An Empirical Study of Two Software Product Line Tools

Kattiana Constantino, Juliana Alves Pereira, Juliana Padilha, Priscilla Vasconcelos, Eduardo Figueiredo

2016

Abstract

In the last decades, software product lines (SPL) have proven to be an efficient software development technique in industries due its capability to increase quality and productivity and decrease cost and time-to-market through extensive reuse of software artifacts. To achieve these benefits, tool support is fundamental to guide industries during the SPL development life-cycle. However, many different SPL tools are available nowadays and the adoption of the appropriate tool is a big challenge in industries. In order to support engineers choosing a tool that best fits their needs, this paper presents the results of a controlled empirical study to assess two Eclipse-based tools, namely FeatureIDE and pure::variants. This empirical study involved 84 students who used and evaluated both tools. The main weakness we observe in both tools are the lack adequate mechanisms for managing the variability, such as for product configuration. As a strength, we observe the automated analysis and the feature model editor.

References

  1. Bagheri, E., and Ensan, F. (2014). Dynamic decision models for staged software product line configuration. Requirements Engineering, 19(2), 187-212.
  2. Batory, D., Sarvela, J. N., and Rauschmayer, A. (2004). Scaling step-wise refinement. IEEE Transactions on Software Engineering, 30(6), 355-371.
  3. Bernardo, M., Ciancarini, P., and Donatiello, L. (2002). Architecting families of software systems with process algebras. ACM Transactions on Software Engineering and Methodology (TOSEM), 11(4), 386-426.
  4. Beuche, D. (2003). Variant management with pure::variants. pure-systems GmbH.
  5. Clements, P., and Northrop, L. (2002). Software product lines: Practices and patterns. Addison-Wesley.
  6. Czarnecki, K., and Eisenecker, U. (2000). Generative programming: methods, tools, and applications.
  7. Djebbi, O., Salinesi, C., and Fanmuy, G. (2007). Industry survey of product lines management tools: Requirements, qualities and open issues. In Int'l Requirements Engineering Conference (RE), 301-306.
  8. Figueiredo, E. et al. (2008). Evolving software product lines with aspects. In International Conference on Software Engineering (ICSE), 261-270.
  9. Jain, R. et al. (2010). The Art of Computer Systems Performance Analysis. John Wiley & Sons.
  10. Jarzabek, S., Ong, W. C., and Zhang, H. (2003). Handling variant requirements in domain modeling. Journal of Systems and Software, 68(3), 171-182.
  11. Kang, K. C. et al. (1990), Feature-Oriented Domain Analysis (FODA) feasibility study. Carnegie-Mellon University, Software Engineering Institute.
  12. Kiczales, G. et al. (1997). Aspect-oriented programming, 220-242. European Conf. on OO Program. (ECOOP).
  13. Machado, L., Pereira, J., Garcia, L., and Figueiredo, E. (2014). SPLConfig: Product configuration in software product line. In Brazilian Conference on Software (CBSoft), Tools Session, 1-8.
  14. Metzger, A., & Pohl, K. (2007). Variability management in software product line engineering. In International Conference on Software Engineering (ICSE), 186-187.
  15. Pereira, J. et al. (2013). Software variability management: An exploratory study with two feature modeling tools. In Brazilian Symposium on Software Components, Architectures and Reuse (SBCARS), 20-29.
  16. Pereira, J. A., Constantino, K., and Figueiredo, E. (2015). A systematic literature review of software product line management tools. In International Conference on Software Reuse (ICSR), 73-89.
  17. Pohl, K., Böckle, G., and van der Linden, F. J. (2005). Software Product Line Engineering: Foundations, Principles and Techniques. Springer.
  18. Prehofer, C. (2001). Feature-oriented programming: A new way of object composition. Concurrency and Computation Practice and Experience, 13(6), 465-501.
  19. Simmonds, J., Bastarrica, M., Silvestre, L., and Quispe, A. (2011). Analyzing methodologies and tools for specifying variability in software processes. Universidad de Chile, Santiago, Chile.
  20. Thüm, T. et al. (2014). FeatureIDE: An extensible framework for feature-oriented software development. Science of Computer Programming, 79, 70-85.
  21. Vale, G.; Albuquerque, D.; Figueiredo, E.; and Garcia, A. (2015) Defining Metric Thresholds for Software Product Lines: A Comparative Study. In International Software Product Line Conference (SPLC), pp. 176- 185.
  22. Wohlin, C. et al. (2012). Experimentation in software engineering. Springer.
Download


Paper Citation


in Harvard Style

Constantino K., Pereira J., Padilha J., Vasconcelos P. and Figueiredo E. (2016). An Empirical Study of Two Software Product Line Tools . In Proceedings of the 11th International Conference on Evaluation of Novel Software Approaches to Software Engineering - Volume 1: ENASE, ISBN 978-989-758-189-2, pages 164-171. DOI: 10.5220/0005829801640171


in Bibtex Style

@conference{enase16,
author={Kattiana Constantino and Juliana Alves Pereira and Juliana Padilha and Priscilla Vasconcelos and Eduardo Figueiredo},
title={An Empirical Study of Two Software Product Line Tools},
booktitle={Proceedings of the 11th International Conference on Evaluation of Novel Software Approaches to Software Engineering - Volume 1: ENASE,},
year={2016},
pages={164-171},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005829801640171},
isbn={978-989-758-189-2},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 11th International Conference on Evaluation of Novel Software Approaches to Software Engineering - Volume 1: ENASE,
TI - An Empirical Study of Two Software Product Line Tools
SN - 978-989-758-189-2
AU - Constantino K.
AU - Pereira J.
AU - Padilha J.
AU - Vasconcelos P.
AU - Figueiredo E.
PY - 2016
SP - 164
EP - 171
DO - 10.5220/0005829801640171