The world is increasingly permeated by software and data. The use and maintenance of these digital artifacts requires their linguistic representation. Otherwise, they remain ‘black boxes’ which not only threaten the achievements of enlightenment, but also jeopardize the protection of investments in software and data. A linguistic representation, for example in the form of well-documented code or, better still, conceptual models, is, however, hardly sufficient on its own. In order to support efficient and secure adaptation to new requirements and thus the long-term competitiveness of companies, abstractions to invariant and from time-varying requirements are necessary. However, common programming and modeling languages only offer limited possibilities for expressing abstractions. The multi-level language architecture developed at the Chair of Information Systems and Enterprise Modeling together with Aston University in Birmingham offers clear advantages here (www.le4mm.org). Multi-level models not only allow any number of classification levels, but also a common representation of models and code.

The representation of existing digital artefacts using multi-level models is suitable for significantly increasing their reusability and adaptability. However, the subsequent manual creation of multi-level models is associated with an effort that cannot be justified in many cases. This is where the ‘AutoMLM’ project comes in. It is aimed at investigating and designing procedures for the (semi-) automatic (re-) construction of static multi-level models from existing representations (code, schemas, flat models) in order to provide a basis for deciding which procedures can be used in individual cases. The project is being funded by the American company Oracle.