Social coding in GitHub

Dabbish, Laura; Stuart, C.; Tsay, Jason; Herbsleb, James D.

doi:10.1145/2145204.2145396

Cited by 712 publications

(136 citation statements)

References 23 publications

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“…RQ1: How do integrators use pull-based development in their projects? 1) Overall use: To understand why and how projects use the pull-based development model, we asked integrators a multiple choice question that included the union of potential uses of pull requests that have been reported in the literature [1], [16], [15]. Respondents also had the opportunity to report other uses not in our list.…”

Section: Resultsmentioning

confidence: 99%

“…Furthermore, our survey brings additional insights to the insightful but smaller scale interviews that have been conducted by other researchers on the pull based model (e.g. [16], [11], [15], [14]). We welcome replications of this work; potential directions include replications with integrators that (1) use different (non-GitHub) repositories, e.g., Bitbucket, (2) work on private repositories, and (3) work on non-pull request intensive projects.…”

Section: Discussionmentioning

confidence: 96%

“…With the raise of transparent work environments [16], and based on previous work on the subject [9], [11], one would expect that the developer's track record would be used by the majority of integrators to make inferences about the quality of incoming contributions. Despite this, the track record is mostly used as an auxiliary signal; in both Figure 5a and Figure 6a, we can see that developers equally mentioned the track record as top and second criterion for quality evaluation and prioritization.…”

Section: Developer Track Recordsmentioning

confidence: 99%

“…Integrators in our study actually mentioned the opposite: it is maintaining the community momentum and motivating contributors to do more work that is not easy. Through transparency [16] and lowered barriers to participation [15], [1], the pull-based model can act as glue for communities build around projects, if integrators are keen enough on fostering their project's communities by helping newcomers cope with tools and project processes, prioritizing the examination of community contributions and, in the extreme case, not rejecting unwanted contributions.…”

Section: E Community Buildingmentioning

confidence: 99%

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Work Practices and Challenges in Pull-Based Development: The Integrator's Perspective

Gousios

Zaidman

Storey

et al. 2015

2015 IEEE/ACM 37th IEEE International Conference on Software Engineering

259

348

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Abstract-In the pull-based development model, the integrator has the crucial role of managing and integrating contributions. This work focuses on the role of the integrator and investigates working habits and challenges alike. We set up an exploratory qualitative study involving a large-scale survey involving 749 integrators, to which we add quantitative data from the integrator's project. Our results provide insights into the factors they consider in their decision making process to accept or reject a contribution. Our key findings are that integrators struggle to maintain the quality of their projects and have difficulties with prioritizing contributions that are to be merged.

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Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 96%

Section: Developer Track Recordsmentioning

confidence: 99%

Section: E Community Buildingmentioning

confidence: 99%

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Work Practices and Challenges in Pull-Based Development: The Integrator's Perspective

Gousios

Zaidman

Storey

et al. 2015

2015 IEEE/ACM 37th IEEE International Conference on Software Engineering

259

348

View full text Add to dashboard Cite

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“…Additionally, when code such as R (an open source coding language) is used to process data and generate figures, these figures can be published (by supporting platforms) with the data and code embedded and automatically generating the figure, which allows for increased scientific transparency. Inferring from open source software development communities, who rely on openness, this additional transparency allows for increased intellectual interaction between the information consumer and the research group who wrote the article, because the consumer can examine the process that went into creating the visualization, which in turn allows for a clearer understanding of the work (Dabbish, Stuart, Tsay, & Herbsleb, 2012).…”

Section: Email Traditional Publicationmentioning

confidence: 99%

Shifting Paradigms in Information Flow: An Open Science Framework (OSF) for Knowledge Sharing Teams

Potterbusch

Lotrecchiano

2018

InformingSciJ

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Aim/Purpose: This paper explores the implications of machine-mediated communication on human interaction in cross-disciplinary teams. The authors explore the relationships between Open Science Theory, its contributions to team science, and the opportunities and challenges associated with adopting open science principles. Background: Open Science Theory impacts many aspects of human interaction throughout the scholarly life cycle and can be seen in action through various technologies, which each typically touch only one such aspect. By serving multiple aspects of Open Science Theory at once, the Open Science Framework (OSF) serves as an exemplar technology. As such it illustrates how Open Science Theory can inform and expand cognitive and behavioral dynamics in teams at multiple levels in a single tool. Methodology: This concept paper provides a theoretical rationale for recommendations for exploring the connections between an open science paradigm and the dynamics of team communication. As such theory and evidence have been culled to initiate a synthesis of the nascent literature, current practice and theory. Contribution: This paper aims to illuminate the shared goals between open science and the study of teams by focusing on science team activities (data management, methods, algorithms, and outputs) as focal objects for further combined study. Findings: Team dynamics and characteristics that will affect successful human/machine assisted interactions through mediators of workflow culture, attitudes about ownership of knowledge, readiness to share openly, shifts from group-driven to user-driven functionality, group-organizing to self-organizing structures, and the development of trust as teams regulate between traditional and open science dissemination. Recommendations for Practitioners: Participation in open science practices through machine-assisted technologies in team projects/scholarship should be encouraged. Recommendation for Researchers: The information provided highlights areas in need of further study in team science as well as new primary sources of material in the study of teams utilizing machine-assisted methods in their work. Impact on Society: As researchers take on more complex social problems, new technology and open science practices can complement the work of diverse stakeholders while also providing opportunities to broaden impact and intensify scholarly contributions. Future Research: Future investigation into the cognitive and behavioral research conducted with teams that employ machine-assisted technologies in their workflows would offer researchers the opportunity to understand better the relationships between intelligent machines and science teams’ impacts on their communities as well as the necessary paradigmatic shifts inherent when utilizing these technologies.

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Ergonomics of Information Technologies at Work

Hanrahan¹,

Carroll²

2017

The Wiley Blackwell Handbook of the Psychology of the Internet at Work

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Social coding in GitHub

Cited by 712 publications

References 23 publications

Work Practices and Challenges in Pull-Based Development: The Integrator's Perspective

Work Practices and Challenges in Pull-Based Development: The Integrator's Perspective

Shifting Paradigms in Information Flow: An Open Science Framework (OSF) for Knowledge Sharing Teams

Ergonomics of Information Technologies at Work

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