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The DOPLER meta-tool for decision-oriented variability modeling: a multiple case study

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Abstract

The variability of a product line is typically defined in models. However, many existing variability modeling approaches are rigid and don’t allow sufficient domain-specific adaptations. We have thus been developing a flexible and extensible approach for defining product line variability models. Its main purposes are to guide stakeholders through product derivation and to automatically generate product configurations. Our approach is supported by the DOPLER (Decision-Oriented Product Line Engineering for effective Reuse) meta-tool that allows modelers to specify the types of reusable assets, their attributes, and dependencies for their specific system and context. The aim of this paper is to investigate the suitability of our approach for different domains. More specifically, we explored two research questions regarding the implementation of variability and the utility of DOPLER for variability modeling in different domains. We conducted a multiple case study consisting of four cases in the domains of industrial automation systems and business software. In each of these case studies we analyzed variability implementation techniques. Experts from our industry partners then developed domain-specific meta-models, tool extensions, and variability models for their product lines using DOPLER. The four cases demonstrate the flexibility of the DOPLER approach and the extensibility and adaptability of the supporting meta tool.

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Authors and Affiliations

  1. Christian Doppler Laboratory for Software Engineering Integration for Flexible Automation Systems, Vienna University of Technology, Vienna, Austria

    Deepak Dhungana

  2. Institute Systems Engineering and Automation, Johannes Kepler University Linz, Linz, Austria

    Paul Grünbacher

  3. Christian Doppler Laboratory for Automated Software Engineering, Johannes Kepler University Linz, Linz, Austria

    Rick Rabiser

Authors
  1. Deepak Dhungana
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  2. Paul Grünbacher
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  3. Rick Rabiser
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Correspondence to Deepak Dhungana.

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Dhungana, D., Grünbacher, P. & Rabiser, R. The DOPLER meta-tool for decision-oriented variability modeling: a multiple case study. Autom Softw Eng 18, 77–114 (2011). https://doi.org/10.1007/s10515-010-0076-6

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