2. – 7. Dezember 2007, Dagstuhl Seminar 07491
Mining Programs and Processes
Auskunft zu diesem Dagstuhl Seminar erteilt
The main goal of the seminar "Mining Programs and Processes" was to create a synergy between researchers of three communities, namely mining software repositories, data mining and machine learning, and empirical software engineering. This goal was only partially met; while we had good response rates from the mining software archives community, we only had little response from the machine learning community. This was due to an unfortunate timing: The Dagstuhl seminar ran at the same time as NIPS 2007, the major machine learning event, and thus had great trouble attracting machine learning researchers. At the time the seminar date was finalized, the NIPS date was not set yet, and when the conflict was discovered, it was too late to change the date of the seminar. We thus lost a number of opportunities for interchange with machine learning ressearchers. Furthermore, one of our organizers (Tao Xie) was unable to come to due Visa issues. Despite these drawbacks, we are convinced that the seminar did generate a deeper understanding of the three communities' research challenges and state-of-the-art works. We thus focused on the interaction between mining software archives and empirical software engineering, with a small influx from the machine learning side.
We had invited a small number of participants to give keynotes that would reach out to different communities; in particular, Katharina Morik showed off the machine learning perspective, and Lionel Briand bridged the gap to empirical software engineering. During the seminar, the participants broke into five working groups, each dedicated to a specific topic. The results of these groups reflect the state of the art, as well as challenges for the future:
- Issues of Mining Software Repositories
- What do Developers (really) Need?
- Empirical Studies and Long-Term Objectives
- An Infrastructure for Mining Software Repositories
- Understanding Code Changes
While there clearly is a need for further interaction between machine learning and mining software repositories, the seminar made clear progress into the interaction between mining software archives and empirical software engineering; this interaction is also reflected in the respective venues, which more and more adopt mining and empiricism as standard techniques. Also, the seminar showed inspiring directions in mining itself, as outlined above.
- Event Processing (main Classification)
- Artificial Intelligence
- Programming Languages
- Semantics/specification/formal Methods
- Software Engineering.
- Event Processing
- Real-time Information Systems
- Reactive systems
- Proactive systems
- Active Technologies.