Investigating developer retention in socio-technical software ecosystems

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Third Madrilenian Seminar on Empirical Software Engineering (MADSESE 2017)

Ciências

Investigating developer retention in
socio-technical software ecosystems
Eleni Constantinou
University of Mons 1

Software ecosystem health
Prof. Dr. Tom Mens
Software Engineering Lab
University of Mons
• Ecosystem evolution
• Ecosystem health
www.secohealth.org
2

Software ecosystem health
Sustainability
Longevity Growth
Success
Resilience Survival
Diversity Popularity
3

Software ecosystem health
Sustainability
Increase or maintain its user/developer
community over longer periods of time and
can survive inherent changes
(such as new technologies or new products)
that can change the population
4

Software ecosystem evolution
Empirical investigation of software ecosystems
• Social changes
• Technical impact of social changes
Social
Changes
Technical
Changes
5

Software ecosystem health
Developer socio-technical activity
• Intensity
• Frequency
• Inactivity length
9

Socio-technical activity
Intensity
• Amount of contributions
Frequency
• How often the contributions are made
Inactivity length
• Max(Continuous period of time of inactivity)
10

Grouping developers (based on combined
socio-technical factors)
Social activity
• Presence (True/False)
• Intensity (NA/Low/High)
• Frequency (NA/Low/High)
• Inactivity (NA/Low/High)
Technical activity
• Intensity (Low/High)
• Frequency (Low/High)
• Inactivity (Low/High)
11

Social Presence
Technical Intensity
Grouping developers (based on combined
socio-technical factors)
Social activity
• Presence (True/False)
• Intensity (NA/Low/High)
• Frequency (NA/Low/High)
• Inactivity (NA/Low/High)
Technical activity
• Intensity (Low/High)
• Frequency (Low/High)
• Inactivity (Low/High)
12

Dataset
RubyGems npm
Developers 56,793 119,114
Developers with >1 month
activity
31,347 63,357
Socially active developers 22,148 44,244
GitHub messages 1.5M 4.2M
Git commits 2.8M 7.8M
14

Social Presence – Technical Frequency
Group 1 Group 2 Group 3 Group 4
Social Presence
Technical Frequency
15

Social Presence – Technical Inactivity
Group 5 Group 6 Group 7 Group 8
Social Presence
Technical Inactivity
16

Social Presence – Technical Intensity
Group 9 Group 10 Group 11 Group 12
Social Presence
Technical Intensity
17

Summary of our findings
Social activity presence
positively affects
developer retention
-
Is it enough?
18

Having frequent commits is necessary but not
enough…
Group 13 Group 14 Group 15 Group 16 Group 17 Group 18
Social
Frequency
Technical
Frequency
NANA
19

Developers need to have low commit inactivity gaps…
Group 19 Group 20 Group 21 Group 22 Group 23 Group 24
Social
Frequency
Technical
Inactivity
NANA
20

Commit commit commit…
Group 31 Group 32 Group 33 Group 34 Group 35 Group 36
Social
Intensity
Technical
Frequency
NANA
21

Developers need to have low commit inactivity gaps…
Group 37 Group 38 Group 39 Group 40 Group 41 Group 42
Social
Intensity
Technical
Inactivity
NANA
22

Social and frequent commit activity
Group 49 Group 50 Group 51 Group 52 Group 53 Group 54
Social
Inactivity
Technical
Frequency
NANA
23

Summary of our findings
Intense and frequent
commit activity is not enough
…
Developers also need to have
intense and frequent
messaging activity
24

Summary of our findings
Low social activity
retains developers for
longer periods of times
compared to social inactivity
25

Summary of our findings
npm developers
tend to remain active
for longer periods of time
compared
to the respective categories of
RubyGems developers
26

What next?
Merge the identities corresponding to the same
individuals
Identify the most important factors that help distinguish
risky developers
• Probably become inactive
Predict inactivity status
Take corrective measures
• Recommend suitable alternatives
27

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Investigating developer retention in socio-technical software ecosystems

