A new approach to model-based test case generation for industrial automation systems

Kevin Pinkal, O. Niggemann
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引用次数: 4

Abstract

In recent years, model-based testing (MBT) of automation systems has gained in importance. However, increasing size and complexity of manufacturing plants also lead to larger models, which again cost time and manpower for modeling tasks. An approach to solve this problem is to subdivide the overall model into several separated models of usual components of automation systems which are reusable. Therefore, we introduce the Synchronized Depth First Search (SDFS), which uses a sub-divided automaton model to generate test cases. The underlying automaton model needs to incorporate synchronous transitions in order to synchronize processes among each other and thus forming an overall model to test with.
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工业自动化系统基于模型的测试用例生成新方法
近年来,基于模型的自动化系统测试(MBT)越来越受到重视。然而,制造工厂的规模和复杂性的增加也导致了更大的模型,这再次花费了建模任务的时间和人力。解决这一问题的一种方法是将整个模型细分为可重用的自动化系统常用组件的几个独立模型。因此,我们引入了同步深度优先搜索(SDFS),它使用细分的自动机模型来生成测试用例。底层的自动化模型需要合并同步转换,以便在彼此之间同步流程,从而形成一个用于测试的整体模型。
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