During the lifecycle of automated production systems (aPS) additional functionalities and evolutions are realized. As a consequence, control software of aPS becomes highly complex and hard to maintain, which rises the need for evaluating and improving the quality of the control software. Tools for assessing and analyzing the quality of control software are rare and mostly lack accessible platforms that allow the use of analysis data by quality officers and stakeholders. Therefore, this paper presents a cloud platform for code-analysis, a developed tool for evaluating control software by means of Semantic Web technologies. The scalability of the cloud platform supports varied volumes of data and allows efficient use of the analysis data in a continuous integration system for trend analysis in combination with software quality model that can indicate the overall quality level of the control software.
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During the lifecycle of automated production systems (aPS) additional functionalities and evolutions are realized. As a consequence, control software of aPS becomes highly complex and hard to maintain, which rises the need for evaluating and improving the quality of the control software. Tools for assessing and analyzing the quality of control software are rare and mostly lack accessible platforms that allow the use of analysis data by quality officers and stakeholders. Therefore, this paper pre...
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