Scalable cloud based semantic code analysis to support continuous integration of industrial PLC code

S. Bougouffa, Sebastian Diehm, Michael Schwarz, B. Vogel‐Heuser
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引用次数: 6

Abstract

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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可扩展的基于云的语义代码分析,支持工业PLC代码的持续集成
在自动化生产系统(ap)的生命周期中,将实现额外的功能和演进。因此,ap的控制软件变得高度复杂和难以维护,这就需要对控制软件的质量进行评估和改进。用于评估和分析控制软件质量的工具很少,而且大多缺乏允许质量官员和利益相关者使用分析数据的可访问平台。因此,本文提出了一个用于代码分析的云平台,这是一种利用语义Web技术对控制软件进行评估的工具。云平台的可扩展性支持不同的数据量,并允许在持续集成系统中有效地使用分析数据,结合可以指示控制软件整体质量水平的软件质量模型进行趋势分析。
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