Skip to main content

Software Metrics in Agile Software: An Empirical Study

  • Conference paper
Agile Processes in Software Engineering and Extreme Programming (XP 2014)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 179))

Included in the following conference series:

Abstract

This paper presents a software metrics analysis of eight object-oriented systems. Five systems had been developed using Agile methodologies and three using plan-driven methodologies; three systems were written in Python and five in Java. For each system, we considered 10 traditional metrics such as LOC and the Chidamber and Kemerer metrics. These metrics were computed at class level. In our study we present empirical results considering systems developed with Agile methodologies and we compare them with previous results for non Agile systems. In particular, we verify that the distributions of software metrics in a software system developed using Agile methodologies does not differ from the distribution in systems developed using plan-driven methodologies.

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 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

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Ant: http://ant.apache.org

  2. Blender: http://www.blender.org/

  3. Weka: http://www.cs.waikato.ac.nz/ml/weka/

  4. Floss-AR: http://www.flosslab.it/node/20

  5. JAPS: Java agile portal system, http://www.japsportal.org

  6. OpenBravo: http://www.openbravo.com

  7. OpenERP: https://www.openerp.com

  8. Zope: http://www.zope.org

  9. Adams, P.J., Capiluppi, A.: Bridging the gap between agile and free software approaches: The impact of sprinting. In: Multi-Disciplinary Advancement in Open Source Software and Processes, p. 54 (2011)

    Google Scholar 

  10. Adams, P.J., Capiluppi, A., De Groot, A.: Detecting agility of open source projects through developer engagement. In: Open Source Development, Communities and Quality, pp. 333–341. Springer US (2008)

    Google Scholar 

  11. Chidamber, S.R., Kemerer, C.F.: A metrics suite for object oriented design. IEEE Transactions on Software Engineering 20(6), 476–493 (1994)

    Article  Google Scholar 

  12. Chidamber, S.R., Darcy, D., Kemerer, C.F.: Managerial Use of Metrics for Object-Oriented Software: An Exploratory Analysis. IEEE Transactions on Software Engineering 24(8), 629–639 (1998)

    Article  Google Scholar 

  13. Basili, V.R., Briand, L., Melo, W.: A Validation of Object-Oriented Design Metrics as Quality Indicators. IEEE Transactions on Software Engineering 22(10), 751–761 (1996)

    Article  Google Scholar 

  14. Subramanyam, R., Krishnan, M.S.: Empirical Analysis of CK Metrics for Object-Oriented Design Complexity: Implications for Software Defects. IEEE Transactions on Software Engineering 29(4), 297–310 (2003)

    Article  Google Scholar 

  15. Concas, G., Marchesi, M., Murgia, A., Pinna, S., Tonelli, R.: Assessing traditional and new metrics for object-oriented systems. In: Proceedings of the 2010 ICSE Workshop on Emerging Trends in Software Metrics, pp. 24–31. ACM (2010)

    Google Scholar 

  16. Concas, G., Marchesi, M., Pinna, S., Serra, N.: Power-laws in a large object-oriented software system. IEEE Transactions on Software Engineering 33(10), 687–708 (2007)

    Article  Google Scholar 

  17. Brito e Abreu: The MOOD Metrics Set. In: Proc. ECOOP 1995 Workshop on Metrics (1995)

    Google Scholar 

  18. Lorenz, M., Kidd, J.: Object-oriented software metrics: a practical guide. Prentice-Hall, Inc., Upper Saddle River (1994)

    Google Scholar 

  19. Agile Manifesto, http://www.agilemanifesto.org

  20. Mohammad, A., Li, W.: An empirical study of system design instability metric and design evolution in an agile software process. Journal of Systems and Software 74(3), 269–274 (2005)

    Article  Google Scholar 

  21. Alshayeb, M., Li, W.: An empirical validation of object-oriented metrics in two different iterative software processes. IEEE Transactions on Software Engineering 29(11), 1043–1049 (2003)

    Article  Google Scholar 

  22. Olague, H.M., et al.: Empirical validation of three software metrics suites to predict fault-proneness of object-oriented classes developed using highly iterative or agile software development processes. IEEE Transactions on Software Engineering 33(6), 402–419 (2007)

