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

    6 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,
    EditorsLidia Fuentes, Ebrahim Bagheri, Antonio Ruiz-Cortes, David Benavides, Rafael Capilla, Yingfei Xiong, Jan Bosch, Mathieu Acher, Daniel Schall, Myra Cohen, Javier Troya
    Place of PublicationNew York
    PublisherAssociation for Computing Machinery, Inc
    Pages215-224
    Number of pages10
    VolumeA
    ISBN (Electronic)9781450352215
    ISBN (Print)978-1-4503-5221-5
    DOIs
    Publication statusPublished - 25 Sep 2017
    Event21st International Systems and Software Product Line Conference (SPLC 2017) - Sevilla, Spain
    Duration: 25 Sep 201729 Sep 2017
    Conference number: 21

    Publication series

    NameACM International Conference Proceeding Series
    Volume1

    Conference

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

    Keywords

    • MATLAB/simulink
    • Software maintainability
    • Variability mining

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