PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
February 9, 2026Systems Engineering0 citations

Product Line Modeling Process to Manage Requirements Confidentiality and Variability

View Full Paper
MBMichel BourdellèsJHJamal El HachemSSSalah Sadou

Key Points

  • The aim is to improve the management of requirements confidentiality and variability in product line modeling through MBSE.
  • Develop a model-based systems engineering solution for product line management
  • Integrate textual requirements as basic elements of the model
  • Ensure protection of confidential assets during the modeling process
  • Demonstrated an effective alternative to Feature Model based solutions
  • Provided a relevant method contrasting Clone and Own practices
  • Illustrated the approach with practical examples showing its effectiveness

Abstract

ABSTRACT Customer references for the specification and design of industrial product systems are generally documentary, obtained by refining customer requirements. The increasing complexity of this specification process requires the migration to modeling using model‐based systems engineering (MBSE) processes and tools. MBSE‐based solutions proposed for product line management integrate a superset of modeled assets, also called a 150% generic model, to be selected and adapted for a particular product need. These solutions consider the modeling elements as basic elements of system specification, and do not address the constraint of secure access to confidential information. In this article, we propose another MBSE driven solution whose basic elements remain textual requirements, and allowing the modeling of product lines with access protection of confidential assets. We illustrate the approach through several examples, showing that it constitutes a relevant alternative to both Feature Model based solutions and Clone and Own practices.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Bourdellès et al. (2026) studied this question.

synapsesocial.com/papers/698979a6f0ec2af6756e76afhttps://doi.org/10.1002/sys.70044
Ask AI
Helpful
Bookmark
Share
View Full Paper