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 augment existing analyses and to
help developers identify relevant souce code during a modification
task, we have developed an approach that applies data mining
techniques to determine change patterns - sets of files that were
changed together frequently in the past - from the change history of
the code base. Our hypothesis is that the change patterns can be
used to recommend potentially relevant source code to a developer
performing a mofidication task. We show that this approach can
reveal valuable dependencies by applying the approach to the Eclipse
and Mozilla open source projects and by evaluating the
predictability and interestingness of the recommendations produced
for actual modification tasks on these systems.