Recommending GitHub Projects for Developer Onboarding

Liu, Chao; Yang, Dan; Zhang, Xiaohong; Ray, Baishakhi; Rahman, Mohammad Masudur

doi:10.1109/access.2018.2869207

Cited by 33 publications

(16 citation statements)

References 39 publications

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“…[5] 1700 22,000 0.07 [26] 1255 58,092 0.02 [27] 1070 1600 0.66 [25] 62,607 9447 0.15 [30] 62,607 9447 0.15 Our study 100 41,280 0.002…”

Section: Paper Id Number Of User Number Of Project Ratio (~)mentioning

confidence: 77%

“…In another study that explored the factors that led a user to join a project, the metrics used included a developer's social connections, programming with a common language, and contributions to the same projects or files [26]. Liu et al designed a neural networkbased recommendation system that used metrics such as working at the same company, previous collaboration with the project owner, and different time-related features of a project [27].…”

Section: Introductionmentioning

confidence: 99%

“…A recommendation was assumed to be correct if the number of commits a certain developer made to the project exceeded a certain value. The average number of commits per project was set as the threshold value in the dataset [27].…”

mentioning

confidence: 99%

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New Developer Metrics for Open Source Software Development Challenges: An Empirical Study of Project Recommendation Systems

2021

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Software collaboration platforms where millions of developers from diverse locations can contribute to the common open source projects have recently become popular. On these platforms, various information is obtained from developer activities that can then be used as developer metrics to solve a variety of challenges. In this study, we proposed new developer metrics extracted from the issue, commit, and pull request activities of developers on GitHub. We created developer metrics from the individual activities and combined certain activities according to some common traits. To evaluate these metrics, we created an item-based project recommendation system. In order to validate this system, we calculated the similarity score using two methods and assessed top-n hit scores using two different approaches. The results for all scores with these methods indicated that the most successful metrics were binary_issue_related, issue_commented, binary_pr_related, and issue_opened. To verify our results, we compared our metrics with another metric generated from a very similar study and found that most of our metrics gave better scores that metric. In conclusion, the issue feature is more crucial for GitHub compared with other features. Moreover, commenting activity in projects can be equally as valuable as code contributions. The most of binary metrics that were generated, regardless of the number of activities, also showed remarkable results. In this context, we presented improvable and noteworthy developer metrics that can be used for a wide range of open-source software development challenges, such as user characterization, project recommendation, and code review assignment.

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“…[5] 1700 22,000 0.07 [26] 1255 58,092 0.02 [27] 1070 1600 0.66 [25] 62,607 9447 0.15 [30] 62,607 9447 0.15 Our study 100 41,280 0.002…”

Section: Paper Id Number Of User Number Of Project Ratio (~)mentioning

confidence: 77%

Section: Introductionmentioning

confidence: 99%

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New Developer Metrics for Open Source Software Development Challenges: An Empirical Study of Project Recommendation Systems

2021

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“…NNLRank [94] is a recommender system for supporting new developers in their selection of an open source project to join. Recommendations are based on the project features and the developer's past experiences.…”

Section: Non-profit Organizations and Agenciesmentioning

confidence: 99%

Adoption of Social Media in Socio-Technical Systems: A Survey

2021

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This article describes the current landscape in the fields of social media and socio-technical systems. In particular, it analyzes the different ways in which social media are adopted in organizations, workplaces, educational and smart environments. One interesting aspect of this integration, is the use of social media for members’ participation and access to the processes and services of their organization. Those services cover many different types of daily routines and life activities, such as health, education, transports. In this survey, we compare and classify current research works according to multiple features, including: the use of Social Network Analysis and Social Capital models, users’ motivations for participation and organizational costs, adoption of the social media platform from below. Our results show that many of these current systems are developed without taking into proper consideration the social structures and processes, with some notable and positive exceptions.

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“…With the advent of large amounts of data and APIs to conveniently access such data, and the identification of more complex contexts [12], specific assistants in the form of sophisticated recommenders [34] have been brought to the attention of software engineering [35]. New opportunities have been explored in the field of recommenders in IDEs for specific programming languages or platforms, e.g., for code completion [8,41], for using external libraries [42], contributing to new projects [27], or solving standard programming tasks [39].…”

Section: Current Landscape Of Intelligent Modeling Assistancementioning

confidence: 99%

Opportunities in intelligent modeling assistance

et al. 2020

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HAL is a multidisciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

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Recommending GitHub Projects for Developer Onboarding

Cited by 33 publications

References 39 publications

New Developer Metrics for Open Source Software Development Challenges: An Empirical Study of Project Recommendation Systems

New Developer Metrics for Open Source Software Development Challenges: An Empirical Study of Project Recommendation Systems

Adoption of Social Media in Socio-Technical Systems: A Survey

Opportunities in intelligent modeling assistance

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