Assessing the applicability of fault-proneness models across object-oriented software projects
IEEE Transactions on Software Engineering
An Empirical Study of Speed and Communication in Globally Distributed Software Development
IEEE Transactions on Software Engineering
Introduction to Machine Learning (Adaptive Computation and Machine Learning)
Introduction to Machine Learning (Adaptive Computation and Machine Learning)
Proceedings of the 28th international conference on Software engineering
How Long Will It Take to Fix This Bug?
MSR '07 Proceedings of the Fourth International Workshop on Mining Software Repositories
Determining Implementation Expertise from Bug Reports
MSR '07 Proceedings of the Fourth International Workshop on Mining Software Repositories
Using Developer Information as a Factor for Fault Prediction
PROMISE '07 Proceedings of the Third International Workshop on Predictor Models in Software Engineering
IEEE Transactions on Software Engineering
Predicting defects with program dependencies
ESEM '09 Proceedings of the 2009 3rd International Symposium on Empirical Software Engineering and Measurement
Characterizing and predicting which bugs get fixed: an empirical study of Microsoft Windows
Proceedings of the 32nd ACM/IEEE International Conference on Software Engineering - Volume 1
Predicting the fix time of bugs
Proceedings of the 2nd International Workshop on Recommendation Systems for Software Engineering
Studying the Impact of Social Structures on Software Quality
ICPC '10 Proceedings of the 2010 IEEE 18th International Conference on Program Comprehension
Usage of multiple prediction models based on defect categories
Proceedings of the 6th International Conference on Predictive Models in Software Engineering
Predicting Re-opened Bugs: A Case Study on the Eclipse Project
WCRE '10 Proceedings of the 2010 17th Working Conference on Reverse Engineering
"Not my bug!" and other reasons for software bug report reassignments
Proceedings of the ACM 2011 conference on Computer supported cooperative work
Proceedings of the 2nd International Workshop on Emerging Trends in Software Metrics
Security versus performance bugs: a case study on Firefox
Proceedings of the 8th Working Conference on Mining Software Repositories
Fuzzy set-based automatic bug triaging (NIER track)
Proceedings of the 33rd International Conference on Software Engineering
Reducing the effort of bug report triage: Recommenders for development-oriented decisions
ACM Transactions on Software Engineering and Methodology (TOSEM)
Characterizing and predicting which bugs get reopened
Proceedings of the 34th International Conference on Software Engineering
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Background: Reopened issues may cause problems in managing software maintenance effort. In order to take actions that will reduce the likelihood of issue reopening the possible causes of bug reopens should be analysed. Aims: In this paper, we investigate potential factors that may cause issue reopening. Method: We have extracted issue activity data from a large release of an enterprise software product. We consider four dimensions, namely developer activity, issue proximity network, static code metrics of the source code changed to fix an issue, issue reports and fixes as possible factors that may cause issue reopening. We have done exploratory analysis on data. We build logistic regression models on data in order to identify key factors leading issue reopening. We have also conducted a survey regarding these factors with the QA Team of the product and interpreted the results. Results: Our results indicate that centrality in the issue proximity network and developer activity are important factors in issue reopening. We have also interpreted our results with the QA Team to point out potential implications for practitioners. Conclusions: Quantitative findings of our study suggest that issue complexity and developers workload play an important role in triggering issue reopening.