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- W2953729744 abstract "Context:Modern software development demands high levels of technical specialization. These conditions make IT companies focus on creating cross-functional teams, such as frontend, backend, and mobile developers. In this context, the success of software projects is highly influenced by the expertise of these teams in each field. Objective:In this paper, we investigate machine-learning based approaches to automatically identify the technical roles of open source developers. Method:For this, we first build a ground truth with 2284 developers labeled in six different roles: backend, frontend, full-stack, mobile, devops, and data science. Then, we build three different machine-learning models used to identify these roles. Results:These models presented competitive results for precision (0.88) and AUC (0.89) when identifying all six roles. Moreover, our results show that programming-languages are the most relevant features to predict the investigated roles. Conclusion:The approach proposed in this paper can assist companies during their hiring process, such as by recommending developers with the expertise required by job positions." @default.
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- W2953729744 date "2021-03-01" @default.
- W2953729744 modified "2023-10-14" @default.
- W2953729744 title "Mining the Technical Roles of GitHub Users" @default.
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- W2953729744 doi "https://doi.org/10.1016/j.infsof.2020.106485" @default.
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