Are Suggestions of Coupled File Changes Interesting?

Jasmin Ramadani, Stefan Wagner

Abstract

Software repositories include information which can be made available for bug fixing or maintenance using repository mining. The identification of coupled changes have been proposed several times. Yet, existing studies focus on the found couplings and ignore feedback from developers. We investigate three development projects and their repositories to find files that frequently change together to support the software developers. We complement the coupled files information with details from the issue tracking system and the project documentation. We contrast our findings with feedback from the developers about how interesting our findings are for them. We found that the small size of the repositories made an insightful analysis difficult. The response to coupled changes both from experienced and inexperienced developers was mostly neutral. They accepted most of the additional attributes we presented. Furthermore, developers also suggested other additional issues to be relevant, e.g. the context of the coupled changes and the way they are presented, which we did not cover in this study. Therefore, coupled change analysis research will need to take the presentation and context information into account.

References

  1. Agrawal, R. and Srikant, R. (1994). Fast algorithms for mining association rules in large databases. In Proceedings of the 20th International Conference on Very Large Data Bases, VLDB 7894, pages 487-499, San Francisco, CA, USA. Morgan Kaufmann Publishers Inc.
  2. Bavota, G., Dit, B., Oliveto, R., Di Penta, M., Poshyvanyk, D., and De Lucia, A. (2013). An empirical study on the developers; perception of software coupling. In Proceedings of the 2013 International Conference on Software Engineering, ICSE 7813, pages 692-701, Piscataway, NJ, USA. IEEE Press.
  3. Bieman, J., Andrews, A., and Yang, H. (2003). Understanding change-proneness in oo software through visualization. In Program Comprehension, 2003. 11th IEEE International Workshop on, pages 44-53.
  4. Bird, C., Rigby, P. C., Barr, E. T., Hamilton, D. J., Germán, D. M., and Devanbu, P. T. (2009). The promises and perils of mining git. In MSR, pages 1-10.
  5. Canfora, G. and Cerulo, L. (2005). Impact analysis by mining software and change request repositories. In Software Metrics, 2005. 11th IEEE International Symposium, pages 9 pp.-29.
  6. Carlsson, E. (2013). Mining git repositories : An introduction to repository mining.
  7. D'Ambros, M., Lanza, M., and Robbes, R. (2009). On the relationship between change coupling and software defects. In WCRE, pages 135-144.
  8. Fischer, M., Pinzger, M., and Gall, H. (2003). Populating a release history database from version control and bug tracking systems. In Proceedings of the International Conference on Software Maintenance, ICSM 7803, pages 23-, Washington, DC, USA. IEEE Computer Society.
  9. Fluri, B., Gall, H., and Pinzger, M. (2005). Fine-grained analysis of change couplings. In Source Code Analysis and Manipulation, 2005. Fifth IEEE International Workshop on, pages 66-74.
  10. Fournier-Viger, P. (2013). How to auto-adjust the minimum support threshold according to the data size. http://data-mining.philippe-fournier-viger.com/.
  11. Frawley, W. J., Piatetsky-shapiro, G., and Matheus, C. J. (1992). Knowledge discovery in databases: an overview.
  12. Gall, H., Jazayeri, M., and Krajewski, J. (2003). Cvs release history data for detecting logical couplings. In Software Evolution, 2003. Proceedings. Sixth International Workshop on Principles of, pages 13-23.
  13. German, D. M. (2004). Mining cvs repositories, the softchange experience. In 1st International Workshop on Mining Software Repositories, pages 17-21.
  14. Gyo?rödi, C. and Gyo?rödi, R. (2004). A comparative study of association rules mining algorithms.
  15. Han, J. (2005). Data Mining: Concepts and Techniques. Morgan Kaufmann Publishers Inc., San Francisco, CA, USA.
  16. Han, J., Pei, J., Yin, Y., and Mao, R. (2004). Mining frequent patterns without candidate generation: A frequent-pattern tree approach. Data Min. Knowl. Discov., 8(1):53-87.
