Dynamic Variability Management Supporting Operational Modes of a Power Plant Product Line

Runtime variability is becoming an attractive technique to support those runtime scenarios for systems that demand some kind of autonomous reconfiguration or adaptive behavior. Nowadays, the challenge of many critical systems that need to handle different operational modes, often in an unattended mode, require specific solutions for which runtime variability mechanisms become relevant. This research describes the challenges of runtime variability to support multiple binding modes for handling the diversity of different operational modes and runtime reconfiguration needs. We validate our approach in a power plant control product line at Toshiba which advances previous work making the transition between the power plant operational modes more automatic and dynamic.

[1]  Luciano Baresi,et al.  Dynamically Evolving the Structural Variability of Dynamic Software Product Lines , 2015, 2015 IEEE/ACM 10th International Symposium on Software Engineering for Adaptive and Self-Managing Systems.

[2]  Vicente Pelechano,et al.  VIVACE: A framework for the systematic evaluation of variability support in process-aware information systems , 2015, Inf. Softw. Technol..

[3]  Yoshihiro Matsumoto,et al.  Variability in Power Plant Control Software , 2013, Systems and Software Variability Management.

[4]  Vicente Pelechano,et al.  Prototyping Dynamic Software Product Lines to evaluate run-time reconfigurations , 2013, Sci. Comput. Program..

[5]  Rafael Capilla,et al.  Context Variability for Context-Aware Systems , 2014, Computer.

[6]  Vicente Pelechano,et al.  Dynamic adaptation of service compositions with variability models , 2014, J. Syst. Softw..

[7]  Klaus Pohl,et al.  Software Product Line Engineering - Foundations, Principles, and Techniques , 2005 .

[8]  Kyo Chul Kang,et al.  Feature-Oriented Domain Analysis (FODA) Feasibility Study , 1990 .

[9]  Yoshihiro Matsumoto,et al.  Management and Financial Controls of a Software Product Line Adoption , 2009 .

[10]  Birger Møller-Pedersen,et al.  Adding Standardized Variability to Domain Specific Languages , 2008, 2008 12th International Software Product Line Conference.

[11]  Klaus Pohl,et al.  Software Product Line Engineering , 2005 .

[12]  Lidia Fuentes,et al.  Creating Self-Adapting Mobile Systems with Dynamic Software Product Lines , 2015, IEEE Software.

[13]  Alois Zoitl,et al.  Development and adaptation of IEC 61499 automation and control applications with runtime variability models , 2009, 2009 7th IEEE International Conference on Industrial Informatics.

[14]  Bradley R. Schmerl,et al.  Rainbow: Architecture-Based Self-Adaptation with Reusable Infrastructure , 2004, Computer.

[15]  Uwe Zdun,et al.  Designing runtime variation points in product line architectures: three cases , 2004, Sci. Comput. Program..

[16]  Malte Lochau,et al.  Context-aware DSPLs: model-based runtime adaptation for resource-constrained systems , 2013, SPLC '13 Workshops.

[17]  Vicente Pelechano,et al.  Autonomic Computing through Reuse of Variability Models at Runtime: The Case of Smart Homes , 2009, Computer.

[18]  Y. Matsumoto A Guide for Management and Financial Controls of Product Lines , 2007 .

[19]  Wolfgang Schröder-Preikschat,et al.  Variability in Time - Product Line Variability and Evolution Revisited , 2010, VaMoS.

[20]  Sooyong Park,et al.  Building Dynamic Software Product Lines , 2012, Computer.

[21]  Richard N. Taylor,et al.  Using Architectural Models to Manage and Visualize Runtime Adaptation , 2009, Computer.

[22]  Andy Schürr,et al.  Staged configuration of dynamic software product lines with complex binding time constraints , 2014, VaMoS.

[23]  Vicente Pelechano,et al.  Designing and Prototyping Dynamic Software Product Lines: Techniques and Guidelines , 2010, SPLC.

[24]  Jan Bosch,et al.  Dynamic Variability in Software-Intensive Embedded System Families , 2012, Computer.

[25]  Luciano Baresi,et al.  Evolution in dynamic software product lines: challenges and perspectives , 2015, SPLC.

[26]  Rafael Capilla,et al.  Context variability modeling for runtime configuration of service-based dynamic software product lines , 2014, SPLC '14.

[27]  David Garlan,et al.  Rainbow: architecture-based self-adaptation with reusable infrastructure , 2004 .

[28]  Jean-Marc Jézéquel,et al.  Dynamic Software Product Lines for Service-Based Systems , 2009, 2009 Ninth IEEE International Conference on Computer and Information Technology.

[29]  Jaejoon Lee,et al.  Engineering Service-Based Dynamic Software Product Lines , 2012, Computer.

[30]  Jeffrey O. Kephart,et al.  The Vision of Autonomic Computing , 2003, Computer.

[31]  Koji Hashimoto,et al.  Dynamic software adaptation for service-oriented product lines , 2011, SPLC '11.

[32]  André van der Hoek,et al.  Design-time product line architectures for any-time variability , 2004, Sci. Comput. Program..

[33]  Vicente Pelechano,et al.  Strategies for variability transformation at run-time , 2009, SPLC.

[34]  Antonio Ruiz Cortés,et al.  Article in Press G Model the Journal of Systems and Software an Overview of Dynamic Software Product Line Architectures and Techniques: Observations from Research and Industry , 2022 .

[35]  Jan Bosch,et al.  The Promise and Challenge of Runtime Variability , 2011, Computer.