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  4. Extended Abstract of Poster: STARS: Tree-Based Classification and Testing of Feature Combinations in the Automated Robotic Domain
 
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2025
Conference Paper
Title

Extended Abstract of Poster: STARS: Tree-Based Classification and Testing of Feature Combinations in the Automated Robotic Domain

Abstract
Testing complex systems is crucial for ensuring safety, especially in automated driving, where diverse data sources and variable environments pose challenges. Here, robust safety validation is critical but exhaustive n-way combinatorial testing is impractical due to the vast number of test cases. The STARS framework uses tree-based scenario classifiers to limit feature combinations in a given domain.
Author(s)
Schallau, Till
Technische Universität Dortmund
Schmid, Dominik
Technische Universität Dortmund
Pawlinorz, Nick
Technische Universität Dortmund
Naujokat, Stefan
Technische Universität Dortmund
Howar, Falk  
Fraunhofer-Institut für Software- und Systemtechnik ISST  
Mainwork
2025 IEEE International Conference on Software Testing Verification and Validation Workshops Icstw 2025
Conference
18th IEEE International Conference on Software Testing, Verification and Validation Workshops, ICSTW 2025
DOI
10.1109/ICSTW64639.2025.10962523
Language
English
Fraunhofer-Institut für Software- und Systemtechnik ISST  
Keyword(s)
  • automated driving

  • feature coverage

  • n-way combinatorial testing

  • scenario classification

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