Leveraging Social Network Analysis for Crowdsourced Software Engineering Research

Abstract

Crowdsourced software engineering (CSE) is an emerging area that has been gaining much attention in the last few years. It refers to the use of crowdsourcing techniques in software engineering activities, including requirements engineering, implementation, design, testing, and verification. CSE is an alternative to traditional software engineering and uses an open call to which online developers can respond to and obtain work on various tasks, as opposed to the assigning of tasks to in-house developers. The great benefits of CSE have attracted the attention of many researchers, and many studies have recently been carried out in the field. This research aims to analyze publications on CSE using social network analysis (SNA). A total of 509 CSE publications from six popular databases were analyzed to determine the characteristics of the collaborative networks of co-authorship of the research (i.e., the co-authors, institutions involved in co-authorship, and countries involved in co-authorship) and of the citation networks on which the publications of the studies are listed. The findings help identify CSE research productivity, trends, performances, community structures, and relationships between various collaborative patterns to provide a more complete picture of CSE research.