Threats on building models from CVS and Bugzilla repositories: the Mozilla case study

ABSTRACT

Information obtained by merging data extracted from problem reporting systems - such as Bugzilla - and versioning systems - such as Concurrent Version System (CVS) - is widely used in quality assessment approaches.

This paper attempts to shed some light on threats and difficulties faced when trying to integrate information extracted from Mozilla CVS and bug repositories. Indeed, the heterogeneity of Mozilla bug reports, often dealing with non-defect issues, and lacking of traceable information may undermine validity of quality assessment approaches relying on repositories integration.

In the reported Mozilla case study, we observed that available integration heuristics are unable to recover thousands of traceability links. Furthermore, Bugzilla classification mechanisms do not enforce a distinction between different kinds of maintenance activities.

Obtained evidence suggests that a large amount of information is lost; we conjecture that to benefit from CVS and problem reporting systems, more systematic issue classification and more reliable traceability mechanisms are needed.

REFERENCES

• 1: Gerardo Canfora , Luigi Cerulo , Massimiliano Di Penta, On the Use of Line Co-change for Identifying Crosscutting Concern Code, Proceedings of the 22nd IEEE International Conference on Software Maintenance, p.213-222, September 24-27, 2006 [doi>10.1109/ICSM.2006.43]
• 2: Michael Fischer , Harald Gall, Visualizing feature evolution of large-scale software based on problem and modification report data: Research Articles, Journal of Software Maintenance and Evolution: Research and Practice, v.16 n.6, p.385-403, November 2004 [doi>10.1002/smr.v16:6]
• 3: Michael Fischer , Martin Pinzger , Harald Gall, Populating a Release History Database from Version Control and Bug Tracking Systems, Proceedings of the International Conference on Software Maintenance, p.23, September 22-26, 2003
• 4: William B. Frakes , Ricardo Baeza-Yates, Information retrieval: data structures and algorithms, Prentice-Hall, Inc., Upper Saddle River, NJ, 1992
• 5: Harald Gall , Karin Hajek , Mehdi Jazayeri, Detection of Logical Coupling Based on Product Release History, Proceedings of the International Conference on Software Maintenance, p.190, March 16-19, 1998
• 6: Harald Gall , Mehdi Jazayeri , René Klösch , Georg Trausmuth, Software Evolution Observations Based on Product Release History, Proceedings of the International Conference on Software Maintenance, p.160, October 01-03, 1997
• 7: Harald Gall , Mehdi Jazayeri , Jacek Krajewski, CVS Release History Data for Detecting Logical Couplings, Proceedings of the 6th International Workshop on Principles of Software Evolution, p.13, September 01-02, 2003
• 8: Reto Geiger, Beat Fluri, Harald Gall, and Martin Pinzger. Relation of code clones and change couplings. In Fundamental Approaches to Software Engineering, 9th International Conference, FASE 2006, Vienna, Austria, March 27--28, 2006, pages 411--425, 2006.
• 9: Daniel M. German, An empirical study of fine-grained software modifications, Empirical Software Engineering, v.11 n.3, p.369-393, September 2006 [doi>10.1007/s10664-006-9004-6]
• 10: Tibor Gyimothy , Rudolf Ferenc , Istvan Siket, Empirical Validation of Object-Oriented Metrics on Open Source Software for Fault Prediction, IEEE Transactions on Software Engineering, v.31 n.10, p.897-910, October 2005 [doi>10.1109/TSE.2005.112]
• 11: Jacek Śliwerski , Thomas Zimmermann , Andreas Zeller, When do changes induce fixes?, Proceedings of the 2005 international workshop on Mining software repositories, p.1-5, May 17-17, 2005, St. Louis, Missouri
• 12: Peter Weißgerber , Stephan Diehl, Are refactorings less error-prone than other changes?, Proceedings of the 2006 international workshop on Mining software repositories, May 22-23, 2006, Shanghai, China [doi>10.1145/1137983.1138011]
• 13: Annie T. T. Ying , Gail C. Murphy , Raymond Ng , Mark C. Chu-Carroll, Predicting Source Code Changes by Mining Change History, IEEE Transactions on Software Engineering, v.30 n.9, p.574-586, September 2004 [doi>10.1109/TSE.2004.52]
• 14: Thomas Zimmermann , Peter Weisgerber , Stephan Diehl , Andreas Zeller, Mining Version Histories to Guide Software Changes, Proceedings of the 26th International Conference on Software Engineering, p.563-572, May 23-28, 2004

INDEX TERMS

Keywords:
bug report and CVS mining, empirical study, evolution modeling, quality modeling, traceability recovery