Ontology-Based Test Case Generation For Simulating Complex Production Automation Systems

被引:0
作者
Moser, Thomas [1 ]
Duerr, Gregor [1 ]
Biffl, Stefan [1 ]
机构
[1] Vienna Univ Technol, Christian Doppler Lab Software Engn Integrat Flex, Vienna, Austria
来源
22ND INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING & KNOWLEDGE ENGINEERING (SEKE 2010) | 2010年
关键词
test case generation; ontology; production automation simulation; explicit testing knowledge;
D O I
暂无
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
The behavior of complex production automation systems is hard to predict, therefore simulation is used to study the likely system behavior. However, in a real-world system many parameter variants need to be tested with limited resources. Therefore, test cases need to be generated in a systematic way to find suitable scenarios efficiently. This paper investigates the effort of two approaches for providing test cases based on available testing knowledge. The traditional approach uses a static generator script based on implicit testing knowledge, which takes significant effort to add new parameters. The innovative approach uses a dynamic generic generator script based on an ontology data model of the testing knowledge. We empirically evaluate these approaches with a use case from the production automation domain. Major result is that the high-level test description of the ontology-based approach takes more initial effort for setup, but increases the usability and reduces the risk of errors during the test case generation process.
引用
收藏
页码:478 / 482
页数:5
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