Talks and Poster Presentations (with Proceedings-Entry):
T Moser, D. Winkler, M. Heindl, S. Biffl:
"Automating the Detection of Complex Semantic Conflicts between Software Requirements";
Talk: 23rd International Conference on Software Engineering and Knowledge Engineering (SEKE 2011),
Eden Roc Renaissance Hotel Miami Beach, USA;
- 2011-07-09; in: "Proceedings of 23rd International Conference on Software Engineering and Knowledge Engineering (SEKE 2011)",
M. Sadjadi (ed.);
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 re-sources. Therefore, test cases need to be generated in a syste-matic 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 test-ing knowledge, which takes significant effort to add new pa-rameters. 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.
test case generation, ontology, production automation simulation, explicit testing knowledge.
Created from the Publication Database of the Vienna University of Technology.