Enriching revision history with interactions

ABSTRACT

Revision history provides a rich source of information to improve the understanding of changes made to programs, but it yields only limited insight into how these changes occurred. We explore an additional source of information - program viewing and editing history - where all historical artifacts associated with the program are included. In particular, we suggest augmenting revision histories with the interaction history of programmers. Using this additional information source enables the development of several interesting applications including an influence-recommendation system and a task-mining system. We present some results from a case study in which interaction histories from professional programmers were obtained and analyzed.

REFERENCES

• 1: Robert DeLine , Amir Khella , Mary Czerwinski , George Robertson, Towards understanding programs through wear-based filtering, Proceedings of the 2005 ACM symposium on Software visualization, May 14-15, 2005, St. Louis, Missouri [doi>10.1145/1056018.1056044]
• 2: Carsten Görg , Peter Weißgerber, Error detection by refactoring reconstruction, Proceedings of the 2005 international workshop on Mining software repositories, p.1-5, May 17-17, 2005, St. Louis, Missouri
• 3: William C. Hill , James D. Hollan , Dave Wroblewski , Tim McCandless, Edit wear and read wear, Proceedings of the SIGCHI conference on Human factors in computing systems, p.3-9, May 03-07, 1992, Monterey, California, United States [doi>10.1145/142750.142751]
• 4: Mik Kersten , Gail C. Murphy, Mylar: a degree-of-interest model for IDEs, Proceedings of the 4th international conference on Aspect-oriented software development, p.159-168, March 14-18, 2005, Chicago, Illinois [doi>10.1145/1052898.1052912]
• 5: Keir Mierle , Kevin Laven , Sam Roweis , Greg Wilson, Mining student CVS repositories for performance indicators, Proceedings of the 2005 international workshop on Mining software repositories, p.1-5, May 17-17, 2005, St. Louis, Missouri
• 6: Gerard Salton , Chris Buckley, Term Weighting Approaches in Automatic Text Retrieval, Cornell University, Ithaca, NY, 1987
• 7: K. Schneider, C. Gutwin, R. Penner, and D. Paquette. Mining a software developer's local interaction history. In MSR '04: Proceedings of the 2004 international workshop on Mining software repositories, pages 106--110, 2004.
• 8: Janice Singer , Robert Elves , Margaret-Anne Storey, NavTracks: Supporting Navigation in Software Maintenance, Proceedings of the 21st IEEE International Conference on Software Maintenance (ICSM'05), p.325-334, September 25-30, 2005 [doi>10.1109/ICSM.2005.66]
• 9: Jacek Śliwerski , Thomas Zimmermann , Andreas Zeller, When do changes induce fixes?, Proceedings of the 2005 international workshop on Mining software repositories, p.1-5, May 17-17, 2005, St. Louis, Missouri

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.4 INFORMATION SYSTEMS APPLICATIONS

Additional Classification:
  D. Software
  D.2 SOFTWARE ENGINEERING
      D.2.8 Metrics
          Subjects: Performance measures; Complexity measures

General Terms:
Measurement

Keywords:
data mining, interaction history, revision history