Recommendation System for Open Source Projects for Minimizing Abandonment

Autor/innen

  • Sarah Sayce
  • Krishnendu Ghosh College of Charleston

DOI:

https://doi.org/10.32473/flairs.v35i.130707

Schlagworte:

Recommendation Systems, Open Source Software, Truck Factor

Abstract

The rise in the creation and maintenance of Open Source

Software have facilitated the software developers to contribute

and prevent abandonment. Software developers often

face a daunting task to select the open source projects that remain

active. In the absence of any resource to guide in the selection

of the Open Source Software projects, recommendation

systems is way to provide guidance to open source contributors.

In this work, we describe several approaches in creation

of recommendation systems for Open Source Software

projects. Experiments on a synthetic data set are performed

to evaluate the performance of the recommendation system.

Downloads

Veröffentlicht

2022-05-04

Zitationsvorschlag

Sayce, S., & Ghosh, K. (2022). Recommendation System for Open Source Projects for Minimizing Abandonment. The International FLAIRS Conference Proceedings, 35. https://doi.org/10.32473/flairs.v35i.130707

Ausgabe

Rubrik

Special Track: Applied Natural Language Processing