Advertisement

Software Quality Journal

, Volume 23, Issue 4, pp 539–566 | Cite as

Handover of managerial responsibilities in global software development: a case study of source code evolution and quality

  • Ronald Jabangwe
  • Jürgen Börstler
  • Kai PetersenEmail author
Article

Abstract

Studies report on the negative effect on quality in global software development (GSD) due to communication and coordination-related challenges. However, empirical studies reporting on the magnitude of the effect are scarce. This paper presents findings from an embedded explanatory case study on the change in quality over time, across multiple releases, for products that were developed in a GSD setting. The GSD setting involved periods of distributed development between geographically dispersed sites as well as a handover of project management responsibilities between the involved sites. Investigations were performed on two medium-sized products from a company that is part of a large multinational corporation. Quality is investigated quantitatively using defect data and measures that quantify two source code properties, size and complexity. Observations were triangulated with subjective views from company representatives. There were no observable indications that the distribution of work or handover of project management responsibilities had an impact on quality on both products. Among the product-, process- and people-related success factors, we identified well-designed product architectures, early handover planning and support from the sending site to the receiving site after the handover and skilled employees at the involved sites. Overall, these results can be useful input for decision-makers who are considering distributing development work between globally dispersed sites or handing over project management responsibilities from one site to another. Moreover, our study shows that analyzing the evolution of size and complexity properties of a product’s source code can provide valuable information to support decision-making during similar projects. Finally, the strategy used by the company to relocate responsibilities can also be considered as an alternative for software transfers, which have been linked with a decline in efficiency, productivity and quality.

Keywords

Global software development Distributed development  Source code analysis Software transfers Object-oriented measures Case study 

Notes

Acknowledgments

This work was funded by the Swedish Knowledge Foundation under the research grant 2009/0249. We thank Professor Claes Wohlin and Dr. Darja Šmite, at Software Engineering Research Lab (SERL), for their valuable comments on the paper.

