True Variability Shining Through Taxonomy Mining

Christoph König; Kamil Rosiak; Loek Cleophas; Ina Schaefer

doi:10.1145/3579027.3608989

True Variability Shining Through Taxonomy Mining

Christoph König, Kamil Rosiak, Loek Cleophas, Ina Schaefer

Engineering of Software-Intensive Systems

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/Congresprocedure › Conferentiebijdrage › Academic › peer review

1 Citaat (Scopus)

Samenvatting

Software variants of a Software Product Line (SPL) consist of a set of artifacts specified by features. Variability models document the valid relationships between features and their mapping to artifacts. However, research has shown inconsistencies between the variability of variants in features and artifacts, with negative effects on system safety and development effort. To analyze this mismatch in variability, the causal relationships between features, artifacts, and variants must be uncovered, which has only been addressed to a limited extent. In this paper, we propose taxonomy graphs as novel variability models that reflect the composition of variants from artifacts and features, making mismatches in variability explicit. Our evaluation with two SPL case studies demonstrates the usefulness of our variability model and shows that mismatches in variability can vary significantly in detail and severity.

Originele taal-2	Engels
Titel	27th ACM International Systems and Software Product Line Conference, SPLC 2023 - Proceedings
Redacteuren	Paolo Arcaini, Maurice H. ter Beek, Gilles Perrouin, Iris Reinhartz-Berger, Miguel R. Luaces, Christa Schwanninger, Shaukat Ali, Mahsa Varshosaz, Angelo Gargantini, Stefania Gnesi, Malte Lochau, Laura Semini, Hironori Washizaki
Uitgeverij	Association for Computing Machinery, Inc
Pagina's	182-193
Aantal pagina's	12
ISBN van elektronische versie	9798400700910
DOI's	https://doi.org/10.1145/3579027.3608989
Status	Gepubliceerd - 28 aug. 2023
Evenement	27th ACM International Systems and Software Product Line Conference, SPLC 2023 - Tokyo, Japan Duur: 28 aug. 2023 → 1 sep. 2023

Publicatie series

Naam	ACM International Conference Proceeding Series
Volume	A-1

Congres

Congres	27th ACM International Systems and Software Product Line Conference, SPLC 2023
Land/Regio	Japan
Stad	Tokyo
Periode	28/08/23 → 1/09/23

Bibliografische nota

Publisher Copyright:
© 2023 ACM.

Financiering

This work was supported by funding from the topic Engineering Secure Systems of the Helmholtz Association (HGF) and by KASTEL Security Research Labs.

Financiers	Financiernummer
KASTEL Security Research Labs
Helmholtz-Gemeinschaft
Helmholtz Association

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10.1145/3579027.3608989

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König, C., Rosiak, K., Cleophas, L., & Schaefer, I. (2023). True Variability Shining Through Taxonomy Mining. In P. Arcaini, M. H. ter Beek, G. Perrouin, I. Reinhartz-Berger, M. R. Luaces, C. Schwanninger, S. Ali, M. Varshosaz, A. Gargantini, S. Gnesi, M. Lochau, L. Semini, & H. Washizaki (editors), 27th ACM International Systems and Software Product Line Conference, SPLC 2023 - Proceedings (blz. 182-193). (ACM International Conference Proceeding Series; Vol. A-1). Association for Computing Machinery, Inc. https://doi.org/10.1145/3579027.3608989

König, Christoph ; Rosiak, Kamil ; Cleophas, Loek et al. / True Variability Shining Through Taxonomy Mining. 27th ACM International Systems and Software Product Line Conference, SPLC 2023 - Proceedings. redacteur / Paolo Arcaini ; Maurice H. ter Beek ; Gilles Perrouin ; Iris Reinhartz-Berger ; Miguel R. Luaces ; Christa Schwanninger ; Shaukat Ali ; Mahsa Varshosaz ; Angelo Gargantini ; Stefania Gnesi ; Malte Lochau ; Laura Semini ; Hironori Washizaki. Association for Computing Machinery, Inc, 2023. blz. 182-193 (ACM International Conference Proceeding Series).

