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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. 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. 2. What are YOUR unanswered questions about FLOSS?
  3. 3. Ours include ...
  4. 4. ... how software is made
  5. 5. ... how software can be better
  6. 6. ... how software can be more efficient
  7. 7. ... how software can be higher quality
  8. 8. ... how software can be lower cost
  9. 9. ... how software can be more fun
  10. 10. ... how groups work
  11. 11. ... how decisions are made
  12. 12. ... how developers talk to each other.
  13. 13. There are two main approaches.
  14. 14. (1) Survey-based or case-study-based 2002, [link] 2013, [link]
  15. 15. 2013, [link]
  16. 16. Surveys can help us answer questions about motivations.
  17. 17. "Why do you develop open source?" "Do you feel valued?"
  18. 18. Some of the most oft-cited facts about FLOSS are based on survey data.
  19. 19. What percentage of FLOSS developers identify as female?
  20. 20. Some of the most venerable "laws" in software development are based on case studies where n=1. Conway's law, Brooks' law.
  21. 21. (2) Artifact-based.
  22. 22. 2005, [link]
  23. 23. 2006, [link]
  24. 24. marc.info debian lists apache lists etc.
  25. 25. unpublished, under review
  26. 26. Geoff Breach, 2008, [link]
  27. 27. 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.
  28. 28. Wang, et al., 2014 [link]
  29. 29. 2013, [link]
  30. 30. What artifacts have I missed?
  31. 31. At first, FLOSS was phenomenological.
  32. 32. We spent a lot of time measuring it...
  33. 33. constructing a vocabulary...
  34. 34. comparing it to other things we'd known and loved.
  35. 35. Our analyses started out simple enough, but have changed over time.
  36. 36. 2006 [link]
  37. 37. current [link]
  38. 38. 2003 [link]
  39. 39. "We gathered data from four different sources. ● "Firstly, we conducted thirteen telephone interviews in two rounds with eight Freenet developers
  40. 40. "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
  41. 41. "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
  42. 42. "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..."
  43. 43. 2012, [link]
  44. 44. 2012, [link]
  45. 45. 2012, [link]
  46. 46. 2013, [link]
  47. 47. 2013, [link]
  48. 48. 2008, [link]
  49. 49. 2008, [link]
  50. 50. 2012 [link]
  51. 51. 2012 [link] Data sources: Gnome and several high-participation projects on Google Code (Go, for example)
  52. 52. 2012, [link]
  53. 53. 2012, [link] data sources: bug reports, code commits
  54. 54. 2012, [link]
  55. 55. 2012, [link]
  56. 56. 2014, [link]
  57. 57. 2014, [link]
  58. 58. 2014, [link]
  59. 59. 2014, [link]
  60. 60. 2014, [link]
  61. 61. 2014, [link]
  62. 62. 2007, [link]
  63. 63. 2007, [link]
  64. 64. 2007, [link]
  65. 65. 2007, [link]
  66. 66. Sometimes we study FLOSS-like artifacts too.
  67. 67. 2014, [link]
  68. 68. 2014, [link]
  69. 69. 2014, [link]
  70. 70. 2014, [link]
  71. 71. unpublished (under review)
  72. 72. unpublished (under review)
  73. 73. 2015, to appear
  74. 74. 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!
  75. 75. 2015, to appear
  76. 76. 2015, to appear
  77. 77. 2015, to appear
  78. 78. 2015, to appear
  79. 79. 2015, to appear
  80. 80. 2015, to appear
  81. 81. 2015, to appear
  82. 82. What did I miss? What should we be studying? What are we doing wrong?
  83. 83. More resources ● FLOSShub/biblio ● Google Scholar ● OSS Conference ● MSR Conference ● ICSE Conference ● 2013 FLOSS Survey ● What We Know and What We Do Not Know

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