![](bg7.png)
Figure 7: Evolution style simplified expression.
6.3 Interests and Benefits of Simplified
Formalism
The simplified formalism allows to build an evolution
style library that can be submitted to analyses in order
to infer on the evolution process of software architec-
tures. Indeed, the work done in this paper leads us to
develop a model for planning and predicting architec-
tural evolution. For this purpose, the style library ob-
tained through the simplified formalism is subjected
to analysis.
Sequential pattern extraction techniques can be
applied to the style library in order to discover the se-
quences of recurrent evolution operations, the archi-
tectural elements more or less affected by the evolu-
tion operations, the evolution actors more or less so-
licited and several other types of information. This in-
formation can be used to build a learning base to pre-
dict and plan future architecture evolution by learn-
ing from past facts and data. This would allow to an-
ticipate the evolutions and to reduce considerably the
costs (competence, delay).
7 CONCLUSION
In this paper we have presented the evolution style
meta-model introduced to represent the software ar-
chitecture evolution process. It models the evolution
as a process by specifying the activity, the evolv-
ing product, the role and the execution date of the
operation. The evolution representation model pro-
vides the necessary concepts for specifying and prop-
erly managing software architecture evolution inde-
pendently of the architecture model and any ADL.
Thus, it considers the different modeling levels of a
software architecture and the need to manage the evo-
lution through these different levels. In addition, we
introduced the model in square which, based on the
introduced evolution representation model, provides
an evolution style representation framework with ab-
straction levels and a simplified software architec-
ture evolution style expression in order to easily col-
lect evolution data while respecting the model policy.
These data collected through the simplified expres-
sion can be submitted to studies or analyses in order
to infer on evolution styles.
The results obtained lead us to plan and predict
the future evolution paths of an evolving software ar-
chitecture from the previous evolution data collected
according to the presented model. From the previ-
ous evolution data of a software architecture evolv-
ing in time A
1
towards A
n
, the aim is to elaborate a
training base in order to predict the possibilities and
the skills required to evolve towards A
n+1
. This work
will be developed in a future study and will facilitate
evolution management in software architectures with
a good management of resources and a better capi-
talization of information in the architect community.
These results can also be applied to other artifacts.
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