Co-change Clusters: Extraction and Application on Assessing Software Modularity
At the seminar we will discuss a paper that proposes the co-change clustering method to detect artifacts that undergo frequent changes.
Using that approach, authors perform a large-scale research of to detect incorrect module structure in popular open source projects.
Speaker: Dmitry Kravchenko.
Presentation language: Russian.
Date and time: April 10th, 8:00-9:30 pm.
Location: Times, room 204.
Videos from previous seminars are available at http://bit.ly/MLJBSeminars
- About seminars
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15 May 2019Who Should Make Decision on this Pull Request? Analyzing Time-Decaying Relationships and File Similarities for Integrator Prediction
8 May 2019Maybe Deep Neural Networks are the Best Choice for Modeling Source Code
24 April 2019Siamese: scalable and incremental code clone search via multiple code representations
17 April 2019An Approach and Benchmark to Detect Behavioral Changes of Commits in Continuous Integration