TY - JOUR
T1 - Supporting distributed product configuration by integrating heterogeneous variability modeling approaches
AU - Galindo, José A.
AU - Dhungana, Deepak
AU - Rabiser, Rick
AU - Benavides, David
AU - Botterweck, Goetz
AU - Grünbacher, Paul
N1 - Funding Information:
This work was supported, in part, by Science Foundation Ireland Grants 03/CE2/I303_1 and 10/CE/I1855 to Lero; by the Christian Doppler Forschungsgesellschaft (Austria), Siemens VAI Metals Technologies, and Siemens Corporate Technology; by the European Commission (FEDER), by the Spanish government under TAPAS (TIN2012-32273) project and the Andalusian government under Talentia program and the COPAS (TIC-1867) project. Also, we would like to express special thanks to Dominik Seichter for his previous contributions to this research.
Publisher Copyright:
© 2015 Elsevier B.V. All rights reserved.
PY - 2015/2/11
Y1 - 2015/2/11
N2 - Context In industrial settings products are developed by more than one organization. Software vendors and suppliers commonly typically maintain their own product lines, which contribute to a larger (multi) product line or software ecosystem. It is unrealistic to assume that the participating organizations will agree on using a specific variability modeling technique—they will rather use different approaches and tools to manage the variability of their systems. Objective We aim to support product configuration in software ecosystems based on several variability models with different semantics that have been created using different notations. Method We present an integrative approach that provides a unified perspective to users configuring products in multi product line environments, regardless of the different modeling methods and tools used internally. We also present a technical infrastructure and a prototype implementation based on web services. Results We show the feasibility of the approach and its implementation by using it with the three most widespread types of variability modeling approaches in the product line community, i.e., feature-based, OVM-style, and decision-oriented modeling. To demonstrate the feasibility and flexibility of our approach, we present an example derived from industrial experience in enterprise resource planning. We further applied the approach to support the configuration of privacy settings in the Android ecosystem based on multiple variability models. We also evaluated the performance of different model enactment strategies used in our approach. Conclusions Tools and techniques allowing stakeholders to handle variability in a uniform manner can considerably foster the initiation and growth of software ecosystems from the perspective of software reuse and configuration.
AB - Context In industrial settings products are developed by more than one organization. Software vendors and suppliers commonly typically maintain their own product lines, which contribute to a larger (multi) product line or software ecosystem. It is unrealistic to assume that the participating organizations will agree on using a specific variability modeling technique—they will rather use different approaches and tools to manage the variability of their systems. Objective We aim to support product configuration in software ecosystems based on several variability models with different semantics that have been created using different notations. Method We present an integrative approach that provides a unified perspective to users configuring products in multi product line environments, regardless of the different modeling methods and tools used internally. We also present a technical infrastructure and a prototype implementation based on web services. Results We show the feasibility of the approach and its implementation by using it with the three most widespread types of variability modeling approaches in the product line community, i.e., feature-based, OVM-style, and decision-oriented modeling. To demonstrate the feasibility and flexibility of our approach, we present an example derived from industrial experience in enterprise resource planning. We further applied the approach to support the configuration of privacy settings in the Android ecosystem based on multiple variability models. We also evaluated the performance of different model enactment strategies used in our approach. Conclusions Tools and techniques allowing stakeholders to handle variability in a uniform manner can considerably foster the initiation and growth of software ecosystems from the perspective of software reuse and configuration.
KW - Computer software reusability
KW - Ecology
KW - Enterprise resource planning
KW - Semantics
KW - Web services
KW - Automated analysis
KW - Industrial experience
KW - Multiple variability
KW - Product configuration
KW - Prototype implementations
KW - Software Product Line
KW - Technical infrastructure
KW - Tools and techniques
KW - Ecosystems
KW - Software product lines
UR - http://www.scopus.com/inward/record.url?scp=84932618234&partnerID=8YFLogxK
U2 - 10.1016/j.infsof.2015.02.002
DO - 10.1016/j.infsof.2015.02.002
M3 - Article
SN - 0950-5849
VL - 62
SP - 78
EP - 100
JO - Information and Software Technology
JF - Information and Software Technology
IS - 1
ER -