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

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

1 Citation (Scopus)

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.

Original language	English
Title of host publication	27th ACM International Systems and Software Product Line Conference, SPLC 2023 - Proceedings
Editors	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
Publisher	Association for Computing Machinery, Inc
Pages	182-193
Number of pages	12
ISBN (Electronic)	9798400700910
DOIs	https://doi.org/10.1145/3579027.3608989
Publication status	Published - 28 Aug 2023
Event	27th ACM International Systems and Software Product Line Conference, SPLC 2023 - Tokyo, Japan Duration: 28 Aug 2023 → 1 Sept 2023

Publication series

Name	ACM International Conference Proceeding Series
Volume	A-1

Conference

Conference	27th ACM International Systems and Software Product Line Conference, SPLC 2023
Country/Territory	Japan
City	Tokyo
Period	28/08/23 → 1/09/23

Bibliographical note

Publisher Copyright:
© 2023 ACM.

Keywords

Software Product Lines
Taxonomy
Variability Modeling

Access to Document

10.1145/3579027.3608989

Cite this

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 (Eds.), 27th ACM International Systems and Software Product Line Conference, SPLC 2023 - Proceedings (pp. 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. editor / 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. pp. 182-193 (ACM International Conference Proceeding Series).

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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 (eds), 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, pp. 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. ed. / 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. p. 182-193 (ACM International Conference Proceeding Series; Vol. A-1).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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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.

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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

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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, editors, 27th ACM International Systems and Software Product Line Conference, SPLC 2023 - Proceedings. Association for Computing Machinery, Inc. 2023. p. 182-193. (ACM International Conference Proceeding Series). doi: 10.1145/3579027.3608989

True Variability Shining Through Taxonomy Mining

Abstract

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Bibliographical note

Keywords

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