Towards verified continuous integration in the engineering of automated production systems
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Jakob Mund
Dr. rer. nat. Jakob Mund works as a research assistant at the Chair IV: Software & Systems Engineering at Technische Universität München, where he also received his Ph.D. on research on quality assessment of requirements specifications of software-intensive systems from the Faculty of Computer Science in 2017. Other research interests include model-driven engineering and the application of formal methods.
Safa Bougouffa, M.Sc. works as a research assistant at the Institute of Automation and Information Systems, Technical University of Munich. Her research interest is on the application of quality assurance methods to improve the development of automated production systems.
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Iman Badr
Dr.-Ing. Iman Badr is a lecturer at Science Faculty, Helwan University, Egypt. She received her Ph.D. from the Institute of Industrial Automation and Software Engineering, University of Stuttgart, Germany, 2010. Her research interests include the application of Artificial Intelligence techniques for enhancing the adaptability of automation control systems and model-based Engineering of automation production systems.
Prof. Dr.-Ing. Birgit Vogel-Heuser graduated in electrical engineering and received the Ph.D. in mechanical engineering from the RWTH Aachen in 1991. She worked for nearly ten years in industrial automation in the machine and plant manufacturing industry. After holding different chairs of automation she has been head of the Institute of Automation and Information Systems at the Technical University of Munich since 2009. Her research work is focused on modeling and education in automation engineering for distributed and intelligent systems.
Abstract
Continuous integration (CI) is widely used in software engineering. The observed benefits include reduced efforts for system integration, which is particularly appealing for engineering automated production systems (aPS) due to the different disciplines involved. Yet, while many individual quality assurance means for aPS have been proposed, their adequacy for and systematic use in CI remains unclear. In this article, the authors provide two key contributions: First, a quality model for a model-based engineering approach specifically developed for aPS. Based thereon, a discussion of the suitable verification techniques for aPS and their systematic integration in a CI process are given. As a result, the paper provide a blueprint to be further studied in practice, and a research agenda for quality assurance of aPS.
Zusammenfassung
Kontinuierliche Integration (Continuous Integration, CI) ist in der Softwareentwicklung weit verbreitet. Einer der offensichtlichen Vorteile von CI ist ein verringerter Aufwand zur Systemintegration. Dies ist besonders in der Entwicklung von automatisierten Produktionssystemen (aPS) interessant, da diese viele verschiedene Disziplinen vereint. Obwohl bereits viele individuelle Vorschläge für Qualitätssicherungsmittel für aPS existieren, ist deren Eignung und systematischer Einsatz in CI jedoch noch unklar. In diesem Artikel liefern die Autoren daher zwei wesentliche Beiträge: Zuerst wird ein Qualitätsmodell für einen modellbasierten Entwicklungsansatz, der speziell für aPS entwickelt wurde, vorgestellt. Darauf aufbauend werden geeignete Verifikationstechniken für aPS sowie deren systematische Integration in einen CI Prozess diskutiert. Als Ergebnis liefert dieser Beitrag eine Vorlage für CI für aPS, die in der Praxis noch weiter erforscht und evaluiert werden muss sowie einen Forschungsplan für die Qualitätssicherung von aPS.
Funding source: Deutsche Forschungsgemeinschaft
Award Identifier / Grant number: SPP1593
Funding statement: This work was supported by the DFG (German Research Foundation) under the Priority Programme SPP1593: Design for Future – Managed Software Evolution (VO937/13-1).
About the authors
Dr. rer. nat. Jakob Mund works as a research assistant at the Chair IV: Software & Systems Engineering at Technische Universität München, where he also received his Ph.D. on research on quality assessment of requirements specifications of software-intensive systems from the Faculty of Computer Science in 2017. Other research interests include model-driven engineering and the application of formal methods.
Safa Bougouffa, M.Sc. works as a research assistant at the Institute of Automation and Information Systems, Technical University of Munich. Her research interest is on the application of quality assurance methods to improve the development of automated production systems.
Dr.-Ing. Iman Badr is a lecturer at Science Faculty, Helwan University, Egypt. She received her Ph.D. from the Institute of Industrial Automation and Software Engineering, University of Stuttgart, Germany, 2010. Her research interests include the application of Artificial Intelligence techniques for enhancing the adaptability of automation control systems and model-based Engineering of automation production systems.
Prof. Dr.-Ing. Birgit Vogel-Heuser graduated in electrical engineering and received the Ph.D. in mechanical engineering from the RWTH Aachen in 1991. She worked for nearly ten years in industrial automation in the machine and plant manufacturing industry. After holding different chairs of automation she has been head of the Institute of Automation and Information Systems at the Technical University of Munich since 2009. Her research work is focused on modeling and education in automation engineering for distributed and intelligent systems.
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© 2018 Walter de Gruyter GmbH, Berlin/Boston
Artikel in diesem Heft
- Frontmatter
- Editorial
- Methods to support the evolution of Cyber Physical Production Systems
- Methods
- Towards verified continuous integration in the engineering of automated production systems
- Using model differencing to reason about observable behavior changes of manufacturing systems
- Change analysis on evolving PLC software in automated production systems
- Model-based generation of run-time data collection systems exploiting AutomationML
- Applicability of generalized test tables: a case study using the manufacturing system demonstrator xPPU
- Applications
- Step-based evolution support among networked production automation systems
- Vertical integration approach for the intelligent Oil & Gas field
Artikel in diesem Heft
- Frontmatter
- Editorial
- Methods to support the evolution of Cyber Physical Production Systems
- Methods
- Towards verified continuous integration in the engineering of automated production systems
- Using model differencing to reason about observable behavior changes of manufacturing systems
- Change analysis on evolving PLC software in automated production systems
- Model-based generation of run-time data collection systems exploiting AutomationML
- Applicability of generalized test tables: a case study using the manufacturing system demonstrator xPPU
- Applications
- Step-based evolution support among networked production automation systems
- Vertical integration approach for the intelligent Oil & Gas field
