Speaker:  Hila Cohen

Title: Mining Version Histories to Guide Software Changes

Abstract:

Software developers are often faced with modification tasks that
involve source which is spread across a code base. Some dependencies
between source code, such as those between source code written in
different languages, are difficult to determine using existing static
and dynamic analyses.   To help developers identify relevant source
code during a modification task, one may apply data mining techniques
to determine change patterns from the change history of the code base,
and use them to make recommendations to the developers.

In this talk we give an introduction to the use of recommendation
systems in software engineering, and review papers by Zimmerman et al.
(IEEE TSE 2005) and by Ying et al. (IEEE TSE 2004) that have applied
these ideas to code change prediction.  We then suggest possible ways
to improve their results.