This is the September 3 2019 AUG edition.
We have two presentations.
- Machine Learning at Ubisoft with Atlassian Data (2 use cases) Jira and Confluence
by Francois Nadeau Ubisoft
Description: In this presentation we will show how we used machine learning with Jira estimation data to predict if a team will ship the content of the sprint or not in a given time window (and what they can change in their sprints to ship it).
We will also show how we can use Deep Learning to read our internal confluence documentation and annotate them with relevant abstract topics.
- commit.guru: Using Analytics to and ML to Warn About Risky Commits
by Concordia University by Emad Shihab PhD, P.Eng
Description: Software development produces a plethora of data that can be leveraged and combined with ML methods to improve the development process. In this talk, I will present a proactive approach where risky changes, i.e., changes that may break or cause errors in the software system, are flagged so defects can be avoided before they are widely integrated into the code. I will also demo a tool that implements our approach and share a vision for the future of using analytics to automatically warn and eliminate risky software changes.
Bio: Emad Shihab is an Associate Professor and Concordia Research Chair in the Department of Computer Science and Software Engineering at Concordia University. Dr. Shihab’s research interests are in Software Quality Assurance, Mining Software Repositories, Technical Debt, and Software Predictive Analytics. More information can be found at http://das.encs.concordia.ca.
If you have questions or suggestions for the User group does not hesitate to contact your user group Leader or post into the community forum.
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