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A user survey of configuration challenges in Linux and eCos

Published:25 January 2012Publication History

ABSTRACT

Operating systems expose sophisticated configurability to handle variability in hardware platforms like mobile devices, desktops, and servers. The variability model of an operating system kernel like Linux contains thousands of options guarded by hundreds of complex constraints. To guide users throughout the configuration and ensure the validity of their decisions, specialized tools known as configurators have been developed. Despite these tools, configuration still remains a difficult and challenging process. To better understand the challenges faced by users during configuration, we conducted two surveys, one among Linux users and another among eCos users. This paper presents the results of the surveys along three dimensions: configuration practice; user guidance; and language expressiveness. We hope that these results will help researchers and tool builders focus their efforts to improve tool support for software configuration.

References

  1. M. Antkiewicz and K. Czarnecki. FeaturePlugin: feature modeling plug-in for Eclipse. In Proceedings of the 2004 OOPSLA workshop on eclipse technology eXchange (eclipse '04), pages 67--72, 2004. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. K. Bak and K. Ali. Improving usability of the Linux kernel configuration tools. http://gsd.uwaterloo.ca/sites/default/files/cs889-report.pdf.Google ScholarGoogle Scholar
  3. D. Benavides, S. Segura, P. Trinidad, and A. Ruiz-Cortés. FAMA: Tooling a framework for the automated analysis of feature models. In Proceedings of the First International Workshop on Variability Modelling of Software-intensive Systems (VaMoS'07), pages 129--134, Limerick, Ireland, January 2007. Lero Technical Report 2007-01.Google ScholarGoogle Scholar
  4. T. Berger, S. She, R. Lotufo, A. Wąsowski, and K. Czarnecki. Variability modeling in the real: a perspective from the operating systems domain. In Proceedings of the 25th International Conference on Automated Software Engineering (ASE'10), pages 73--82, Antwerp, Belgium, 2010. ACM. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. D. Beuche. Modeling and building software product lines with pure::variants. In Proceedings of the 2008 12th International Software Product Line Conference (SPLC '08), page 358, Washington, DC, USA, 2008. IEEE Computer Society. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. BigLever Software (Inc.). Product line engineering solutions for systems and software. http://www.biglever.com/extras/BigLever_Solution_Brochure.pdf, November 2011.Google ScholarGoogle Scholar
  7. L. Chen and M. Ali Babar. A systematic review of evaluation of variability management approaches in software product lines. Information and Software Technology, 53(4):344--362, 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. K. Czarnecki, S. Helsen, and U. W. Eisenecker. Formalizing cardinality-based feature models and their specialization. Software Process: Improvement and Practice, 10(1):7--29, 2005.Google ScholarGoogle ScholarCross RefCross Ref
  9. D. Dhungana, P. Grünbacher, and R. Rabiser. DecisionKing: A flexible and extensible tool for integrated variability modeling. In Proceedings of the First International Workshop on Variability Modelling of Software-intensive Systems (VaMoS'07), pages 119--127, Limerick, Ireland, January 2007. Lero Technical Report 2007-01.Google ScholarGoogle Scholar
  10. A. Hubaux, A. Classen, M. Mendonça, and P. Heymans. A preliminary review on the application of feature diagrams in practice. In Proceedings of the Fourth International Workshop on Variability Modelling of Software-intensive Systems (VaMoS'10), pages 53--59, Linz, Austria, January 2010. Universität Duisburg-Essen.Google ScholarGoogle Scholar
  11. A. Hubaux, Y. Xiong, and K. Czarnecki. Configuration challenges in Linux and eCos: A survey. Technical Report GSDLAB-TR 2011-09-29, Generative Software Development Laboratory, University of Waterloo, 2011.Google ScholarGoogle Scholar
  12. M. Janota. Do SAT solvers make good configurators? In Workshop on Analyses of Software Product Lines (ASPL 2008), pages 191--195, Limerick, Ireland, September 2008.Google ScholarGoogle Scholar
  13. M. Janota. SAT Solving in Interactive Configuration. PhD thesis, University College Dublin, 2010.Google ScholarGoogle Scholar
