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Composing Source-to-Source Data-Flow Transformations with Rewriting Strategies and Dependent Dynamic Rewrite Rules

  • Karina Olmos
  • Eelco Visser
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3443)

Abstract

Data-flow transformations used in optimizing compilers are also useful in other programming tools such as code generators, aspect weavers, domain-specific optimizers, and refactoring tools. These applications require source-to-source transformations rather than transformations on a low-level intermediate representation. In this paper we describe the composition of source-to-source data-flow transformations in the program transformation language Stratego. The language supports the high-level specification of transformations by means of rewriting strategy combinators that allow a natural modeling of data- and control-flow without committing to a specific source language. Data-flow facts are propagated using dynamic rewriting rules. In particular, we introduce the concept of dependent dynamic rewrite rules for modeling the dependencies of data-flow facts on program entities such as variables. The approach supports the combination of analysis and transformation, the combination of multiple transformations, the combination with other types of transformations, and the correct treatment of variable binding constructs and lexical scope to avoid free variable capture.

Keywords

Constant Propagation Abstract Syntax Source Language Program Transformation Concrete Syntax 
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 2005

Authors and Affiliations

  • Karina Olmos
    • 1
  • Eelco Visser
    • 1
  1. 1.Institute of Information and Computing SciencesUtrecht UniversityUtrechtThe Netherlands

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