Security versus performance bugs: a case study on Firefox
Proceedings of the 8th Working Conference on Mining Software Repositories
Modeling the evolution of topics in source code histories
Proceedings of the 8th Working Conference on Mining Software Repositories
What topics do Firefox and Chrome contributors discuss?
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
DRETOM: developer recommendation based on topic models for bug resolution
Proceedings of the 8th International Conference on Predictive Models in Software Engineering
Proceedings of the 2013 International Conference on Software Engineering
Using citation influence to predict software defects
Proceedings of the 10th Working Conference on Mining Software Repositories
Improving software modularization via automated analysis of latent topics and dependencies
ACM Transactions on Software Engineering and Methodology (TOSEM)
Studying software evolution using topic models
Science of Computer Programming
Static test case prioritization using topic models
Empirical Software Engineering
How changes affect software entropy: an empirical study
Empirical Software Engineering
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Topics are collections of words that co-occur frequently in a text corpus. Topics have been found to be effective tools for describing the major themes spanning a corpus. Using such topics to describe the evolution of a software system’s source code promises to be extremely useful for development tasks such as maintenance and re-engineering. However, no one has yet examined whether these automatically discovered topics accurately describe the evolution of source code, and thus it is not clear whether topic models are a suitable tool for this task. In this paper, we take a first step towards deter-mining the suitability of topic models in the analysis of software evolution by performing a qualitative case study on 12 releases of JHot Draw, a well studied and documented system. We define and compute various metrics on the identified topics and manually investigate how the metrics evolve over time. We find that topic evolutions are characterizable through spikes and drops in their metric values, and that the large majority of these spikes and drops are indeed caused by actual change activity in the source code. We are thus encouraged by the use of topic models as a tool for analyzing the evolution of software.