  17. Hassan, A. E. and Holt, R. C. (2004). Predicting change propagation in software systems. In Proceedings of the 20th IEEE International Conference on Software Maintenance, ICSM 7804, pages 284-293, Washington, DC, USA. IEEE Computer Society.
  18. Hattori, L., dos Santos Jr, G., Cardoso, F., and Sampaio, M. (2008). Mining software repositories for software change impact analysis: A case study. In Proceedings of the 23rd Brazilian Symposium on Databases, SBBD 7808, pages 210-223, Porto Alegre, Brazil, Brazil. Sociedade Brasileira de Computação.
  19. Kagdi, H., Collard, M. L., and Maletic, J. I. (2007). A survey and taxonomy of approaches for mining software repositories in the context of software evolution. J. Softw. Maint. Evol., 19(2):77-131.
  20. Kagdi, H., Yusuf, S., and Maletic, J. I. (2006). Mining sequences of changed-files from version histories. In Proceedings of the 2006 International Workshop on Mining Software Repositories, MSR 7806, pages 47- 53, New York, NY, USA. ACM.
  21. Garry, K. (2005). A survey of interestingness measures for knowledge discovery. Knowl. Eng. Rev., 20(1):39- 61.
  22. Revelle, M., Gethers, M., and Poshyvanyk, D. (2011). Using structural and textual information to capture feature coupling in object-oriented software. Empirical Softw. Engg., 16(6):773-811.
  23. Runeson, P. and Höst, M. (2009). Guidelines for conducting and reporting case study research in software engineering. Empirical Softw. Engg., 14(2):131-164.
  24. Sayles, J. et al. (2011). z/OS Traditional Application Maintenance and Support. IBM Redbooks.
  25. Shirabad, J., Lethbridge, T., and Matwin, S. (2003). Mining the maintenance history of a legacy software system. In Software Maintenance, 2003. ICSM 2003. Proceedings. International Conference on, pages 95-104.
  26. Steven, J. and Zach, W. (2013). Bad commit smells. http://pages.cs.wisc.edu/ sjj/docs/commits.pdf.
  27. Stevens, W. P., Myers, G. J., and Constantine, L. L. (1974). Structured design. IBM Syst. J., 13(2):115-139.
  28. Strauss, A. and Corbin, J. M. (1998). Basics of Qualitative Research : Techniques and Procedures for Developing Grounded Theory. SAGE Publications.
  29. van Rysselberghe, F. and Demeyer, S. (2004). Mining Version Control Systems for FACs (frequently Applied changes). In the International Workshop on Mining Repositories, Edinburgh, Scotland, UK.
  30. Wu, R., Zhang, H., Kim, S., and Cheung, S.-C. (2011). Relink: Recovering links between bugs and changes. In Proceedings of the 19th ACM SIGSOFT Symposium and the 13th European Conference on Foundations of Software Engineering, ESEC/FSE 7811, pages 15-25, New York, NY, USA. ACM.
  31. Ying, A. T. T., Murphy, G. C., Ng, R. T., and Chu-Carroll, M. (2004). Predicting source code changes by mining change history. IEEE Transactions on Software Engineering, 30(9):574-586.
  32. Zimmermann, T., Kim, S., Zeller, A., and Whitehead, Jr., E. J. (2006). Mining version archives for co-changed lines. In Proceedings of the 2006 International Workshop on Mining Software Repositories, MSR 7806, pages 72-75, New York, NY, USA. ACM.
  33. Zimmermann, T., Weisgerber, P., Diehl, S., and Zeller, A. (2004). Mining version histories to guide software changes. In Proceedings of the 26th International Conference on Software Engineering, ICSE 7804, pages 563-572, Washington, DC, USA. IEEE Computer Society.
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Paper Citation


in Harvard Style

Ramadani J. and Wagner S. (2016). Are Suggestions of Coupled File Changes Interesting? . 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 15-26. DOI: 10.5220/0005854400150026


in Bibtex Style

@conference{enase16,
author={Jasmin Ramadani and Stefan Wagner},
title={Are Suggestions of Coupled File Changes Interesting?},
booktitle={Proceedings of the 11th International Conference on Evaluation of Novel Software Approaches to Software Engineering - Volume 1: ENASE,},
year={2016},
pages={15-26},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005854400150026},
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 - Are Suggestions of Coupled File Changes Interesting?
SN - 978-989-758-189-2
AU - Ramadani J.
AU - Wagner S.
PY - 2016
SP - 15
EP - 26
DO - 10.5220/0005854400150026