WipeOutR: automated redundancy detection for feature models.

Viet-Man Le, Alexander Felfernig, Mathias Uta, Thi Ngoc Trang Tran, Cristian Vidal Silva

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review


Feature models are used to specify variability and commonality properties of software artifacts. In order to assure high-quality models, different feature model analysis and testing operations can be applied. In this paper, we present two new algorithms that help to make feature model configuration as well as different kinds of analysis operations more efficient. Specifically, we focus on the automated identification of redundancies in feature models and cor-responding test suites. Redundant constraints in feature models can lead to low-performing configuration (solution) search and also to additional efforts in feature model debugging. Redundant feature model test cases can trigger inefficiencies in testing operations. In this paper, we introduce WipeOutR which is an algorithmic approach to support the automated identification of redundancies. This approach has the potential to significantly improve the quality of feature model development and configuration.
Original languageEnglish
Title of host publication26th ACM International Systems and Software Product Line Conference, SPLC 2022 - Proceedings
EditorsAlexander Felfernig, Lidia Fuentes, Jane Cleland-Huang, Wesley K.G. Assuncao, Wesley K.G. Assuncao, Andreas Falkner, Maider Azanza, Miguel A. Rodriguez Luaces, Megha Bhushan, Laura Semini, Xavier Devroey, Claudia Maria Lima Werner, Christoph Seidl, Viet-Man Le, Jose Miguel Horcas
PublisherAssociation of Computing Machinery
Number of pages6
ISBN (Electronic)9781450394437
Publication statusPublished - 12 Sept 2022
Event26th ACM International Systems and Software Product Line Conference: ASPLC 2022 - Graz, Austria
Duration: 12 Sept 202216 Sept 2022


Conference26th ACM International Systems and Software Product Line Conference
Abbreviated titleSPLC'22
Internet address


  • feature models
  • quality assurance
  • redundancy detection
  • testing and debugging
  • variability modeling

ASJC Scopus subject areas

  • Software

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