Effective development of automation systems through domain-specific modeling in a small enterprise context

  • Authors:

  • Andrea Leitner;Christopher Preschern;Christian Kreiner

  • Affiliations:

  • Institute for Technical Informatics, Graz University of Technology, Graz, Austria;Institute for Technical Informatics, Graz University of Technology, Graz, Austria and HOFERNET IT-Solutions, Lendorf, Austria 9811;Institute for Technical Informatics, Graz University of Technology, Graz, Austria

  • Venue:
  • Software and Systems Modeling (SoSyM)
  • Year:
  • 2014

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Abstract

High development and maintenance costs and a high error rate are the major problems in the development of automation systems, which are mainly caused by bad communication and inefficient reuse methods. To overcome these problems, we propose a more systematic reuse approach. Though systematic reuse approaches such as software product lines are appealing, they tend to involve rather burdensome development and management processes. This paper focuses on small enterprises. Since such companies are often unable to perform a "big bang" adoption of the software product line, we suggest an incremental, more lightweight process to transition from single-system development to software product line development. Besides the components of the transition process, this paper discusses tool selection, DSL technology, stakeholder communication support, and business considerations. Although based on problems from the automation system domain, we believe the approach may be general enough to be applicable in other domains as well. The approach has proven successful in two case studies. First, we applied it to a research project for the automation of a logistics lab model, and in the second case (a real-life industry case), we investigated the approaches suitability for fish farm automation systems. Several metrics were collected throughout the evolution of each case, and this paper presents the data for single system development, clone&own and software product line development. The results and observable effects are compared, discussed, and finally summarized in a list of lessons learned.