The Journal of Machine Learning Research
The Journal of Machine Learning Research
Fast collapsed gibbs sampling for latent dirichlet allocation
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Empirical Software Engineering
An Application of Latent Dirichlet Allocation to Analyzing Software Evolution
ICMLA '08 Proceedings of the 2008 Seventh International Conference on Machine Learning and Applications
Evaluation methods for topic models
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Using Latent Dirichlet Allocation for automatic categorization of software
MSR '09 Proceedings of the 2009 6th IEEE International Working Conference on Mining Software Repositories
Software traceability with topic modeling
Proceedings of the 32nd ACM/IEEE International Conference on Software Engineering - Volume 1
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
DRETOM: developer recommendation based on topic models for bug resolution
Proceedings of the 8th International Conference on Predictive Models in Software Engineering
Using citation influence to predict software defects
Proceedings of the 10th Working Conference on Mining Software Repositories
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Software repositories, such as source code, email archives, and bug databases, contain unstructured and unlabeled text that is difficult to analyze with traditional techniques. We propose the use of statistical topic models to automatically discover structure in these textual repositories. This discovered structure has the potential to be used in software engineering tasks, such as bug prediction and traceability link recovery. Our research goal is to address the challenges of applying topic models to software repositories.