Reference Representation Techniques for Large Models


Abstract—If models consist of more and more objects, time and space required to process these models becomes an issue. To solve this we can employ different existing frameworks that use different model representations (e.g. trees in XMI or relational data with CDO). Based on the observation that these frameworks reach different performance measures for different operations and different model characteristics, we rise the question if and how different model representations can be combined to mitigate performance issues of individual representations.

In this paper, we analyze different techniques to represent references, which are one important aspect to process large models efficiently. We present the persistence framework EMF-Fragments, which combines the representation of references as source-object contained sets of target-objects (e.g. in XMI) within the representation as relations similar to those in relational databases (e.g. with CDO). We also present a performance evaluation for both representations and discuss the use of both representations in three applications: models for source-code repositories, scientific data, and geo-spatial data.

KeywordsEMF, persistence, databases


 author = {Scheidgen, Markus},
 title = {Reference Representation Techniques for Large Models},
 booktitle = {Proceedings of the Workshop on Scalability in Model Driven Engineering},
 series = {BigMDE '13},
 year = {2013},
 isbn = {978-1-4503-2165-5},
 location = {Budapest, Hungary},
 pages = {5:1--5:9},
 articleno = {5},
 numpages = {9},
 url = {},
 doi = {10.1145/2487766.2487769},
 acmid = {2487769},
 publisher = {ACM},
 address = {New York, NY, USA},
 keywords = {EMF, big data, meta-modeling, mining software repositories, model persistence},

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