Bridging the Gap between Software Variability and System Variant Management: Experiences from an Industrial Machinery Product Line

Stefan Fischer, Lukas Linsbauer, Roberto Erick Lopez-Herrejon, Alexander Egyed, Rudolf Ramler

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

Abstract

Companies that develop complex systems often do so in the form of product lines, where each product variant can be configured to a certain degree to fit a customer's specific requirements. Features cannot be combined arbitrarily in a product line. The knowledge which features require or exclude each other is represented in form of variability models. Unfortunately, in practice, such variability models do not exist or they are oriented towards the needs and viewpoints of specific organizational units, e.g. Sales, manufacturing, hardware engineering, or software development. In this paper we present our experiences in building a variability model for the highly configurable software part of a complex mechatronic system produced by one of our industrial partner companies. The company already had support and processes for product variant management in place for sales and hardware manufacturing. However, the corresponding variability model was at the level of the overall system and excluded the variability of the software part. The paper discusses the resulting problems and challenges and describes the approach we selected to bridge the gap that existed between product variants and software configurations. The goal and driving motivation for our work was the improvement of the software development process and specifically the testing of software variants. The paper also shows how software configuration and testing activities can benefit from an appropriate variability model.
Original languageEnglish
Title of host publication41st Euromicro Conference on Software Engineering and Advanced Applications, EUROMICRO-SEAA 2015, Madeira, Portugal, August 26-28, 2015
Editors IEEE
Pages402-409
Number of pages8
ISBN (Electronic)9781467375856
DOIs
Publication statusPublished - 20 Oct 2015

Fields of science

  • 102 Computer Sciences
  • 102022 Software development

JKU Focus areas

  • Computation in Informatics and Mathematics
  • Engineering and Natural Sciences (in general)

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