Abstract
Control software for automated Production Systems (aPSs) becomes increasingly complex. Respective systems undergo constant evolution. Yet, proper documentation may not always be present, entailing maintenance issues in the long run. While manual examination of software for aPSs is an error-prone task, static analysis can improve system quality. However, it has not been applied to describe software evolution by means of changed systems artifacts. The authors address this issue and perform change analyses on IEC61131-3 projects, identifying introduced and removed systems artifacts as well as existing ones affected. By that, the authors aim to support sustainable evolution. Two feasibility studies, implemented independently, but for the same evolution scenarios for an automation plant, are used for evaluation. The technique is shown to be efficient and highly precise.
Zusammenfassung
Software für automatisierte Produktionssysteme wird zunehmend komplex und unterliegt der ständigen Weiterentwicklung. Dabei ist eine detaillierte Dokumentation der Änderungen nicht immer gegeben, welches signifikante Wartungsprobleme nach sich zieht. Entgegen einer manuellen, fehleranfälligen Identifikation der Änderungen kann auf statische Analyseverfahren zurückgegriffen werden. Im Umfeld der automatisierten Produktionssysteme ist dies jedoch noch nicht zur Beschreibung von evolvierender Software eingesetzt worden. Die Autoren nutzen die statische Analyse von IEC61131-3 Projekten und identifizieren Softwareartefakte, welche der Evolution unterliegen. Das Verfahren wird an zwei Machbarkeitsstudien, welche unabhängig voneinander implementiert wurden, dargelegt.
Funding source: Deutsche Forschungsgemeinschaft
Award Identifier / Grant number: SCHA 1635/12-1
Award Identifier / Grant number: VO 937/31-1
Funding statement: This work was supported by the DFG (German Research Foundation) (SCHA 1635/12-1) & (VO 937/31-1).
About the authors
Alexander Schlie graduated in computer science at the TU Braunschweig, Germany and received his M.Sc. in 2016. He works as a research assistant at the Institute of Software Engineering and Automotive Informatics. His research interests are on reverse-engineering variability information from legacy systems to allow for their restructuring and migration towards software product lines.
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.
Juliane Fischer, M.Sc., graduated in mechanical engineering from the Technical University of Munich (TUM) in 2017. She is a research assistant at the Institute of Automation and Information Systems at TUM. Her main research interests are the design of modular, reusable control software and flexible material flow systems in automated production systems.
Prof. Dr. Ina Schaefer directs the Institute for Software Technology and Vehicle Informatics at the Technical University of Braunschweig, Germany. After completing her Ph.D. at the Technical University of Kaiserslautern, she, was postdoc at Chalmers University of Technology in Göteborg, Sweden. Her research interests include methods for verification and testing for variant-rich and evolving software 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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