Shariat Yazdi, Hamed;
Statistical Analysis of Changes for Synthesizing
Realistic Test Models;
Proc. Software Engineering 2013,
Fachtagung des GI-Fachbereichs Softwaretechnik,
Lecture Notes in Informatics 213, GI,
Abstract: Tools and methods which support Model-Driven
Engineering have to be evaluated and tested.
Unfortunately, adequate test models are scarcely available
in many application domains, and available models often
lack required properties.
Test model generators have been proposed recently to
overcome this deficiency. Their basic principle is to
synthesize test models by controlled application of edit
operations from a given set of edit operation definitions.
Test models are created by randomly selecting edit
operations are often unnatural and do not exhibit
real-world characteristics; generated sequences of edit
operation should rather be similar to realistic model
To this end, we have reverse-engineered a carefully
selected set of open-source Java projects to class
diagrams and computed the differences between subsequent
revisions in terms of various edit operations, including
generic low-level graph edit operations and high-level
edit operations such as model refactorings.
Finally, we statistically analyzed the distribution of
the frequency of these edit operations.
We have checked the fitness of 60 distributions in order
to correctly represent the statistical properties. Only
four distributions have been able to adequately describe
the observed evolution.
The successful distributions are being used to configure
our model generator in order to produce more realistic