2020 Fiscal Year Research-status Report
A Social Developer Digital Footprint for Skills Proficiency
| Project/Area Number |
20K19774
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| Research Institution | Nara Institute of Science and Technology |
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Principal Investigator |
ラウラ ガイコビナ・クラ 奈良先端科学技術大学院大学, 先端科学技術研究科, 助教 (80749094)
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| Project Period (FY) |
2020-04-01 – 2024-03-31
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| Keywords | newcomer candidate / conformance patterns / pythonic code |
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| Outline of Annual Research Achievements |
Follow the schedule as outlined in the proposed, FY2020 has been the setup of our research environment and subsequent skill proficiency mining. As part of this, I have been studying the skills and expertise of newcomer developers to social coding platforms like GitHub. As such, we have successfully identified newcomer candidates to OSS projects. We have now collected over 10 million GitHub repositories. Here is a summary of achieved publications.
-Coding patterns. I have started research on pythonic coding styles to identify specific writing patterns that appear in python developer.
-Candidate Open Source newcomers. I have started looking at the skills of potential developers that are learning skills to onboard an Open Source Project
-Other social activities. I published work in the field of code review and security activities.
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| Current Status of Research Progress |
Current Status of Research Progress
2: Research has progressed on the whole more than it was originally planned.
Reason
I have now collected evidence of the newcomer candidate, which is evident by the publications.
The next step is to identify and develop the digital skills footprint. I plan to analyze the social activities to analyze how this affects their skills. Furthermore, I plan to trace the social media impact of the developer. I hope to publish my results on this topic.
I have found that some of the terminology proposed has changed since the proposal, but this has no impacted the results and goal of the result.
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| Strategy for Future Research Activity |
Currently, I am successfully on target to the phase of skills proficiency mining. Since data is always evolving, we still need to continuously update our datasets. In 2021, I hope to start phase of anonymizing the the digital skills footprint. Furthermore, if I can also complete this part of the research, I might start the phase of evaluating its impact on a software ecosystem.
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