Domain-spanning Maintainability Estimation of Information and Manufacturing Automation Systems (DoMain)

Information systems and manufacturing automation systems face very similar challenges with respect to evolution. Both struggle with changing requirements and architectures that have grown over time. Frequently, information systems as well as automated production systems (aPS) are in operation over decades while they are continuously modified. Modifications may include corrections, improvements, or adaptations of the system to changes in its environment (e.g., hardware or software platform, technology, as well as user properties) and in requirements. Thus, maintainability is an important quality aspect, especially for longliving systems. Accordingly, research in methods to improve maintainability are of scientific interest, e.g. in the DFG Priority Program “Design for Future – Managed Software Evolution” (SPP 1593).

The DoMain project targets at the analysis of an information system or aPS with respect to its maintainability by giving an impression of the change effort initiated by a change request. Rather than identifying which changes were performed from a system alternative to another one, maintenance tasks are derived from a certain change request and for a given architecture. These maintenance tasks can be used to identify the effort for changing the system architecture. In order to realize such a maintainability estimation for both information system and aPS, an architecture description in terms of metamodeling and an architecture-based change effort identification for automating this procedure are necessary.

Evolving an aPS is, in contrast to plain software systems in the information systems domain, a multidimensional challenge: various disciplines (e.g. mechanical, electrical / electronic and software engineering) are involved, physical maintenance tasks have to be executed by human personnel, dependability requirements have to be considered, etc. These challenges are exacerbated due to the high variability present for aPS resulting from this multitude of persons involved in the aPS engineering process. Hence, rather than providing a methodology or workflow for estimating efforts, the technological basis for domain-spanning maintainability estimation based on change effort identification of information and aPS’ architectures is aspired in this project.

We first analyse requirements and specify maintainability scenarios based on which we prepare evolution scenarios of CoCoME and xPPU. We propose meta-models to reflect domain-specific constructs. Based on the meta-models, we come up with a novel procedure to maintainability estimation by identifying change efforts for information systems and aPS. The procedure considers the interrelations between processes and the system as well as their effects on maintainability estimation while spanning over all life-phases of the system.