Scalable Armies of Model Clones through Data Sharing - Inria - Institut national de recherche en sciences et technologies du numérique
Conference Papers Year : 2014

Scalable Armies of Model Clones through Data Sharing

Erwan Bousse
Benoit Combemale
Benoit Baudry
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Abstract

Cloning a model is usually done by duplicating all its runtime objects into a new model. This approach leads to memory consumption problems for operations that create and manipulate large quantities of clones (e.g., design space exploration). We propose an original approach that exploits the fact that operations rarely modify a whole model. Given a set of immutable properties, our cloning approach determines the objects and fields that can be shared between the runtime representations of a model and its clones. Our generic cloning algorithm is parameterized with three strategies that establish a trade-off between memory savings and the ease of clone manipulation. We implemented the strategies within the Eclipse Modeling Framework (EMF) and evaluated memory footprints and computation overheads with 100 randomly generated metamodels and models. Results show a positive correlation between the proportion of shareable properties and memory savings, while the worst median overhead is 9,5% when manipulating the clones.
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Dates and versions

hal-01023681 , version 1 (31-07-2015)

Identifiers

  • HAL Id : hal-01023681 , version 1

Cite

Erwan Bousse, Benoit Combemale, Benoit Baudry. Scalable Armies of Model Clones through Data Sharing. Model Driven Engineering Languages and Systems, 17th International Conference, MODELS 2014, Sep 2014, Valencia, Spain. ⟨hal-01023681⟩
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