Abstract
Free/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.
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Notes
- 1.
FLEX syntax is used by Adobe Flex, a tool that generates programs for pattern matching in text. It receives user-specified input and produces a C source file.
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Mukala, P., Cerone, A., Turini, F. (2015). Process Mining Event Logs from FLOSS Data: State of the Art and Perspectives. In: Canal, C., Idani, A. (eds) Software Engineering and Formal Methods. SEFM 2014. Lecture Notes in Computer Science(), vol 8938. Springer, Cham. https://doi.org/10.1007/978-3-319-15201-1_12
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