  14. K. Kang, S. G. Cohen, J. A. Hess, W. E. Novak, and A. S. Peterson. Feature-Oriented Domain Analysis (FODA) Feasibility Study. Technical report, Software Engineering Institute, Carnegie Mellon University, 1990.Google ScholarGoogle ScholarCross RefCross Ref
  15. C. Kästner, T. Thüm, G. Saake, J. Feigenspan, T. Leich, F. Wielgorz, and S. Apel. FeatureIDE: A tool framework for feature-oriented software development. In Proceedings of the 31st International Conference on Software Engineering (ICSE'09, pages 611--614, Vancouver, Canada, 2009. IEEE. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. O. Koren. A study of the Linux kernel evolution. ACM SIGOPS Operating Systems Review, 40:110--112, 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. M. Mendonca, M. Branco, and D. Cowan. S. P. L. O. T.: software product lines online tools. In Proceeding of the 24th ACM SIGPLAN conference companion on Object oriented programming systems languages and applications (OOPSLA'09), pages 761--762, New York, NY, USA, 2009. ACM. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. M. Mendonca, A. Wąsowski, and K. Czarnecki. SAT-based analysis of feature models is easy. In Proceedings of the 13th International Software Product Line Conference (SPLC'09), pages 231--240, San Francisco, CA, USA, 2009. Carnegie Mellon University. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. M. Mendonça. Efficient Reasoning Techniques for Large Scale Feature Models. PhD thesis, University of Waterloo, 2009.Google ScholarGoogle Scholar
  20. R. Michel, A. Classen, A. Hubaux, and Q. Boucher. A formal semantics for feature cardinalities in feature diagrams. In Proceedings of the 5th International Workshop on Variability Modelling of Software-intensive Systems (VaMoS'11), pages 82--89, Namur, Belgium, 2011. ACM Press. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. A. Nöhrer and A. Egyed. Conflict resolution strategies during product configuration. In Proceedings of the Fourth International Workshop on Variability Modelling of Software-intensive Systems (VaMoS'10), pages 107--114, Linz, Austria, 2010. Universität Duisburg-Essen.Google ScholarGoogle Scholar
  22. R. Rabiser, P. Grünbacher, and D. Dhungana. Requirements for product derivation support: Results from a systematic literature review and an expert survey. Information and Software Technology, 52(3):324--346, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. K. Schmid, R. Rabiser, and P. Grünbacher. A comparison of decision modeling approaches in product lines. In Fifth International Workshop on Variability Modelling of Software-Intensive Systems (VaMoS'11), ACM International Conference Proceedings Series, pages 119--126. ACM, 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. J. Sincero and W. Schröder-Preikschat. The Linux kernel configurator as a feature modeling tool. In Proceedings of the 1st Workshop on Analyses of Software Product Lines (ASPL'08), pages 257--260, Limerick, Ireland, 2008.Google ScholarGoogle Scholar
  25. J. White, D. C. Schmidt, D. Benavides, P. Trinidad, and A. Ruiz-Cortés. Automated diagnosis of product-line configuration errors in feature models. In Proceedings of the 12th International Software Product Line Conference (SPLC'08), pages 225--234, Limercick, Ireland, 2008. IEEE Computer Society. Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. Y. Xiong, A. Hubaux, S. She, and K. Czarnecki. Generating range fixes for software configuration. Technical Report GSDLAB-TR 2011-10-27, Generative Software Development Laboratory, University of Waterloo, 2011.Google ScholarGoogle Scholar
  27. Z. Yin, X. Ma, J. Zheng, Y. Zhou, L. Bairavasundaram, and S. Pasupathy. An empirical study on configuration errors in commercial and open source systems. In Proceedings of 23rd ACM Symposium on Operating Systems Principles (SOSP), pages 159--172. ACM, 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library

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  • Published in

    cover image ACM Other conferences
    VaMoS '12: Proceedings of the 6th International Workshop on Variability Modeling of Software-Intensive Systems
    January 2012
    193 pages
    ISBN:9781450310581
    DOI:10.1145/2110147

    Copyright © 2012 ACM

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    New York, NY, United States

    Publication History

    • Published: 25 January 2012

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