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Title: A product line systems engineering process for variability identification and reduction
Authors: Li, Mole
Grigg, Alan
Dickerson, Charles E.
Guan, Lin
Ji, Siyuan
Keywords: Product line
Relational orientation
Variability modeling
Systems engineering
Systems modeling language
Issue Date: 2019
Publisher: © IEEE
Citation: LI, M. ... et al, 2019. A product line systems engineering process for variability identification and reduction. IEEE Systems Journal, doi: 10.1109/JSYST.2019.2897628.
Abstract: Software Product Line Engineering has attracted attention in the last two decades due to its promising capabilities to reduce costs and time to market through reuse of requirements and components. In practice, developing system level product lines in a large-scale company is not an easy task as there may be thousands of variants and multiple disciplines involved. The manual reuse of legacy system models at domain engineering to build reusable system libraries and configurations of variants to derive target products can be infeasible. To tackle this challenge, a Product Line Systems Engineering process is proposed. Specifically, the process extends research in the System Orthogonal Variability Model to support hierarchical variability modeling with formal definitions; utilizes Systems Engineering concepts and legacy system models to build the hierarchy for the variability model and to identify essential relations between variants; and finally, analyzes the identified relations to reduce the number of variation points. The process, which is automated by computational algorithms, is demonstrated through an illustrative example on generalized Rolls-Royce aircraft engine control systems. To evaluate the effectiveness of the process in the reduction of variation points, it is further applied to case studies in different engineering domains at different levels of complexity. Subject to system model availability, reduction of 14% to 40% in the number of variation points are demonstrated in the case studies.
Description: © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Sponsor: This work was supported in part by the Rolls-Royce Controls and Data Service team.
Version: Accepted for publication
DOI: 10.1109/JSYST.2019.2897628
URI: https://dspace.lboro.ac.uk/2134/36829
Publisher Link: https://doi.org/10.1109/JSYST.2019.2897628
ISSN: 1932-8184
Appears in Collections:Published Articles (Mechanical, Electrical and Manufacturing Engineering)

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