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Bidirectional Model Transformation with Precedence Triple Graph Grammars

Lauder, Marius ; Anjorin, Anthony ; Varró, Gergely ; Schürr, Andy
eds.: Fachgebiet Echtzeitsysteme (Real-Time Systems Lab), TU Darmstadt (2012)
Bidirectional Model Transformation with Precedence Triple Graph Grammars.
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Item Type: Report
Type of entry: Primary publication
Title: Bidirectional Model Transformation with Precedence Triple Graph Grammars
Language: English
Date: 21 March 2012
Place of Publication: Darmstadt
Publisher: tuprints
Corresponding Links:
Abstract:

Triple Graph Grammars (TGGs) are a rule-based technique with a formal background for specifying bidirectional model transformation. In practical scenarios, the unidirectional rules needed for the forward and backward transformations are automatically derived from the TGG rules in the specification, and the overall transformation process is governed by a control algorithm. Current implementations either have a worst case exponential runtime complexity or pose such strong restrictions on the class of supported TGGs that practical real-world applications become infeasible. This paper, therefore, introduces a new class of TGGs together with a control algorithm that drops a number of practice-relevant restrictions for TGG rules and still has a polynomial runtime complexity.

Uncontrolled Keywords: triple graph grammars, control algorithm of unidirectional transformations, node precedence analysis, rule dependency analysis
Alternative keywords:
Alternative keywordsLanguage
triple graph grammars, control algorithm of unidirectional transformations, node precedence analysis, rule dependency analysisEnglish
URN: urn:nbn:de:tuda-tuprints-29162
Classification DDC: 000 Generalities, computers, information > 004 Computer science
Divisions: 18 Department of Electrical Engineering and Information Technology > Institute of Computer Engineering > Real-Time Systems
Date Deposited: 21 Mar 2012 14:21
Last Modified: 04 Jan 2024 09:44
URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/2916
PPN: 291931960
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