Please use this identifier to cite or link to this item:

http://hdl.handle.net/10609/78226
Title: Backwards reasoning for model transformations: method and applications
Author: Clarisó Viladrosa, Robert  
Cabot Sagrera, Jordi  
Guerra, Esther
Lara, Juan de
Others: Universitat Oberta de Catalunya (UOC)
Universidad Autónoma de Madrid
Keywords: model transformation
OCL
weakest pre-condition
graph transformation
validation and verification
backwards reasoning
Issue Date: 7-Aug-2015
Publisher: Journal of Systems and Software
Citation: Clarisó, R., Cabot, J., Guerra, E. & de Lara Jaramillo, J. (2016). Backwards reasoning for model transformations: method and applications. Journal of Systems and Software, 116(), 113-132. doi: 10.1016/j.jss.2015.08.017
Also see: https://doi.org/10.1016/j.jss.2015.08.017
Abstract: Model transformations are key elements of model driven engineering. Current challenges for transformation languages include improving usability (i.e., succinct means to express the transformation intent) and devising powerful analysis methods. In this paper, we show how backwards reasoning helps in both respects. The reasoning is based on a method that, given an OCL expression and a transformation rule, calculates a constraint that is satisfiable before the rule application if and only if the original OCL expression is satisfiable afterwards. With this method we can improve the usability of the rule execution process by automatically deriving suitable application conditions for a rule (or rule sequence) to guarantee that applying that rule does not break any integrity constraint (e.g. meta-model constraints). When combined with model finders, this method facilitates the validation, verification, testing and diagnosis of transformations, and we show several applications for both in-place and exogenous transformations.
Language: English
URI: http://hdl.handle.net/10609/78226
ISSN: 0164-1212MIAR
Appears in Collections:Articles
Articles

Share:
Export:
Files in This Item:
File Description SizeFormat 
ClarisoEtAl_JSS_PrePrint.pdf699.73 kBAdobe PDFView/Open

This item is licensed under a Creative Commons License Creative Commons