A Study of Trust in Open Source Software

Abstract

This study developed an algorithm which can be used to identify trust network from evaluation network. The algorithm developed uses global trust value of the members and their evaluation network to approximate local trust between members who are not directly connected to each other. Moreover, the computed approximated local trust was used to examine to what extent evaluation network can approximate trust information within OSS community and the results show that it is possible to approximate trust information by using evaluation network. Furthermore, this study analyses the likeliness of evaluation between members having di erent trust rank status. So, clustering of members was done and evaluation between groups shows that "Richer gets rich"phenomenon and about 72% of member evaluated other members through their members account pro les and 28% evaluated other members through their accounts as contributors. This means that a lot of members are likely to evaluate other member because they have much of information about their personal details rather than their contribution details in di erent projects. Finally, the study uses one of the contribution metric known as man month to analyses the evolution of trust ranks against time based on members contributions. Furthermore, results show that the developers contribution will make him or her to be trusted in OSS community. Qualitative study was conducted to analyses the data collected from OpenHub data repository. This is because OpenHub data repository o ers data of di erent projects, developers activities in OSS communities and trust information like kudo rank which are signi cant base data used to conduct this study.