Identification-method research for open-source software ecosystems

In recent years, open-source software (OSS) development has grown, with many developers around the world working on different OSS projects. A variety of open-source software ecosystems have emerged, for instance, GitHub, StackOverflow, and SourceForge. One of the most typical social-programming and code-hosting sites, GitHub, has amassed numerous open-source-software projects and developers in the same virtual collaboration platform. Since GitHub itself is a large open-source community, it hosts a collection of software projects that are developed together and coevolve. The great challenge here is how to identify the relationship between these projects, i.e., project relevance. Software-ecosystem identification is the basis of other studies in the ecosystem. Therefore, how to extract useful information in GitHub and identify software ecosystems is particularly important, and it is also a research area in symmetry. In this paper, a Topic-based Project Knowledge Metrics Framework (TPKMF) is proposed. By collecting the multisource dataset of an open-source ecosystem, project-relevance analysis of the open-source software is carried out on the basis of software-ecosystem identification. Then, we used our Spectral Clustering algorithm based on Core Project (CP-SC) to identify software-ecosystem projects and further identify software ecosystems. We verified that most software ecosystems usually contain a core software project, and most other projects are associated with it. Furthermore, we analyzed the characteristics of the ecosystem, and we also found that interactive information has greater impact on project relevance. Finally, we summarize the Topic-based Project Knowledge Metrics Framework

Assessing technical candidates on the social web

This is the pre-print version of this Article. The official published version can be accessed from the link below - Copyright @ 2012 IEEEThe Social Web provides comprehensive and publicly available information about software developers: they can be identified as contributors to open source projects, as experts at maintaining weak ties on social network sites, or as active participants to knowledge sharing sites. These signals, when aggregated and summarized, could be used to define individual profiles of potential candidates: job seekers, even if lacking a formal degree or changing their career path, could be qualitatively evaluated by potential employers through their online contributions. At the same time, developers are aware of the Web’s public nature and the possible uses of published information when they determine what to share with the world. Some might even try to manipulate public signals of technical qualifications, soft skills, and reputation in their favor. Assessing candidates on the Web for technical positions presents challenges to recruiters and traditional selection procedures; the most serious being the interpretation of the provided signals. Through an in-depth discussion, we propose guidelines for software engineers and recruiters to help them interpret the value and trouble with the signals and metrics they use to assess a candidate’s characteristics and skills

Influence Of Developer Sentiment And Stack Overflow Developers On Open Source Project Success: An Empirical Examination

The collaborative effort of software developers around the world produces Open Source Software (OSS) products, and most importantly, the source code of the software product is shared publicly. A recent survey of 1300 IT professionals by Black Duck Software showed that the percentage of companies using open source software grew from 42% to 78% between 2010 and 2015. There has been a significant increase in the formation of self-organizing virtual teams to produce open source software products and services. The current literature does not address the factors affecting the success of open source projects through the lens of self-organizing virtual teams and the sentiment among the developers and the sentiment among software developers. This phenomenon suggests a need to understand how successful project teams are created in a virtual collaborative environment. This research investigates how successful virtual teams are formed through the influence of an online developer community. The focus of this research is to assess how the online developer community, Stack Overflow (SO), influences the success of open source projects. More precisely, the study empirically tests the influence of the SO community on successful Github (GH) projects. The investigation also empirically examines how the ties among the software developers in the SO community initiate the self-creation of OSS project teams. The research also explores the perception of the developers about open source projects. Furthermore, the study probes the impact of OSS artifacts, namely “feature” and “patch” requests, on open source projects. The findings indicate that the perception of the developers in the SO community, prior ties among the developers in the community, and the artifact type of the project are the factors that influence the success of OSS projects. The research discusses the implications of the outcomes concerning self-organizing open source project teams