Information-flow and data-flow analysis of while-programs
ACM Transactions on Programming Languages and Systems (TOPLAS)
Selecting Software Test Data Using Data Flow Information
IEEE Transactions on Software Engineering
Object-oriented metrics that predict maintainability
Journal of Systems and Software - Special issue on object-oriented software
Understanding “why” in software process modelling, analysis, and design
ICSE '94 Proceedings of the 16th international conference on Software engineering
A Metrics Suite for Object Oriented Design
IEEE Transactions on Software Engineering
The Journal of Machine Learning Research
Mining Version Histories to Guide Software Changes
IEEE Transactions on Software Engineering
MSR '05 Proceedings of the 2005 international workshop on Mining software repositories
Mining metrics to predict component failures
Proceedings of the 28th international conference on Software engineering
Unsupervised prediction of citation influences
Proceedings of the 24th international conference on Machine learning
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
Software Structure Metrics Based on Information Flow
IEEE Transactions on Software Engineering
Predicting defects using network analysis on dependency graphs
Proceedings of the 30th international conference on Software engineering
Can developer-module networks predict failures?
Proceedings of the 16th ACM SIGSOFT International Symposium on Foundations of software engineering
Validation of network measures as indicators of defective modules in software systems
PROMISE '09 Proceedings of the 5th International Conference on Predictor Models in Software Engineering
Predicting build failures using social network analysis on developer communication
ICSE '09 Proceedings of the 31st International Conference on Software Engineering
Does calling structure information improve the accuracy of fault prediction?
MSR '09 Proceedings of the 2009 6th IEEE International Working Conference on Mining Software Repositories
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
Putting it all together: using socio-technical networks to predict failures
ISSRE'09 Proceedings of the 20th IEEE international conference on software reliability engineering
Validating the Use of Topic Models for Software Evolution
SCAM '10 Proceedings of the 2010 10th IEEE Working Conference on Source Code Analysis and Manipulation
Estimating the Optimal Number of Latent Concepts in Source Code Analysis
SCAM '10 Proceedings of the 2010 10th IEEE Working Conference on Source Code Analysis and Manipulation
Using Relational Topic Models to capture coupling among classes in object-oriented software systems
ICSM '10 Proceedings of the 2010 IEEE International Conference on Software Maintenance
Software process recovery using Recovered Unified Process Views
ICSM '10 Proceedings of the 2010 IEEE International Conference on Software Maintenance
Studying the impact of dependency network measures on software quality
ICSM '10 Proceedings of the 2010 IEEE International Conference on Software Maintenance
Comparing fine-grained source code changes and code churn for bug prediction
Proceedings of the 8th Working Conference on Mining Software Repositories
Mining software repositories using topic models
Proceedings of the 33rd International Conference on Software Engineering
Proceedings of the 25th European conference on Object-oriented programming
Software Engineering Economics
IEEE Transactions on Software Engineering
| Hi-index | 0.00 |
The software dependency network reflects structure and the developer contribution network reflects process. Previous studies have used social network properties over these networks to predict whether a software component is defect-prone. However, these studies do not consider the strengths of the dependencies in the networks. In our approach, we use a citation influence topic model to determine dependency strengths among components and developers, analyze weak and strong dependencies separately, and apply social network properties to predict defect-prone components. In experiments on Eclipse and NetBeans, our approach has higher accuracy than prior work.