All Things Open 2014 - Day 2 Thursday, October 23rd, 2014 Dr. Megan Squire Associate Professor of Computing Sciences with FLOSSmole Project & Elon University Business Case Study: We're Watching You: How and Why Researchers Study Open Source And What We've Found So Far

1. Why researchers study open source
and what we've found so far
Megan Squire @MeganSquire0
Elon University & FLOSSmole / FLOSSdata / FLOSShub
October 23, 2014 (All Things Open)

2. What are YOUR
unanswered
questions about FLOSS?

3. Ours include ...

4. ... how software is made

5. ... how software can be better

6. ... how software can be more efficient

7. ... how software can be higher quality

8. ... how software can be lower cost

9. ... how software can be more fun

10. ... how groups work

11. ... how decisions are made

12. ... how developers talk to each other.

13. There are two main approaches.

14. (1) Survey-based or case-study-based
2002, [link]
2013, [link]

15. 2013, [link]

16. Surveys can help us answer
questions about motivations.

17. "Why do you develop open source?"
"Do you feel valued?"

18. Some of the most oft-cited facts
about FLOSS
are based on survey data.

19. What percentage of FLOSS
developers identify as female?

20. Some of the most venerable
"laws" in software development are
based on case studies where n=1.
Conway's law, Brooks' law.

21. (2) Artifact-based.

22. 2005, [link]

23. 2006, [link]

25. marc.info
debian lists
apache lists
etc.

26. unpublished, under review

28. Geoff Breach, 2008, [link]

34. Data Source: Sourceforge.net
Data: Projects & Developers
Method: Social network analysis
Finding: OSS shows many characteristics
of a scale-free network, but so far has
stopped short of exhibiting winner-take-all
behavior.

36. Wang, et al., 2014 [link]

38. 2013, [link]

39. What artifacts have I missed?

40. At first,
FLOSS was
phenomenological.

41. We spent a lot of time
measuring it...

42. constructing a vocabulary...

43. comparing it to other things
we'd known and loved.

44. Our analyses started out simple enough,
but have changed over time.

45. 2006 [link]

47. current [link]

48. 2003 [link]

49. "We gathered data from four different sources.
● "Firstly, we conducted thirteen telephone interviews in two rounds with
eight Freenet developers

50. "We gathered data from four different sources.
● "Firstly, we conducted thirteen telephone interviews in two rounds with
eight Freenet developers
● "Secondly, we collected the project’s public email conversations stored in
the projects’ mailing lists which is archived on Freenet’s website

51. "We gathered data from four different sources.
● "Firstly, we conducted thirteen telephone interviews in two rounds with
eight Freenet developers
● "Secondly, we collected the project’s public email conversations stored in
the projects’ mailing lists which is archived on Freenet’s website
● "The third source of data included the history of changes to the software
code available via the project’s software repository within the CVS

52. "We gathered data from four different sources.
● "Firstly, we conducted thirteen telephone interviews in two rounds with
eight Freenet developers
● "Secondly, we collected the project’s public email conversations stored in
the projects’ mailing lists which is archived on Freenet’s website
● "The third source of data included the history of changes to the software
code available via the project’s software repository within the CVS
● "Fourthly, in order obtain contextual understanding of the project we
collected publicly available documents related to open source in general
and to the project in particular..."

54. 2012, [link]

55. 2012, [link]

56. 2012, [link]

57. 2013, [link]

58. 2013, [link]

59. 2008, [link]

60. 2008, [link]

61. 2012 [link]

62. 2012 [link]
Data sources: Gnome and several high-participation projects on Google Code (Go, for example)

63. 2012, [link]

64. 2012, [link]
data sources: bug reports, code commits

65. 2012, [link]

66. 2012, [link]

67. 2014, [link]

68. 2014, [link]

69. 2014, [link]

70. 2014, [link]

71. 2014, [link]

72. 2014, [link]

73. 2007, [link]

74. 2007, [link]

75. 2007, [link]

76. 2007, [link]

77. Sometimes we study FLOSS-like
artifacts too.

78. 2014, [link]

79. 2014, [link]

80. 2014, [link]

81. 2014, [link]

82. unpublished (under review)

83. unpublished (under review)

84. 2015, to appear

85. 2015, to appear
Building data sets for automatic detection & study of...
1. Profanity
a. strong
b. mild
2. General Insults
a. personal
b. code-based
c. both
3. Gender-based language & attitudes
a. your mom / maternal insults
b. that's what she said
c. gender stereotyping
i. Aunt Tillie / grandma
ii. wives/girlfriends don't let you code!

86. 2015, to appear

87. 2015, to appear

88. 2015, to appear

89. 2015, to appear

90. 2015, to appear

91. 2015, to appear

92. 2015, to appear

93. What did I miss?
What should we be studying?
What are we doing wrong?

94. More resources
● FLOSShub/biblio
● Google Scholar
● OSS Conference
● MSR Conference
● ICSE Conference
● 2013 FLOSS Survey
● What We Know and What We Do Not Know