A Validation of Object-Oriented Design Metrics as Quality Indicators
IEEE Transactions on Software Engineering
Predicting Fault-Prone Software Modules in Telephone Switches
IEEE Transactions on Software Engineering
A mathematical theory of communication
ACM SIGMOBILE Mobile Computing and Communications Review
Hipikat: recommending pertinent software development artifacts
Proceedings of the 25th International Conference on Software Engineering
ICSE '76 Proceedings of the 2nd international conference on Software engineering
Code Churn: A Measure for Estimating the Impact of Code Change
ICSM '98 Proceedings of the International Conference on Software Maintenance
Product metrics for object-oriented systems
ACM Computing Surveys (CSUR)
Analyzing and Relating Bug Report Data for Feature Tracking
WCRE '03 Proceedings of the 10th Working Conference on Reverse Engineering
Predictors of customer perceived software quality
Proceedings of the 27th international conference on Software engineering
Use of relative code churn measures to predict system defect density
Proceedings of the 27th international conference on Software engineering
MSR '05 Proceedings of the 2005 international workshop on Mining software repositories
Proceedings of the 28th international conference on Software engineering
Predicting component failures at design time
Proceedings of the 2006 ACM/IEEE international symposium on Empirical software engineering
Predicting Defects for Eclipse
PROMISE '07 Proceedings of the Third International Workshop on Predictor Models in Software Engineering
Using Software Dependencies and Churn Metrics to Predict Field Failures: An Empirical Case Study
ESEM '07 Proceedings of the First International Symposium on Empirical Software Engineering and Measurement
Predicting defects using network analysis on dependency graphs
Proceedings of the 30th international conference on Software engineering
Extracting structural information from bug reports
Proceedings of the 2008 international working conference on Mining software repositories
Can developer-module networks predict failures?
Proceedings of the 16th ACM SIGSOFT International Symposium on Foundations of software engineering
Predicting failures with developer networks and social network analysis
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
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
Predicting build failures using social network analysis on developer communication
ICSE '09 Proceedings of the 31st International Conference on Software Engineering
Predicting faults using the complexity of code changes
ICSE '09 Proceedings of the 31st International Conference on Software Engineering
Cross-project defect prediction: a large scale experiment on data vs. domain vs. process
Proceedings of the the 7th joint meeting of the European software engineering conference and the ACM SIGSOFT symposium on The foundations of software engineering
Improving bug triage with bug tossing graphs
Proceedings of the the 7th joint meeting of the European software engineering conference and the ACM SIGSOFT symposium on The foundations of software engineering
Fair and balanced?: bias in bug-fix datasets
Proceedings of the the 7th joint meeting of the European software engineering conference and the ACM SIGSOFT symposium on The foundations of software engineering
Models of Communication Dynamics for Simulation of Information Diffusion
ASONAM '09 Proceedings of the 2009 International Conference on Advances in Social Network Analysis and Mining
Test coverage and post-verification defects: A multiple case study
ESEM '09 Proceedings of the 2009 3rd International Symposium on Empirical Software Engineering and Measurement
Software Dependencies, Work Dependencies, and Their Impact on Failures
IEEE Transactions on Software Engineering
Why Programs Fail, Second Edition: A Guide to Systematic Debugging
Why Programs Fail, Second Edition: A Guide to Systematic Debugging
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
Proceedings of the 2010 ACM-IEEE International Symposium on Empirical Software Engineering and Measurement
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
Are popular classes more defect prone?
FASE'10 Proceedings of the 13th international conference on Fundamental Approaches to Software Engineering
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Correcting software defects accounts for a significant amount of resources in a software project. To make best use of testing efforts, researchers have studied statistical models to predict in which parts of a software system future defects are likely to occur. By studying the mathematical relations between predictor variables used in these models, researchers can form an increased understanding of the important connections between development activities and software quality. Predictor variables used in past top-performing models are largely based on source code-oriented metrics, such as lines of code or number of changes. However, source code is the end product of numerous interlaced and collaborative activities carried out by developers. Traces of such activities can be found in the various repositories used to manage development efforts. In this paper, we develop statistical models to study the impact of social interactions in a software project on software quality. These models use predictor variables based on social information mined from the issue tracking and version control repositories of two large open-source software projects. The results of our case studies demonstrate the impact of metrics from four different dimensions of social interaction on post-release defects. Our findings show that statistical models based on social information have a similar degree of explanatory power as traditional models. Furthermore, our results demonstrate that social information does not substitute, but rather augments traditional source code-based metrics used in defect prediction models.