References

  1. Aspray, W., Mayadas, F., & Vardi, M. Y. (2006). Globalization and offshoring of software: A report of the ACM job migration task force. New York, USA.Google Scholar
  2. Bansiya, J., & Davis, C. G. (2002). A hierarchical model for object-oriented design quality assessment. IEEE Transactions on Software Engineering, 28(1), 4–17.CrossRefGoogle Scholar
  3. Basili, V. R., Briand, L. C., & Melo, W. L. (1996). A validation of object-oriented design metrics as quality indicators. IEEE Transactions on Software Engineering, 22(10), 751–761.CrossRefGoogle Scholar
  4. Bird, C., Nagappan, N., Devanbu, P., Gall, H., & Murphy, B. (2009). Does distributed development affect software quality? An empirical case study of Windows Vista. In Proceedings of the 31st international conference on software engineering, pp. 85–93.Google Scholar
  5. Briand, L., & Wüst, J. (2002). Empirical studies of quality models in object-oriented systems. Advances in computers, pp. 97–166.Google Scholar
  6. Brooks, F. P, Jr. (1995). The mythical man-month (anniversary ed.). Boston, USA: Addison-Wesley Longman Publishing.Google Scholar
  7. Cagnazzo, L., & Taticchi, P. (2009). Six sigma: A literature review analysis. In Proceedings of the international conference on e-activities and information security and privacy, pp. 29–34.Google Scholar
  8. Carmel, E. (1999). Global software teams: Collaborating across borders and time zones. New Jersey, USA: Prentice Hall PTR.Google Scholar
  9. Carmel, E., & Tjia, P. (2005). Offshoring information technology: Sourcing and outsourcing to a global workforce. Cambridge, UK: Cambridge University Press.CrossRefGoogle Scholar
  10. Conchúir, E. O., Holmström, H., Ågerfalk, P. J., & Fitzgerald, B. (2006). Exploring the assumed benefits of global software development. In Proceedings of the 1st international conference on global software engineering, pp. 159–168.Google Scholar
  11. Diehl, S. (2007). Software visualization—Visualizing the structure, behaviour, and evolution of software. Berlin: Springer.zbMATHGoogle Scholar
  12. Griffith, T. L., & Sawyer, J. E. (2006). Supporting technologies and organizational practices for the transfer of knowledge in virtual environments. Group Decision and Negotiation, 15, 407–423.CrossRefGoogle Scholar
  13. Herbsleb, J. D., & Grinter, R. E. (1999). Splitting the organization and integrating the code: Conway’s law revisited. In Proceedings of the 21st international conference on software engineering, pp. 85–95.Google Scholar
  14. Herraiz, I., & Hassan, A. E. (2012). Making software—What really works, and why we believe it, chapter Beyond lines of code: Do we need more complexity metrics? pp. 125–141. O’Reilly Media.Google Scholar
  15. Huckman, R. S., Staats, B. R., & Upton, D. M. (2009). Team familiarity, role experience, and performance: Evidence from Indian software services. Management Science, 55(1), 85–100.CrossRefGoogle Scholar
  16. ISO/IEC/IEEE-24765. (2010). Systems and software engineering—Vocabulary. International organization for standardization.Google Scholar
  17. Jabangwe, R., Börstler, J., Šmite, D., & Wohlin, C. (2013). Empirical evidence on the link between object-oriented measures and external quality attributes: A systematic literature review. Accepted for publication at Empirical software engineering.Google Scholar
  18. Jabangwe, R., & Šmite, D. (2012). An exploratory study of software evolution and quality: Before, during and after a transfer. In Proceedings of the 7th IEEE international conference on global software engineering, pp. 41–50.Google Scholar
  19. Kanellopoulos, Y., Antonellis, P., Antoniou, D., Makris, C., Theodoridis, E., Tjortjis, C., et al. (2010). Code quality evaluation methodology using the ISO/IEC 9126 standard. International Journal of Software Engineering and Applications, 1(3), 17–36.CrossRefGoogle Scholar
  20. Lagerström, R., Würtemberg, L. M., Holm, H., & Luczak, O. (2012). Identifying factors affecting software development cost and productivity. Software Quality Control, 20(2), 395–417.CrossRefGoogle Scholar
  21. Lehman, M. M. (1980). Programs, life cycles, and laws of software evolution. Proceedings of the IEEE, 68, 1060–1076.CrossRefGoogle Scholar
  22. Lincke, R. d., Lundberg, J., & Löwe, W. (2008). Comparing software metrics tools. In Proceedings of the international symposium on software testing and analysis, pp. 131–142.Google Scholar
  23. Lu, H., Zhou, Y., Xu, B., Leung, H., & Chen, L. (2012). The ability of object-oriented metrics to predict change-proneness: A meta-analysis. Empirical Software Engineering, 17, 200–242.CrossRefGoogle Scholar
  24. Mens, T., & Demeyer, S. (2008). Software evolution. Berlin: Springer.zbMATHCrossRefGoogle Scholar
  25. Mockus, A., & Weiss, D. M. (2001). Globalization by chunking: A quantitative approach. IEEE Software, 18, 30–37.CrossRefGoogle Scholar
