The Journal of Machine Learning Research
Discovering evolutionary theme patterns from text: an exploration of temporal text mining
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Mining Eclipse Developer Contributions via Author-Topic Models
MSR '07 Proceedings of the Fourth International Workshop on Mining Software Repositories
Mining business topics in source code using latent dirichlet allocation
ISEC '08 Proceedings of the 1st India software engineering conference
Visual Exploration of Large-Scale System Evolution
WCRE '08 Proceedings of the 2008 15th Working Conference on Reverse 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
Macro-level software evolution: a case study of a large software compilation
Empirical Software Engineering
MSR '09 Proceedings of the 2009 6th IEEE International Working Conference on Mining Software Repositories
Explicit Concern-Driven Development with ArchEvol
ASE '09 Proceedings of the 2009 IEEE/ACM International Conference on Automated Software Engineering
Bug localization using latent Dirichlet allocation
Information and Software Technology
Modeling the evolution of topics in source code histories
Proceedings of the 8th Working Conference on Mining Software Repositories
The onion patch: migration in open source ecosystems
Proceedings of the 19th ACM SIGSOFT symposium and the 13th European conference on Foundations of software engineering
IEEE Software
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The development of a software system is now ever more frequently a part of a larger development effort, including multiple software systems that co-exist in the same environment: a software ecosystem. Though most studies of the evolution of software have focused on a single software system, there is much that we can learn from the analysis of a set of interrelated systems. Topic modeling techniques show promise for mining the data stored in software repositories to understand the evolution of a system. In my research I seek to explore how topic modeling techniques can aid in understanding the evolution of a software ecosystem. The results of this research have the potential to improve how topic modeling techniques are used to predict, plan, and understand the evolution of software, and will inform the design of tools that support software engineering activities such as feature location, expertise identification, and bug detection.