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From Ontologies to Input Models for Combinatorial Testing

  • Franz WotawaEmail author
  • Yihao Li
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11146)

Abstract

Ordinary tools for computing combinatorial test suites rely on simple input models comprising variables together with their domains and constraints limiting possible combinations. Modeling for combinatorial testing requires to represent the input domain of the application in a way such that it fits to the combinatorial testing input model. Depending on the application’s domain this mapping ranges from trivial to more complicated. In this paper, we focus on modeling for combinatorial testing in cases the application’s domain can be represented in form of an ontology, i.e., concepts and their relationships. We formally introduce the notation of ontology we rely on in this paper, and show how such ontologies can be automatically mapped to a combinatorial testing input model. We discuss the algorithm and show its properties.

Keywords

Combinatorial testing Ontologies Combinatorial testing input models 

Notes

Acknowledgment

The research was supported by ECSEL JU under the project H2020 737469 AutoDrive - Advancing fail-aware, fail-safe, and fail-operational electronic components, systems, and architectures for fully automated driving to make future mobility safer, affordable, and end-user acceptable. AutoDrive is funded by the Austrian Federal Ministry of Transport, Innovation and Technology (BMVIT) under the program “ICT of the Future” between May 2017 and April 2020. More information https://iktderzukunft.at/en/ Open image in new window .

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Copyright information

© IFIP International Federation for Information Processing 2018

Authors and Affiliations

  1. 1.Institute for Software TechnologyTechnische Universität GrazGrazAustria

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