1. Analytics for
Software Development
Thomas Zimmermann
Microsoft Research
ICSM 2010, Timisoara
http://thomas-zimmermann.com
Twitter: @tomzimmermann
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2. Researcher
(since 2008)
Assistant
Professor
(2007-2008) Microsoft
Research
University
PhD of Calgary
Saarland
University
Mining Empirical
University Software Software
of Passau Repositories Engineering
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3. Mining
Software
Repositories
Software
Analytics
Empirical
Software
Engineering
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4. Mining
Software
Repositories
Software
Development
Analytics
Empirical
Software
Engineering
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5. Analytics
“Use of analysis, data,
and systematic reasoning
to make decisions”
Financial services
Retail
Manufacturing
Health care
Energy
And more…
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6. Analytics
Past Present Future
What What is What will
Information happened? happening now? happen?
(Reporting) (Alerts) (Extrapolation)
What’s the
How and why What’s the next
best/worst that
Insight did it happen? best action?
can happen?
(Modeling) (Recommendation)
(Prediction)
From Davenport et al. “Analytics at Work”.
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7. Web analytics
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8. Mining
Software
Repositories
Software
Development
Analytics
Empirical
Software
Engineering
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9. Understanding data is hard!
The peak at
A is correct! So
Why is the
peak at B? what?
B
Researcher A
Developer
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10. Each project is different!
Has to learn about
Knows how to analysis to understand
analyze data and act on results
Researcher Makes assumptions Knows project
about project very well Developer
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11. Software development analyst
Knows enough
about data analysis
Knows enough
about project to
make the right
assumptions
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12. Stakeholders have different needs
Researcher Developer Tester Dev Lead Test Lead Manager
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13. Stakeholders have different needs
Researcher Developer Tester Dev Lead Test Lead Manager
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14. A single tool is not enough
Surveys
Qualitative data
Measurements
Benchmarking
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15. Make data actionable and accessible
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16. #1: Data collection
Data focused
Integration
Scenario focused
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17. #2: Data quality
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18. #3: Privacy
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19. #4: Understand user needs
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20. #4: Understand user needs
Developers: well studied
(ICSM: 26 papers)
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21. #4: Understand user needs
Managers: not many studies
(ICSM: 7 papers)
Developers: well studied
(ICSM: 26 papers)
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22. #4: Understand user needs
Managers: not many studies
(ICSM: 7 papers)
Communication: not many studies
(ICSM: 5 papers)
Developers: well studied
(ICSM: 26 papers)
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23. #5: User experience
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24. Make data actionable and accessible
Data collection
Data quality Privacy
Education
Understand
user needs
User experience
http://msrconf.org
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