Detecting variability in MATLAB/Simulink models : an industry-inspired technique and its evaluation

A. Schlie, D. Wille, S. Schulze, L.G.W.A. Cleophas, I. Schaefer

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

4 Citations (Scopus)

Abstract

Model-based languages such as MATLAB/Simulink play an essential role in the model-driven development of software systems. To comply with new requirements, it is common practice to create new variants by copying existing systems and modifying them. Commonly referred to as clone-and-own, severe problems arise in the long-run when no dedicated variability management is installed. To allow for a documented and structured reuse of systems, their variability information needs to be reverse-engineered. In this paper, we propose an advanced comparison procedure, the Matching Window Technique, and a customizable metric. Both allow us to overcome structural alterations commonly performed during clone-and-own. We analyze related MATLAB/Simulink models and determine, classify and represent their variability information in an understandable way. With our technique, we assist model engineers in maintaining and evolving existing variants. We provide three feasibility studies with real-world models from the automotive domain and show our technique to be fast and precise. Furthermore, we perform semi-structured interviews with domain experts to assess the potential applicability of our technique in practice.
Original languageEnglish
Title of host publicationSPLC '17 : Proceedings of the 21st International Systems and Software Product Line Conference, SPLC 2017, 25-29 September 2017, Sevilla, Spain,
Place of PublicationNew York
PublisherAssociation for Computing Machinery, Inc
Pages215-224
Number of pages10
VolumeA
ISBN (Print)978-1-4503-5221-5
DOIs
Publication statusPublished - 2017
Event21st International Systems and Software Product Line Conference (SPLC 2017) - Sevilla, Spain
Duration: 25 Sep 201729 Sep 2017
Conference number: 21

Conference

Conference21st International Systems and Software Product Line Conference (SPLC 2017)
Abbreviated titleSPLC 2017
CountrySpain
CitySevilla
Period25/09/1729/09/17

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MATLAB
Industry
Copying
Engineers

Cite this

Schlie, A., Wille, D., Schulze, S., Cleophas, L. G. W. A., & Schaefer, I. (2017). Detecting variability in MATLAB/Simulink models : an industry-inspired technique and its evaluation. In SPLC '17 : Proceedings of the 21st International Systems and Software Product Line Conference, SPLC 2017, 25-29 September 2017, Sevilla, Spain, (Vol. A, pp. 215-224). New York: Association for Computing Machinery, Inc. https://doi.org/10.1145/3106195.3106225
Schlie, A. ; Wille, D. ; Schulze, S. ; Cleophas, L.G.W.A. ; Schaefer, I. / Detecting variability in MATLAB/Simulink models : an industry-inspired technique and its evaluation. SPLC '17 : Proceedings of the 21st International Systems and Software Product Line Conference, SPLC 2017, 25-29 September 2017, Sevilla, Spain, . Vol. A New York : Association for Computing Machinery, Inc, 2017. pp. 215-224
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Schlie, A, Wille, D, Schulze, S, Cleophas, LGWA & Schaefer, I 2017, Detecting variability in MATLAB/Simulink models : an industry-inspired technique and its evaluation. in SPLC '17 : Proceedings of the 21st International Systems and Software Product Line Conference, SPLC 2017, 25-29 September 2017, Sevilla, Spain, . vol. A, Association for Computing Machinery, Inc, New York, pp. 215-224, 21st International Systems and Software Product Line Conference (SPLC 2017), Sevilla, Spain, 25/09/17. https://doi.org/10.1145/3106195.3106225

Detecting variability in MATLAB/Simulink models : an industry-inspired technique and its evaluation. / Schlie, A.; Wille, D.; Schulze, S.; Cleophas, L.G.W.A.; Schaefer, I.

SPLC '17 : Proceedings of the 21st International Systems and Software Product Line Conference, SPLC 2017, 25-29 September 2017, Sevilla, Spain, . Vol. A New York : Association for Computing Machinery, Inc, 2017. p. 215-224.

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

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AB - Model-based languages such as MATLAB/Simulink play an essential role in the model-driven development of software systems. To comply with new requirements, it is common practice to create new variants by copying existing systems and modifying them. Commonly referred to as clone-and-own, severe problems arise in the long-run when no dedicated variability management is installed. To allow for a documented and structured reuse of systems, their variability information needs to be reverse-engineered. In this paper, we propose an advanced comparison procedure, the Matching Window Technique, and a customizable metric. Both allow us to overcome structural alterations commonly performed during clone-and-own. We analyze related MATLAB/Simulink models and determine, classify and represent their variability information in an understandable way. With our technique, we assist model engineers in maintaining and evolving existing variants. We provide three feasibility studies with real-world models from the automotive domain and show our technique to be fast and precise. Furthermore, we perform semi-structured interviews with domain experts to assess the potential applicability of our technique in practice.

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Schlie A, Wille D, Schulze S, Cleophas LGWA, Schaefer I. Detecting variability in MATLAB/Simulink models : an industry-inspired technique and its evaluation. In SPLC '17 : Proceedings of the 21st International Systems and Software Product Line Conference, SPLC 2017, 25-29 September 2017, Sevilla, Spain, . Vol. A. New York: Association for Computing Machinery, Inc. 2017. p. 215-224 https://doi.org/10.1145/3106195.3106225