OSS 2019
Sun 26 - Mon 27 May 2019 Montreal, QC, Canada
co-located with ICSE 2019
Sun 26 May 2019 15:00 - 15:30 at Mansfield - Technical Session 2 - OSS in Practice

GitHub is the largest open source source development platform with millions of repositories on variety of topics. The number of stars received by a repository is often considered as a measure of its popularity. Predicting the number of stars of a repository has been associated with the number of forks, commits, followers, documentation size, and programming language in the literature. We extend prior studies in terms of input features and algorithm: We de ne six features from GitHub events corresponding to the development activities, and additional six features incorporating the influence of users (followers and contributors) on the popularity of projects into their development activities. We propose a time-series based forecast model using Recurrent Neural Networks to predict the number of stars received in consecutive k days. We assess the performance of our proposed model with varying k (1,7,14,30 days) and with varying input features. Our analysis on fi ve topmost starred repositories in data visualization area shows that the error rate ranges between 19.76 and 70.57 among the projects. The best performing models use either features from development activities only, or all metrics including all the features.

Sun 26 May
Times are displayed in time zone: (GMT-04:00) Eastern Time (US & Canada) change

14:00 - 15:30: OSS 2019 Papers - Technical Session 2 - OSS in Practice at Mansfield
oss2019-papers14:00 - 14:30
Research paper
Yutaro Kashiwa, Akinori IharaWakayama University, Masao OhiraWakayama University
oss2019-papers14:30 - 15:00
Research paper
Debora Maria Coelho NascimentoFederal University of Sergipe, São Cristovão, Brazil, Christina von Flach Garcia ChavezFederal University of Bahia, Roberto Almeida BittencourtState University of Feira de Santana, Feira de Santana, Brazil
oss2019-papers15:00 - 15:30
Research paper
Sefa Eren SahinFaculty of Computer and Informatics Engineering, Istanbul Technical University, Kubilay KarpatFaculty of Computer and Informatics Engineering, Istanbul Technical University, Ayse TosunIstanbul Technical University