  26. Nagappan, N., Murphy, B., & Basili, V. (2008). The influence of organizational structure on software quality: An empirical case study. In Proceedings of the 30th international conference on software engineering, pp. 521–530.Google Scholar
  27. Nidhra, S., Yanamadala, M., Afzal, W., & Torkar, R. (2013). Knowledge transfer challenges and mitigation strategies in global software development—A systematic literature review and industrial validation. International Journal of Information Management, 33(2), 333–355.CrossRefGoogle Scholar
  28. Nurdiani, I., Jabangwe, R., Šmite, D., & Damian, D. (2011). Risk identification and risk mitigation instruments for global software development: Systematic review and survey results. In Proceedings of the 6th international conference on global software engineering workshop, pp. 36–41.Google Scholar
  29. Petersen, K., & Gencel, C. (2013). Worldviews, research methods, and their relationship to validity in empirical software engineering research. In Joint conference of the 23rd international workshop on software measurement and international conference on software process and product measurement, pp. 81–89.Google Scholar
  30. Petersen, K., & Wohlin, C. (2009). Context in industrial software engineering research. In Proceedings of the 3rd international symposium on empirical software engineering and measurement, pp. 401–404.Google Scholar
  31. Petersen, K., & Wohlin, C. (2010). Software process improvement through the lean measurement (SPI-LEAM) method. Journal of Systems and Software, 83(7), 1275–1287.CrossRefGoogle Scholar
  32. Ramasubbu, N., & Balan, R. K. (2007). Globally distributed software development project performance: An empirical analysis. In European software engineering conference and the ACM SIGSOFT symposium on the foundations of software engineering, pp. 125–134.Google Scholar
  33. Robson, C. (2011). Real world research (2nd ed.). West Sussex, UK: Wiley.Google Scholar
  34. Runeson, P., Höst, M., Rainer, A., & Regnell, B. (2012). Case study research in software engineering. New Jersey, USA: Wiley.CrossRefGoogle Scholar
  35. Singh, Y., Kaur, A., & Malhotra, R. (2009). Comparative analysis of regression and machine learning methods for predicting fault proneness models. International Journal of Computer Applications in Technology, 35(2), 183–193.CrossRefGoogle Scholar
  36. Singh, Y., Kaur, A., & Malhotra, R. (2010). Empirical validation of object-oriented metrics for predicting fault proneness models. Software Quality Journal, 18(1), 3–35.CrossRefGoogle Scholar
  37. Spinellis, D. (2006). Global software development in the freeBSD project. In P. Kruchten, Y. Hsieh, E. MacGregor, D. Moitra, & W. Strigel (Eds.), Proceedings of the international workshop on global software development for the practitioner, pp. 73–79.Google Scholar
  38. Verner, J., Brereton, O., Kitchenham, B., Turner, M., & Niazi, M. (2012). Systematic literature reviews in global software development: A tertiary study. In Proceedings of the 16th international conference on evaluation assessment in software engineering, pp. 2–11.Google Scholar
  39. Šmite, D., & Wohlin, C. (2011). Strategies facilitating software product transfers. IEEE Software, 28(5), 60–66.CrossRefGoogle Scholar
  40. Šmite, D., & Wohlin, C. (2012). Lessons learned from transferring software products to india. Journal of Software: Evolution and Process, 24(6), 605–623.Google Scholar
  41. Šmite, D., Wohlin, C., Aurum, A., Jabangwe, R., & Numminen, E. (2013). Offshore insourcing in software development: Structuring the decision-making process. Journal of Systems and Software, 86(4), 1054–1067.CrossRefGoogle Scholar
  42. Šmite, D., Wohlin, C., Feldt, R., & Gorschek, T. (2008). Reporting empirical research in global software engineering: A classification scheme. In Proceedings of the 3rd international conference on global software engineering, pp. 173–181.Google Scholar
  43. Šmite, D., Wohlin, C., Gorschek, T., & Feldt, R. (2010). Empirical evidence in global software engineering: A systematic review. Empirical Software Engineering, 15(1), 91–118.CrossRefGoogle Scholar
  44. Wieringa, R. (2013). Case study research in information systems engineering: How to generalize, how not to generalize, and how not to generalize too much. In 25th International conference on advanced information systems engineering, CAiSE, pp. xii–xii.Google Scholar
  45. Wohlin, C., Runeson, P., Höst, M., Ohlsson, M. C., Regnell, B., & Wesslén, A. (2012). Experimentation in software engineering: An introduction. Berlin: Springer.CrossRefGoogle Scholar
  46. Wohlin, C., & Šmite, D. (2012). Classification of software transfers. In Proceedings of the 19th Asia-Pacific software engineering conference, Vol. 1, pp. 828–837.Google Scholar

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Ronald Jabangwe
    • 1
  • Jürgen Börstler
    • 1
  • Kai Petersen
    • 1
    Email author
  1. 1.Blekinge Institute of TechnologyKarlskronaSweden

Personalised recommendations