Case Study: We're Watching You: How and Why Researchers Study Open Source And What We've Found So Far
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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
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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?
- 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.
- 22. 2005, [link]
- 23. 2006, [link]
- 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?
- 41. We spent a lot of time measuring it...
- 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]
- 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