    Article  Google Scholar 

  23. Zhang, H.: An investigation of the relationships between lines of code and defects. In: IEEE International Conference on Software Maintenance, ICSM 2009. IEEE (2009)

    Google Scholar 

  24. Dorairaj, S., Noble, J., Malik, P.: Understanding Team Dynamics in Distributed Agile Software Development. In: Wohlin, C. (ed.) XP 2012. LNBIP, vol. 111, pp. 47–61. Springer, Heidelberg (2012)

    Chapter  Google Scholar 

  25. Bachmann, A., Bernstein, A.: Software process data quality and characteristics: a historical view on open and closed source projects. In: IWPSE-Evol 2009 Proceedings of the Joint International and Annual ERCIM Workshops on Principles of Software Evolution (IWPSE) and Software Evolution (Evol) Workshops. ACM (2009)

    Google Scholar 

  26. Dybå, T., Dingsyr, T.: Empirical studies of agile software development: A systematic review. Information and Software Technology 50(9), 833–859 (2008)

    Article  Google Scholar 

  27. Concas, G., Marchesi, M., Destefanis, G., Tonelli, R.: An empirical study of software metrics for assessing the phases of an agile project. International Journal of Software Engineering and Knowledge Engineering 22, 525–548 (2012)

    Article  Google Scholar 

  28. Tasharofi, S., Ramsin, R.: Process Patterns for Agile Methodologies. In: Ralyté, J., Brinkkemper, S., Henderson-Sellers, B. (eds.) Proceeding of: Situational Method Engineering: Fundamentals and Experiences, Geneva, Switzerland, September 12-14. IFIP – The International Federation for Information Processing, vol. 244, pp. 222–237. Springer, Bostan (2007)

    Chapter  Google Scholar 

  29. Martin, R.: Agile Software Development: Principles, Patterns, and Practices. Prentice Hall PTR, Upper Saddle River (2003)

    Google Scholar 

  30. Hoda, R., Noble, J., Marshall, S.: How much is just enough?: some documentation patterns on Agile projects. In: Proceedings of the 15th European Conference on Pattern Languages of Programs (EuroPLoP 2010), Article 13, 13 pages. ACM, New York (2010)

    Google Scholar 

  31. Martinez, J., Diaz, J., Perez, J., Garbajosa, J.: Software Product Line Engineering Approach for Enhancing Agile Methodologies. In: Abrahamsson, P., Marchesi, M., Maurer, F. (eds.) XP 2009. LNBIP, vol. 31, pp. 247–248. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  32. Olague, H.M., et al.: An empirical validation of objectoriented class complexity metrics and their ability to predict errorprone classes in highly iterative, or agile, software: a case study. Journal of Software Maintenance and Evolution: Research and Practice 20(3), 171–197 (2008)

    Article  Google Scholar 

  33. Hartmann, D., Dymond, R.: Appropriate agile measurement: Using metrics and diagnostics to deliver business value. In: Agile Conference 2006. IEEE (2006)

    Google Scholar 

  34. Frank, M., Martel, S.: On the productivity of agile software practices: An industrial case study (2002) (retrieved september 20, 2004)

    Google Scholar 

  35. Concas, G., Destefanis, G., Marchesi, M., Ortu, M., Tonelli, R.: Micro Patterns in Agile Software. In: Baumeister, H., Weber, B. (eds.) XP 2013. LNBIP, vol. 149, pp. 210–222. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

  36. Olague, Hector, M., et al.: An empirical validation of objectoriented class complexity metrics and their ability to predict errorprone classes in highly iterative, or agile, software: a case study. Journal of Software Maintenance and Evolution: Research and Practice 20(3), 171–197 (2008)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this paper

Cite this paper

Destefanis, G., Counsell, S., Concas, G., Tonelli, R. (2014). Software Metrics in Agile Software: An Empirical Study. In: Cantone, G., Marchesi, M. (eds) Agile Processes in Software Engineering and Extreme Programming. XP 2014. Lecture Notes in Business Information Processing, vol 179. Springer, Cham. https://doi.org/10.1007/978-3-319-06862-6_11

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-06862-6_11

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-06861-9

  • Online ISBN: 978-3-319-06862-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics