Schema Evolution publication categorizer

If a modeling task is distributed, it will frequently be necessary
to merge models developed by different team members.
Existing approaches to model merging make assumptions
about the types of model to be merged, and the nature of the
relationship between them. This makes it hard to compare
approaches. In this paper, we present a manifesto for research
on model merging. We propose a framework for comparing
different approaches to merging, by treating merge as
an algebraic operator over models and model relationships.
We specify the algebraic properties of an idealized merge
operator, as well as related operators such as match, diff,
split, and slice. We then show how our framework can be
used to compare existing approaches by applying it to two of
our own research projects on model merging. We show how
this analysis permits a detailed comparison of approaches,
reveals the key features of each, and identifies weaknesses
that require further research. Most importantly, the framework
emphasizes the need to make explicit all assumptions
about the relationships between models, and indeed to treat
model relationships as first class objects.