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Contributors Classification - Replication Package

<p><strong>Contributors Classification - Replication Package:</strong> Contains three .py files to for the classification of contributors, and the resulting data in .csv files. ElbowMethod.py is used to identify the optimal number of clusters for the studied data. BradfordsClassification.py is used to collect the data necessary to classify reactors based on their number of commits as described in our paper. TruckFactor.py is the implementation of the algorithm of Avelino et al. on each month and each project to estimate the truck factor of a project.</p>

ShareScore

24/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
4
Harmonization
4
Access
16
Reuse readiness
0
Engagement
0