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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/29143

Title: Extracting A Collaboration Model From VCS Logs Based On Process Mining Techniques
Authors: Jooken, Leen
Creemers, Mathijs
Jans, Mieke
Issue Date: 2019
Publisher: Springer
Citation: Di Francescomarino, Chiara; Dijkman, Remco; Zdun, Uwe (Ed.). Business Process Management - 17th International Conference, BPM 2019, Vienna, Austria, September 1-6, 2019, Proceedings, Springer,p. 213-224 (Art N° 21)
Abstract: A precise overview on how software developers collaborate oncode could reveal new insights such as indispensable resources, potentialrisks and better team awareness. Version control system logs keep trackof what team members worked on and when exactly this work took place.Since it is possible to derive collaborations from this information, theselogs form a valid data source to extract this overview from. This conceptshows many similarities with how process mining techniques can extractprocess models from execution logs. The fuzzy mining algorithm [5] inparticular holds many useful ideas and metrics that can also be appliedto our problem case. This paper describes the development of a toolthat extracts a collaboration graph from a version control system log. Itexplores to what extend fuzzy mining techniques can be incorporated toconstruct and simplify the visualization. A demonstration of the tool ona real-life version control system log is given. The paper concludes witha discussion of future work.
URI: http://hdl.handle.net/1942/29143
Link to publication: https://surfdrive.surf.nl/files/index.php/s/1x7PMzTjsFRfw6y
ISBN: 9783030266189
Category: C1
Type: Proceedings Paper
Appears in Collections: Research publications

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