01411nas a2200133   4500008004100000245008100041210006900122260001900191520090300210100002001113700002001133700001901153856010501172       2014                        eng d00aProcess mining event logs from FLOSS data: state of the art and perspectives0 aProcess mining event logs from FLOSS data state of the art and p  bSpringer, Cham3 aFree/Libre Open Source Software (FLOSS) is a phenomenon that has undoubtedly triggered extensive research endeavors. At the heart of these initiatives is the ability to mine data from FLOSS repositories with the hope of revealing empirical evidence to answer existing questions on the FLOSS development process. In spite of the success produced with existing mining techniques, emerging questions about FLOSS data require alternative and more appropriate ways to explore and analyse such data.

In this paper, we explore a different perspective called process mining. Process mining has been proved to be successful in terms of tracing and reconstructing process models from data logs (event logs). The chief objective of our analysis is threefold. We aim to achieve: (1) conformance to predefined models; (2) discovery of new model patterns; and, finally, (3) extension to predefined models.

1 aMukala, Patrick1 aCerone, Antonio1 aTurini, Franco  uhttps://kdd.isti.cnr.it/publications/process-mining-event-logs-floss-data-state-art-and-perspectives