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abstract = "Software variants of a Software Product Line (SPL) consist of a set of artifacts specified by features. Variability models document the valid relationships between features and their mapping to artifacts. However, research has shown inconsistencies between the variability of variants in features and artifacts, with negative effects on system safety and development effort. To analyze this mismatch in variability, the causal relationships between features, artifacts, and variants must be uncovered, which has only been addressed to a limited extent. In this paper, we propose taxonomy graphs as novel variability models that reflect the composition of variants from artifacts and features, making mismatches in variability explicit. Our evaluation with two SPL case studies demonstrates the usefulness of our variability model and shows that mismatches in variability can vary significantly in detail and severity.",

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König, C, Rosiak, K, Cleophas, L & Schaefer, I 2023, True Variability Shining Through Taxonomy Mining. in P Arcaini, MH ter Beek, G Perrouin, I Reinhartz-Berger, MR Luaces, C Schwanninger, S Ali, M Varshosaz, A Gargantini, S Gnesi, M Lochau, L Semini & H Washizaki (uitgave), 27th ACM International Systems and Software Product Line Conference, SPLC 2023 - Proceedings. ACM International Conference Proceeding Series, vol. A-1, Association for Computing Machinery, Inc, blz. 182-193, 27th ACM International Systems and Software Product Line Conference, SPLC 2023, Tokyo, Japan, 28/08/23. https://doi.org/10.1145/3579027.3608989

True Variability Shining Through Taxonomy Mining. / König, Christoph; Rosiak, Kamil; Cleophas, Loek et al.
27th ACM International Systems and Software Product Line Conference, SPLC 2023 - Proceedings. uitgave / Paolo Arcaini; Maurice H. ter Beek; Gilles Perrouin; Iris Reinhartz-Berger; Miguel R. Luaces; Christa Schwanninger; Shaukat Ali; Mahsa Varshosaz; Angelo Gargantini; Stefania Gnesi; Malte Lochau; Laura Semini; Hironori Washizaki. Association for Computing Machinery, Inc, 2023. blz. 182-193 (ACM International Conference Proceeding Series; Vol. A-1).

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/Congresprocedure › Conferentiebijdrage › Academic › peer review

TY - GEN

T1 - True Variability Shining Through Taxonomy Mining

AU - König, Christoph

AU - Rosiak, Kamil

AU - Cleophas, Loek

AU - Schaefer, Ina

PY - 2023/8/28

Y1 - 2023/8/28

N2 - Software variants of a Software Product Line (SPL) consist of a set of artifacts specified by features. Variability models document the valid relationships between features and their mapping to artifacts. However, research has shown inconsistencies between the variability of variants in features and artifacts, with negative effects on system safety and development effort. To analyze this mismatch in variability, the causal relationships between features, artifacts, and variants must be uncovered, which has only been addressed to a limited extent. In this paper, we propose taxonomy graphs as novel variability models that reflect the composition of variants from artifacts and features, making mismatches in variability explicit. Our evaluation with two SPL case studies demonstrates the usefulness of our variability model and shows that mismatches in variability can vary significantly in detail and severity.

AB - Software variants of a Software Product Line (SPL) consist of a set of artifacts specified by features. Variability models document the valid relationships between features and their mapping to artifacts. However, research has shown inconsistencies between the variability of variants in features and artifacts, with negative effects on system safety and development effort. To analyze this mismatch in variability, the causal relationships between features, artifacts, and variants must be uncovered, which has only been addressed to a limited extent. In this paper, we propose taxonomy graphs as novel variability models that reflect the composition of variants from artifacts and features, making mismatches in variability explicit. Our evaluation with two SPL case studies demonstrates the usefulness of our variability model and shows that mismatches in variability can vary significantly in detail and severity.

KW - Software Product Lines

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DO - 10.1145/3579027.3608989

M3 - Conference contribution

T3 - ACM International Conference Proceeding Series

SP - 182

EP - 193

BT - 27th ACM International Systems and Software Product Line Conference, SPLC 2023 - Proceedings

A2 - Arcaini, Paolo

A2 - ter Beek, Maurice H.

A2 - Perrouin, Gilles

A2 - Reinhartz-Berger, Iris

A2 - Luaces, Miguel R.

A2 - Schwanninger, Christa

A2 - Ali, Shaukat

A2 - Varshosaz, Mahsa

A2 - Gargantini, Angelo

A2 - Gnesi, Stefania

A2 - Lochau, Malte

A2 - Semini, Laura

A2 - Washizaki, Hironori

PB - Association for Computing Machinery, Inc

T2 - 27th ACM International Systems and Software Product Line Conference, SPLC 2023

Y2 - 28 August 2023 through 1 September 2023

ER -

König C, Rosiak K, Cleophas L, Schaefer I. True Variability Shining Through Taxonomy Mining. In Arcaini P, ter Beek MH, Perrouin G, Reinhartz-Berger I, Luaces MR, Schwanninger C, Ali S, Varshosaz M, Gargantini A, Gnesi S, Lochau M, Semini L, Washizaki H, redacteurs, 27th ACM International Systems and Software Product Line Conference, SPLC 2023 - Proceedings. Association for Computing Machinery, Inc. 2023. blz. 182-193. (ACM International Conference Proceeding Series). doi: 10.1145/3579027.3608989

True Variability Shining Through Taxonomy Mining

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