1. Investigating developer retention in socio-technical software ecosystems Eleni Constantinou University of Mons 1

2. Software ecosystem health Prof. Dr. Tom Mens Software Engineering Lab University of Mons • Ecosystem evolution • Ecosystem health www.secohealth.org 2

3. Software ecosystem health Sustainability Longevity Growth Success Resilience Survival Diversity Popularity 3

4. Software ecosystem health Sustainability Increase or maintain its user/developer community over longer periods of time and can survive inherent changes (such as new technologies or new products) that can change the population 4

5. Software ecosystem evolution Empirical investigation of software ecosystems • Social changes • Technical impact of social changes Social Changes Technical Changes 5

6. Social changes 6

7. Impact on the ecosystem 7

8. Developer retention 8

9. Software ecosystem health Developer socio-technical activity • Intensity • Frequency • Inactivity length 9

10. Socio-technical activity Intensity • Amount of contributions Frequency • How often the contributions are made Inactivity length • Max(Continuous period of time of inactivity) 10

11. Grouping developers (based on combined socio-technical factors) Social activity • Presence (True/False) • Intensity (NA/Low/High) • Frequency (NA/Low/High) • Inactivity (NA/Low/High) Technical activity • Intensity (Low/High) • Frequency (Low/High) • Inactivity (Low/High) 11

12. Social Presence Technical Intensity Grouping developers (based on combined socio-technical factors) Social activity • Presence (True/False) • Intensity (NA/Low/High) • Frequency (NA/Low/High) • Inactivity (NA/Low/High) Technical activity • Intensity (Low/High) • Frequency (Low/High) • Inactivity (Low/High) 12

13. Grouping developers (based on combined socio-technical factors) Social activity • Presence (True/False) • Intensity (NA/Low/High) • Frequency (NA/Low/High) • Inactivity (NA/Low/High) Technical activity • Intensity (Low/High) • Frequency (Low/High) • Inactivity (Low/High) 66 combinations of factors Survival analysis 13

14. Dataset RubyGems npm Developers 56,793 119,114 Developers with >1 month activity 31,347 63,357 Socially active developers 22,148 44,244 GitHub messages 1.5M 4.2M Git commits 2.8M 7.8M 14

15. Social Presence – Technical Frequency Group 1 Group 2 Group 3 Group 4 Social Presence Technical Frequency 15

16. Social Presence – Technical Inactivity Group 5 Group 6 Group 7 Group 8 Social Presence Technical Inactivity 16

17. Social Presence – Technical Intensity Group 9 Group 10 Group 11 Group 12 Social Presence Technical Intensity 17

18. Summary of our findings Social activity presence positively affects developer retention - Is it enough? 18

19. Having frequent commits is necessary but not enough… Group 13 Group 14 Group 15 Group 16 Group 17 Group 18 Social Frequency Technical Frequency NANA 19

20. Developers need to have low commit inactivity gaps… Group 19 Group 20 Group 21 Group 22 Group 23 Group 24 Social Frequency Technical Inactivity NANA 20

21. Commit commit commit… Group 31 Group 32 Group 33 Group 34 Group 35 Group 36 Social Intensity Technical Frequency NANA 21

22. Developers need to have low commit inactivity gaps… Group 37 Group 38 Group 39 Group 40 Group 41 Group 42 Social Intensity Technical Inactivity NANA 22

23. Social and frequent commit activity Group 49 Group 50 Group 51 Group 52 Group 53 Group 54 Social Inactivity Technical Frequency NANA 23

24. Summary of our findings Intense and frequent commit activity is not enough … Developers also need to have intense and frequent messaging activity 24

25. Summary of our findings Low social activity retains developers for longer periods of times compared to social inactivity 25

26. Summary of our findings npm developers tend to remain active for longer periods of time compared to the respective categories of RubyGems developers 26

27. What next? Merge the identities corresponding to the same individuals Identify the most important factors that help distinguish risky developers • Probably become inactive Predict inactivity status Take corrective measures • Recommend suitable alternatives 27

28. http://www.econst.eu @eleni_const 28

Investigating developer retention in socio-technical software ecosystems

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