Tom: Piggybacking Rewriting on Java

Balland, Émilie; Brauner, Paul; Kopetz, Radu; Moreau, Pierre-Étienne; Reilles, Antoine

doi:10.1007/978-3-540-73449-9_5

Cited by 105 publications

(132 citation statements)

References 16 publications

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“…The strategy expressions used in graph programs are generated by the grammar rules from the nonterminal S. A strategy expression combines applications, generated by A, and focusing operations, generated by F . The application constructs and some of the strategy constructs are strongly inspired from term rewriting languages such as Elan [11], Stratego [42] and Tom [7]. The syntax presented here is a revised and simplified version of the one used in [2,20]; the main difference is that we now have an explicit notion of banned subgraph, a more concise syntax for iterative commands and a non-deterministic construct for rule applications.…”

Section: Syntax and Informal Descriptionmentioning

confidence: 99%

“…These choices affect fundamental properties of computations such as laziness, strictness, completeness, termination and efficiency, to name a few (see, e.g., [43,41,28]). Used for a long time in λ-calculus [8], strategies are present in programming languages such as Clean [33], Curry [24], and Haskell [25] and can be explicitely defined to rewrite terms in languages such as Elan [11], Stratego [42], Maude [29] or Tom [7]. They are also present in graph transformation tools such as PROGRES [39], AGG [19], Fujaba [32], GROOVE [37], GrGen [21] and GP [36].…”

Section: Introductionmentioning

confidence: 99%

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A Strategy Language for Graph Rewriting

Fernández¹,

Kirchner²,

Namet³

2012

Lecture Notes in Computer Science

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Abstract. We give a formal semantics for a graph-based programming language, where a program consists of a collection of graph rewriting rules, a user-defined strategy to control the application of rules, and an initial graph to be rewritten. The traditional operators found in strategy languages for term rewriting have been adapted to deal with the more general setting of graph rewriting, and some new constructs have been included in the language to deal with graph traversal and management of rewriting positions in the graph. This language is part of the graph transformation and visualisation environment PORGY.

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Section: Syntax and Informal Descriptionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Strategy Language for Graph Rewriting

Fernández¹,

Kirchner²,

Namet³

2012

Lecture Notes in Computer Science

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“…In Sect. 5 we show how this can be used to extend the target language to make it better suited for code generation. For example, we have created an extension of Java with identifier composition, interface extraction, and partial classes and methods to simplify code generation rules.…”

Section: Outlinementioning

confidence: 99%

“…However, these languages provide limited programmability for strategies controlling the application of transformation rules. In contrast, Tom [5] supports rewrite rules and strategies. Tom is implemented as an extension of Java, using a preprocessor approach to map the Tom language features to standard Java.…”

Section: Rewriting Toolsmentioning

confidence: 99%

“…The present paper demonstrates how the Stratego language is capable of expressing all information required to generate a target model from a source model automatically, as required by (4). Stratego can be used to implement views through transformations (5). For example, a view of all names of pages defined in a WebDSL model can be generated through a transformation that collects all page names in the model.…”

Section: Qvt Request For Proposalsmentioning

confidence: 99%

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Code generation by model transformation: a case study in transformation modularity

et al. 2009

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The realization of model-driven software development requires effective techniques for implementing code generators for domain-specific languages. This paper identifies techniques for improving separation of concerns in the implementation of generators. The core technique is code generation by model transformation, that is, the generation of a structured representation (model) of the target program instead of plain text. This approach enables the transformation of code after generation, which in turn enables the extension of the target language with features that allow better modularity in code generation rules. The technique can also be applied to 'internal code generation' for the translation of high-level extensions of a DSL to lower-level constructs within the same DSL using model-to-model transformations. This paper refines our earlier description of code generation by model transformation with an improved architecture for the composition of model-to-model normalization rules, solving the problem of combining type analysis and transformation. Instead of coarse-grained stages that alternate between normalization and type analysis, we have developed a new style of type analysis that can be integrated with normalizing transformations in a fine-grained manner. The normalization strategy has a simple extension interface and integrates non-local, context-sensitive transformation rules. We have applied the techniques in a realistic case study of domain-specific language engineering, i.e. the code generator for WebDSL, using Stratego, a high-level transformation language that integrates model-to-model, modelto-code, and code-to-code transformations.

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Effective strategic programming for Java developers

2012

Self Cite

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SUMMARYIn object programming languages, the Visitor design pattern allows separation of algorithms and data structures. When applying this pattern to tree‐like structures, programmers are always confronted with the difficulty of making their code evolve. One reason is that the code implementing the algorithm is interwound with the code implementing the traversal inside the visitor. When implementing algorithms such as data analyses or transformations, encoding the traversal directly into the algorithm turns out to be cumbersome as this type of algorithm only focuses on a small part of the data‐structure model (e.g., program optimization). Unfortunately, typed programming languages like Java do not offer simple solutions for expressing generic traversals. Rewrite‐based languages like ELAN or Stratego have introduced the notion of strategies to express both generic traversal and rule application control in a declarative way. Starting from this approach, our goal was to make the notion of strategic programming available in a widely used language such as Java and thus to offer generic traversals in typed Java structures. In this paper, we present the strategy language SL that provides programming support for strategies in Java. Copyright © 2012 John Wiley & Sons, Ltd.

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Tom: Piggybacking Rewriting on Java

Cited by 105 publications

References 16 publications

A Strategy Language for Graph Rewriting

A Strategy Language for Graph Rewriting

Code generation by model transformation: a case study in transformation modularity

Effective strategic programming for Java developers

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