Introduction to Algorithms
Mining Process Models from Workflow Logs
EDBT '98 Proceedings of the 6th International Conference on Extending Database Technology: Advances in Database Technology
Workflow Mining: Discovering Process Models from Event Logs
IEEE Transactions on Knowledge and Data Engineering
Introduction to Machine Learning (Adaptive Computation and Machine Learning)
Introduction to Machine Learning (Adaptive Computation and Machine Learning)
Why Programs Fail: A Guide to Systematic Debugging
Why Programs Fail: A Guide to Systematic Debugging
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Inference in Hidden Markov Models (Springer Series in Statistics)
Inference in Hidden Markov Models (Springer Series in Statistics)
Proceedings of the 28th international conference on Software engineering
Proceedings of the 2006 international workshop on Mining software repositories
Supporting change request assignment in open source development
Proceedings of the 2006 ACM symposium on Applied computing
Designing task visualizations to support the coordination of work in software development
CSCW '06 Proceedings of the 2006 20th anniversary conference on Computer supported cooperative work
Detection of Duplicate Defect Reports Using Natural Language Processing
ICSE '07 Proceedings of the 29th 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
MSR '07 Proceedings of the Fourth International Workshop on Mining Software Repositories
Detecting Patch Submission and Acceptance in OSS Projects
MSR '07 Proceedings of the Fourth International Workshop on Mining Software Repositories
Predicting Eclipse Bug Lifetimes
MSR '07 Proceedings of the Fourth International Workshop on Mining Software Repositories
Proceedings of the twenty-second IEEE/ACM international conference on Automated software engineering
An approach to detecting duplicate bug reports using natural language and execution information
Proceedings of the 30th international conference on Software engineering
Efficient ticket routing by resolution sequence mining
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Pervasive QoS routing in next generation networks
Computer Communications
Can developer-module networks predict failures?
Proceedings of the 16th ACM SIGSOFT International Symposium on Foundations of software engineering
Latent social structure in open source projects
Proceedings of the 16th ACM SIGSOFT International Symposium on Foundations of software engineering
Proceedings of the 16th ACM SIGSOFT International Symposium on Foundations of software engineering
A social network based study of software team dynamics
Proceedings of the 3rd India software engineering conference
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
Evolution of developer collaboration on the jazz platform: a study of a large scale agile project
Proceedings of the 4th India Software Engineering Conference
Empirical software engineering at Microsoft Research
Proceedings of the ACM 2011 conference on Computer supported cooperative work
"Not my bug!" and other reasons for software bug report reassignments
Proceedings of the ACM 2011 conference on Computer supported cooperative work
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
Selecting discriminating terms for bug assignment: a formal analysis
Proceedings of the 7th International Conference on Predictive Models in Software Engineering
Fuzzy set and cache-based approach for bug triaging
Proceedings of the 19th ACM SIGSOFT symposium and the 13th European conference on Foundations of software engineering
Inferring specifications for resources from natural language API documentation
Automated Software Engineering
An adaptive approach to impact analysis from change requests to source code
ASE '11 Proceedings of the 2011 26th IEEE/ACM International Conference on Automated Software Engineering
Developer prioritization in bug repositories
Proceedings of the 34th International Conference on Software Engineering
WhoseFault: automatic developer-to-fault assignment through fault localization
Proceedings of the 34th International Conference on Software Engineering
Integrated impact analysis for managing software changes
Proceedings of the 34th International Conference on Software Engineering
Characterizing and predicting which bugs get reopened
Proceedings of the 34th International Conference on Software Engineering
Inferring developer expertise through defect analysis
Proceedings of the 34th International Conference on Software Engineering
Learning to classify bug reports into components
TOOLS'12 Proceedings of the 50th international conference on Objects, Models, Components, Patterns
Predicting defect numbers based on defect state transition models
Proceedings of the ACM-IEEE international symposium on Empirical software engineering and measurement
Recommender systems for manual testing: deciding how to assign tests in a test team
Proceedings of the ACM-IEEE international symposium on Empirical software engineering and measurement
The bug report duplication problem: an exploratory study
Software Quality Control
Studying the impact of social interactions on software quality
Empirical Software Engineering
Samiksha: mining issue tracking system for contribution and performance assessment
Proceedings of the 6th India Software Engineering Conference
Towards understanding software change request assignment: a survey with practitioners
Proceedings of the 17th International Conference on Evaluation and Assessment in Software Engineering
A hybrid bug triage algorithm for developer recommendation
Proceedings of the 28th Annual ACM Symposium on Applied Computing
PorchLight: a tag-based approach to bug triaging
Proceedings of the 2013 International Conference on Software Engineering
Proceedings of the 2013 International Conference on Software Engineering
Proceedings of the 10th Working Conference on Mining Software Repositories
Bug report assignee recommendation using activity profiles
Proceedings of the 10th Working Conference on Mining Software Repositories
Bug resolution catalysts: identifying essential non-committers from bug repositories
Proceedings of the 10th Working Conference on Mining Software Repositories
The eclipse and mozilla defect tracking dataset: a genuine dataset for mining bug information
Proceedings of the 10th Working Conference on Mining Software Repositories
What type of thread can get feedback in OSS user mailing list?
Proceedings of the 2013 International Workshop on Social Software Engineering
A new perspective on the socialness in bug triaging: a case study of the eclipse platform project
Proceedings of the 2013 International Workshop on Social Software Engineering
International Journal of Open Source Software and Processes
Topic-based, time-aware bug assignment
ACM SIGSOFT Software Engineering Notes
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bug report is typically assigned to a single developer who is then responsible for fixing the bug. In Mozilla and Eclipse, between 37%-44% of bug reports are "tossed" (reassigned) to other developers, for example because the bug has been assigned by accident or another developer with additional expertise is needed. In any case, tossing increases the time-to-correction for a bug. In this paper, we introduce a graph model based on Markov chains, which captures bug tossing history. This model has several desirable qualities. First, it reveals developer networks which can be used to discover team structures and to find suitable experts for a new task. Second, it helps to better assign developers to bug reports. In our experiments with 445,000 bug reports, our model reduced tossing events, by up to 72%. In addition, the model increased the prediction accuracy by up to 23 percentage points compared to traditional bug triaging approaches.