Continuous Domain Input Abstraction and Fault Detection Capability in Combinatorial Testing

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Abstract

Combinatorial Testing (CT) is a fundamental approach for testing varying applications ranging from mobile applications to autonomous driving. Input modeling is a prerequisite to CT. When the input domain is continuous, abstraction is necessary to generate a CT test suite. In this study, we discuss three novel, work-in-progress research avenues. With these avenues, we aim to maximize the fault detection capability of CT test suites through continuous domain input abstraction optimization. We motivate our research on abstraction by demonstrating how it affects the fault detection capability of CT test suites on three audio plugin implementations. Overall, continuous domain input abstraction optimization remains a promising open challenge.

Original languageEnglish
Title of host publicationProceedings - 2023 38th IEEE/ACM International Conference on Automated Software Engineering Workshops, ASEW 2023
PublisherIEEE
Pages167-170
Number of pages4
ISBN (Electronic)9798350330328
DOIs
Publication statusPublished - 2023
Event38th IEEE/ACM International Conference on Automated Software Engineering Workshops: ASEW 2023 - Echternach, Luxembourg
Duration: 11 Sept 202315 Sept 2023

Conference

Conference38th IEEE/ACM International Conference on Automated Software Engineering Workshops
Abbreviated titleASEW 2023
Country/TerritoryLuxembourg
CityEchternach
Period11/09/2315/09/23

Keywords

  • abstraction
  • combinatorial testing
  • continuous domain input models
  • mutation testing

ASJC Scopus subject areas

  • Control and Optimization
  • Software
  • Safety, Risk, Reliability and Quality

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