Automation systems are mostly individual highly customized system variants, consisting both of hardware and software. In order to reduce development effort, it is a common practice to use a clone-and-own approach by modifying an existing variant to fit the changed requirements of a new variant. The information about the commonalities and di erences between those variants is usually not well documented and leads to problems in maintenance, testing and evolution. To alleviate these problems, in this paper, we present an improved version of a family mining approach for automatically discovering commonality and variability between related system variants. We apply this approach to function block diagrams used to develop automation software and show its feasibility by a manufacturing case study.     «

Automation systems are mostly individual highly customized system variants, consisting both of hardware and software. In order to reduce development effort, it is a common practice to use a clone-and-own approach by modifying an existing variant to fit the changed requirements of a new variant. The information about the commonalities and di erences between those variants is usually not well documented and leads to problems in maintenance, testing and evolution. To alleviate these problems, in th...     »