Predicting Fault Incidence Using Software Change History
IEEE Transactions on Software Engineering
Recovering Traceability Links between Code and Documentation
IEEE Transactions on Software Engineering
Recovering documentation-to-source-code traceability links using latent semantic indexing
Proceedings of the 25th International Conference on Software Engineering
Detection of Logical Coupling Based on Product Release History
ICSM '98 Proceedings of the International Conference on Software Maintenance
Populating a Release History Database from Version Control and Bug Tracking Systems
ICSM '03 Proceedings of the International Conference on Software Maintenance
Mining Version Histories to Guide Software Changes
Proceedings of the 26th International Conference on Software Engineering
Incremental Change in Object-Oriented Programming
IEEE Software
Predicting Source Code Changes by Mining Change History
IEEE Transactions on Software Engineering
Hipikat: A Project Memory for Software Development
IEEE Transactions on Software Engineering
Toward Understanding the Rhetoric of Small Source Code Changes
IEEE Transactions on Software Engineering
MSR '05 Proceedings of the 2005 international workshop on Mining software repositories
Impact Analysis by Mining Software and Change Request Repositories
METRICS '05 Proceedings of the 11th IEEE International Software Metrics Symposium
Empirical Validation of Object-Oriented Metrics on Open Source Software for Fault Prediction
IEEE Transactions on Software Engineering
Where is bug resolution knowledge stored?
Proceedings of the 2006 international workshop on Mining software repositories
An empirical study of fine-grained software modifications
Empirical Software Engineering
On the Use of Line Co-change for Identifying Crosscutting Concern Code
ICSM '06 Proceedings of the 22nd IEEE International Conference on Software Maintenance
IEEE Transactions on Software Engineering
Mining Software Repositories for Traceability Links
ICPC '07 Proceedings of the 15th IEEE International Conference on Program Comprehension
ACM Transactions on Software Engineering and Methodology (TOSEM)
Threats on building models from CVS and Bugzilla repositories: the Mozilla case study
CASCON '07 Proceedings of the 2007 conference of the center for advanced studies on Collaborative research
Journal of Software Maintenance and Evolution: Research and Practice
Do Crosscutting Concerns Cause Defects?
IEEE Transactions on Software Engineering
Is it a bug or an enhancement?: a text-based approach to classify change requests
CASCON '08 Proceedings of the 2008 conference of the center for advanced studies on collaborative research: meeting of minds
Fault detection and prediction in an open-source software project
PROMISE '09 Proceedings of the 5th International Conference on Predictor Models in Software Engineering
Discovering and representing systematic code changes
ICSE '09 Proceedings of the 31st International Conference on Software Engineering
Combining textual and structural analysis of software artifacts for traceability link recovery
TEFSE '09 Proceedings of the 2009 ICSE Workshop on Traceability in Emerging Forms of Software Engineering
Bug localization using latent Dirichlet allocation
Information and Software Technology
Improving Source Code Lexicon via Traceability and Information Retrieval
IEEE Transactions on Software Engineering
Multi-layered approach for recovering links between bug reports and fixes
Proceedings of the ACM SIGSOFT 20th International Symposium on the Foundations of Software Engineering
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Traceability links can be recovered using data mined from a revision control system, such as CVS, and an issue tracking system, such as Bugzilla. Existing approaches to recover links between a bug and the methods changed to fix the bug rely on the presence of the bug's identifier in a CVS log message. In this paper we present an approach that relies instead on the presence of a patch in the issue report for the bug. That is, rather than analyzing deltas retrieved from CVS to recover links, our approach analyzes patches retrieved from Bugzilla. We use BugTrace, the tool implementing our approach, to conduct a case study in which we compare the links recovered by our approach to links recovered by manual inspection. The results of the case study support the efficacy of our approach. After describing the limitations of our case study, we conclude by reviewing closely related work and suggesting possible future work.