DirectDebug: Automated Testing and Debugging of Feature Models

V. -M. Le, A. Felfernig, M. Uta, D. Benavides, J. Galindo, T. N. T. Tran

Research output: Chapter in Book/Report/Conference proceedingConference paper

Abstract

Variability models (e.g., feature models) are a common way for the representation of variabilities and commonalities of software artifacts. Such models can be translated to a logical representation and thus allow different operations for quality assurance and other types of model property analysis. Specifically, complex and often large-scale feature models can become faulty, i.e., do not represent the expected variability properties of the underlying software artifact. In this paper, we introduce DirectDebug which is a direct diagnosis approach to the automated testing and debugging of variability models. The algorithm helps software engineers by supporting an automated identification of faulty constraints responsible for an unintended behavior of a variability model. This approach can significantly decrease development and maintenance efforts for such models.
Original languageEnglish
Title of host publication2021 IEEE/ACM 43rd International Conference on Software Engineering: New Ideas and Emerging Results (ICSE-NIER)
Pages81-85
Number of pages5
DOIs
Publication statusPublished - 7 May 2021
Event2021 IEEE/ACM 43rd International Conference on Software Engineering: New Ideas and Emerging Results - Virtuell, Spain
Duration: 25 May 202128 May 2021
https://conf.researchr.org/track/icse-2021/icse-2021-New-Ideas-and-Emerging-Results?

Conference

Conference2021 IEEE/ACM 43rd International Conference on Software Engineering: New Ideas and Emerging Results
Abbreviated titleICSE-NIER 2021
CountrySpain
CityVirtuell
Period25/05/2128/05/21
Internet address

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