TY - GEN
T1 - Beyond Software Product Lines: Variability Modeling in Cyber-Physical Systems
AU - Krüger, Jacob
AU - Nielebock, Sebastian
AU - Krieter, Sebastian
AU - Diedrich, Christian
AU - Leich, Thomas
AU - Saake, Gunter
AU - Zug, Sebastian
AU - Ortmeier, Frank
N1 - DBLP License: DBLP's bibliographic metadata records provided through http://dblp.org/ are distributed under a Creative Commons CC0 1.0 Universal Public Domain Dedication. Although the bibliographic metadata records are provided consistent with CC0 1.0 Dedication, the content described by the metadata records is not. Content may be subject to copyright, rights of privacy, rights of publicity and other restrictions.
PY - 2017
Y1 - 2017
N2 - Smart IT has an increasing influence on the control of daily life. For instance, smart grids manage power supply, autonomous automobiles take part in traffic, and assistive robotics support humans in production cells. We denote such systems as Cyber-physical Systems (CPSs), where cyber addresses the controlling software, while physical describes the controlled hardware. One key aspect of CPSs is their capability to adapt to new situations autonomously or with minimal human intervention. To achieve this, CPS s reuse, reorganize and reconfigure their components during runtime. Some components may even serve in different CPSs and different situations simultaneously. The hardware of a CPS usually consists of a heterogeneous set of variable components. While each component can be designed as a software product line (SPL), which is a well established approach to describe software and hardware variability, it is not possible to describe CPSs’ variability solely on a set of separate, non-interacting product lines. To properly manage variability, a CPS must specify dependencies and interactions of its separate components and cope with variable environments, changing requirements, and differing safety properties. In this paper, we i) propose a classification of variability aspects, ii) point out current challenges in variability modeling, and iii) sketch open research questions. Overall, we aim to initiate new research directions for variable CPSs based on existing product-line techniques.
AB - Smart IT has an increasing influence on the control of daily life. For instance, smart grids manage power supply, autonomous automobiles take part in traffic, and assistive robotics support humans in production cells. We denote such systems as Cyber-physical Systems (CPSs), where cyber addresses the controlling software, while physical describes the controlled hardware. One key aspect of CPSs is their capability to adapt to new situations autonomously or with minimal human intervention. To achieve this, CPS s reuse, reorganize and reconfigure their components during runtime. Some components may even serve in different CPSs and different situations simultaneously. The hardware of a CPS usually consists of a heterogeneous set of variable components. While each component can be designed as a software product line (SPL), which is a well established approach to describe software and hardware variability, it is not possible to describe CPSs’ variability solely on a set of separate, non-interacting product lines. To properly manage variability, a CPS must specify dependencies and interactions of its separate components and cope with variable environments, changing requirements, and differing safety properties. In this paper, we i) propose a classification of variability aspects, ii) point out current challenges in variability modeling, and iii) sketch open research questions. Overall, we aim to initiate new research directions for variable CPSs based on existing product-line techniques.
KW - Software Prodcut Line
KW - Cyber-Physical System
KW - Modeling
U2 - 10.1145/3106195.3106217
DO - 10.1145/3106195.3106217
M3 - Conference contribution
SP - 237
EP - 241
BT - International Systems and Software Product Line Conference (SPLC)
PB - Association for Computing Machinery, Inc
ER -