CodeCV: Mining Expertise of GitHub Users from Coding Activities

Atzberger, Daniel; Scordialo, Nico; Cech, Tim; Scheibel, Willy; Trapp, Matthias; Döllner, Jürgen

doi:10.1109/scam55253.2022.00021

Cited by 6 publications

(1 citation statement)

References 17 publications

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“…All activities and the entire history of a project are stored in a repository, which provides extensive information for further analysis. Example applications for analyzing git repositories include capturing static and dynamic software metrics [18][19][20], locating expertise among developers [21], or measuring environmental sustainability [22]. The extraction of relevant data requires efficient processing tools, e.g., for compiling software metrics [23].…”

Section: Tools For Mining Software Repositoriesmentioning

confidence: 99%

Integrated Visual Software Analytics on the GitHub Platform

Scheibel,

Blum,

Lauterbach

et al. 2024

Computers

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Readily available software analysis and analytics tools are often operated within external services, where the measured software analysis data are kept internally and no external access to the data is available. We propose an approach to integrate visual software analysis on the GitHub platform by leveraging GitHub Actions and the GitHub API, covering both analysis and visualization. The process is to perform software analysis for each commit, e.g., static source code complexity metrics, and augment the commit using the resulting data, stored as git objects within the same repository. We show that this approach is feasible by integrating it into 64 open source TypeScript projects. Furthermore, we analyze the impact on Continuous Integration (CI) run time and repository storage. The stored software analysis data are externally accessible to allow for visualization tools, such as software maps. The effort to integrate our approach is limited to enabling the analysis component within a project’s CI on GitHub and embed an HTML snippet into the project’s website for visualization. This enables a large amount of projects to have access to software analysis as well as provide means to communicate the current status of a project.

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Section: Tools For Mining Software Repositoriesmentioning

confidence: 99%

Integrated Visual Software Analytics on the GitHub Platform

Scheibel,

Blum,

Lauterbach

et al. 2024

Computers

Self Cite

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Aligning technical knowledge to an industry domain in global software development: A systematic mapping

de Campos,

David,

Ströele

et al. 2024

J Software Evolu Process

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Finding software developers with expertise in specific technologies that align with industry domains is an increasingly critical requirement. However, due to the ever‐changing nature of the technology industry, locating these professionals has become a significant challenge for companies and institutions. This research presents a comprehensive overview of studies exploring suitable recommendation systems that can assist companies in addressing this pressing need. To conduct this study, we employ a hybrid systematic mapping approach with an initial number of 1,251 studies and a final selection of 21 studies. Our work focuses on collecting data on key technologies, methodologies, and data sets utilized in proposed recommendation systems, to design a new recommendation system that can effectively identify specialists capable of aligning specific technical knowledge with industry domains. The outcomes of this study include insights into the current research trends in this field, alongside a practical overview of considerations necessary for developing a recommendation system that successfully meets the criteria for aligning technical skills with industry domains. By following a hybrid systematic mapping methodology and presenting the outcomes in the form of insights, this research addresses the challenge of finding software developers with domain‐specific expertise in a rapidly changing technology industry, laying the groundwork for aligning technical skills with industry domains.

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