Mining Software Repositories. Where to get data? Where to publish?

1. Mining Software Repositories What to do? And where to get data? Israel Herraiz < [email_address] > Universidad Alfonso X el Sabio June 18 th 2010

5. 1. What is Mining Software Repositories?

8. Working Conference since 2008

10. Also includes any software artifact

12. Bug tracking systems

13. Public communication tools (mailing lists)

14. Differences between artifact and repository #include <stdio.h> int main() { printf(“Hello world”); return 0; } Artifact Source code file hello.c - printf(“Hello world”); + printf(“Hello world”); Author: rms Date: 20100618 04:34 UTC Change: +1 -1 Log: Forgot to add new line hello.c.diff Repository Change to an artifact Meta-information

15. 2. Conferences and journals of interest

16. Working conferences of interest IEEE Int. Working Conf. Source Code Analysis & Manipulation (SCAM) http://www.ieee-scam.org IEEE Int. Working Conf. Mining Software Repositories (MSR) http://msr.uwaterloo.ca Deadlines Accept rate Journal possib. January (Februray for the challenge) April 26% (2007) 38% (2008) 45% (2009) 19% (2008) 31% (2010) JSS SCP EMSE IEEE TSE

17. Conferences of interest IEEE Int. Conf. Software Engineering (ICSE) http://www.sbs.co.za/ICSE2010/ IEEE Int. Conf. Software Maintenance (ICSM) http://icsm2010.upt.ro/ Deadlines Accept rate Journal possib. April August September 15% (2008) 12% (2009) 14% (2010) 21% (2007) 26% (2008) 22% (2009) No special issues No special issues Empirical Software Eng. & Measurement (EMSE) http://www.esem-conferences.org/ March ? EMSE

23. 3. Tools for Mining Software Repositories

25. CVSAnaly – CVS/SVN/Git repositories log parser

26. MLStats – Mailman and Mboxes parser

28. 4. Datasets for Mining Software Repositories

32. Datasheets, databases, scripts, with information about Eclipse bug reports for several releases

33. http://www.st.cs.uni-saarland.de/softevo/bug-data/eclipse/

35. Control version repositories, mailing list archives, bug tracking databases

37. http://www.flossmetrics.org/

39. ~150,000 projects

40. Mainly metainformation, obtained through parsing the web pages of the projects

41. No low level or fine grained information

42. http://flossmole.org

44. http://promisedata.org/

46. Effort prediction (18)

47. General (9)

48. Model-based SE (7)

49. Text mining (9)