A. van Deursen, E. Visser, and J. Warmer. CSMR Workshop on Model-Driven Software Evolution (MoDSE 2007), page 41--49. Amsterdam, The Netherlands, (March 2007)
S. Easterbrook, and M. Chechik. First International Workshop on Inconsistency in Data and Knowledge, at the International Joint Conference on Artificial Intelligence, (IJCAI-01), Seattle, USA, (August 2001)
W. Lam, and M. Loomes. Euromicro Conference on Software Maintenance and Reengineering, page 121-127. Florence, Italy, IEEE, (March 1998)Requirements evolve, not only during system development but also after a system has been installed. The aim of the work on the EVE (EVolution Engineering) project is to develop practi-cal methods for dealing with requirements evolution. This pa-per presents the early output from our work-the EVE frame-work for requirements evolution. The EVE framework is com-prised of two components: a meta-model and an associated process model. The EVE meta-model captures a set of model-ling concepts in requirements evolution, including change, impact, risk and viewpoint. The EVE process model provides technologists with a framework for handling the emergence of new or changing requirements during the lifetime of a system. The paper illustrates the EVE framework on a simple example, and highlights the importance of social and environmental re-sponsibility in requirements evolution..
S. Nejati, M. Sabetzadeh, M. Chechik, S. Easterbrook, and P. Zave. (May 2007)Model Management addresses the problem of managing
an evolving collection of models, by capturing the relationships
between models and providing well-defined operators
to manipulate them. In this paper, we describe two
such operators for manipulating hierarchical Statecharts:
Match, for finding correspondences between models, and
Merge, for combining models with respect to known correspondences
between them. Our Match operator is heuristic,
making use of both static and behavioural properties
of the models to improve the accuracy of matching. Our
Merge operator preserves the hierarchical structure of the
input models, and handles differences in behaviour through
parameterization. In this way, we automatically construct
merges that preserve the semantics of Statecharts models.
We illustrate and evaluate our work by applying our operators
to AT&T telecommunication features..