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Improving Reuse by means of Asymmetrical Model Migrations: An Application to the Orcc Case Study

Paola Vallejo 1 Mickaël Kerboeuf 1 Kevin Martin 2 Jean-Philippe Babau 1
1 Lab-STICC_UBO_CACS_MOCS
Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance, UBO - Université de Brest
2 Lab-STICC_UBS_CACS_MOCS
Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance
Abstract : The legacy code of a tool handling domain specific data gathers valuable expertise. However in many cases, it must be rewritten to make it apply to structurally incompatible data. We investigate a co-evolution approach to avoid this update by making the call context meet the a legacy tool definition domain. The data conforming to the call context co-evolve into data conforming to the definition domain. Once processed by the tool, they can be put back into their original context thanks to a specific reverse transformation which enables the recovery of elements that had been initially removed. This approach is applied to Orcc, a compiler for dataflow applications. Orcc requires many common functions that are expected to be adapted to its own context. Our approach is an effective way to reuse them instead of rewriting them.
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Conference papers
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https://hal.univ-brest.fr/hal-01220427
Contributor : Mickaël Kerboeuf <>
Submitted on : Monday, October 26, 2015 - 12:40:29 PM
Last modification on : Wednesday, June 24, 2020 - 4:19:24 PM

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  • HAL Id : hal-01220427, version 1

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Paola Vallejo, Mickaël Kerboeuf, Kevin Martin, Jean-Philippe Babau. Improving Reuse by means of Asymmetrical Model Migrations: An Application to the Orcc Case Study. 2015 ACM/IEEE 18th International Conference on Model Driven Engineering Languages and Systems (MODELS), Sep 2015, Ottawa, Canada. ⟨hal-01220427⟩

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