based on the paradigm of rewriting strategies. It supports the separation of strategies from transformation rules, thus allowing careful control over the application of these rules. As a result of this separation, transformation rules are reusable in multiple difierent transformations and generic strategies capturing patterns of control can be described independently of the transformation rules they apply. Such strategies can even be formulated independently of the object language by means of the generic term traversal capabilities of Stratego.

In this short paper I give a description of version 0.5 of the Stratego system, discussing the features of the language (Section 2), the library (Section 3), the compiler (Section 4) and some of the applications that have been built (Section 5). Stratego is available as free software under the GNU General Public License from http://www.stratego-language.org.

Keywords

Transformation Rule Object Language Program Transformation Subject Term Abstract Syntax Tree 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Eelco Visser
    • 1
  1. 1.Institute of Information and Computing SciencesUniversiteit UtrechtUtrechtThe Netherlands

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