skip to main content
10.1145/2791060.2791101acmotherconferencesArticle/Chapter ViewAbstractPublication PagessplcConference Proceedingsconference-collections
short-paper

Evolution in dynamic software product lines: challenges and perspectives

Published: 20 July 2015 Publication History

Abstract

In many domains systems need to run continuously and cannot be shut down for reconfiguration or maintenance tasks. Cyber-physical or cloud-based systems, for instance, thus often provide means to support their adaptation at runtime. The required flexibility and adaptability of systems suggests the application of Software Product Line (spl) principles to manage their variability and to support their reconfiguration. Specifically, Dynamic Software Product Lines (dspl) have been proposed to support the management and binding of variability at runtime. While spl evolution has been widely studied, it has so far not been investigated in detail in a dspl context. Variability models that are used in a dspl have to co-evolve and be kept consistent with the systems they represent to support reconfiguration even after changes to the systems at runtime. In this short paper we present a classification of the required operations for jointly evolving problem and solution space in a dspl. We analyze the impact of such operations on the consistency of a dspl and propose an approach to deal with the described issues. We describe a runtime monitoring system used in the domain of industrial automation software as an example of a dspl evolving at runtime to motivate and explain our work.

References

[1]
L. Baresi and C. Quinton. Dynamically Evolving the Structural Variability of Dynamic Software Product Lines. In SEAMS, 2015.
[2]
D. Benavides, S. Segura, and A. R. Cortés. Automated analysis of feature models 20 years later: A literature review. Inf. Syst., 35(6):615--636, 2010.
[3]
N. Bencomo, J. Lee, and S. O. Hallsteinsen. How Dynamic is your Dynamic Software Product Line? In SPLC (vol. 2), pages 61--68, 2010.
[4]
P. Borba, L. Teixeira, and R. Gheyi. A Theory of Software Product Line Refinement. Theor. Comput. Sci., 455: 2--30, 2012.
[5]
G. Botterweck and A. Pleuss. Evolution of software product lines. In Evolving Software Systems, Mens, T., Serebrenik, A., and Cleve, A. (eds.), pages 265--295. Springer, 2014.
[6]
R. Capilla, J. Bosch, P. Trinidad, A. Ruiz-Cortés, and M. Hinchey. An Overview of Dynamic Software Product Line Architectures and Techniques: Observations from Research and Industry. JSS, 91: 3--23, 2014.
[7]
K. Czarnecki, P. Grünbacher, R. Rabiser, K. Schmid, and A. Wasowski. Cool features and tough decisions: A comparison of variability modeling approaches. In VaMoS, pages 173--182. ACM, 2012.
[8]
D. Dhungana, P. Grünbacher, and R. Rabiser. The dopler meta-tool for decision-oriented variability modeling: A multiple case study. Automated Software Engineering, 18(1):77--114, 2011.
[9]
W. Heider, R. Rabiser, and P. Grünbacher. Facilitating the Evolution of Products in Product Line Engineering by Capturing and Replaying Configuration Decisions. STTT, 14(5):613--630, 2012.
[10]
A. Helleboogh, D. Weyns, K. Schmid, T. Holvoet, K. Schelfthout, and W. Van Betsbrugge. Adding Variants on-the-fly: Modeling Meta-Variability in Dynamic Software Product Lines. In DSPL, SPLC, pages 18--27, 2009.
[11]
M. Hinchey, S. Park, and K. Schmid. Building Dynamic Software Product Lines. Computer, 45(10):22--26, 2012.
[12]
J. McGregor. The Evolution of Product Line Assets. Technical Report CMU/SEI-2003-TR-005, 2003.
[13]
L. Passos, T. Leopoldo, N. Dintzner, S. Apel, A. Wasowski, K. Czarnecki, P. Borba, and J. Guo. Coevolution of Variability Models and Related Software Artifacts: A Fresh Look at Evolution Patterns in the Linux Kernel. Empirical Software Engineering, To appear 2015.
[14]
C. Quinton, A. Pleuss, D. Le Berre, L. Duchien, and G. Botterweck. Consistency Checking for the Evolution of Cardinality-based Feature Models. In SPLC, pages 122--131. ACM, 2014.
[15]
C. Quinton, D. Romero, and L. Duchien. SALOON: a platform for selecting and configuring cloud environments. Software:Practice and Experience, 2015.
[16]
R. Rabiser, M. Vierhauser, and P. Grünbacher. Variability management for a runtime monitoring infrastructure. In VaMoS, pages 35--42. ACM, 2015.
[17]
C. Seidl, F. Heidenreich, and U. Aßmann. Co-evolution of Models and Feature Mapping in Software Product Lines. In SPLC, pages 76--85. ACM, 2012.
[18]
R. Tartler, D. Lohmann, J. Sincero, and W. Schröder-Preikschat. Feature Consistency in Compile-time-configurable System Software: Facing the Linux 10,000 Feature Problem. In EuroSys, pages 47--60. ACM, 2011.
[19]
M. Vierhauser, P. Grünbacher, A. Egyed, R. Rabiser, and W. Heider. Flexible and scalable consistency checking on product line variability models. In ASE, pages 63--72. ACM, 2010.
[20]
M. Vierhauser, R. Rabiser, P. Grünbacher, C. Danner, S. Wallner, and H. Zeisel. A flexible framework for runtime monitoring of system-of-systems architectures. In WICSA, pages 57--66. IEEE, 2014.

Cited By

View all

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Other conferences
SPLC '15: Proceedings of the 19th International Conference on Software Product Line
July 2015
460 pages
ISBN:9781450336130
DOI:10.1145/2791060
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

  • Vanderbilt University: Vanderbilt University
  • Biglever: BigLever Software, Inc.

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 20 July 2015

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. consistency
  2. dynamic software product lines
  3. evolution

Qualifiers

  • Short-paper

Conference

SPLC '15
Sponsor:
  • Vanderbilt University
  • Biglever

Acceptance Rates

SPLC '15 Paper Acceptance Rate 34 of 87 submissions, 39%;
Overall Acceptance Rate 167 of 463 submissions, 36%

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)11
  • Downloads (Last 6 weeks)0
Reflects downloads up to 14 Sep 2024

Other Metrics

Citations

Cited By

View all

View Options

Get Access

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media