Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/29331
Title: An exploration to what extent process mining techniques can be applied to extract a collaboration model from version control system logs
Authors: JOOKEN, Leen 
Advisors: JANS, Mieke
Issue Date: 2019
Publisher: UHasselt
Abstract: A precise overview on how software developers collaborate on code could reveal new insights such as indispensable resources, potential risks and better team awareness. One might have an idea about how these developers work together, but this will often deviate from and be less nuanced than reality. Version control system logs keep track of what team members worked on and when exactly this work took place. Since it is possible to derive collaborations from this information, these logs form a valid data source to extract this overview from. This concept shows many similarities with how process mining techniques can extract process models from execution logs. The fuzzy mining algorithm in particular holds many useful ideas and metrics that can also be applied to our problem case. This paper describes the development of a tool that extracts a collaboration graph from a version control system log. It explores to what extend fuzzy mining techniques can be incorporated to construct and simplify the visualization. A demonstration of the tool on a real-life event log is given. The paper concludes with a discussion of the business relevance.
Notes: master in de toegepaste economische wetenschappen: handelsingenieur in de beleidsinformatica
Document URI: http://hdl.handle.net/1942/29331
Category: T2
Type: Theses and Dissertations
Appears in Collections:Master theses

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