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.
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.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.