Skip to main content

An Approach for Prioritizing Software Features Based on Node Centrality in Probability Network

  • Conference paper
  • First Online:
Software Reuse: Bridging with Social-Awareness (ICSR 2016)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 9679))

Included in the following conference series:

  • 892 Accesses

Abstract

Due to the increasing complexity of software products as well as the restriction of the development budget and time, requirements prioritization, i.e., selecting more crucial requirements to be designed and developed firstly, has become increasingly important in the software development lifetime. Considering the fact that a feature in a feature model can be viewed as a set of closely related requirements, feature prioritization will contribute to requirements prioritization to a large extent. Therefore, how to measure the priority of features within a feature model becomes an important issue in requirements analysis. In this paper, a software feature prioritization approach is proposed, which utilizes the dependencies between features to build a feature probability network and measures feature prioritization through the nodes centrality in the network. Experiments conducted on real world feature models show that the proposed approach can accurately prioritize features in feature models.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    http://www.splot-research.org/.

  2. 2.

    http://www.softpedia.com/.

  3. 3.

    Feature Model Editor, http://www.splot-research.org/.

References

  1. Tong, Z., Zhuang, Q., Guo, Q., Ma, P.: Research on technologies of software requirements prioritization. In: Yuan, Y., Wu, X., Lu, Y. (eds.) ISCTCS 2013. CCIS, vol. 426, pp. 9–21. Springer, Heidelberg (2014)

    Google Scholar 

  2. Hofmann, H.F., Lehner, F.: Requirements engineering as a success factor in software projects. IEEE Softw. 4, 58–66 (2001)

    Article  Google Scholar 

  3. Perini, A., Susi, A., Avesani, P.: A machine learning approach to software requirements prioritization. IEEE Trans. Softw. Eng. 39(4), 445–461 (2013)

    Article  Google Scholar 

  4. Peter, H., Olson, D., Rodgers, T.: Multi-criteria preference analysis for systematic requirements negotiation. In: 26th Annual International Conference on Computer Software and Applications, pp. 887–892. IEEE Press, New York (2002)

    Google Scholar 

  5. Saaty, R.W.: The analytic hierarchy process: what it is and how it is used. Math. Model. 9(3), 161–176 (1987)

    Article  MathSciNet  MATH  Google Scholar 

  6. Tonella, P., Susi, A., Palma, F.: Interactive requirements prioritization using a genetic algorithm. Inf. Softw. Technol. 55(1), 173–187 (2013)

    Article  Google Scholar 

  7. Harker, P.T.: Incomplete pairwise comparisons in the analytic hierarchy process. Math. Model. 9(11), 837–848 (1987)

    Article  MathSciNet  Google Scholar 

  8. Easmin, R., Gias, A.U., Khaled, S.M.: A partial order assimilation approach for software requirements prioritization. In: 3rd International Conference on Informatics, Electronics and Vision (ICIEV), pp. 1–5. IEEE Press, New York (2014)

    Google Scholar 

  9. Khari, M., Kumar, N.: Comparison of six prioritization techniques for software requirements. J. Glob. Res. Comput. Sci. 4(1), 38–43 (2013)

    Google Scholar 

  10. Achimugu, P., Selamat, A., Ibrahim, R., Mahrin, M.N.: A systematic literature review of software requirements prioritization research. Inf. Softw. Technol. 56(6), 568–585 (2014)

    Article  Google Scholar 

  11. Kang, K.C., Cohen, S.G., Hess, J.A., Novak, W.E., Peterson, A.S.: Feature-oriented domain analysis (FODA) feasibility study. Technical report, Carnegie Mellon University (1990)

    Google Scholar 

  12. Radatz, J., Geraci, A., Katki, F.: IEEE standard glossary of software engineering terminology. IEEE Stand. 610121990(121990), 3 (1990)

    Google Scholar 

  13. Zhang, W., Yan, H., Zhao, H., Jin, Z.: A BDD-based approach to verifying clone-enabled feature models’ constraints and customization. In: Mei, H. (ed.) ICSR 2008. LNCS, vol. 5030, pp. 186–199. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  14. Czarnecki, K., Helsen, S., Eisenecker, U.: Staged configuration using feature models. In: Nord, R.L. (ed.) SPLC 2004. LNCS, vol. 3154, pp. 266–283. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  15. White, J., Dougherty, B., Schmidt, D.C., Benavides, D.: Automated reasoning for multi-step feature model configuration problems. In: 13th International Conference on Software Product Line, pp. 11–20. Carnegie Mellon University (2009)

    Google Scholar 

  16. Stoiber, R., Glinz, M.: Supporting stepwise, incremental product derivation in product line requirements engineering. In: 4th International Workshop on Variability Modelling of Software-Intensive Systems. ICB-Research report, pp. 77–84. University Duisburg-Essen (2010)

    Google Scholar 

  17. Bagheri, E., Asadi, M., Gasevic, D., Soltani, S.: Stratified analytic hierarchy process: prioritization and selection of software features. In: Bosch, J., Lee, J. (eds.) SPLC 2010. LNCS, vol. 6287, pp. 300–315. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  18. Acher, M., Cleve, A., Perrouin, G., Heymans, P., Vanbeneden, C., Collet, P., Lahire, P.: On extracting feature models from product descriptions. In: 6th International Workshop on Variability Modeling of Software-Intensive Systems, pp. 45–54. ACM, New York (2012)

    Google Scholar 

  19. Benavides, D., Segura, S., Ruiz-Corts, A.: Automated analysis of feature models 20 years later: a literature review. Inf. Syst. 35(6), 615–636 (2010)

    Article  Google Scholar 

  20. Davril, J.M., Delfosse, E., Hariri, N., Acher, M., Cleland-Huang, J., Heymans, P.: Feature model extraction from large collections of informal product descriptions. In: 9th Joint Meeting on Foundations of Software Engineering, pp. 290–300. ACM, New York (2013)

    Google Scholar 

  21. Rincn, L.F., Giraldo, G.L., Mazo, R., Salinesi, C.: An ontological rule-based approach for analyzing dead and false optional features in feature models. Electron. Notes Theoret. Comput. Sci. 302, 111–132 (2014)

    Article  Google Scholar 

  22. Opsahl, T., Agneessens, F., Skvoretz, J.: Node centrality in weighted networks: generalizing degree and shortest paths. Soc. Netw. 32(3), 245–251 (2010)

    Article  Google Scholar 

  23. Zar, J.H.: Significance testing of the Spearman rank correlation coefficient. J. Am. Stat. Assoc. 67(339), 578–580 (1972)

    Article  MATH  Google Scholar 

Download references

Acknowledgments

The work is supported by the National Basic Research Program of China under grant No. 2014CB340404, and the National Natural Science Foundation of China under Nos. 61373037, 61272111, 61572186 and 61562073. The authors would like to thank anonymous reviewers for their valuable suggestions. Jian Wang is the corresponding author.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jian Wang .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this paper

Cite this paper

Peng, Z., Wang, J., He, K., Li, H. (2016). An Approach for Prioritizing Software Features Based on Node Centrality in Probability Network. In: Kapitsaki, G., Santana de Almeida, E. (eds) Software Reuse: Bridging with Social-Awareness. ICSR 2016. Lecture Notes in Computer Science(), vol 9679. Springer, Cham. https://doi.org/10.1007/978-3-319-35122-3_8

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-35122-3_8

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-35121-6

  • Online ISBN: 978-3-319-35122-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics