  All methodologies for detecting plagiarism to date have focused on the final
digital "outcome", such as a document or source code. Our novel approach takes
the creation process into account using logged events collected by special
software or by the macro recorders found in most office applications. We look
at an author's interaction logs with the software used to create the work.
Detection relies on comparing the histograms of multiple logs' command use. A
work is classified as plagiarism if its log deviates too much from logs of
"honestly created" works or if its log is too similar to another log. The
technique supports the detection of plagiarism for digital outcomes that stem
from \emph{unique} tasks, such as theses and \emph{equal} tasks such as
assignments for which the same problem sets are solved by multiple students.
Focusing on the latter case, we evaluate this approach using logs collected by
an interactive development environment (IDE) from more than sixty students who
completed three programming assignments.
