Abstract:
Open Source Software (OSS) applications are free software products where the source code is open to
everyone. This source code can be modified, used, and extended based on the OSS license disciplines
and restrictions. OSS projects are developed and maintained by a community of developers and
coordinators. OSS developers contribute to the projects using online platforms such as SourceForge,
FreshMeat, and GitHub. Software development is a socio-technical practice. Developers require
technical knowledge of software engineering to develop a software solution. Also, soft skills are crucial
for successful collaboration among team members. OSS developers use social coding platforms to
develop the software, collaborate, and communicate with each other in the absence of face-to-face
interactions.
The success of OSS projects such as Linux, MySQL, Android, Hadoop, and, Firefox attracts
practitioners and scholars to study and analyse the OSS community from different perspectives. This
thesis focused on analysing the OSS community with a socio-technical lens grounding on the previous
literature. This study aimed to support the OSS community from different angles. In this thesis, several
research methods and theories were employed to study the large data set of OSS projects.
This study is defined as a large-scale analysis of socio-technical interactions in the open source
community in a broader scope. This thesis contributes to the body of the OSS literature by finding the
right match among developers and projects. We have applied the design science research method to
develop an artefact that recommends projects to developers. Also, we have applied social network
analytics, statistics, and econometric techniques to analyse the OSS projects’ success factors.
Furthermore, we have investigated the role of newcomers in the OSS community. We have proved the
role of newcomers’ supportive strategies on the success of OSS projects. To support newcomers in their
initial contribution to the OSS community, we have applied data mining techniques to find efficient
pathways for newcomers.