Work

Assessing Open Source Software Survivability using Kaplan-Meier Survival Function and Polynomial Regression

Year: 2024

Type: conference-paper

Abstract: This study evaluates OSS project survivability using the Kaplan-Meier Survival Function and polynomial regression models. The key factors identified include the number of contributors and project popularity, which significantly influence survivability. Traditional indicators like project age do not directly correlate with OSS survivability. Instead, community engagement and recognition are crucial, offering valuable guidelines for managing and selecting Survivable OSS projects.

Source: IEEE/ACM International Conference on Automated Software Engineering (ASE)

DOI: 10.1145/3691620.3695333

Authors: Sohee Park, Ryeonggu Kwon, Gihwon Kwon

Institution: Kyonggi University

Language: English

Topic: Open Source Software Innovations

Subfield: Computer Science Applications

Field: Computer Science

Domain: Physical Sciences

Open Access status: bronze

Funders: Ministry of Science and ICT, South Korea, Institute for Information and Communications Technology Promotion

Awards: G1042626139, G771576505