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BeTTy: benchmarking and testing on the automated analysis of feature models

Published:25 January 2012Publication History

ABSTRACT

The automated analysis of feature models is a flourishing research topic that has called the attention of both researchers and practitioners during the last two decades. During this time, the number of tools and techniques enabling the analysis of feature models has increased and also their complexity. In this scenario, the lack of specific testing mechanisms to assess the correctness and good performance of analysis tools is becoming a major obstacle hindering the development of tools and affecting their quality and reliability. In this paper, we present BeTTy, a framework for BEnchmarking and TesTing on the analYsis of feature models. Among other features, BeTTy enables the automated detection of faults in feature model analysis tools. Also, it supports the generation of motivating test data to evaluate the performance of analysis tools in both average and pessimistic cases. Part of the functionality of the framework is provided through a web-based interface facilitating the random generation of both classic and attributed feature models.

References

  1. D. Benavides, S. Segura, and A. Ruiz-Cortés. Automated analysis of feature models 20 years later: A literature review. Information Systems, 35(6):615--636, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. D. Benavides, S. Segura, P. Trinidad, and A. Ruiz-Cortés. A first step towards a framework for the automated analysis of feature models. In Managing Variability for Software Product Lines: Working With Variability Mechanisms, 2006.Google ScholarGoogle Scholar
  3. FaMa Tool Suite. http://www.isa.us.es/fama/, accessed November 2011.Google ScholarGoogle Scholar
  4. J. A. Galindo, D. Benavides, and S. Segura. Debian packages repositories as software product line models. towards automated analysis. In Proceeding of the First International Workshop on Automated Configuration and Tailoring of Applications (ACOTA), 2010.Google ScholarGoogle Scholar
  5. Graphviz.. http://www.graphviz.org/, accessed November 2011.Google ScholarGoogle Scholar
  6. G. Kapfhammer. The Computer Science Handbook, chapter Software Testing. CRC Press, 2nd edition, June, 2004.Google ScholarGoogle Scholar
  7. Apache Math. Apache math. http://commons.apache.org/math/, accessed November 2011.Google ScholarGoogle Scholar
  8. M. Mendonca, D. D. Cowan, W. Malyk, and T. Oliveira. Collaborative product configuration: Formalization and efficient algorithms for dependency analysis. Journal of Software, 3(2):69--82, 2008.Google ScholarGoogle ScholarCross RefCross Ref
  9. S. Segura. Functional and Performance Testing of Feature Model Analysis Tools. Extending the FaMa Ecosystem. PhD thesis, Dept. of Computer Languages and Systems, University of Seville, 2011.Google ScholarGoogle Scholar
  10. S. Segura, D. Benavides, and A. Ruiz-Cortés. Functional testing of feature model analysis tools: a test suite. Software, IET, 5(1):70--82, february 2011.Google ScholarGoogle ScholarCross RefCross Ref
  11. S. Segura, Robert M. Hierons, D. Benavides, and A. Ruiz-Cortés. Automated metamorphic testing on the analyses of feature models. Information and Software Technology, 53(3):245--258, 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. S. Segura, Robert M. Hierons, D. Benavides, and A. Ruiz-Cortés. Mutation testing on an object-oriented framework: An experience report. Information and Software Technology Special Issue on Mutation Testing, 2011.Google ScholarGoogle ScholarCross RefCross Ref
  13. S. Segura, JA. Parejo, Robert M. Hierons, D. Benavides, and A. Ruiz-Cortés. ETHOM: An evolutionary algorithm for optimized feature models generation. Tech Report ISA-2011-TR-03 (v. 1.0), Applied Software Engineering Research Group, 2011.Google ScholarGoogle Scholar
  14. S. Segura and A. Ruiz-Cortés. Benchmarking on the automated analyses of feature models: A preliminary roadmap. In Third International Workshop on Variability Modelling of Software-intensive Systems, pages 137--143, Seville, Spain, 2009.Google ScholarGoogle Scholar
  15. S. She, R. Lotufo, T. Berger, A. Wasowski, and K. Czarnecki. The variability model of the linux kernel. In Fourth International Workshop on Variability Modelling of Software-intensive Systems (VAMOS'10), Linz, Austria, January 2010.Google ScholarGoogle Scholar
  16. S. She, R. Lotufo, T. Berger, A. Wasowski, and K. Czarnecki. Reverse engineering feature models. In Proceedings of the 27th International Conference on Software Engineering, pages 461--470, 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. S. P. L. O. T.: Software Product Lines Online Tools. http://www.splot-research.org/, accessed November 2011.Google ScholarGoogle Scholar
  18. T. Thüm, D. Batory, and C. Kästner. Reasoning about edits to feature models. In International Conference on Software Engineering, pages 254--264, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. P. Trinidad, A. Ruiz-Cortés, D. Benavides, and S. Segura. Three-dimensional feature diagrams visualization. In 2nd International Workshop on Visualisation in Software Product Line Engineering (ViSPLE 2008), 2008.Google ScholarGoogle Scholar
  20. E. J. Weyuker. On testing non-testable programs. The Computer Journal, 25(4):465--470, 1982.Google ScholarGoogle ScholarCross RefCross Ref
  21. J. White, B. Dougherty, and D. Schmidt. Selecting highly optimal architectural feature sets with filtered cartesian flattening. Journal of Systems and Software, 82(8):1268--1284, 2009. 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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    Publication History

    • Published: 25 January 2012

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